Learning to read and spell single words: a case study of a Slavic language.

Marcin Szczerbiriski

A thesis submitted for the degree of Doctor of Philosophy University College London August 2001 ProQuest Number: U643611

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ProQuest LLC 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, Ml 48106-1346 ABSTRACT

We now have a good knowledge of the initial period of literacy acquisition in English, but the development of literacy in other languages, and the implication of this for our understanding of cognitive processing of written language, is less well explored. In this study, Polish T* - 3'*^ grade children (7;6-9;6 years old) were tested on reading and spelling of words, with controls for factors which have been shown to affect performance in other languages (lexicality, frequency, orthographic complexity). Moreover, each participant was individually tested on a range of linguistic skills understood to be essential components of literacy acquisition. These included: phonological awareness (detection, analysis, blending, deletion and replacement of sound segments in words) serial naming (of pictures, digits, letters) and morphological skills (using prefixes and suffixes). Some higher-level visual skills, and general intellectual ability (vocabulary knowledge, reasoning) were also assessed. In comparison with the existing data, Polish children appeared to acquire basic reading and spelling skills somewhat faster than their English counterparts, but slower than the consistent orthography learners (e.g. German). Some complex, conditional orthographic rules that occur in Polish were not fully mastered even in grade 3. This fits the description of Polish orthography as only moderately consistent overall. Success in learning to read and spell was independently predicted by two factors: phonological awareness and naming ability, with other skills (morphological and visual) playing a minor or negligible role. This outcome is broadly consistent with that observed in other languages in which it has been studied, suggesting that the essential mechanisms of learning written language may be the same across orthographies. Additionally, the performance of the few children who were falling behind in their reading was systematically analysed. Distinct sub-groups of inaccurate and slow readers could be identified. Both types of difficulties could usually be attributed to the co-occurrence of poor phonological awareness and slow naming. ACKNOWLEDGEMENTS

Carrying out this project was much more than a scholarly exercise: it was an experience of mutual support, collaboration and friendship. My thanks go first and foremost to my supervisors: Prof. Ruth Campbell and Dr. Nata Goulandris. The learning opportunities they offered me were truly exceptional. They took great care of my progress, providing the right blend of inspiration, freedom, challenge and encouragement - and remaining patient in the face of me failing so many solemnly sworn deadlines! I was privileged to receive even more, however, as the support and friendship they gave extended much beyond the boundaries of this project. A memorable aim: “to establish you as an independent researcher” formulated by Ruth during one of our meetings was to be a serious promise they both worked hard to fulfil. I was equally privileged to have the UCL Department of Human Communication Science as my place of study. When going to study abroad I was hoping to find academic excellence - and I was not disappointed. I was offered excellent facilities, leamt a great deal about speech and language research and therapy (a new, exciting world for me), and was given an opportunity to teach that I enjoyed so much. The departmental studentship I received supported me for the large part of this study. I felt very welcome by all members of staff, and was privileged to collaborate and become friends with a number of people, particularly Liz Nathan, Michael Coleman, Mairead MacSweeney, Liz Milne, Fiona Kyle and Vassiliki Diamanti. Indeed, the lure of Human Communication Sciences was strong, and it is now the Sheffield HCS department that I can also thank for giving me ample time and resources to finish this project - as well as carry out new ones! The fieldwork of this project was carried out mostly in the Primary School 14 in Krakow-Salwator. I am indebted to all the children who agreed to take part in what - I now realize - was too long and tedious a series of tests. I would also like to thank all the teachers and, particularly, the school psychologists. Dr. Jadwiga Wrohska and Ms Ewa Nowak. They made me feel welcome at their school, provided important information about my participants, and patiently endured the disruption I caused to their working schedule. Important pilot data for this project were also collected in two other primary schools (149 and 57 in Krakow- Kurdwanow). My gratitude extents to all pupils, parents, teachers and special needs staff that I met there. The project was also supported by several other people in a very tangible way. Considerable part of the pilot data was collected by Ms Aneta Wojcik. A daunting task of setting up SPSS databases was made much easier thanks to assistance from Mrs Malogrzata Wysocka-Pleczyk, Ms Natalia Fijak, Ms Malgorzata Hoffmann and - in a last minute emergency - Ms Vesna Stojanovik. Ms Natalia Fijak deserves a particular mention here, also for her patience and perseverance in the face of my most unreasonable e-mail request for doing

3 literature searches in Krakow libraries. Assistance with literature searches was also given by Ms Joanna Sadowska. Apart from my supervisors, who corrected my awkward writing style (and tried, with little success, to teach me the correct usage of definite and indefinite articles) a number of people read and commented on different parts of the manuscript. Chapters 3 and 4 were reviewed (at various stages of writing) by Dr. Liz Nathan, Prof. Bozydar Kaczmarek, and Dr. Ewa D^browska; chapter 1 by Dr. Patty Cowell, and chapter 9 by Vesna Stojanovik.. Final proofreading assistance was offered by Dr. Richard Body, Dr. Patty Cowell, Sarah James, Liz Milne, Dr. Liz Nathan, Vesna Stojanovik, and Fay Windsor. I owe a great deal to my Polish colleagues involved in reading research; Dr Grazyna Krasowicz-Kupis, Dr Urszula Oszwa, Dr Alicja Maurer and Ms Krystyna Sochacka. They provided me with their unpublished or otherwise hard to access papers, and hours of stimulating face-to-face and e-mail discussions. Grazyna Krasowicz and Krystyna Sochacka both allowed me to access their datasets, and we spent an exciting and fruitful time analysing them together. Their ideas inspired this project greatly. Nothing would be possible without the love, support and encouragement of my family. My father deserves a particular mention here. Without his encouragement to ‘think big and brave’, and his financial support during the difficult year before I formally registered as a PhD student, this project would certainly not have even been attempted. Decisive encouragement and advice to ‘go for if was also given by my master thesis supervisors and examiners: Dr. Janusz Palczyhski, Dr. Andrzej Kokoszka, and Dr. Dorota Jasiecka. I cannot fail to acknowledge Dr. Ewa Szurek-Skwierawska, a lecturer who introduced me to the subject of dyslexia. She arose my interest in this problem, encouraged my PhD efforts, and assisted me in arranging the pilot study. I also cannot fail to mention my wonderful friends, in Poland, England and elsewhere. I will always cherish the love, fun and wisdom I received from them - not to mention the food, lodgings and computer power they offered me at quite a few critical junctures! The project also received financial support from the British Council Fellowship, Overseas Research Scheme and the departmental teaching studentship from the Department of Human Communication Sciences, UCL. This work is dedicated to my siblings: Kinga, Magda and Rafal, who were the greatest discovery of my PhD years. CONTENTS

Abstract 2 Acknowledgements 3 Contents 5 List of tables 10 List of figures 13 List of appendices 15

1. Reading, spelling and learning 1.1. Definitions 16 1.2. Reading research - main problems and controversies 18 1.2.1. fVhat is the ro/e o fdecoding/or reading comprehension 2 18 /. 2.2. fVord reading andspeiiing: is the taskprimarifyperceptuai or iinguisticF 22 1.2.3. fVhat are the hasic mechanisms or learning to read andspeiiF 27 J.2. d. Is shiiled word recognition phonoiogicaily mediated? 33 1.2. S. Are reading andspeiiing essentia/iy the sameprocess.^ 35 1.3. Models or reading acquisition 38 /.S.I. Stage andphase models 39 1.3.2. ^^Processes and resources models 41 1.3.3. Connectionist models 44

2. Literacy acquisition and linguistic skills 48 2.1. Phonological processing 49 2.1.1. Phonological awareness 49 2.1. J. J. The concept o f linguistic awareness 49 2. J.J. 2. Developntent o f phonological awareness 51 2. J. J. 3. The role o f phonological awareness in the acquisition o f literacy 55 2.1.2. Phonological retrieval 66 2.1.3. Working memory 74 2.2. Literacy and other linguistic skills 79 2.2.1. Syntactic awareness 80 2.2.2. Morpkoiogicalawareness 84 2.3. Conclusions 89

3. Cross-linguistic differences in literacy acquisition 91 3.1. Spoken language and literacy 91 3.1.1. Segmentalpkonoiogy 92 3.1.2. Suprasegmentalphonology 92 3.1.3. Syntax andmorphology 94 3.1.4. IVord length 95 3.2. Orthography and literacy 95 3.2.1. Descrihing orthographies 95 3.2.2. The relationship between teaching methods and orthographies 103 3.2.3. The impact o/orthography on acquisition processes - summary o fhypotheses 104 3.2.4. Language, orthography and the acquisition ofliteracy - a review o fdata 106 3.2.4. J. The relative dij^cu/ty of acquisition 106 3.2.4.2. The differences in reading strategies 111 3.2.4.3. The differences in Unguis tic awareness 114 3.2.4.4. Predictors o f literacy acquisition in different orthographies 116 3.3. Reading difficulties in different alphabetic orthographies 119 3.3. J. L. Simple orthographies - do they remove dyslexiaF 119 3.3. J. 2. Simple orthographies - is dyslexia manifested differently!*\ 2 0 3.3. J. 3. Simple orthography dyslexias - is the nature o fthe problem differentF 124 3.4. Reading research in Polish 127 4. Polish language, orthography and literacy teaching 133 4.1. The language 133 4.J.I, Morpko/ogy andsyntax 133 4.1. J.J. Inflections 133 4. J.J. 2. Derivational morphology 137 4.1.2. Phonology 138 4. J. 2. J. Segments 138 4. J. 2.2. Suprasegmentalphonology 142 4.2. The orthography 145 4.2.1. The alphabet 146 4.2.2. Transparency, regularity, consistency 146 4.2.2. J. Reading 146 4.2.2.2. Spelling 150 4.3. Teaching literacy 153

5. The study 156 5.1. Research problem and hypotheses 156 5.2. Participants 158 5.3. Methods 161 5. 3.1. Control measures 161 S. 3.2. Verbal memory 162 S. 3.3. Phonologicalsensitivity 162 5.3.4. Phonological awareness 164 5.3.5. Naming 166 5.3.6. Verbal/Iuency 167 5.3.7. J\Iorphologicalprocessing 168 5.3. S. Visual-motorprocessing 170 5.3.9. Reading andspelling measures 172 5.4. Procedure 174 5.5. Reliability of tests 175 6. Reading and spelling development 177 6.1. Components of literacy - their organisation and growth 177 6.1.1. Change heth^een the grades 178 6. J. 2. Internaistructure ofiiteracy shills 181 6.1.3. Age-related changes In the structure o/literacy shills 184 6.2. ANOVA analyses 185 6.2.1. Reading accuracy 187 6.2.2. Reading time 190 6.2.3. Spelling accuracy 194 6.2.1. Summary o fANOVA analyses 197 6.3. Error analyses 199 6.3.1. Reading errors 200 6.3.1.1. Errors as the function oforthographic complexity 203 6.3.2. Spelling errors 204 6.3.2.1. Sensitivity to orthographic conventions 207 6.4. Summary and conclusions 208

7. Literacy and other cognitive factors 212 7.1. Development of cognitive skills 212 7.2. Phonological, morphological and visual skills - internal structure 216 7.3. Development of phonological awareness 222 7.4. Cross-linguistic comparisons of phonological skills 227 7.4.1. Phoneme analysis and blending 227 7.4.2. Oddity tests 231 7.4.3. Vofvel replacement test 233 7.4.4. Speed andfluency tests 233 7.5. Cognitive predictors of literacy 236 7.3.J. Predicting word reading andspelling 237 7.S. I. J. Contribution o findividual variables 237 7. S. 1.2. l/nlgue contribution o f latent factors 240 7.5.2. Predicting non word reading andspelling 244 7.5.2.1 Contribution o f Individual variables 245 7.5.2.2. L/nlgue contribution o f latent factors 246 7. s. s. /heading andphonologicai an^areness - analysis ofindividual cases 250 7.5.d. The role o/graphemenaming 253 7.5.5. Changes in predictors o fliteracy over time 256 7.6. Summary and conclusions 259

8. The cognitive profile of dyslexies and poor readers 263 8.1. Identifying dyslexic cases 265 8.2. Cognitive profile of dyslexic participants 271 8.3. Cognitive profile of poor readers 277 8.4. Visual deficits in dyslexia? 282 8.5. Testing the double deficit hypothesis 286

9. Summary and conclusions 290 9.1. Reading and spelling acquisition in Polish 290 9.J.I. Processing written words: ages, stages, mechanisms 290 9.1.2. Cognitive correlates o fliteracy 293 9.1. S. fVritten language difficulties: symptoms and mechanisms 294 9.2. Broader theoretical issues 295 9.2.1. Language-specific and cognitive-universal aspects ofliteracy acquisition 295 9.2.2. Phonological recoding versus orthographicprocessing 299 9.2. S. Reading versus speiiing 300 9.3. Limitations of the study and future directions 301

References 304 Appendices 328 Appendix 1: descriptive statistics 328 Appendix 2: tests used in the study 334 LIST OF TABLES

Table 1-1 Schematic comparison of some influential stage and phase models of 39 literacy acquisition.

Table 2-1 The scope of metalinguistic skills. 51

Table 3-1 Summary of cross-linguistic studies of early reading accuracy. 108

Table 3-2 Summary of dyslexia studies in English and other languages. 121

Table 3-3 Reading accuracy and time of dyslexies and chronological age controls 124 - the summary of existing non-English studies.

Table 4-1 Polish consonantal phonology. 141

Table 5-1 Age and gender characteristics of the sample. 159

Table 5-2 Participants’ performance on standardised measures. 160

Table 5-3 Reliability coefficients of non-standardised measures used in the 176 study.

Table 6-1 Reading and spelling measures - descriptive statistics. 179

Table 6-2 Correlations between reading and spelling measures. 182

Table 6-3 Pattern matrix of the factor analysis of reading and spelling measures. 183

Table 6-4 Intercorrelations between various indices of reading and spelling, 185 presented separately for each grade.

Table 6-5 Accuracy of reading of diffemt types of stimuli (the short list). 187

Table 6-6 Accuracy of reading different types of stimuli (the long list). 189

Table 6-7 Reading times (in seconds per item) of different types of stimuli (the 190 short list).

Table 6-8 Reading times (in seconds per item) of different types of stimuli (the 192 long list).

Table 6-9 Accuracy of spelling different types of stimuli (the short list). 194

Table 6-10 Accuracy of spelling different types of stimuli. 196

10 Table 6-11 The frequency of ortho graphically illegal and implausible renditions of 207 the target stimuli.

Table 6-12 Easiest and hardest tasks and stimuli (in 2"‘* and grade). 211

Table 7-1 Descriptive statistics for the cognitive measures used in the study. 213

Table 7-2 Ten tests showing largest developmental gains between the grades. 215 Growth is expressed in terms of effect sizes.

Table 7-3 Pattern matrix of the first factor analysis. Values represent factor 217 loadings, and are sorted by size. Table 7-4 Pattern matrix of the third factor analysis, which included only 219 linguistic measures. Table 7-5 Summary of phonemic analysis studies. 228 Table 7-5 Summary of phoneme blending studies. 230 Table 7-6 The summary of sound categorisation studies. Rhyme detection 232 accuracy % is averaged across middle V and final C conditions. Table 7-7 Performance of the Polish children on verbal fluency and rapid naming 234 tasks, compared to English norms. Table 7-8 Multiple regression analyses predicting word reading and spelling 237 skills from individual tests. Table 7-9 Multiple regression analyses predicting word reading and spelling 241 from six latent factors. Overall and adjusted R squared changes are based on the significant predictors only. Tab. 7-10 Results of multiple hierarchical regression analyses predicting reading 242 and spelling from selected variables (best predictors in each factor). Table 7-11 Multiple regression analyses predicting nonword reading and spelling 245 skills from individual tests. Table 7-12 Multiple regression analyses predicting nonword reading and spelling 247 from six latent factors. Table 7-13 Results of hierarchical multiple regression analyses predicting reading 248 and spelling from selected tests (best predictors in each factor). Table 7-14 Cross-tabulation of reading and phonological awareness scores 251 (children selected for extreme reading scores). Table 7-15 Cross-tabulation of reading and phonological awareness scores 252 (children selected for extreme scores on phonological awareness tests).

11 Table 7-16 Results of hierarchical multiple regression analyses predicting reading 253 and spelling skills from grapheme knowledge and naming speed. Table 7-17 Results of hierarchical regression analyses predicting word reading and 255 spelling skills from grapheme mastery and nonword decoding. Table 7-18 Accuracy of reading as a function of letter knowledge. 256 Table 7-19 The results of hierarchical regression analyses predicting word reading, 257 carried out separately for each grade. Table 8-1 Criteria for identifying dyslexia and the list of identified children. 266 Table 8-2 ‘Relaxed’ criteria for identifying dyslexia, with the lists of identified 267 children. Table 8-3 Selection criteria and basic characteristics of dyslexic and control 268 groups. Z scores are relative to a grade level. Table 8-4 Word reading and intelligence tests scores in dyslexies and controls. 269 Table 8-5 Educational background of participants’ parents. 270 Table 8-6 Performance of dyslexies and controls on individual cognitive tests. 272 Table 8-7 Summary of significant differences between dyslexies and controls. 273 Table 8-8 Scores of dyslexic participants on phonological processing and reading 275 composites. Table 8-9 Selection criteria and basic characteristics of poor readers and control 277 groups. Z scores are relative to a grade level. Table 8-10 Word reading and intelligence tests scores in poor readers and control 278 groups. Table 8-11 Performance of poor readers aid controls on individual cognitive 279 tasks. Table 8-12 Summary of significant differences between poor readers and controls. 280 Table 8-13 Scores of poor readers on phonological processing and reading 281 composites. Table 8-14 Mean scores on reading composites adjusted for general ability 285 (WISC-R Vocabulary and Columbia) z-scores. Table 8-15 Scores of children with single and double phonological impairments on 286 reading and phonological processing composites. Table 8-16 Mean scores on reading composites adjusted for general ability 287 (WISC-R Vocabulary and Columbia) z-scores.

12 LIST OF FIGURES

Figure 3-1 Schematic classification of alphabetic orthographies on the 103 dimensions of complexity and consistency.

Figure 3-2 The % accuracy of word and nonword reading in English and other 109 languages.

Figure 3-3 % accuracy of word and nonword reading of dyslexies and reading 122 age control children - comparison between English and other language studies.

Figure 5-1 The study and its relation to the primary education system. 158

Figure 6-1 Relative gains in reading and spellings skills, expressed as effect sizes 180 of change between grades.

Figure 6-2 Mean accuracy of reading different types of stimuli (the short list). 187

Figure 6-3 Mean reading times (secs/item) for different types of stimuli (the 191 short list).

Figure 6-4 Mean spelling accuracy of different types of stimuli (the short list). 194

Figure 6-5 Relative frequencies of different types of word errors in grades 1-3. 201

Figure 6-7 Relative frequencies of different types of word spelling errors in 205 grades 1-3.

Figure 6-8 Relative frequencies of different types of nonword spelling errors in 206 grades 1-3.

Figure 7-1 Accuracy on phonological awareness tests in T* - 3'^* grade (boxplot). 224

Figure 7-2 The number of correct responses per minute generated in four verbal 226 fluency tests at each grade level.

Figure 7-3 Results of verbal fluency and rapid naming tests transformed to 235 PhAB English standard scores.

Figure 8-1 The median scores of dyslexies and chronological age controls on the 276 five composites.

Figure 8-2 The median scores of poor readers and controls on five composites. 281

13 Figure 8-3 Median scores of poor readers and controls on phonological and 283 visual composites. Figure 8-4 Performance of children with different types of impairment and the 284 unimpaired controls. Figure 8-5 Performance of children with single and double phonological 287 deficits, and their controls. Figure 8-6 The effects of low general ability and phonological impairments on 288 reading performance.

14 LIST OF APPENDICES 1. Descriptive statistics 328 Table A-1 Reading and spelling variables 328 Table A-2 Phonological and morphological variables 329 Table A-3 Naming speed and fluency variables 331 Table A-4 Visual variables 333 2. Tests used in the study 334 Nonword repetition 335 Alliteration oddity 336 Feminine rhyme oddity 337 Masculine rhyme oddity 338 Phoneme analysis 339 Phoneme blending 340 Phoneme deletion 341 Consonant replacement 342 Vowel replacement 343 Rapid naming - pictures 344 Rapid naming - digits 348 Grapheme naming speed 351 Fluency - semantic 355 Fluency - alliteration 356 Fluency - feminine rhymes 357 Fluency - masculine rhymes 358 Comparison of adjectives 359 Derivative forms 361 Prefixes 363 Diminutives 365 Chinese letters 367 Rey-Osterreith figure 373 Symbol discrimination 374 Letter discrimination 377 Reading and spelling 380

15 CHAPTER 1

READING, SPELLING AND LEARNING

This chapter introduces the central problem of the thesis - the development of word- level reading and spelling skills - and shows its place in the field of literacy research. First, I will examine the relationship between the ability to recognise and decode individual words and general reading ability - that is, the ability to comprehend messages conveyed in writing. I will also evaluate some contrasting assumptions about the nature of reading and spelling, which gave rise to different research paradigms. Finally, I shall focus on learning mechanisms of reading and spelling, discussing them in the context of formal models of literacy acquisition. This broad overview will set the background for discussing more specific cognitive, linguistic and cross-linguistic aspects of written word processing, which will follow in chapters 2-4.

1.1. DEFINITIONS

The thesis will investigate the development of word identification, nonword reading and spelling to dictation. Those specific skills, however, will be treated primarily as indicators of two more fundamental cognitive competencies of a literate person: phonological recoding and orthographic processing. Because of the central importance of those concepts for the following argument, I shall start by defining them. The term phonological recoding ^ be used to denote all reading and spelling processes that utilise information about phonological structure of words (Share, 1995). The concept implies some form of (implicit or explicit) knowledge about mappings between phonology and orthography, yet is neutral with respect to specific modes of representing and applying this knowledge. These may involve sub-lexical units of different size (individual phonemes, onset-rimes, syllables and corresponding letter strings) and different processing mechanisms (explicit application of grapheme- phoneme correspondence rules, implicit analogy making, or some quasi-regular processes utilising distributional frequency information). Phonological recoding is operationalized most directly through decoding (sounding out) of nonwords, and also a ‘reverse’ skill of producing phonoiogicaily plausible spellings of words and nonwords. Orthographic processing (or orthographic shiiis) is defined in relation to its specific content: orthographic codes. This is a type of information (about basic units - 16 graphemes - and their arrangements) that is unique to writing and constitutes a representational domain that is separate from phonology, morphology or semantics. There are different ways of characterising the scope of orthographic processing (Share, 1995). Some of them emphasise word-specific knowledge: storage of orthographic representations of individual words and the ability to use them in word recognition and spelling. “The orthographic” may also refer to the hypothetical direct connections between orthographic and semantic representations of words, which allow for reading without phonological recoding. Other definitions imply more general forms of knowledge. These may include sensitivity to grapho-tactic and grapho-statistic constraints of a given orthographic system (ability to judge the typicality or legality of a given letter sequence), or sensitivity to grammatical constraints that determine what spelling is legal for a word, given its morphological or syntactic properties. Like phonological recoding, orthographic processing is a theoretically neutral term that does not specify the nature of underlying cognitive mechanisms. Orthographic processing undoubtedly has to involve both visual and phonological processes, yet it cannot be fully subsumed under either of those, since orthographic codes are neither intrinsically visual (they are independent of font shape and can be conveyed by oral spelling) nor phonological (their match with phonological structures is usually not a one-to-one correspondence). There are some controversies regarding operationalization of orthographic processing (Vellutino, Scanlon & Chen, 1994). However, all tasks used in this context share basic similarities: they require decisions about letter sequences that cannot be made solely on the basis of phonological recoding. The tasks include: naming and spelling of exception words, homophone choice ( e. g. “Which one is a number: ate or eighfT') or letter string choice (deciding which one out of two written nonwords bears more resemblance to a real word, e.g.: nack or cka/i). Less directly, orthographic processing is also reflected in the efficiency (speed and accuracy) of naming any familiar words.

17 1.2. READING RESEARCH - MAIN PROBLEMS AND CONTROVERSIES

1.2.1. What is the role of decoding for reading comprehension?

How does general reading ability - that is, the ability to comprehend written material - relate to the ability to decode and recognize individual written words? This question has arguably been the most hotly debated one throughout the history of reading acquisition research. It re-surfaced in different forms (Adams, 1990) and over the last thirty years it crystallised into controversy between two general approaches, labelled as ‘whole language’ and ‘code emphasis’. The former stresses the developmental primacy of comprehension, and the role of texts in learning to read, perceiving word-level skills merely as a by-product of meaning-oriented text activities. The latter approach recognises word decoding and recognition as skills in their own right, which are essential prerequisites of reading comprehension. Within the “whole language” framework reading is conceptualised as meaning- seeking: a psycholinguistic process through which a reader actively re-constructs the writer’s message (Goodman & Goodman, 1982). It involves continuous generation and testing of hypotheses about the meanings conveyed in print. Specific skills involved in reading (such as word identification) are just aspects of this core process of meaning re­ construction, and cannot be understood in isolation from it. The emphasis is put on the top-down processing: to succeed in reading, a child has to bring in all levels of the linguistic skills she already possesses, and her general knowledge about the world. The same process of hypothesis testing is responsible not only for text comprehension, but also for a child’s understanding of the very nature of writing, and the development of word-level skills. Individual words in a text are in fact predicted from their linguistic context to a greater extent than they are identi/ied. hence referring to reading as a “psycholinguistic guessing game” (Goodman, 1967/1982). The bottom- up “cues” from a word are also essential, yet they are sampled parsimoniously, insofar as they are necessary to confirm or reject the top-down hypothesis about that word’s identity. Detailed processing of individual words is unnecessary because of considerable text redundancies: identity of individual words is richly over-specified by the combination of context and bottom-up cues (Smith, 1994). Identifying words by extracting sounds from letters (i.e. decoding) is also available and desirable, yet constitutes just one of many available bottom-up cues. Learning to read is essentially a process of discovery, the autonomous activity of the learner. The teacher’s role is

18 important, yet mainly facilitatory; direct instruction into the ‘mechanics’ of reading is neither necessary nor desirable. The whole language approach is primarily focused on the applied issues of literacy education (Goodman, 1992) and produced relatively little basic research into the mechanisms of reading acquisition. Some evidence, however, is forthcoming (notably, also from the opponents of this approach) to support at least some of the conjectures just presented. The importance of top-down processing in word recognition has been demonstrated in a number of different research paradigms. Indeed, early research by Goodman (1965/1982) found that story context enabled children to successfully read words they failed to read in isolation; a finding confirmed by other authors (e.g. Goswami, 1990). This can be experimentally demonstrated in semantic priming: preceding a word with a semantically related prime (a word or a sentence) facilitates recognition; conversely, recognition is inhibited if the preceding material is inconsistent with the target (e.g. Stanovich & West, 1979; Ehrlich & Rayner, 1981; for overview see Stanovich & Stanovich, 1995; Neely, 1991). Continuous top-down monitoring of word decoding and recognition is also reflected in reading errors. Skilled and unskilled readers alike err predominantly by producing whole word substitutions that are syntactically and semantically plausible in their context (e.g. Goodman, 1967/1982, Danielsson, 2000). Even in those experimental paradigms that remove all contextual cues and require processing of isolated words (naming, lexical decision) performance is influenced by factors such as age of acquisition or imageability of a word (Besner & Humphreys, 1991). This implies that written word recognition is never a fully autonomous, encapsulated process, but is always supported by other parts of the language system. Finally, for skilled readers, reading comprehension and listening comprehension abilities show near-perfect correlation (Ellis, 1993), suggesting their common nature. Correlation between reading comprehension and single word recognition, on the other hand, tend to diminish as word recognition improves (Vellutino, Scanlon & Tanzman, 1994). The evidence for reading without decoding is also consistent with the whole language claims. Purely visual and non-orthographic information about words (such as their shape, length, salient letter parts) can indeed be used to make informed guesses at their identity (Haber, Haber & Purlin, 1983; Seymour & Elder, 1986). Moreover, children are able to acquire considerable reading vocabulary while knowing very little about letter names and sounds, and not relating to this knowledge (Seymour & Elder,

19 1986). Even substituting some content words with pictures may leave reading undisturbed. The competing ‘code emphasis’ approach is expounded in a number of different theories, all of which share at least four basic tenets. First of all, general reading ability is a product of several partially independent components - rather than a unitary comprehension-driven process. Secondly, word recognition skills are a prerequisite of reading comprehension, rather than its by-product. Thirdly, that the optimal way to develop proficient word recognition goes through systematic use of phonological recoding. Finally, phonological recoding and word recognition benefit from explicit instruction. Those claims are supported by a large body of research, and seem ultimately consistent even with those findings that are apparently supportive for the ‘whole language’ claims. This regards, first of all, the basic mechanisms of word identification. Contextually-based inferences are, on their own, clearly insufficient to guess word identity (giving only 20 - 30% chance of success; for overview of relevant studies see Stanovich & Stanovich, 1995; Share, 1995). Adding visual cues (word shapes and length) raises the ability of success considerably, yet only to a still moderate 60% (Haber, Haber & Furlin, 1983). Most importantly, guessing can, in principle, succeed only if the word already forms part of the reader’s vocabulary. Young children indeed deduce words from context, recognise their shapes (as in case of environmental print: brand names, company logos, etc.) or use other incidental cues. However, contrary to the expectations of whole language theorists, the ability to deal with written language this way bears no relation, or a negative relation, to subsequent progress in reading (for review see Adams, 1990; Share, 1995; see also section 1.3.2. for further discussion). This is largely inevitable, since the mappings between the meaning of words and their visual or contextual attributes are arbitrary. As no underlying principle can be extracted to rely on, no possibility exists for self-teaching and independent development of reading vocabulary (Share, 1995). It is only the reliance on letter-sound correspondences that may provide a basis for such self-tuition, thus allowing one to learn words that are truly new and unpredictable (non-redundant in their context). The central importance of recoding skills is also confirmed by longitudinal studies which show that early recoding ability is predictive of later reading; particularly word recognition, but also reading comprehension (Share, 1995; Stanovich, 1994a). Systematic training in phonological awareness and recoding was also shown to benefit literacy. Although the training effects tend to dissipate over time (especially for word

20 recognition) they are still detectable after more than a year in spelling and reading comprehension (see Bus & Vanijzendoorm, 1999, for meta-analysis of existing studies). Not only successful word decoding, but even attempts at such decoding (errors indicative of phonological recoding strategy) are positive predictors of later reading, whereas errors that suggest global, visual guessing are associated with poorer reading outcome (Stuart & Coltheart, 1988). Contextual facilitation of word recognition is indeed important, yet it can bring success in unfamiliar word reading only if combined with (at least rudimentary) decoding skills (Share, 1995; Nation & Snowling, 1998). The results of contextual facilitation studies are somewhat ambiguous, as the magnitude of obtained effects depends on the way they are computed (Nation & Snowling, 1998). In most studies, however, the absolute context-related facilitation was largest in inexperienced readers and dyslexies (for review see Stanovich & Stanovich, 1995; Share, 1995). Relying on context may, therefore not be a predictor of reading success (as whole language theories would suggest) but rather a compensation for inadequate decoding skills (Stanovich, 1980). The evidence also exists - contrary to the whole language claims - that reading is not a holistic process, but reflects the interaction of autonomous components. In particular, word decoding and recognition abilities are partially independent from higher-language comprehension skills, making their own contribution to reading comprehension. A number of correlational studies showed that reading comprehension is jointly determined by word decoding skills and general language ability; the latter reflected most directly in listening comprehension (Tunmer & Hoover, 1992). It is not clear whether their contributions are additive (reading comprehension = decoding + listening comprehension), interactive (decoding x listening comprehension) or constitute the combination of additive and interactive terms (decoding + listening comprehension + decoding x listening comprehension); in any case, however, both show independent contribution to the variance in reading comprehension across groups of readers (Chen & Vellutino, 1997). In young, unskilled readers it is the weak word- level skills that are the main constraint on reading comprehension. Once these are mastered, reading comprehension becomes limited only by general language comprehension (Vellutino, Scanlon & Tanzman, 1994). Double dissociations between developmental reading disorders of decoding and comprehension (dyslexia and hyperlexia) also support the functional independence of those two core components of reading ability (Stothard & Hulme, 1995, Nation, 1999).

21 Interpretation of reading as a unitary or ‘holistic’ (Grundin, 1994) process may be partially accurate with respect to the earliest phase of acquisition, when narrative skills or context-based inferences play an important role in word identification (Roth, Speece, Cooper & De La Paz, 1996; Share, 1995). Yet reading development is accompanied by increasing dissociation, or modularisation of its component sub­ processes (Perfetti, 1992). They eventually emerge partially segregated at the brain level (Carr & Posner, 1993) and become vulnerable to selective functional impairments, which lead to different types of acquired dyslexia (Ellis &Young, 1988; McCarthy & Warrington, 1990). This modularisation is also reflected in the growing specificity of connections between reading sub-components, and their linguistic predictors. Thus, phonological recoding is directly and reciprocally connected with phonological awareness, but only indirectly related to the ability to use contextual facilitation. The reverse, however, may be true for reading comprehension (Stothard & Hulme, 1992). The evidence for the dissociation between the predictors of phonological recoding and orthographic skills is less clear. Some studies suggest that, for the latter, an important role is played by the ability of rapid and automatic retrieval of verbal codes (operationalized with rapid naming tasks: Bowers, Sunseth & Golden, 1999; Manis, Seidenberg & Doi, 1999) or by syntactic and morphological awareness (Bryant, 1993). I shall discuss the cognitive predictors of reading in more detail in chapter 2. Overall, despite some outstanding issues, the cumulative body of findings suggests that the reading process may be seen as a hierarchical structure. General reading (comprehension) ability is a product of partially independent skills (word recognition and spoken language comprehension), each comprising its own set of basic cognitive processes (e.g. phonological recoding and orthographic processing in word recognition) and having their unique developmental history and developmental pre­ requisites (e.g. phonological awareness, efficient phonological retrieval) (e.g. Carver & Clark, 1998; Tunmer & Hoover, 1992).

1.2.2. Word reading and spelling: is the task primarily perceptual or linguistic?

A simple formal analysis of reading and spelling immediately reveals their complex character. Both activities are inherently /ingnistic, since writing conveys language. They are also perceptual and motor, as they require discrimination, recognition and production of visual stimuli and sounds, as well as the execution of complex movements. Moreover, this diverse information has to be constantly integrated across

22 modalities. Finally, efficient reading and spelling must be rapid 2ccA automatic. Each one of those aspects became, at some point of reading research history, a focus of special attention, was assumed to be critical and became the tenet of formal theory. Undoubtedly, all the aspects just mentioned are involved in reading, from which does not follow, however, that all are equally important in the sense of posing non-trivial demands on a learner and being a frequent source of reading difficulties. During its long early period, the research was dominated by the assumption of word recognition and spelling being complex perceptuai tasks. Visual aspects of reading, and links between reading and other visual processes have been particularly thoroughly investigated (for overview and critical discussion see Rayner, 1998; Willows, Kruk & Corcos, 1993; Rayner & Pollatsek, 1989, Vellutino, 1979), although motor skills, cross-modal integration and linguistic skills were also the object of extensive scrutiny. Characteristically, however, if linguistic processes (e.g. discrimination of speech sounds) were investigated within the perceptual paradigm, they were usually treated merely as an instance of general perceptual skills. Such an assumption was reflected in the terminology, e.g. the habit of referring to various phonological units (syllables, rhymes, phonemes) as ‘sounds’ and labelling the tasks that employed them as ‘auditory’. This perceptual paradigm has been seriously challenged over the last three decades. One impulse for change came from the general developments in cognitive theory, namely the concept of modularity (Fodor, 1983). The modular theory understands mind/brain as a set of semi-independent, encapsulated skills, each having its own evolutionary history, biologically pre-specified aim, and its own internal representational code. This leaves less room for general-purpose perceptual processes, on which reading acquisition could easily capitalise. Secondly, new insights came from psycholinguistics, especially research on the nature of phonological representations, which appeared to have unique properties, quite different from those exhibited by representations of non-linguistic auditory stimuli (e.g. Liberman & Mattingly, 1985, 1989). Those two paths were most consistently combined and applied to reading acquisition research by scientists at Haskins Laboratories in New Haven (e.g. Liberman & Liberman, 1990/1992; Liberman, 1995). In their view, no plausible psychology of reading can be proposed until the true nature of speech is understood. Speech comes before writing - both phylogenetically (in the history of human species) and ontogenetically (during individual development). Moreover, speech is universal and natural - we are biologically endowed with the ability of its reception and production.

23 Although superficially auditory (i.e. received by ear) speech constitutes a separate modality, based on its own specific code - articulatory gestures. Writing is secondary to speech (or indeed, in the Libermans’ metaphor, ‘parasitic’ on it) as it constitutes a more or less successful attempt at recording underlying sound structures by the means of arbitrary visual symbols. Those symbols are not naturally suited for linguistic processing; it is only when they are systematically linked with the units of speech that they acquire linguistic values. Forming such secondary links is the essence of learning to read. No links could be formed, however, if a future reader was not aware of the units being associated. Visual units are explicitly provided, but the corresponding sound units - phonemes - have to be brought to conscious awareness. Phonemes underlie speaking and listening, yet under normal circumstances they are not consciously attended to. Demands of speech efficiency require them to be coarticulated, i.e. merge into one seamless sound package corresponding to a syllable or even larger unit. In the process of learning to read, underlying phonemic structures have to be ‘unpacked’ from the surface speech signal - a somewhat unnatural act which makes learning to read difficult. According to its proponents, the linguistie explanation of reading given above avoids some paradoxes the perceptual theories fell into. If reading and listening were two parallel perceptual processes (simply utilising different sensory channels) then both should be equally easy or difficult. If anything, it is reading that should be easier than listening: visual stimuli enjoy the advantage of not being transient, and vision seems to be the preferred sensory pathway of homo sapiens. Yet it is precisely learning to read and spell that requires - at least from some learners - a prolonged, conscious effort, which does not always bring full success. What is the evidence that could settle down the dispute between the perceptual and the linguistic paradigm? It has to meet certain formal criteria. Within the developmental perspective, one must identify the cognitive processes or skills (either perceptual or linguistic) that constitute direct prerequisites or precursors of learning to read and spell. In other words, one must find causa/ developmental links between reading and spelling and other cognitive skills. In order to identify any link as causal, it must meet several conditions (e.g. Goswami & Bryant, 1990): 1. Be selective: the skill in question should show strongest association with literacy, not other areas of academic achievement (e.g. numeracy) 2. Be specific: the significant association must remain also after potential confounding factors are controlled or partialled out.

24 3. Be longitudinal - earlier level of the skill should predict later level of reading/spelling performance. 4. Training or teaching of the skill in question should bring improvement in reading/spelling. 5. People with selective impairment of reading/spelling should also be poor, or deficient, on that skill. A wide array of perceptual and linguistic skills and processes has been exposed to such causal scrutiny. On the perceptual side, significant correlations (also longitudinal) were found between reading and spelling and the measures of visual, motor and nonverbal auditory functions, as well as their inter-modal and cross-modal integration. Poor readers, in particular, often obtain low scores on the measures of perception and perceptual-motor integration (for overview, see Vellutino, 1979; Willows, Kruk & Corcos, 1993). Some types of acquired dyslexia were also described in adult patients, which can be interpreted in terms of breakdown of higher-order visual processing (McCarthy & Warrington, 1990). However, it is questionable whether the associations between reading and perceptual skills observed in the developmental studies are selective and specific. Successful performance on some complex perceptual tasks may, in fact, depend on good verbal skills that allow one to apply a strategy of verbal labelling (Hicks, 1980; Crispin, Hamilton & Trickey, 1984). Typically, the correlations between perceptual tasks and reading are only modest (usually of magnitude between 0.30 - 0.50; e.g. Bond & Dykstra, 1967/1997) and become stronger if a task contains phonological components (e.g. Bogdanowicz, 1997). Perceptual deficits are not selectively associated with poor reading; rather, they reflect general learning difficulties (Rutter & Yule, 1975; Stanovich, 1994b). Many studies have shown that children with dyslexia are indistinguishable from their normal peers on visual analysis and memory (Vellutino, 1979). Training of perceptual skills usually does not bring any measurable improvement in reading (Adams, 1990). Successful remediation of poor reading is primarily related to improvement in linguistic (especially phonological) skills, much less perceptual ones (Vellutino et. al., 1996). Overall, there is little evidence for perceptual skills being a direct constraint on reading acquisition - at least it is so with respect to higher-level perceptual skills that demand conscious processing (see below). In contrast, evidence of causal links between language and reading has been produced in many studies. The factor that seems to mediate this connection is awareness of linguistic structures (metalinguistic awareness), in particular, awareness of sound structure of words (phonological awareness). Several studies found that early

25 metalinguistic awareness predicted later reading attainment even after possible concomitants (like IQ) were controlled for (for reviews, see e.g. Goswami & Bryant, 1990; Roth, Speece, Cooper & De La Paz, 1996). Phonological awareness is also if not fully specific then at least more important to reading and spelling than to other scholastic skills (e.g. Bradley & Bryant, 1983; Bryant, MacLean, Bradley & Crossland, 1990). Pre-school abnormalities and delays in language development, unless resolved early, are an important risk factor for reading failure (Stackhouse & Wells, 1997). Poor readers and dyslexies, although they may not experience any problems with oral communication (Snyder & Downey, 1997) were consistently found to be impaired on a wide variety of tasks that require access to a segmental (phonemic) level of language (Rutter & Yule, 1975; Stanovich & Siegel, 1994) and speed of naming (Wolf & Bowers, 1999). Successful amelioration of reading failure is usually related to a significant improvement in phonological skills (Vellutino et. al., 1996). Finally, experimental studies demonstrate that training in phonological awareness skills improves literacy. The improvement is typically small or even negligible if phonological awareness training is administered on its own, yet considerable gains occur if it is combined with tuition on letter sound-correspondences (Adams, 1990). Experimentally manipulated phonological awareness, combined with early alphabetic knowledge, explains about 12% of variance in later word recognition skills (see Bus & Vanijzendoorm, 1999 for the meta-analysis of the training studies). This quantification (which clearly suggests that there must be a host of other factors important to reading) probably downplays the role of phonology. Dyslexia research suggests that difficulties in phonological processing skills can have profound and lasting deleterious effect on reading development; an effect which can only be compensated for in a highly able person, with a great deal of effort and in favourable educational circumstances (e.g. Campbell & Butterworth, 1985). Although the specific mechanisms of interaction between reading and linguistic skills remain a hotly debated issue (and I shall return to those controversies later on), the available data support the general conclusion about the central role of linguistic processes in reading acquisition, and support the validity of the linguistic paradigm. Recently, after a period of relative dormancy, perceptual theories of reading made their reappearance, especially in the field of dyslexia research. The new theories linked reading problems to general difficulties with automatizing complex skills (Fawcett & Nicolson, 1994), processing rapidly changing visual stimuli (Lovegrove & Williams, 1993; Lovegrove, 1994) or rapid sound contrasts (Tallal et. al., 1996;

26 Merzenich et. al., 1996). There are also attempts at bringing the visual and auditory findings into one overarching theory of general deficit of rapid signal processing, caused by defects in magnocellular pathways throughout the brain (Livingstone, Rosen, Drislane & Galaburda, 1991; Stein, 1993; Stein, Talcott & Witton, 2001). The new perceptual theories differ from the old ones in two important aspects. They are less concerned with the higher-level processing of perceptual stimuli, occurring under voluntary, conscious control. Rather, they look at early stages of perceptual analysis: fast and default processes that take place at the intake of perceptual signal. Secondly, the new theories acknowledge the central (and causal) role of linguistic processes in reading. However, they seek an even more basic cognitive level at which those linguistic processes can, in turn, be described. At the moment, those theories are undergoing intensive empirical scrutiny (e.g. Wimmer, Mayringer & Raberger, 1999; Mody, Studdert-Kennedy & Brady, 1997; Cestnick &Coltheart, 1999), and it remains to be seen whether they will mark a new paradigm shift. The general problem may be formulated as follows: Are the linguistic processes the u/t/mate level of cognitive explanation for the development of recoding and orthographic skills? Alternatively, is it the case that those linguistic processes that are required for reading acquisition can be broken down into even more basic cognitive components, whieh are not modularly specific (not limited to language)? This controversy is likely to become central in the field of reading research in the coming years. Whatever the outcome, the conclusion about the central role of linguistic skills for reading seems to be secure.

1.2.3. What are the basic mechanisms of learning to read and spell?

The question posed here can be further broken down into several connected problems. Can children understand writing (that is - leam to decode) implicitly and spontaneously, or is explicit tuition necessary (or at least helpful)? What are the linguistic units children attend to when they try to relate written to spoken language? Does learning to read and spell recruit other-purpose learning mechanisms or does a specific mechanism exist that is uniquely suited to learning written language? The sides of this debate partially overlap with the ‘whole language’ and ‘code emphasis’ approaches outlined above, and much of the evidence discussed in relation to the role of decoding skills is also relevant here. The whole language theories are primarily concerned with writing as a meaning- carrier. The nature of print and writing is discovered (largely implicitly) by a beginning reader who generates, falsifies and refines his own hypotheses about them while trying

27 to understand texts. This process may be facilitated by enhancing her general linguistic development, but not by explicit code instruction. In contrast, the code-oriented approach maintains that any account of reading acquisition must explain, first of all, how children come to realise that writing constitutes a code (or, more precisely, a cipher: Gough 1992) and thus acquire alphabetic decoding skills. The beneficial effect of direct, structured instruction about the cipher (i.e. phonics teaching) is nearly always stressed within this approach. However, various code-oriented theories may differ with respect to the grain-size of sublexical phonological units (phonemes versus other intrasyllabic units, such as onset-rime) they consider critical for the development of decoding ability; and also may disagree as to how exp/ic/tS}ci\?> learning process is. The ‘contextualisf view of reading acquisition advocated by the whole language proponents finds some support in sociological and ethnographic research that points out the importance of trans-generational patterns of literacy transmission. Home background is crucial in providing information about the structure and purpose of reading, exercising pre-reading skills (like learning the alphabet, using pen and pencil, or working with a computer). Most importantly, the home environment may develop or hinder children’s motivation to become literate. Reading aloud to pre-school children, and engaging in a discussion about the text being read seems a particularly powerful factor (Adams, 1990), explaining some 8% of variance in later reading skills (Bus, Vanijzendoom & Pellegrini, 1995). The role of home background and learning opportunities (easy access to books, etc.) has also been powerfully confirmed in cross­ national studies of literacy (Elley, 1992, 1993). In terms of instruction, the case of precocious readers illustrates that becoming literate may indeed be a process of discovery, with minimal or no input from formal code instruction. Within the code-oriented approach, social and cultural factors (and the general linguistic competence which they influence) are treated as distal preconditions of reading success, which should not, however, be confused with the proximal mechanism of learning. This mechanism is often conceptualised in terms of three components (e.g. Byrne, 1998; Share, 1995). Children have to realise the phonological structure of words (i.e. develop phonological awareness), leam about the way phonemes are represented in writing (letter-sound correspondences) and combine those two areas of knowledge together. Once even minimal competence in those three components is acquired, phonological decoding becomes possible and the way is indeed open for further independent self-teaching. Learners can use their rudimentary decoding ability in combination with context-based guessing in order to identify unfamiliar words. In this

28 way, orthographic knowledge becomes gradually accumulated and decoding skills are strengthened further (Share, 1995). The majority of evidence is consistent with the hypothesis that children do not spontaneously discover the cipher nature of writing. They are capable of memorising a large stock of written words but are unable to generalise this knowledge in a way that would enable them to read unfamiliar words. This was shown in the real-classroom context with children being taught to read by the Took and say’ method (Seymour & Elder, 1986) as well as using the experimental procedure of learning an artificial orthography (Byrne, 1998). The latter series of experiments showed that children are able to generate hypotheses about writing and spontaneously break its cipher as long as it is based on the linguistic units that are naturally available to them - morphemes and syllables. However, children do not spontaneously hypothesise about writing as representing phonemes. Thus, they are unable to discover the alphabetic principle. However, once even minimal explicit instruction is provided, the principle may be grasped and generalised to new instances. Even literate adults, when faced with an artificial orthography are unable to spontaneously extract its underlying mapping principles, if they are unaware of the linguistic units (articulatory features: Byrne, 1992, experiment 1) comprising the code. Children who are left to discover the nature of print on their own, most often form misconceptions about reading. They attend to the most salient, often misleading cues (Gough, Juel & Griffith, 1992) or develop the idea that “reading is about remembering” a large stock of shapes. A number of studies showed that only reliance on phonological recoding enables fast growth in general reading proficiency - in particular, efficient accumulation of detailed orthographic representations of words. Reliance on other, visual and contextual, cues shows either no correlation, or a negative correlation, with subsequent progress in reading (Share, 1995; Gough, Juel & Griffith, 1992; Ehri, 1992). Even phonological reading errors (indicating reliance on imperfect decoding skills) are associated with better reading outcome than non-phonological errors that imply no use of phonological recoding (Stuart & Coltheart, 1988). The beneficial effect of exp/icit instruction for the development of phonological recoding and word recognition was demonstrated in a number of training studies with pre-readers or early readers. They showed that the teaching of phonological awareness or of letter-sound correspondences were not particularly beneficial for subsequent reading, if each was conducted in isolation. However, combining the two was clearly so (Bradley & Bryant, 1983; Adams, 1990, Byrne, 1998; Bus & Vanijzerdoom, 1999).

29 Studies exploring the effectiveness of various methods of teaching literacy bring converging evidence. It is true that children may be successfully introduced into reading with a wide variety of methods, and the factors such as teacher’s motivation, enthusiasm and belief in using “the right method” may be more important than method itself (Chall, 1967). Nevertheless, children taught by the methods that explicitly explore letter-sound correspondences usually do better than those taught otherwise, particularly in word decoding, but also spelling and reading comprehension (Bond, Dykstra, 1967/1997; Chall, 1967; Adams, 1990; National Reading Panel, 1999). Some authors, while acknowledging the crucial role of phonological recoding for reading development, question the necessity of explicit instruction. Instead they propose some kind of analogy-making mechanism by which children implicitly induce sound-symbol relations. A recent version of this position, which makes the distinction between explicit and implicit learning very clear, has been proposed by Thompson (2000). In his Knowledge Sources theory children may base their reading either on explicitly taught recoding or on lexicalised phonological recoding. The latter is a form of phonological reading that involves all relationships between letters and phonemes that children are able to implicitly induce from their reading vocabularies by detecting how several words containing common sound also share the same letters. Thompson maintains that children may acquire phonological decoding by means of such implicit induction and still show normal reading progress; the claims he supports with a number of studies exploring reading development in a whole-language instructional environment (e.g. Thompson & Johnson, 2000). The idea of implicit analogy-making as an early learning mechanism was also proposed by Goswami (Goswami & Bryant, 1990; Goswami, 1999). The possibilities and limitations of explicit (taught) and implicit (induced) mechanisms of learning to decode require further investigation. It seems that, while explicit instruction may succeed with relatively few written word exemplars (Byrne, 1998) implicit analogy making becomes possible only for children who have already accumulated considerable lexical knowledge (Thompson, 2000; Savage, 1998). Also, some experimental procedures designed to detect spontaneous analogy making (such as the clue word paradigm; Goswami, 1986) may, in fact, provide more direct and explicit teaching than initially assumed; their modifications that tried to remove the explicit cues resulted in reduced or removed analogy-making effect (Muter, Snowling & Taylor, 1994; Savage, 1998). The problem of the size of phonological unit used for recoding is perhaps most controversial; it will be discussed in more detail in chapter 2. At this point, it is

30 important to highlight the existing areas of consensus. All authors involved in this debate agree that, in every alphabetic orthography, learners have to understand that letters ultimately represent phonemes - that is, they must grasp the alphabetic principle (Byrne, 1998, Goswami, 1999; Seymour, Duncan & Bolik, 1999). The disagreements, however, occur regarding the relative role of other phonological units (especially intrasyllabic ones: onsets and rimes) in the discovery of the alphabetic principle and in recoding. One theory (Goswami, 1999; Goswami & Bryant, 1990) proposes that the application of the alphabetic principle to reading is preceded by (and partially contingent upon) an analogy-based decoding strategy, which detects invariance between intrasyllabic phonological units of onset and rime and corresponding orthographic structures. The contrasting theory (Seymour, Duncan & Bolik, 1999) maintains that the reliance on those larger intrasyllabic units, however important, occurs later in development and is preceded by (and contingent upon) an earlier appreciation of the alphabetic principle. The fact that use of a rhyme-based analogy-making strategy increases with overall reading proficiency (Bowey & Hansen, 1994) and seems to require some phoneme-level skills, such as phoneme identification or letter-sound decoding ability (Seymour, Duncan & Bolik, 1999) supports the latter hypothesis. Most authors agree that the mechanisms and resources employed for learning to read and spell are not task specific, but ‘borrowed’ from other cognitive processes. This consensus seems to bridge the whole-language and code-emphasis divide, although each side identifies altogether different kinds of cognitive resources that are recruited for the task of learning to read. For the code-emphasis approach, these resources are intrinsic to the phonological module, i.e. mechanisms of representing and processing the sound structure of words. This is consistent with describing reading in terms of emergent modularity, whereby resources and mechanisms that are specific to one module (such as storage, retrieval and manipulation of phonological codes) give rise to new cognitive structures and processes (such as orthographic lexicons, word recognition and decoding) that gradually acquire their own quasi-modular autonomy. Whole- language theories perceive reading as resting on general-purpose perceptual abilities and language comprehension (Smith, 1994)', and thus also imply some ‘borrowed’ resources. Few dissidents from this view propose that learning to read does not borrow other-purpose resources, but uses a learning mechanism unique to this task (Cossu &

1 “There is nothing distinctive about learning to read. Reading requires no special talent or unique brain development. Any child who can see well enough to distinguish one face from another in a photograph and who can understand the familiar language of family and friends has the ability to learn to read.” (Smith, 1994, p. 1). 31 Marshal, 1990; Cossu, 1994). This mechanism was recently characterised (Cossu, 1999) as a “metaphonological parser”, that is, “a cross-modal device for the (automatic) connection between phonology and other perceptual domains” (p. 226). It is understood to be modular in the strong sense of being innate and anatomically and functionally separate from other learning processes. The authors justify their conclusion with neuropsychological case studies, which bring evidence of reading being independent not only from general intelligence and perceptual and motor skills, but also from phonological awareness. The latter finding came from investigations of children with Down’s syndrome, who often could read very well despite low IQ and abysmally low performance on phonological awareness tests. Cossu (1999) also points to the limited effects of different types of remediation (including phonological training) on reading in developmental dyslexia, which, again, suggest a breakdown in a specific, autonomous learning mechanism. These radical conclusions have been criticised, both on theoretical and methodological grounds (Marcel, 1990; Butterworth, 1994). Theoretically, it seems implausible that reading (which is a recent cultural artifact) could correspond to some pre-wired brain modules. The hypothesis of reading being parasitic on other-purpose mechanisms that have a long evolutionary history (like phonological processes) is more plausible. Methodologically, some of Cossu and Marshall’s conclusions are based on a highly idiosyncratic group of subjects (children with Down’s syndrome), which brings doubts about the generalizability of findings. Cossu (1999) responds to those criticisms by agreeing that the cross-modal parser he postulates as the neural mechanism of reading indeed evolved long before reading was invented. It originally served other purposes, or perhaps was non-adaptive. Later it was recruited for the purpose of reading and writing as it was very well suited for those tasks - in fact, writing probably could not have been invented in the first place had this mechanism not already been in place. Phylogenetically, then, we are indeed dealing with the case of an existing mechanism being ‘hijacked’ for the purpose of new task. Ontogenetically, however, we end up with a specific task (reading) having its unique, pre-wired neural mechanism. Whatever final conclusions are reached in the debates outlined above, certain areas of broad agreement seem to have emerged already. Normal development of literacy in an alphabetic orthography requires, first of all, insight into its underlying principle of mapping letters onto phonemes - that is, breaking the alphabetic code. This process involves the formation of an intricate web of connections between orthographic units (letters and their strings) and sublexical phonological units (phonemes, but also

32 larger structures). While those connections are formed, phonemic structure of native words normally becomes accessible to conscious awareness. This conscious access to phonology may not be essential, but it is clearly helpful, and the teaching approaches that make phonological structures (and their mappings onto orthography) explicit generally produce superior effects in terms of reading progress. The interplay between phonological awareness, phonological recoding and word reading in the context of such explicit phonics teaching is one of the main topics of this thesis.

1.2.4. Is skilled word recognition phonologically mediated?

In the previous paragraphs I presented some evidence for the central and causal role of phonological recoding skills in the acquisition of literacy, including reading comprehension. Recoding skills enable an apprentice reader to deal with words that are unfamiliar in their written form and to expand her orthographic mental lexicon. The question, however, remains about the nature of skilled word recognition. Is activating the sound of the word always necessary to access its meaning, or can a familiar word be recognised directly without any phonological mediation? The controversy is often stated in terms of routes allowing for lexical access: single (always via phonology) or dual (both phonologically mediated and direct access are possible). Until recently, the dual-route theories dominated the research field, and their variant proposed by Max Coltheart and his co-workers gained a particularly wide acceptance (e.g. Coltheart, Curtis, Atkins & Haller, 1993; see also Ellis, 1993). This view proposes that familiar words are recognised directly: they have stored orthographic representations that are activated each time the word is encountered, and which trigger corresponding semantic and phonological information. The indirect route, on the other hand, is a default procedure for dealing with unfamiliar words, whereby a letter string is first sequentially converted into sounds, which in turn enables semantic access. An unfamiliar letter string, once assembled a few times, acquires its own orthographic representation and becomes subject to direct processing. The direct route has the advantage of being faster due to parallel, rather than sequential, processing of the orthographic input. The dual models of word recognition are well supported by the experimental evidence (McCusker, Hillinger & Bias, 1981) and the clinical data on acquired reading disorder, especially the dissociation between phonological and surface dyslexia (Ellis,

33 1993). Recently, however, they have been challenged by the data from some novel experimental paradigms, as well as by broader theoretical conceptualisations (especially the development of connectionism). The new evidence was summarised by Frost (1998), who made a particularly strong case for phonological recoding as a default intermediate stage of lexical access. He argued (similarly to Liberman, 1995) that, since reading is learned after spoken language, orthographic representations have to build on the existing phonological representations. The evidence he accumulated from several different experimental paradigms showed that - in contrast to Coltheart’s assumption - phonological recoding can be a quick, parallel and default process (occurring also when it interferes with task requirements), which precedes and facilitates lexical access. The important feature of this pre-lexical phonology is its underspecification: only minimal phonological clues, necessary for identifying the appropriate location in the semantic lexicon are activated. Skilled phonological recoding described here is thus very different from the overt or covert ‘sounding out’ observable in early stages of reading acquisition. It should not even be understood to involve any surface, detailed speech gestures or acoustic representations, but only an ‘abstract structural description’ (Frost, 1998, p. 73) of the underlying phonology. The hypothesis of a single route for reading has been excessively explored using computer simulations based on connectionist (parallel-distributed) processing principles (Seidenberg & McClelland, 1989; Harm & Seidenberg, 1999). The connectionist networks accomplish reading tasks for all classes of stimuli (frequent words, infrequent words, nonwords) with the same network of connections between semantic, phonological and orthographic sublexical units; a network not divided into distinct routes. Although the relative involvement of phonological activation changes as a function of stimulus properties (especially its frequency), phonology is never excluded from word identification, since this identification is always the product of the whole network. Although the debate between the protagonists of dual and single route models is largely orthogonal to the developmental issues covered by this thesis, it does affect the way one looks at the role of phonological recoding in reading development, especially the relation between recoding and orthographic skills. Within the dual route framework, phonological recoding and orthographic skills may be seen as dichotomous. The single route (or single process) approach, on the other hand, perceives orthographic competence as always underpinned by phonological processing, if partially autonomous. Each approach has different methodological implications. The former may attempt to

34 identify dichotomous classes of stimuli (or phases of reading acquisition); one requiring phonological recoding, the other not. The latter goes beyond this dichotomy and tries to observe how changing stimulus characteristics interact with reading experience, determining to what extent (and in what form) phonology is activated, specified and obligatory for lexical access. The literature on skilled word recognition is helpful in the developmental context, as it shows what word characteristics should be taken into consideration while investigating developmental changes in phonological processing (e.g. word frequency, orthographic consistency, neighbourhood size, type of task: naming vs. lexical decision, etc.; e.g. Underwood & Batt, 1996).

1.2.5. Are reading and spelling essentially the same process?

The formal comparison of reading and spelling reveals similarities as well as differences. Both tasks deal with the same “objects” - written words - but the information is processed in a different order: in reading, letter-to-sound; in spelling, sound-to-letter. In most orthographies, letter-sound and sound-letter mappings are not fully equivalent, or isomorphic (Hanna, Hanna, Hodges & Rudorf, 1966) so that only a partial overlap exists between knowledge necessary to read and that necessary to spell. Also, reading and spelling may be contrasted as recognition and recall tasks, respectively, which suggests that spelling may require more detailed knowledge, thus be more difficult, than reading. From the perspective of cognitive psychology, the problem may be stated in terms of the orthographic representations necessary to carry out reading and spelling (a single lexicon for both tasks versus separate lexicons for each). The evidence pertaining to this problem comes, first of all, from clinical studies of acquired disorders of written language. They show double dissociation between reading and spelling (Ellis & Young, 1988), although in the majority of cases both impairments coincide. Some experimental studies with adult subjects were also carried out, which required making judgements about the accuracy of one’s own spellings. They brought mixed results, with some authors finding discrepancies between spellings and decisions on their accuracy (suggesting separate lexicons: Campbell, 1987), and others reporting consistent responses (Holmes & Carruthers, 1998). The developmental data regarding the relationship between reading and spelling come from various sources. Numerous correlational studies consistently show at least moderate association between both skills, and frequently exceeding r=0.70, which is

35 close to the reliability values expected of tests measuring the same ability (Ehri, 2000). Yet it is also commonly observed (though few systematic studies attempted to qualify this) that the development of proficient spelling is much slower than the development of reading, and a large proportion of people never fully master spelling skills. Spelling surveys carried out among teenage students and young adults consistently find a sizeable (and sometimes surprisingly high) incidence of errors (Upward, 1992; Wing & Baddeley, 1980; Grzçdowa, 1976). Some indirect evidence suggests that weak spelling skills and a developmental asynchrony between reading and spelling may be limited to complex, inconsistent orthographies with their non-reversible letter-sound correspondences (Upward, 1992; see also chapter 3). Much of the discussion about the developmental relationships between reading and spelling was triggered by cases of “unexpected spelling problems” (Frith, 1980), i.e. developmental dysgraphia in the absence of apparent reading difficulties. The possible explanations included visual problems (Goulandris & Snowling, 1991); particularly encoding serial order of visually presented stimuli (Romani, Ward & Olson, 1999). Yet most explanations focus on the atypical strategies of dealing with print exhibited by poor spellers. Frith (1980) approached the problem assuming different strategies are required for reading and spelling. Successful word recognition may be based on only partial letter cues, but good spelling requires the retrieval of fully specified, letter-by- letter sequences. It may be said, with some degree of simplification, that reading is more ‘global’, but spelling more ‘analytical’ and ‘phonological’ (see also Goswami & Bryant, 1990 for similar considerations). Unexpectedly poor spellers are generally biased toward the global strategy of dealing with print. Such excessive reliance on partial cues still allows for efficient reading (although more fine-grained analysis reveal subtle problems in this domain, too: Goulandris & Snowling, 1991) but is clearly insufficient for spelling. The errors of unexpectedly poor spellers remain phonologically plausible, but disregard conventional orthography. Such children “spell by eye” or “the way they read”, missing the fine details of words’ spelling. Frith (1980) did not find her unexpectedly poor spellers deficient in any way (especially in terms of decoding skills) and understood their difficulties to stem merely from a ‘strategic choice’ that is too rigid. There must, however, be some reasons for such choice. The predominantly global approach to print is likely to be an “echo” of earlier problems with phonological awareness and decoding. Those difficulties could be small and become resolved over time, yet the early preference for a global strategy (which was adopted as a compensatory measure) persists. Such interpretation is

36 consistent with the fact that the decoding skills of unexpectedly poor spellers, although within norm, are usually below average (Frith, 1980). Also, people with specific spelling problems usually show some history of reading difficulties (Goulandris & Snowling, 1991). Some more pervasive developmental difficulties affecting both reading and spelling can also be explained in terms of a compensatory strategy of global or lexical processing, which was adopted in the face of transient early difficulties in decoding and which persisted until adulthood, although it was no longer necessary (Funnell & Davison, 1989). The contrast between different demands and strategies of reading and spelling was also incorporated into the models of normal literacy acquisition proposed by Frith (1985) as well as Goswami & Bryant (1990). The developmental process they proposed may be described as dialectic. Reading and spelling first emerge independently, each underpinned by a different processing strategy. However, the global, lexicalised reading process starts to interact with the analytic, sequential, decoding-based spelling process, triggering the development of orthographic representations that can serve both tasks. Orthographic representations represent higher-order synthesis: they are both highly specified and lexicalised, which allows for reconciliation of conflicting demands of speed and accuracy. The problem of the relationship between the development of reading and spelling may, then, be posed as follows: How does their interaction bring about proficient orthographic skills? Orthographic information is accumulated from reading experience (print exposure: Stanovich, 1986; Cunningham & Stanovich, 1997). However, the efficiency of this accumulation shows considerable individual variation. Its most important constraint is the quality of phonological recoding, which allows print exposure to be transformed into a successful self-teaching opportunity (Share, 1995). Phonological skills provide a ‘frame’ (Snowling, Hulme, Wells & Goulandris, 1992) on which orthographic information can be organised. The second constraint is the individual cognitive style of print processing, as discussed above. A processing style that is too global makes it more difficult to lay down orthographic representations that are fully specified. Visual processing may also further constrain the efficiency of orthographic learning (at least in some cases: Goulandris & Snowling, 1991). Severe problems with phonological recoding would strongly constrain orthographic learning, with deleterious effects for both reading and spelling. Mild (or compensated) phonological difficulties, limited print exposure, or global reading strategies would result in mild orthographic difficulties, apparent mainly in spelling. Such

37 conceptualisation can accommodate the data on the developmental course and remediation of dyslexia, which show that poor spelling is the most persistent and stubborn problem. It is also consistent with the incidence studies, which show few (if any) cases of dyslexia without dysgraphia, and find the ‘dyslexia + dysgraphia’ profile to be associated with more serious cognitive deficits than the ‘dysgraphia only’ condition (e.g. Bogdanowicz, 1985).

1.3. MODELS OF READING ACQUISITION.

Cognitive psychology made it popular to construct mode/s of various behavioural and mental phenomena to be used as tools for description and explanation. Models may be defined as “a kind of a metaphor which is not meant to be taken literally but is more of a suggestion as to how we might think of people’s behaviour, again, in order to understand it better. A model entails a single, fundamental idea or image and is not as complex as a theory (although sometimes the terms are used interchangeably)” (Gross, 1996, p .ll). The boundary between models and theories is indeed fuzzy; models are usually employed as a user-friendly, ‘distilled’ way of introducing a theory, frequently employing visual means of presentations (e.g. flow charts). Savage (1995) provided a specification for a comprehensive model of reading acquisition:

It should be causal: provide not only descriptive account of change in ability (even if couched in terms of processes and strategies) but also discuss the nature of mechanisms that cause change. The evidence must be ecologically valid: be demonstrably relevant to natural reading situations (in the classroom, at school, etc.) It must be comprehensive in a sense of accounting not just for initial phases of literacy but also higher levels of competency. This implies that developmental models should eventually map onto some model of adult reading. It should consider the nature of the orthography the child is dealing with and how it may affect the nature of the reading task. The following section discusses how different models of literacy acquisition meet those general criteria. This picture will be painted with broad strokes: instead of detailed description and evaluation of individual models the main types of models will be contrasted, and their inherent potential and limitations discussed. In other words, 1 will try to identify general ways of theorising about literacy development (or metaphors of that development) that can encompass a maximum of existing data in the most parsimonious way.

38 1.3.1. Stage and phase models

A family of models that gained particularly wide currency presents reading acquisition as a succession of stages or phases, with each phase defined by a qualitatively different processing strategy (e.g. Marsh, Friedman, Welch & Desberg, 1981; Frith, 1985; Ehri, 1995). Models of this type vary considerably in terms of the number of phases proposed, their labelling and description (see table 1-1). However, in a majority of cases, this variability can be reduced into the same three broad developmental periods. The initial one is characterised by a predominantly global, instance-based processing of words. Words are identified mainly via unsystematic use of visual cues (such as salient letter parts), with decoding skills playing a secondary (if any) role. Some authors (e.g. Ehri, 1995) maintain that skills developed during this initial period still do not constitute ‘proper’ reading insofar as no appreciation of the alphabetic principle is evident. Insight into the nature of alphabetic orthography is the main achievement of the second period, where children acquire basic decoding skills, focusing on basic, ‘small unit’ letter-to- sound correspondences. The following third period involves the mastery of orthography-specific knowledge, characterised by complex, conditional rules and corresponding to the morphological level of language. This is usually described as the end point of development, as far as word recognition (and spelling) are concerned. A few authors (e.g. Chall, 1996) proposed further stages characterising the development of reading comprehension.

Marsh et. al. Frith Kirby Ehri (1995) Bakker (1990) Chall (1996) (1981) (1985) (1990) prereading glance and ^uess logographic global pre-alphabetic elementary reading (right hemisphere, sophisticated partial perceptually-based) guessing alphabetic

acquisition of alphabetic analytic fully alphabetic initial reading or decoding simple grapheme stage -phonem e correspondences

the skilled reader orthographic synthetic consolidated advanced reading confirmation, fluency, alphabetic (left hemisphere, ungluing from print linguistically based)

meta- reading for learning the com pre­ new hension multiple viewpoints construction and reconstruction - a word view

Table 1-1. Schematic comparison of some influential stage and phase models of literacy acquisition (based on Krasowicz-Kupis, 1999, p. 81). 39 Stage and phase models are attractive through their descriptive parsimony. A simple set of underlying notions (stages, strategies) encompasses both quantitative and qualitative developmental changes. Stage models are particularly valuable in the applied context of education, as they take into consideration overt reading behaviour (such as sounding out) and allow for easy classification of learners as ‘falling within a certain stage’. However, they were also met with serious criticisms, especially during the last decade. Some of these have challenged the very assumption of reading as a stage process. Following Piaget, the notion of a stage process bears a tacit assumption of a universal (i.e. culture independent) sequence of discrete cognitive gains. This aspect of universality, in particular, may be inappropriate in the context of reading, which (unlike such ‘natural’ skills as speaking or object recognition) is not acquired spontaneously and relates to a cultural artefact. At least some purported universal stages of reading acquisition may simply be a reification of the type of reading instruction children happen to be exposed to. This criticism is particularly directed at the notion of an initial, purely visual (‘logographic’: Frith, 1985) phase, which probably occurs only in the context of the ‘look and say’ teaching method that was developed as an attempt to deal with the specific demands of inconsistent English orthography (Wimmer & Hummer, 1990; Wimmer, 1990; Ellis, 1993). Most phase models avoid this ‘false universality’ criticism, however, as they explicitly reject the strong stage assumption (stage A is a precondition of B) and talk about reading as a sequence of phases (phase A usually precedes B, but B does not require A to develop). However, many authors also question this weaker assumption. Literature reviews (e.g. Stuart & Coltheart, 1988; Share, 1995) suggest that processing strategies applied to written stimuli at any particular point in time vary considerably depending on stimuli properties (such as their familiarity and orthographic complexity: see the previous section). Thus, the choice of processing strategy is predominantly stimulus-driven, and children may have a number of strategies at their disposal at any given time (Share, 1995). Phase models, then, result in an oversimplified view of reading acquisition if they treat the strategy that is used most frequently at any given phase of development (for those written stimuli that lie within a typical range of experience) as the only one that is available at the time. Some phase models (e.g. Kirby, 1990) partially accommodate this criticism as they describe the transition into higher phases as the broadening of a strategic repertoire, rather than the mere superseding of one strategy by another.

40 Even if we do assume the predominance of one strategy at any given point in development, we must take individual differences into account. The same absolute level of performance accuracy may be achieved with the help of different processing strategies (Stuart & Coltheart, 1988; Beminger, 1994). Such dissociation between quantitative (attainment) and qualitative (processing strategies) aspects of performance is, again, difficult to accommodate within a standard phase framework. Finally, phase and stage models tend to be more descriptive than causal, although some of them (e.g. Frith, 1985 with her notion of developmental steps) do propose some mechanisms that bring about the transition between the stages. Crucially, these models may confound description and explanation, due to implicit assumption that the output of a cognitive system (reading behaviour) directly reflects the internal organisation of this system.

1.3.2. “Processes and resources” models.

Under this label I describe models of reading acquisition, which borrow some crucial elements from the stage framework (e.g. the concept of reading strategies), yet dispose of the assumption of a single sequence of phases. Instead, they propose a parallel development of two or more basic modes of processing, the rudiments of which are present from the very beginning of learning to read. The interaction of those distinct modes, processes or strategies eventually brings about proficient reading skills. A model of reading acquisition proposed by Goswami and Bryant (Goswami & Bryant, 1990; Bryant, MacLean, Bradley & Crossland, 1990; Goswami, 1999) is an example of this category. Following Frith (1985), they suggest an initial dissociation between reading and spelling. Phonemic awareness and the alphabetic principle are first learned and applied for spelling. Initial reading, on the other hand, proceeds with the help of the analogy-making mechanism that is underpinned by the awareness of larger, intrasyllabic phonological units (onsets and rimes), not phonemes. Eventually, the two different strategies merge, and the alphabetic recoding ability developed for spelling becomes incorporated into reading. The model stresses the importance of early sensitivity to intrasyllabic phonological units. This sensitivity contributes to reading both directly (enabling analogy making) and indirectly (facilitating the development of phonemic awareness that is cmcial for spelling and, later on, for reading as well). The model proposed by Goswami and Bryant retains the phase framework insofar as it proposes age-related, qualitative change in reading strategies. Also, the

41 hypothesis of a universal, sequential development of phonological awareness (from large to small units) reflects the stage assumption. However, the emphasis is put on different skills and strategies that operate at the same time in different contexts (reading vs. spelling) and their interaction as the condition of learning success. Another model proposing the availability of different developmental resources at the same time was proposed by Seymour (1997, 1998) and referred to as the dual­ foundation model. It postulates two parallel processes that account for the acquisition of orthographic knowledge. One - logographic - deals with words as units and allows one to acquire word-specific information (sight vocabulary). The learning mechanisms proposed here are, however, markedly different from those entailed in Frith’s (1985) concept of the logographic stage: global shape recognition or visual cue identification play but a marginal role; word representations encoded by the logographic process normally consist of at least partial information about letter identities. The other, alphabetic process involves sequential letter sounding and assembly. It is triggered by unfamiliar words and is closely tied to phonemic awareness. Interaction of the alphabetic and logographic processes leads to the development of the Orthographic Framework. It contains knowledge of correspondences between spelling and pronunciation that extends beyond individual letter-phoneme mappings but links letter sequences with the phonological structure of a syllable. The orthographic framework is a generalised mode of representation: it entails word-specific knowledge yet also allows unfamiliar items to be read without requiring the alphabetic process (that is, sequential letter sounding). The capacity of the orthographic framework is essentially limited to single morpheme mono- and bi-syllables. Longer words of complex morphemic structure (e.g. containing prefixes or suffixes) are processed within the Morphographic Framework. This component emerges from the Orthographic Framework (which contains representations of individual syllables building longer words) and linguistic - especially morphological - awareness. Seymour’s model is consistent with the stage assumption insofar as the highest, morphographic framework requires earlier formation of the orthographic framework, which, in turn, cannot develop unless the two foundation processes have already been established at least partially. However, no sequential order in the development of those foundations is proposed. An interactive-compensatory model of reading proposed by Stanovich (1980) should also be mentioned. It was set up to solve the problem of the relationship between the different levels of processing involved in word recognition: low-level (sublexical

42 analysis of individual words) and high-level (syntactic and semantic, which allow for context-based inferences). Stanovich argues against the serial model of processing (whereby information is relayed sequentially through the processing levels) and for the interactive one. Different levels of analysis (e.g. feature extraction, orthographic, lexical, syntactic and semantic) operate simultaneously, each seeking to synthesise the stimulus on its own, yet using and being constrained by the information coming from other levels. This way, a process at any level can compensate for deficiencies at any other level. It implies that, as one level is deficient, the relative importance of other levels increases. For example, a reader with poor word decoding skills may rely more on the contextual factors as a compensatory source of information. The model was developed primarily to account for individual differences in processing strategies used by good and poor readers of the same age. However, it also has potential for explaining developmental change in reading strategies (e.g. a decrease in reliance on context-based inferences accompanying an improvement in decoding ability) and has been used in this capacity (cf. Share, 1995). In comparison with the phase framework, the processes and resources models seem more capable of accounting for individual differences in reading at the same level of ability. In fact, explaining individual variance may be their explicit aim (cf. Stanovich, 1980). Individual preferences for certain strategies are explained by the relative strength or weakness of different component (foundation) processes. An account is given for the existence of different subtypes of developmental dyslexia (Stanovich, 1980; Seymour, 1999) - instead of explaining them in terms of developmental arrest at different phases of reading development, as phase models do (Frith, 1985). Also, process and resources models are generally more specific with respect to the mechanism of development, especially the role of phonological skills (although they may differ significantly in terms of how this role is formulated - the issue I shall return to in the next chapter). However, just as for the stage models, the process models seem much more concerned with the early period of development than with the more advanced one. Most of the empirical evidence collected or interpreted in the context of those models relates to the basic (foundation: Seymour, 1999) processes, and attempts to map those developmental models onto the adult architecture of skilled reading are sketchy.

43 1.3.3. Connectionist models

Connectionist approaches to learning and knowledge representation have been gaining popularity in the cognitive sciences in the last two decades; this impact is felt perhaps particularly strongly in the field of reading research. Most connectionist models of learning are the variants of the same core architecture. They constitute a network built of two or more sets of basic units (representing different aspects of input and output) interlinked through adjustable connections. Information is devolved throughout the system and stored in the strength of the connections between input and output. This non-localised, parallel-distributed (Seidenberg & McClelland, 1989) mode of processing the information means that the distinction between item-specific and mle-general knowledge is effectively abolished. In the context of reading it implies the rejection of any dual-route architecture that proposes separate procedures for reading familiar and unfamiliar words (e.g. Coltheart, 1978a). Even further, it implies that the assumption of lexical entries - distinct entities stored at some specific location within the system and representing information about individual words - is not required. Connectionist networks are capable of learning, which is based on the associative principle (repeated pairing of input with output). Some form of feedback is usually provided to the network after each trial, allowing it to adjust the weights on its connections, and thus make its performance more accurate. The network usually contains the intermediate level of ‘clean-up’ units to optimise the learning process. The connectionist models of reading (e.g. Seidenberg & McClelland, 1989; van Orden, Pennington & Stone, 1990; Hinton & Shallice, 1991) may consist of input orthographic units (representing letters, letter triplets or onset-rime structures), output phonological units (representing phonemes, phonetic features or their triplets, onset- rimes); sometimes also semantic units corresponding to some arbitrarily specified dimension of the semantic space (such as ‘green’, ‘sweef, ‘animate’, ‘flying’ etc.) Arguably the most attractive aspect of connectionist models is the possibility of mathematical formalisation, which allows the models to be physically implemented (in the form of computer neuronetworks) and tested against the predictions coming from human studies. So far, parallel-distributed computer neuronetworks set up to simulate reading prove capable of replicating a range of effects observed in human studies of skilled word recognition (such as frequency by regularity interaction: Seidenberg & McClelland, 1989). Manipulating network parameters (limiting the amount of learning

44 experience, removing connections or hidden units, or reducing the rate at which information can be accumulated within the system) can simulate different forms of acquired and developmental dyslexia (Hinton & Shallice, 1991; Manis, Seidenberg, Doi, McBride-Chang & Peterson, 1996; Harm & Seidenberg, 1999). From the developmental point of view, connectionist models are attractive as they effectively remove the problem of ‘bridging the gap’ between the learning process and the skilled performance. This is the problem faced by other classes of developmental models described here, and even more so by some models of skilled word recognition, which - like the dual route account - are essentially static in the sense of describing mainly the end product of the developmental process. Within the connectionist framework, learning and skilled performance are accounted for by the same structural framework of units and interconnections, and a unitary processing mechanism. Growth in competence corresponds to the gradual change and refinement in the pattern of weights. This itself can lead to qualitative change in the nature of performance, or the emergence of radically new structures. Connectionist modelling can also account for the role of phonology in reading acquisition (e.g. it can show how underspecified phonological representations impair the rate of learning: Harm & Seidenberg, 1999), individual differences in reading strategies, or compensatory mechanisms (which are understood to be the consequence of changing network parameters, such as removing certain types of units or connections). The blurring of the distinction between instance-based and rule-based learning (that is, the assumption of a single processing route for all types of words) is perhaps the most hotly contested aspect of connectionist models. It is criticised both in the specific context of reading (Coltheart et. al., 1993; Zorzi, Houghton & Butterworth, 1998) and in the broader context of human language processing (Pinker, 1994) The dispute is not easy to settle in the light of experimental data on skilled human reading performance: it seems that both connectionist and dual-route models can account for the pattern of findings rather well, and no clear winner is in sight (although the protagonists of each view strive to prove otherwise: Coltheart et. al., 1993; Harm & Seidenberg, 1999). The decisive evidence is more likely to come from brain studies (neuroimaging of normal and impaired reading, and neuropsychological studies of acquired dyslexias). It must be acknowledged, however (against the strong claims of connectionism), that the system that mimics human performance very well (such as a computer neuronetwork) may do so by employing learning mechanisms totally different from those used by the human brain. Indeed, at least the most popular class of connectionist models (implemented in

45 so called supervised networks: Seidenberg & McClelland, 1989) contains some elements that are not plausible in the context of normal learning to read (e.g. the assumption of immediate feedback following each and every trial) or some learning algorithms that are generally implausible biologically (e.g. back-propagation through time). Also, even those neuronetworks that are very successful in mimicking the qualitative features of human reading performance usually leam much slower (sometimes by several degrees of magnitude). From the developmental point of view the connectionist account is problematic through its assumption of fully parallel processing. Although robust evidence from various sources (e.g. eye movement studies: Rayner, 1998) shows that skilled readers indeed process strings of letters in parallel under most circumstances, the same is not the case with apprentice readers who were often shown to use serial processing (e.g. sounding out and blending). The parallel-distributed framework, unlike other models previously discussed, does not leave obvious room for such strictly serial processes. A solution to some of the problems discussed above may be offered by the recent development of connectionist dual process models of reading, which implement dual-route architecture (separate whole-word and sublexical processing mechanisms) in a connectionist network (Coltheart et. al., 1993; Zorzi et. al., 1998). Connectionist dual­ process models are capable of learning (they are, therefore, developmental, not static) and can mimic the acquisition of orthographic rules (i.e. grapheme-to-phoneme mappings) as well as serial decoding (e.g. through the deployment of a competitive queuing algorithm).

In the light of the general criteria for the evaluation of models of reading development adopted in the beginning of this section, no model is fully satisfactory, and every model type reveals its own unique profile of strengths and weaknesses. Stage models may be particularly adept at describing developmental changes in overt reading behaviour. Processes and resources models as well as connectionist models deal thoroughly with the relationship between phonological skills and reading. Connectionist models have the advantage of computational formalisation and deal most directly with the question of learning mechanisms. No single theoretical framework can, thus, be recommended as being fully comprehensive or generally superior to all the others. At present, some degree of theoretical eclecticism seems, then, inevitable in explaining reading acquisition. Indeed, some of the models discussed so far explicitly combined elements

46 taken from different frameworks (e.g. the stage framework and connectionism: Seymour, 1999; or a dual-route framework and connectionism: Coltheart et. al., 1993; Zorzi et. al., 1998).

47 CHAPTER 2

LITERACY ACQUISITION AND LINGUISTIC SKILLS

In the previous chapter literacy was characterised as a set of skills that are intrinsically linguistic. In this chapter I will try to justify this assertion from the developmental perspective. This will be attempted by exploring how acquisition of reading and writing is causally linked with different aspects of language development. Different theories of causal connection will be discussed, based on data drawn from three main categories of developmental studies: ability-match comparisons; longitudinal and concurrent correlational investigations; and training or intervention experiments. The task is complex since practically all aspects of language processing have been postulated to have links with literacy acquisition. These can be classified in at least three different ways:

1. By linguistic domain: processing within different language sub-modules: phonology, morphology, syntax, semantics and pragmatics. 2. By location along the language processing route: input processes (reception), internal representations (storage), output processes (retrieval, production). 3. By the degree of involvement of explicit control: automatic, obligatory processes, as opposed to those requiring linguistic awareness.

The following review will generally follow the first classification: I shall separately discuss different domains of linguistic processing in relation to literacy, with particular emphasis on phonology and grammar (including both syntax and morphology). Across different linguistic domains, I will focus on the development and role of explicit processes (i.e. linguistic awareness). Given the scope of the research in this thesis, the review will focus on the connections between linguistic processing and the acquisition of word-level literacy skills (decoding, recognition and spelling).

48 2.1. PHONOLOGICAL PROCESSING

The notion of phonological processing (or phonological skills) refers to the mastery of the sound structure of a language, and the use of this when listening, speaking, reading or writing (Wagner & Torgesen, 1987; Wagner, 1988; Wagner, Torgesen, Laughton, Simmons & Rashotte, 1993). Historically, research on phonological processing in relation to literacy was independently pursued in three main areas (Wagner & Torgesen, 1987): phonological awareness, phonological coding in working memory, and retrieval of phonological codes from long-term store (usually operationalized as confrontation naming or rapid naming). Recently, these three main strains seem to have merged into one research programme (e.g. de Jong & van der Leil, 1999; Wagner et. al., 1993, 1997). For the following review, however, the division between awareness, memory and retrieval will be retained: it is not only helpful in presenting the empirical findings, but also reflects, to some degree, the actual structure of phonological skills (see sections 2.1.2-2.1.3.).

2.1.1. Phonological awareness

2.1.1.1. The concept of linguistic awareness

Before proceeding to review the empirical data, the concept of linguistic awareness and its relationship to other aspects of language processing needs explanation. Linguistic awareness (also referred to as: metalinguistic awareness or metalinguistic skills) implies explicit access to linguistic structures, and the possibility of conscious (voluntary) control over them. Different authors (Tunmer, Pratt & Herriman, 1984; Gombert, 1992; Krasowicz-Kupis, 1999) emphasise different attributes of being “linguistically aware”; some common threads, however, can be identified: • Objectification of language: it ceases to be merely a (transparent) medium or tool of communication, but also becomes an object of reflection and play. • Ability to analyse and manipulate linguistic structures. • Control over language that is conscious and deliberate, as opposed to the tacit knowledge necessary to speak and understand speech. • Insight, control, analysis and manipulation that are instance-free, i.e. presuppose the grasp of underlying rules. 49 All authors also agree in stressing the functional role of linguistic awareness. Children acquire explicit control over linguistic structures as it helps them to handle growing demands of communication - especially using written language. Given the above characteristics, an analogy may be drawn between the child gaining linguistic insights, and the work of an adult linguist (Krasowicz-Kupis, 1999). Both treat language as the subject of inquiry, and each of them build, in their own way, a theory of language. This analogy is implicit in endowing children with meM-linguistic abilities, since the term ‘metalinguistic’ was originally used only in the context of formal scientific investigations. The analogy has its limitations, too. Whereas a linguist has to use some meta-language (a set of formal notions used to describe language), a linguistically aware child may have insights that enable her to control and manipulate language at will, without necessarily being able to utilise such formal descriptions (she might be able to verbalise her insights but informally, e.g. through prosodic manipulation: “Not WAbbitt but RAbbitt”). The concept of linguistic awareness may be construed as a developmental continuum that is orthogonal to other aspects of linguistic processing. Thus, processes within different language sub-modules (phonology, morphology, syntax, etc.) and having different locations along the processing path (reception, production), may be subjected to explicit control. Some disagreement exists as to what tasks (and what ordinary manifestations of language use) may be interpreted as true manifestations of linguistic awareness (Roth et. al., 1996; Krasowicz-Kupis, 1999). Those disagreements are not surprising if we assume that linguistic awareness is indeed a continuum or it develops gradually across a number of levels or stages (e.g. Gombert, 1992). Table 2-1 lists some aspects of linguistic functioning that are commonly seen as the manifestations of linguistic awareness (cf. Gombert, 1992; Krasowicz-Kupis, 1999).

50 language language manifestations of metalinguistic skills domain units phonology syllables, • making up poems intrasyllabic units, • sound-based games (e.g. secret languages) phonemes • identification of target phonological units • segmentation and blending • manipulation: deletion, substitution and replacement of target phonological units morphology words • correction and self-correction of grammatical errors & syntax phrases • judging the grammatical acceptability of sentences sentences semantics & words • understanding and appreciation of figurative language and linguistic pragmatics sentences humour (e.g. puns) texts • detecting contradictions and inconsistencies • adjusting the style to the listener/reader • structuring the written/spoken stories • using appropriate stylistic conventions Table 2-1. The scope of metalinguistic skills. Adapted from Krasowicz-Kupis, 1999, p.56.

2.1.1.2. Development of phonological awareness

Phonological awareness is the subset of linguistic awareness skills that enables one to access and manipulate the sound structure of language. The cumulative body of evidence shows clearly that the developmental course of phonological awareness varies with the size of phonological elements involved (syllables, intrasyllabic units, phonemes). The awareness of syllables seems to occur first. The classic studies of Liberman and her colleagues (e.g. Liberman, Shankweiler, Fisher & Carter, 1974) showed that some 4-year olds and many 5-year olds were able to tap the number of syllables in a word (or lay out tokens corresponding to syllables: Treiman & Baron, 1981). This achievement occurred spontaneously, without any prior instruction and in children who were pre-literate. The availability of syllable level awareness to many children before the onset of formal literacy instruction has since been confirmed in many languages (Italian: Cossu, Shankweiler, Liberman, Katz & Tola, 1988; Japanese: Mann, 1986; Chinese: Ho & Bryant, 1997a, b; Polish: Krasowicz & Bogdanowicz, 1997; Krasowicz- Kupis, 1999). The ‘natural’ character of this ability is confirmed by the finding that many illiterates and near-illiterates can also segment words on the level of syllables (Morals, Bertelson, Cary & Alegria, 1986; Morals, Content, Bertelson, Cary & Colinsky, 1988; Lukatela, Carello, Shankweiler & Liberman, 1995).

51 The awareness of intrasyllabic units also emerges early. It is widely agreed that a syllable is not merely a string of phonemes, but a hierarchical structure that clusters phonemes into two intra-syllabic units. A syllable divides either between the initial consonant or consonant cluster {onset) and the vowel with following consonants {rime), e.g. TW - 1ST; or between initial consonants with the vowel {body) and the remaining consonants {coda), e.g. TWI - ST. There are arguments from linguistic theory, experimental data and the analysis of spontaneous language use (speech errors, word games) for either onset-rime and body-coda models of syllables (Duncan, Seymour & Hill, 1997). However, most experimental studies with pre-school and early school children found onset-rime division to be most naturally available to a child (Kirtley, Bryant, MacLean & Bradley, 1989; Treiman, 1992). This division corresponds to poetic devices of alliteration and rhyme' (Goswami & Bryant, 1990). Classic studies on that topic, carried out by Bryant and colleagues (Bradley & Bryant, 1978, 1983) employed sound categorisation tasks (also known as oddity tasks) in which participants had to say which one of three or four monosyllables was the “odd one” because it did not share a complete rime or onset with the others. Many 4- and 5-year olds were found to be sensitive to onset-rime division; a finding corroborated by a number of subsequent studies (for review and discussion see Goswami & Bryant, 1990; Goswami, 1999). Even some 3-year olds could perform this task when pictures were used in order to remove memory load (MacLean, Bryant & Bradley, 1987). The validity of the sound categorisation paradigm for the assessment of phonological awareness is disputable, however. It seems that the detection of an odd-sounding item in the stream of monosyllables may be accomplished with a low-level phonemic discrimination that does not necessarily require explicit access to sound structure of the stimuli. Thus, oddity tasks, although undoubtedly measuring phonological processing, may not measure awareness. A recent validity study (Schatschneider, Francis, Foorman, Fletcher & Mehta, 1999) seemed to confirm these reservations, as it found the oddity task to be a poor indicator of a general latent factor of phonological awareness. However, early developmental emergence of rime-onset awareness has also been confirmed with other methods. Some 4-year old children are capable of forced-choice rime detection (they can say which two of three or four words rhyme: Muter, Hulme & Snowling, 1998) as well as onset and rime production (generating exemplars that rhyme or share alliteration

Strictly speaking, masculine rhyme (see chapter 3) 52 with a target word: MacLean et al., 1987; Stuart, 1986, reported in Bunn, 1995). Most importantly, studies of pre-school language play demonstrated the children enjoy, remember and make poems, both spontaneously and in experimental settings (Dowker, 1989). These are often based on phonological devices of rhyme and alliteration, although marked cross-linguistic differences are observed in terms of frequency of their use (Dowker, Pinto, 1993; Dowker, Krasowicz, Pinto, Roazzi & Smith, 1998; see also chapter 3). The ability to rhyme seems, again, at least partially independent of literacy. This is demonstrated by the superior rhyming abilities of illiterate or semi-literate Portugese and Brasilian oral poets (Morals, 1991; Roazzi, Dowker & Bryant, 1993). In contrast, the ability to perceive words in terms of their phonemic structure, and the ability to manipulate those phonemic strings - that is, phonemic awareness - is linked to instruction in alphabetic reading and spelling. Numerous studies have confirmed the seminal findings of Bruce (1964) and Liberman et. al. (1974) that pre­ literate children find it very difficult to delete a specific phoneme from a word, or tap a number of phonemes in a word. Such lack of explicit control over phonemic structure is particularly striking in children who are fully pre-literate (i.e. lack not only reading ability but also knowledge of letter names or sounds), although such children may perform with some degree of success on the tasks that involve phoneme-level representations, yet do not require explicit segmental manipulation (phoneme oddity, detection and blending: Burgess & Lonigan, 1998; Naslund & Schneider, 1996; Wimmer, Mann & Signson, 1999). However, even short acquaintance with alphabetic writing, (evidenced by partial letter knowledge and minimal decoding skills) is associated with significant growth of phonemic awareness. This was demonstrated in developmental studies (e.g. Bowey, 1994; Wimmer, Landerl, Linortner & Hummer, 1991) as well as those involving semi-literate adult participants (Lukatela et. al., 1995). The specific connection between alphabetic literacy and phonemic awareness is also evidenced by studies of people who read non-alphabetic scripts. The comparison of native speakers of Chinese using only the traditional, morpho-syllabic script, with those taught to use the alphabetic orthography (Pinyin) found the former very poor on phoneme deletion and addition (Read, Zhang, Nie & Ding, 1986). Likewise, Japanese six-year old children were much poorer than their American counterparts on phoneme tapping, whereas no difference was observed for tapping or deleting syllables. Although the users of syllable-based Japanese orthography do eventually become aware of

53 phonemes, the development of these skills is very protracted in the absence of alphabetic facilitation (Mann, 1986). The picture of phonological awareness development, which I sketched separately for different size-levels of phonological units, becomes more complicated when task- specific factors are taken into consideration. Performance on all levels is influenced by the nature of the required operation, and the characteristics of the phonological material. The detection of difference or similarity is generally easier than operations requiring explicit segmentation, deletion, addition or transposition; words are easier than nonwords; performance is also affected by the phonological properties of the target unit, such as its position within a word, phonemic category (vowel, consonant, consonant type), the presence of consonant clusters or sonority hierarchy (Goswami, Bryant, 1990; Krasowicz-Kupis, 1999; Schatschneider et. al., 1999, Stahl & Murray, 1994; Yopp, 1988; Goswami, 2000). It must also be stressed that the performance of pre-literate children is far from perfect on all levels of phonological awareness. Induction into alphabetic writing consolidates and enhances performance across the board - although it has the most direct and dramatic impact on the awareness of phonemes (e.g. Cossu et. al., 1988). The internal structure of phonological awareness is a matter of some debate. Factorial analyses showed syllable awareness and phonemic awareness to emerge as two separate, yet correlated, latent variables (Wagner & Torgesen, 1987). Rime-onset level skills and phonemic level skills were shown, in some studies, to load on the same factor (Wagner et. al, 1993, Stahl & Murray, 1994, Schatschneider et. al, 1999) whereas others found them to emerge separately (Muter et. al., 1998). Other factorial analyses suggested that the division should be drawn not between the size-levels of phonological units, but between the type of operations involved. Thus, two-factor solutions were found which correspond to phonological analysis and synthesis (Wagner et. al, 1993, Schatschneider et. al, 1999) or ‘simple’ and ‘compound’ operations (Yopp, 1988). Most studies agree, however, that the emerging factors are highly intercorrelated (especially in pre-school children: Wagner et. al., 1993) and that phonological awareness can be described as a single broad domain. Individual differences in phonological awareness were observed to be relatively stable, at least over a medium-time span (kindergarten to grade four: Wagner, Torgesen & Rashotte, 1994; Wagner et. al., 1997).

54 2.1.1.3. The role of phonological awareness in the acquisition of literacy.

It is widely agreed that phonological awareness plays a central role in the acquisition of word decoding, recognition and spelling. The specific mechanisms linking phonological awareness and literacy are, however, a matter of some controversy. Any successful theory has to accommodate a paradoxical set of findings: phonological awareness is necessary for reading and spelling, yet the ability to read and spell is also necessary for phonological awareness. The main evidence for the latter claim (becoming literate leads to phonological awareness) was discussed in the previous section. Phonemic awareness, in particular, seems to occur only after the onset of alphabetic literacy, though even limited exposure (such as the knowledge of the alphabet: Burgess & Lonigan, 1998) is usually sufficient to elicit it. Syllabic and intrasyllabic level awareness, although they occur earlier, also improve greatly with the acquisition of reading. The reverse causal connection (phonological awareness is necessary for the acquisition of literacy) is evidenced, first of all, by a number of longitudinal studies which showed that the pre-school awareness of syllables, rimes and phonemes is related to subsequent reading and spelling performance, even when likely general confounds, such as IQ, chronological age or mother’s educational level are controlled (see Wagner & Torgesen, 1987; Goswami, Bryant, 1990; Share, 1995 for a review of the literature; for recent replication see Wagner et. al. 1994, 1997; Torgesen, Wagner, Rashotte, Burgess & Hecht, 1997; de Jong & van der Leil, 1999). However, a correlation between two variables (even the longitudinal one) is never an unequivocal proof of causation since it can always be a product of a third factor (Dancey & Reidy, 1999; Goswami & Bryant, 1990). In this case, letter knowledge is likely to be such a third factor, causal to both pre-school phonological awareness and subsequent reading progress. Knowledge of letter names and sounds is a very strong predictor of later reading (Denckla & Rudel, 1967/1997, Adams, 1990) and also correlates with pre-school phonological awareness (Burgess & Lonigan, 1998). Unfortunately, very few studies have controlled for this possibility. Those which did take letter knowledge into account gave somewhat ambiguous results: in some the relationship between pre-school phonological awareness and first-grade reading achievement disappeared (Lundberg, Olofsson & Wall, 1980, reanalysed in Wagner & Torgesen, 1987; de Jong & van der Leil, 1999) whereas others (Wagner, et. al., 1994; Naslund & Schneider, 1996) still found a significant longitudinal 55 link. The latter outcome is consistent with Maclean’s et.al. (1987) data showing that rime and alliteration sensitivity at age 3 could predict children’s ability to recognise words a year later, but was not related to the knowledge of the alphabet or to early arithmetic skills. Cross-linguistic differences may be important here, as both studies that failed to find the predictive role of pre-school phonological awareness involved non- English participants (see chapter 3). Longitudinal studies provide more consistent support for the idea that phonological awareness measured during early school years exerts a causal influence on reading and spelling progress. Individual differences in phonological awareness measured at the beginning of first grade predict later reading achievement even when differences in IQ, phonological working memory and - most importantly - concurrent reading skills are partialled out (de Jong & van der Leil, 1999; Wagner et. al, 1994; Torgesen et. al., 1997). A unique contribution of phonological awareness to reading during the first year of school was observed even when pre-school differences in phonological awareness were not predictive (de Jong & van der Leil, 1999). In English- speaking children phonological awareness exerts such unique influence on subsequent reading achievement until the 4'^ grade, and possibly longer, although the effects tend to diminish with age (Wagner et. al., 1994, 1997; Torgesen et. al., 1997). This suggests that the role of phonological awareness may be most crucial in the early phase of reading acquisition (in the context of learning to decode) and may decrease as children become more skilled and make greater use of lexical-based reading strategies (Bus & Ijzendoorn, 1999). However, this outcome may also be an artifact of a ceiling effect on the experimental measures of phonological awareness, which are typically tailored to differentiate the lower range of performance. The second, most direct type of evidence for a causal role of phonological awareness in the acquisition of literacy comes from training and intervention studies. Explicit instruction in phonological awareness is generally found to benefit subsequent word reading, spelling, and reading comprehension attainment. The effect is specific to literacy and does not generalise to mathematical achievement (National Reading Panel, 2000). A meta-analysis of existing studies (Bus & van Ijzendoorn, 1999) showed that experimental intervention on phonological awareness explains about 12% of variance in later reading skills. However, the benefits were observed mainly in the studies that combined phonological and letter training, while ‘pure’ phonological awareness training brought smaller and often non-significant results (e.g. Bradley & Bryant, 1983). It may 56 be argued, therefore, that it is an early phonics reading instruction, rather than phonological awareness training per se, that is beneficial. The benefits of training are usually transient (below 6 months) for word identification. However, longer-lasting (if small) effects occur for spelling and reading comprehension. This (together with the results of longitudinal studies discussed previously) suggests that phonological awareness may directly facilitate the process of learning to read (especially the self­ teaching mechanism based on decoding) but only indirectly the learning outcomes (Share, 1995; Bus & van Ijzendoorn, 1999). The third piece of evidence for the causal role of phonological awareness in reading acquisition comes from studies of developmental dyslexia employing reading level-match design (i.e. comparing poor readers with younger normal children of the same reading age). A number of studies have found that dyslexies perform worse than reading-age controls on phonological awareness tasks. These include: rhyme and alliteration oddity (Bradley & Bryant, 1978), the Tig Latin’ game (in which the initial phoneme of a word has to be moved to the end and the sound ‘ay’ added, eg. pig - igpay: Olson, Wise, Conners, Rack & Fulker, 1989), or phoneme deletion (Olson, Rack & Forsberg, 1990, reported by Rack, 1994). The reading-level-match design rules out the possibility that such differences are simply the result of the limited reading skill and experience of dyslexic participants, and suggests that the phonological deficit is a primary cause of dyslexic difficulties. The results are mixed, however, and several studies (e.g. Beech & Harding, 1984) failed to find a phonological awareness deficit in dyslexia - instead, they observed a developmental delay (performance commensurate with reading ability: worse than in chronological-age matched, but the same as in reading-age matched controls). This inconsistency may be resolved if we take the size of phonological unit into consideration. At least in older dyslexies, the awareness deficit seems to be limited to the phonemic level, whereas the syllabic and onset-rime deficit may be accounted for by the word-finding difficulties also observed in dyslexies (Goswami, 1997; Swan & Goswami, 1996). Differences may also be observed regarding the type of dyslexic difficulties. A deficit in phonological awareness can characterise poor readers who have specific problems with alphabetic skills (phonological dyslexies), but may not occur in surface dyslexies, whose difficulties are predominantly orthographic (Stanovich, Siegel & Gottardo, 1997). Overall, the pattern of findings presented above provides a strong case for reciprocal causation: phonological awareness is a condition for reading, but reading also 57 engenders phonological awareness. A number of theories have been put forward to explain this reciprocality, most of which share the same general structure. They assume that the development of phonological awareness can be divided into at least two main stages, phases or levels. The earlier one(s) occur as a natural part of language development, and constitute the prerequisite of successful reading and spelling acquisition. The later one(s) are a direct product of becoming literate. Diverse terminology is used to demarcate them: ‘epilinguistic’ and ‘metalinguistic’ control (Gombert, 1992); ‘implicit’ and ‘explicit’ phonological awareness (Perfetti, Georgi & Beck, 1993); phonological ‘sensitivity’ and ‘awareness’ (Adams, 1990; Burgess & Lonigan, 1998); ‘shallow’ and ‘deep’ phonological sensitivity (Stanovich, 1992), or onset-rhyme and phonemic awareness (Goswami & Bryant, 1990). There is no consensus, either, as to what constitutes those distinct levels of phonological awareness, and what the actual mechanisms are that connect them with literacy. In the following part I shall discuss some of the most influential theoretical proposals. An early theory of interaction between phonological awareness and literacy was developed by Perfetti and his colleagues (Perfetti, Beck, Bell & Hughes, 1987; Perfetti, Georgi & Beck, 1993). They drew the distinction between levels of phonological awareness that was based on the type of required operation and the explicitness of conscious access. A “dim, inexplicit form” of phonological awareness encompasses blending (synthesis); it is supposed to occur earlier and constitutes a prerequisite of learning to read. Phonological analysis, on the other hand, is a more advanced, explicit form of awareness, which occurs only as a result of learning to read. This stance finds some support in the results of factorial analyses which described phonological awareness as two separate (albeit highly correlated) latent dimensions of synthesis and analysis, which are orthogonal to the distinction between intrasyllabic-level and phoneme-level representations (Wagner et. al, 1993, Schatschneider et. al, 1999). However, Perfetti’s et.al. theory also predicts that synthesis is easier than analysis, and that most children master synthesis before they start learning to read. While most studies indeed find synthesis easier for children with at least rudimentary alphabetic knowledge (see chapter 6), pre-literate synthesis ability is generally weak or non-existent (Wimmer, 1993a). One large-scale study also showed that analysis, rather than synthesis, skills best predict first grade reading acquisition, while synthesis is more important in later progress from first to second grade (Wagner et. al., 1994). 58 Another, arguably the most influential, theory of the literacy-phonology connection was proposed by Goswami and Bryant (1990; see also Bryant et. ah, 1990; Goswami, 1999). Their distinction between the levels of phonological awareness is based less on the explicitness of conscious access, and more on the size of phonological units involved. Children become aware of syllables first, then of intrasyllabic onset-rime units; both insights are a natural part of language development. Awareness of phonemes occurs last, and only through the acquisition of alphabetic writing. Review of existing studies and path analyses of their own data (Bryant et. ah, 1990) led Goswami and Bryant to postulate a double causal connection between pre-school onset-rime sensitivity and the acquisition of literacy. First of all, spontaneously emerging intrasyllabic awareness directly supports earliest attempts at reading, as it enables children to discover that words which share letter patterns also share sound structures. Those earliest generalisations about print take the form of analogy-based reasoning that focuses on the onset-rime units. A new word can be read if it shares a phono-graphic (i.e. identical in sound and spelling) onset and rime with other words a child is already capable of reading. For example, an unfamiliar word PEAK can be read successfully by a phonologically aware child already familiar with PAN and BEAK. The second connection is an indirect one: intrasyllabic awareness facilitates the development of phonemic awareness, which, in turn, supports later progress in reading. Phonemic awareness is a direct result of learning to spell, yet it cannot be induced easily unless control over intrasyllabic structures is already established. Intrasyllabic awareness of single-segment onsets is particularly important in this context. Phonemic awareness is first acquired and used in spelling, and only later becomes recruited to support reading. The most original part of Goswami and Bryant’s contribution is specifying the role of intrasyllabic awareness. It also turned out to be the most controversial and questionable on various grounds. First of all, their theory predicts that pre-school sensitivity to onsets and rimes is directly linked with initial progress at reading. Indeed, a number of longitudinal studies found that pre-school alliteration and rhyming skills correlate with later reading achievement. This result was obtained not only with oddity tests, but also with other measures, such as knowledge of nursery rhymes (MacLean, Bryant & Bradley, 1987) forced-choice rhyme and alliteration detection (Bryant et. al., 1990) or deletion of onsets from rimes (Stahl & Murray, 1994). However, most of the studies did not control for letter knowledge and - even more importantly - failed to 59 disentangle sensitivity to intrasyllabic units from rudimentary phoneme awareness, which can already be observed in some pre-school children. Some studies that did include separate measures of onset-rime skills and phonemic awareness found that each make an independent contribution to early word decoding (Bowey & Hansen, 1994; Naslund & Schneider, 1996) or that the onset-rime skills are more strongly associated with early reading than the phonemic skills (Bryant et. al., 1990; Stahl & Murray, 1994). Others, however, failed to find any unique contribution of intrasyllabic-level sensitivity over and above phonemic segmentation (Nation & Hulme, 1997; Muter et. al., 1998; Duncan, Seymour & Hill, 1997). It remains, therefore, contentious whether intrasyllabic sensitivity directly contributes to early reading. The studies mentioned above also provide consistent evidence against the idea that children fail to use phonemic awareness in the earliest stages of learning to read, and this claim has been dropped from a recent re-formulation of the theory (Goswami, 1999). Another implication of Goswami and Bryant’s proposal is that early readers should reveal a strong tendency to make rime-based analogies when reading new, unfamiliar words. The ability to use an analogy-based decoding strategy was indeed observed in a series of experimental studies with 5 to 7-years old early readers, and it was also found to correlate with rime awareness (for overviews see Goswami & Bryant, 1990; Goswami, 1999). However, subsequent studies questioned whether, in a natural context, children rely on analogy-making mechanisms to any significant extent before they acquire the rudiments of reading by some other means. It was shown that the ability to make rime-based analogies depends partially on having some letter-sound knowledge and decoding ability, and the prior establishment of an adequate sight vocabulary (see Seymour, Duncan & Bolik, 1999 for review and discussion). Also, analogies in reading may be made with orthographic units of different size (e.g. vowel graphemes) and rime may not be particularly privileged in that respect (Savage, 1998). The part of the Goswami and Bryant’s theory best supported by empirical data is the hypothesis of developmental continuity between earlier sensitivity to intrasyllabic units, and later awareness of phonemes. This was suggested by longitudinal studies (eg. MacLean, Bryant & Bradley, 1987) and by factorial analyses which showed a strong relationship between intrasyllabic-level and phonemic-level awareness (Wagner et. al. 1993). The authors acknowledge that the applicability of their theory may be limited to the English orthography, where reliance on onset-rime division may be a particularly 60 reliable route to reading and spelling (Treiman, Mullennix, Bijeljac-Babic & Richmond- Welty, 1995). The role of rimes, in particular, may be reduced in languages with more straightforward letter-sound correspondences, or emerge only in later, orthographic phase of development (Wimmer, Landerl & Schneider, 1994; Goswami et. al., 1997, 1998, Goswami 1999; see also chapter 3). A different solution to the role of intrasyllabic-level skills was recently proposed by Seymour and colleagues (Duncan, Seymour & Hill, 1997; Seymour, Duncan &

Bolik, 1999). They adopted a central distinction between epilinguistic and metalinguistic awareness, originally proposed by Gombert (1992) in his theory of psycholinguistic development. Epilinguistic awareness (or, in Gombert’s original formulation - epilinguistic control) constitutes the second main phase of language development, which occurs after a child has accumulated some rudimentary vocabulary and speaking ability. As a child faces growing external demands for precision and efficiency of oral communication, internal reorganisation of linguistic knowledge is triggered. The resulting functional control over language structures - epilinguistic control - is largely inaccessible to consciousness. A third, metalinguistic, phase of development also results from external pressures - this time, coming primarily from the demands of learning to be literate. As a result, the child gains explicit, intentional control over language elements, which can also be described as differentiation of procedural and declarative knowledge. Unlike epilinguistic control, metalinguistic awareness is an optional phase of development, contingent on the acquisition of literacy. Seymour et. al. proposed that, in the domain of phonology, epilinguistic awareness follows a natural, fixed developmental sequence from larger units (syllables) toward smaller ones (intrasyllabic structures and, possibly, phonemes). Epilinguistic control can be operationalized with tasks that involve matching and comparison, e.g. working on the principle of oddity or same-different judgement. This part of the model is consistent with Goswami and Bryant’s account. Unlike them, however, Seymour et. al. emphasise the qualitative difference between (epilinguistic) sensitivity and (metalinguistic) awareness, and the independence of their developmental trajectories. As metalinguistic skills are intrinsically bound to literacy, they do not unfold in some naturally pre-specified, universal order, but are contingent on the orthography children learn. In an alphabetic orthography, explicit control over phonological units develops first for phonemes, and only later for larger intrasyllabic structures. Metalinguistic awareness can be measured with tasks that involve isolation and manipulation of 61 linguistic units, e.g. tapping, deletion or transposition. Studies carried out by Seymour and his colleagues used mostly the ‘common unit’ task: children were presented with word pairs and required to pronounce their shared part (whose size and location within a word was systematically manipulated). Data from various English-speaking countries and different teaching regimes generally confirmed the prediction: the ability to explicitly isolate single phonemes (especially in the onset position) develops before the ability to isolate longer strings: rimes, bodies or consonant clusters (see Seymour, Duncan & Bolik, 1999, for a review). Seymour et. al.’s and Goswami et. al.’s theories also diverge in explaining the role of rhyming skills for literacy. In Seymour’s account, epilinguistic sensitivity to onsets and rimes is not directly linked with early reading acquisition. Initial progress in reading hinges on the metalinguistic awareness of phonemes. Epilinguistic ability does, however, play an indirect role, as it allows metalinguistic awareness to be induced easily through the experience of learning to read and write. The metalinguistic awareness of rimes (which, according to Seymour’s data, develops only beyond the age of 7) may, however, play a direct role in reading and in spelling beyond the foundation level; namely, it may underpin the development of the orthographic framework (Seymour 1997, 1998). A theory that puts even stronger emphasis on the external origin of phonemic awareness was proposed by Wimmer and his colleagues (Wimmer, Landerl, Linortner & Hummer, 1991; Wimmer, 1993a, Wimmer, Mann & Singson, 1999). It was developed mainly in opposition to the claim (Perfetti et al., 1987, 1993) that some forms of phonemic awareness are preconditions of literacy. Wimmer et. al. studied German­ speaking children who, unlike their English-language counterparts, were not exposed to any kindergarten instruction on letters, blending or word recognition. When tested in the beginning of their first grade at school most of them knew few or no letters, could not decode the simplest words, and also failed the tests of phonemic awareness. Despite this, most of them made quick progress in reading and spelling during their first school year, accompanied by equally rapid development of phonemic awareness skills. Children with less satisfactory progress in literacy also tended to have lower scores on the measures of phonemic awareness. According to Wimmer et. al. those findings can be accommodated if we assume that reading does not require phonemic awareness as a prerequisite, but depends on the ease with which phonemic awareness is induced by the initial experience with writing. Pre-schoolers who have no opportunity to learn letters 62 and blending skills will lack phonemic awareness. It would be a mistake, however, to interpret this inability as an indicator of subsequent reading failure. Once children are exposed to an even minimal amount of reading materials and alphabetic instruction most of them will develop phonemic awareness very rapidly. Only if phonemic awareness is not induced easily, will further reading and spelling development be compromised. Those children who fail to develop phonemic awareness after a few months of reading instruction should indeed be considered at high risk of reading failure (see also de Jong and van der Leil, 1999, for similar findings and conclusions). It is important to remember that Wimmer’s theory is the only one among those discussed so far that is based predominantly on non-English data. Failure to predict reading progress from pre-school phonemic awareness, and rapid acquisition of reading and phonemic skills may reflect the characteristics of the German orthography (consistent letter-sound correspondences) and schooling (reading instruction does not start until 7 and is phonics-based). Those linguistic and educational constraints are acknowledged; in fact, understanding cross-linguistic differences in literacy acquisition is perhaps the most important part of Wimmer's project (see chapter 3). This involves the role of intrasyllabic sensitivity, as well. Wimmer, Landerl and Schneider (1994) found that only onset, but not rime sensitivity measured at kindergarten was related to first-grade reading progress, yet both were predictive of later, fourth-grade reading and spelling. This pattern was attributed to the characteristics of the German orthography, although it does also agree with the subsequent English-language findings of Seymour’s group (Duncan, Seymour & Hill, 1997) and their suggestion that rhyming ability underpins the development of orthographic skills. It must be added, however, that another German study (Naslund & Schneider, 1996) did find an independent contribution of rhyming skills to early reading, so, too, for the German language, the issue does not seem to be settled. Moreover, Wimmer’s account is not very specific about the possible indirect role of pre-school intrasyllabic sensitivity for reading, as a prerequisite or facilitator of phonemic awareness. Perhaps the most attractive aspect of Wimmer’s theory is the distinction it makes between external factors that bring about the development of phonemic awareness and internal factors responsible for individual differences in the rate of that development. Phonemic awareness is acquired because children are taught alphabetic literacy. Why, then, do some children find it harder to become aware of phonology than others (when all other factors are held constant)? A number of authors (e.g. Fowler, 1991; Elbro, 63 1996; Elbro, Borstrom & Petersen, 1998; Shankweiler, Crain, Brady, & Macaruso, 1992; Goswami, 2000) attribute those differences to the quality of underlying phonological word representations. Such representations constitute tacit linguistic knowledge, which may become a substrate of meta-linguistic reflection. Representations of poor quality: underspecified (e.g. Shankweiler et. al., 1992) or not sufficiently distinct and segmental (Elbro et. al., 1998) are harder to reflect upon. Thus, phonological sensitivity and awareness may be seen merely as the reflection of something more fundamental: the structure and quality of the representational phonology (cf. Goswami, 2000). The ‘phonological representation’ hypothesis (Goswami, 2000) is attractive, as it may offer a unitary explanation for a host of phonological processing difficulties that tend to cluster together with poor phonological awareness and poor reading. This includes problems with speech input (e.g. categorical perception of phonemic transitions, or perceiving speech in noise: Shankweiler & Crain, 1986; Adlard & Hazan, 1998) speech output (articulatory difficulties: Stackhouse & Wells, 1997), or phonological working memory (see section 2.1.3). Word-finding difficulties, problems with naming and fluency can perhaps also be partially attributed to poor quality phonological representations (see section 2.1.2). Despite the numerous contradictions in empirical findings and their conceptualisation, as discussed so far, some general consensus seems to emerge, at least regarding the nature of phonological awareness. Explicit awareness of sound structures is increasingly seen as a necessary condition of normal literacy acquisition, but not a pre-requisite, or precursor. In other words, it is an intrinsic part of becoming literate, rather than a distinct set of skills. This conceptualisation is supported not only by the developmental data discussed so far, but also by studies on the interaction between orthographic knowledge and phonological awareness, which show that the two are automatically co-activated and hard to distinguish between. Literate participants, when asked to make judgements about phonological structures of words, have difficulty inhibiting their tendency to invoke their knowledge about words’ spellings, even if it interferes with the task (Tunmer & Neasdale, 1985; Tanenhaus, Flanigan & Seidenberg, 1980; Ben-Dror, Frost & Bentin, 1994; Ehri & Wilce, 1980; Scholes, 1998). Also, they often report that performing phonological awareness tasks inadvertently triggers mental images of spelled words. Generating an orthographic image of the word, mentally reordering the word’s letters and ‘reading’ the results ‘in the mind’s eye’ may be a 64 viable strategy of performing more complex phonemic awareness tasks (Tunmer & Hoover, 1992). The strength of the mutual connection between phonology and orthography increases with reading proficiency, so, under certain conditions, dyslexies or pre-literate children may report ‘true’ word pronunciation more accurately than their better reading peers (Landerl, Frith & Wimmer, 1994; Read, 1986). In this context, describing phonological awareness in terms of ‘insight’ into underlying phonological representations, a discovery of ‘what is there in the mind’ (e.g. Fowler, 1991) may be a simplification. Explicit knowledge about the sound structures available to a literate person is as much discovered as it is constructed from orthography. It is knowledge based on a basic realisation that words can be perceived as linear strings of discrete elements - a realisation largely embedded in orthographic imagery. As such, it is markedly different from an objective description of sound structures a linguist may provide. This difference is clearly illustrated by the experience of learning phonetic transcript: it is frequently surprising or even frustrating, as it requires one to un-learn a good deal of spelling-based misconceptions about ‘how words really sound like’. If our opinions about sound structure of words (phonological awareness sensu stricto) are influenced by our experience with alphabetic writing, is the same the case with underlying phonological representations? Only circumstantial evidence is available, yet it seems that learning to read an alphabetic orthography may indeed be one of the factors that trigger (or at least speed up) the restructuring of phonological representations, from more global and imprecise into fully specified, phoneme-based representations (see Goswami, 2000, Elbro, 1996 for discussion). This hypothesis also finds some support in adult data which show that not only verbal report on sound structure, but also perception of words (e.g. auditory lexical decision on rhymes) is affected by the knowledge of spellings (Ziegler & Ferrand, 1998). Also, a historical process of ‘spelling pronunciation’ - tendency for the pronunciation of some words to alter in line with their spellings (Ellis, 1993) - can also be interpreted as reshaping of phonological representations by reading experience. Some authors (e.g. Faber, 1992) go so far as to interpret the history of phonology as a scientific discipline - specifically, the central importance it attributed to the notion of phoneme - as reflecting the ‘alphabetic bias’. Indeed, although systematic reflection on the sound structure of language occurred in many civilisations at different points in time, with similar concepts (e.g. articulatory features) being independently invented, the notion of a phoneme has only appeared in the Western world - the world that had been 65 using the alphabetic writing. The very concept of alphabetic writing - which to an alphabetically literate person may seem like an obvious and inevitable discovery - probably evolved only once, very gradually, and thanks to a rather peculiar set of linguistic and historical circumstances (Coalmans, 1989; Gelb, 1963). Writing as such, on the other hand, has been invented several times over, mainly on the syllabic principle. The idea of phonemes as basic ‘building blocks’ of language that can be linearly rearranged - the idea that dominated phonological theory for some time - may then, be rooted in an alphabetically biased imagery of its authors. It is only recently that the non-linear descriptions of phonology (eg. Chomsky & Halle, 1968; Goldsmith, 1996) started to shift focus away from the concept of the phoneme, showing the limits of its applicability - or, as some would argue (Faber, 1992), even suggesting its redundancy.

2.1.2. Phonological retrieval

The second aspect of phonological processing repeatedly demonstrated to be linked with literacy is the efficiency of accessing and retrieving names of familiar objects or symbols. This efficiency is operationalized with naming tasks that employ stimuli other than written words: letters, digits, colours, or pictures of common objects. Discrete, or confrontation naming tasks present one stimulus at a time, and the familiarity of stimuli may be varied systematically. This way, both accuracy and latency data may be collected. Serial, or rapid automatized naming (RAN) tasks use small sets (usually around 5 items) of highly overlearned stimuli which are displayed repeatedly in a pseudo-random order and have to be named continuously. With the latter procedure, a high degree of accuracy is assured, and only naming time data are typically collected. Most of the studies investigating the relationship between naming and reading employed the RAN paradigm. Following the seminal studies of Denckla & Rudel (e.g. 1976), a large and consistent body of evidence has been accummulated which shows that naming abilities are strong concurrent and longitudinal predictor of reading, independent of general intelligence (for review, see Wolf, 1991; Wagner & Torgesen, 1987; Wolf & Bowers, 1999). Moreover, naming and phonological awareness were consistently shown to load on different (albeit usually correlated) factors, each accounting for independent variance of reading. A unique contribution of naming was observed with both normal and 66 reading impaired participants, yet it is usually greater for disabled readers (Manis, Seidenberg & Doi, 1999). Naming generally explains a smaller amount of reading variance than does phonological awareness, and its contribution may even disappear once stringent controls for reading level are introduced (Torgesen et. al., 1997). The association between reading and naming also diminishes with age, generally faster than the association between reading and phonological awareness (Wagner et. al., 1997). In alphabetic orthographies other than English, however, the relative role of naming seems greater and more enduring (see chapter 3). Regression studies have shown that phonological awareness and naming not only explain non-overlapping variance of reading, but also that each is best at explaining different aspects of reading. Although both skills predict reading accuracy as well as speed, naming is usually best at predicting (concurrently and prospectively) reading speed and reading comprehension, worse at predicting word identification accuracy and poor at predicting nonword decoding accuracy (Manis, Seidenberg & Doi, 1999; Wolf & Bowers, 1999). The reverse is typically the case with phonological awareness. This suggests some degree of specificity: whereas phonological awareness skills may be most important for the acquisition of phonological recoding, naming tasks may index the ability to identify familiar words quickly. The relation of naming speed to reading comprehension may be indirect: naming contributes to word identification accuracy and speed, which are prerequisites of good reading comprehension (Wolf & Bowers, 1999; Kail & Hall, 1994). Corroborative evidence for a separate role for naming and phonological awareness in reading acquisition comes from dyslexia studies. Although most dyslexic cases show double deficits (of phonological awareness/recoding as well as naming) smaller, single-deficit subgroups can always be identified (Wolf & Bowers, 1999). Dyslexies with a selective deficit of phonological awareness and/or recoding tend to make more errors in word reading than those with a selective naming speed problem; the latter group, however, takes more time to read (Lovett, 1995, reported by Wolf & Bowers, 1999). Such patterns of difference do not always reach significance, however, (Bowers, 1995 & Wolf, 1997, reported by Wolf & Bowers, 1999). Children with double deficits were consistently shown to perform much worse on all aspects of reading than children with either single deficit. This, however, may reflect the fact that double deficit groups tend to be more severely impaired on both phonological awareness and naming than the respective single-deficit groups. Once single and double groups are matched on 67 the severity of individual deficits (Compton, De Fries & Olson, 2001), then phonological awareness alone seems to limit decoding accuracy (nonword reading equal in phonological awareness deficit and double deficit groups), and naming alone limits word reading speed and comprehension (they are equal in naming deficit and double deficit groups). When children are grouped by their reading performance, poor readers showing selective difficulties with reading speed (but normal accuracy) exhibit a single deficit of naming, yet those with selective difficulties of reading accuracy (but normal speed) show a double deficit of naming and phonemic awareness (Lovett, 1987). These results imply at least partial dissociation between phonological awareness and rapid naming as predictors of reading. Some authors (e.g. Manis, Seidenberg & Doi, 1999) presented evidence for naming ability being an especially strong predictor of specifically orthographic skills: judging orthographic legality of nonword spellings (letter string choice), homophone choice, or exception word reading. However, the comparison of severity-matched single and double deficit groups (Compton, DeFries & Olson, 2001) revealed no difference between phonological awareness, naming and double deficit groups on orthographic skills, suggesting that the two types of phonological processing may be equivalent with respect to orthographic ability. There seem to be two main unresolved theoretical issues regarding the connections between naming and literacy. The first concerns the functional architecture of naming, and the nature of resources it relies on. Some authors (e.g. Wagner & Torgesen, 1987, Wagner et. al., 1993) describe naming tasks as fundamentally phonological. All kinds of naming (including reading) share the same core demand for access and retrieval of phonological information. Common variance of reading and naming reflects differences in efficiency of access and retrieval processes. Any problems with retrieval accuracy and speed are phonological in nature and can be ultimately explained by the poor quality of underlying phonological representations (e.g. Katz, 1986). Alternative accounts stress that some crucial aspects of naming may not be specifically phonological. This is consistent with the fact that correlations between naming measures and other aspects of phonological processing (e.g. working memory, phonological awareness) are moderate at best (and often non-significant), suggesting a substantial degree of dissociation. Another argument for the importance of non- phonological aspects of naming is inherent in the fact that not all naming tasks are 68 equally good predictors of reading. Most of the positive findings described so far involved rapid automatized naming (RAN) of alphanumeric stimuli (letters, digits), while weaker or negative results were found in studies using RAN format with pictures and colours and, weaker still, with confrontational naming tasks (for review and discussion see Wolf, 1991; Wolf & Bowers, 1999). This is unsurprising, since serial naming of letters or digits resembles reading activity more than other types of naming (an issue I shall return to in the end of this section). However, there may be some deeper reasons, too. Reading and naming may share not only a phonological processing

requirement, but also the demand for automaticity: something that is indexed more directly by naming highly overlearned arbitrary symbols (e.g. letters) than by naming pictures. Several authors, in particular. Wolf and Bowers (Wolf, 1991; Bowers & Wolf, 1993; Wolf & Bowers, 1999) see rapid serial naming as an index of general ability to automatize complex cross-modal perceptual and motor skills. The underlying mechanism of this ability may be the precise timing of all component subprocesses (Wolf, 1991; Bowers & Wolf, 1993). To support this stance. Wolf & Bowers (1999) collated different strains of evidence showing that reading difficulties are related to problems with speed of processing, precise timing and co-ordination that are evident in a variety of tasks, not only naming. Poor readers, when compared to chronological-age matched controls, have difficulties in processing rapidly changing visual information (Lovegrove & Williams, 1993; Lovegrove, 1994) and judging the temporal order of two stimuli presented in rapid succession, both in visual and auditory domains (Kinsbourne, Rufo, Gamzu, Palmer & Berliner, 1991). Similar difficulties in temporal order judgement and perception of very brief tones were also implied in children with speech output and articulation difficulties, which constitute a group at high risk of dyslexia (Tallal et. al., 1996; Merzenich et.al., 1996). Dyslexies also perform significantly worse than controls on motor tasks which are complex and asynchronous, or which have to be performed together with a distracting activity (Fawcett & Nicolson, 1994). Those difficulties cannot, however, be accounted for by a general slowness of processing, since dyslexies are not different from normal readers on simple reaction times (Fawcett & Nicolson, 1994). It seems rather that reading problems are related to difficulties in

making fine temporal judgement, or speeded co-ordination of information across modalities. At present, this conclusion remains highly speculative and it remains to be demonstrated whether the apparently disparate difficulties listed by Wolf & Bowers (1999) can indeed be traced to the same underlying problem with temporal and cross- 69 modal integration. It must be said that the findings of non-verbal deficits in dyslexia reported above are contentious and have been criticised on methodological and theoretical grounds (eg. Wimmer, Mayringer & Raberger, 1999; Studdert-Kennedy & Mody, 1995; Skottun & Parke, 1999). Studies directly exploring the connection between naming ability and nonverbal speeded processing are sparse but promising. Kail and Hall (1994) reported that different nonverbal measures of processing speed: a cross-out (cancellation) task, visual matching, WISC-R coding, are indeed intercorrelated and predict RAN performance, which, in turn, predicts word recognition. Kinsbourne et. al. (1991) demonstrated temporal order judgement deficits for both visual light flashes and auditory clicks in adult dyslexic reading, and showed that performance on these tasks was highly correlated with naming speed. However, Wimmer, Mayringer and Landerl (1999) who used several measures of visual and motor processing speed, alongside with RAN tests found that only naming but not other speed measures could reliably discriminate dyslexies (both surface and phonological) from normal readers. His study did not, however, address the question of whether different measures of processing speed share common variance. It is important to remember that the two accounts of naming (a phonological code retrieval vs. general timing/integration mechanism) are not necessarily exclusive. Cognitive architecture of naming may incorporate both phonology-specific and cross- modal components; either of them (or both) can constrain reading development (Wolf & Bowers, 1999). The second controversy regards the hypothesis of naming being specifically linked with the acquisition of orthographic, rather than alphabetic skills. The proponents of this view (e.g. Manis, Seidenberg & Doi, 1999) point out that naming involves arbitrary connections between visual representations and their names (phonological labels). It is precisely the formation and activation of such arbitrary connections that is required for skilled reading. Alphabetic skills, on the other hand, rely on systematic letter-sound correspondences, and thus require phonological awareness. Wolf and Bowers (Wolf & Bowers, 1993; Bowers & Wolf, 1999) also developed this view. They emphasised the associative nature of learning to read, which requires formation of stable connections between frequently co-activated units. Those connections are both orthographic (when co-activated letter recognition units merge into familiar orthographic patterns) and phonographic (when different-size phonological elements - single letters, intrasyllabic units, whole words - are co-activated with the corresponding 70 letter strings). This network of connections cannot form properly unless the corresponding units are activated in sufficiently close temporal proximity. Activation asynchrony will disrupt associate learning and require more practice (greater number of pairings) to establish internal orthographic representations of sufficient quality. The same mechanism may also account for slow naming. A similar account was also proposed by Wimmer (1999), who pointed out that phonological and orthographic representations of words have distinct anatomical locations. Robust association between phonological and orthographic word-forms can form only if the flow of activation between those two domains is rapid enough. Theories of this type can successfully accommodate data showing that naming ability is better at predicting specifically orthographic skills than is phonological recoding (e.g. Manis, Seidenberg & Doi, 1999). They are also consistent with studies showing that children who are slow at reading require more practice to familiarise themselves with orthographic patterns. Words and sub-lexical orthographic patterns that are familiar elicit faster responses than matched unfamiliar patterns, yet people slow at naming words require significantly more previous exposures before the same degree of familiarity-related facilitation is observed (for a review see Wolf & Bowers, 1999). If the number of exposures is held constant, then children slow at naming show a smaller increase in the speed of reading isolated words (Bowers & Kennedy, 1993). Slow naming is more detrimental for quick recognition of whole words than of sublexical orthographic units (Levy & Bourassa, 1998, reported in Wolf & Bowers, 1999). Thus, naming difficulties seem related to an impoverished store of sight words. The hypothesis of a specific link between slow naming and orthographic knowledge has interesting implications for understanding the variability of developmental dyslexia. It is widely agreed that the manifestations of developmental reading difficulties may be classified on the ‘phonological-surface’ continuum. Phonological dyslexia is characterised by particular problems with decoding (evidenced by difficulties in nonword reading) whereas a presenting problem of surface dyslexia is the lack of a good sight vocabulary (evidenced by errors on reading exception words). A standard explanation of surface - phonological difference invokes the dual route models of word recognition developed in the context of adult, skilled reading (see chapter 1). The phonological form of dyslexia is understood to result from underdevelopment of the indirect route responsible for sublexical letter-sound conversion, whereas the surface form stems from underdevelopment of the direct route, linking orthographic, 71 phonological and semantic representations of whole words (e.g. Ellis, 1993). An alternative explanation is provided within the connectionist framework. The reading profile of phonological dyslexia is best simulated by the network whose capacity to represent phonological structures has been damaged (e.g. through removing connections between phonological units). Reading in surface dyslexia, on the other hand, bears more resemblance to the output of an undamaged, yet ‘inexperienced’ network - one in an early point of its learning curve, before it has mastered the entire training corpus. Surface dyslexia can also be simulated by a network with limited computational resources (i.e. removed hidden units) that is slower at learning all types of stimuli (Harm & Seidenberg, 1999; Stanovich, Siegel & Gottardo, 1997; Manis et. al., 1996). This implies that phonological dyslexia is a developmental deviance, whereas surface dyslexia a developmental delay. Such a formulation is consistent with the human data. Phonological dyslexies usually exhibit a deficit of phonological awareness and nonword decoding (in comparison with reading-age matched controls), whereas surface dyslexies show performance very similar to younger participants of similar reading age, though worse than chronological age controls (Stanovich, Siegel & Gottardo, 1997). Those differential patterns are often explained in terms of the interplay between (innate) deficits of phonological awareness and reading experience (print exposure). Children with large phonological awareness deficits are compromised in all aspects of their literacy development, and develop the phonological form of dyslexia. Children whose phonological awareness deficit is milder, but accompanied by very limited reading experience, will acquire basic decoding skills but have small sight vocabularies (orthographic lexicons) thus demonstrating surface dyslexia. However, since slow naming speed is specifically related to the difficulties in the acquisition of a sight vocabulary, surface dyslexia may also result from a deficit in automatizing grapho- phonological associations. With such a deficit, the process of building the orthographic lexicon from print exposure will be less effective. Even much reading practice may, then, be insufficient to form robust representations of sight words. Unfortunately, most studies of dyslexia subtypes have not included measures of naming speed. However, Murphy and Pollatsek (1994, reported in Wolf & Bowers, 1999) showed that, within a sample of dyslexic children, problems with reading exception words were specifically associated with naming speed, among other factors. It also seems plausible that the ‘low accuracy’ and ‘low rate’ subtypes of dyslexia, differentiated by Lovett (1987) overlap with phonological and surface 72 sub types, respectively. Orthographic processing difficulties (problems with acquiring sight vocabulary, or with parallel processing of longer letter strings in general) should manifest themselves in poor reading of exception words - a hallmark of surface dyslexia. The same orthographic difficulties may also require over-reliance on sequential decoding, which should result in slow reading. Orthographies with more regular letter-sound correspondences than English may give few opportunities for misreading irregular words, and there slow reading (accompanying by stubborn tendency to sound words out) may be a primary sign of surface dyslexia (Wimmer, Mayringer & Landerl, 1999). The relationship between the ‘accuracy-rate’ and the ‘phonological-surface’ classifications of dyslexias will be further discussed in chapter 3. The theory of a specific link between naming and orthographic skills is not without its problems. As noted in the beginning of this section, the dissociation of naming and phonological awareness is only partial, and both skills may be necessary for word reading accuracy (Lovett, 1987). Also, as children’s sensitivity to orthographic patterns and constraints grows with literacy experience, the specific contribution of naming to reading should increase accordingly, yet in fact it decreases with age (e.g. Torgesen & Wagner, 1994). Some studies also demonstrated that slow readers can benefit from repetition practice on naming words just as much, if not more, than the fast readers (Lemoine, Levy & Hutchinson, 1993). Those controversies may perhaps be resolved if a task analysis approach is adopted. This should tease apart distinct components of naming to understand what specific contribution each of them may make into reading. This step was taken by Bowers and Wolf (1999). They hypothesised that those components of RAN tests that are most task-specific are selectively related to lexical and orthographic processing. The non-specific, speed-related components are involved in all aspects of visual and auditory processing and constrain all aspects of reading - for example, they may compromise the development of phonological awareness. A somewhat different analysis of naming tasks was proposed by Manis,

Seidenberg & Doi (1999). They emphasise the shared demand for processing arbitrary sound-symbol mappings as the key reason for the observed associations between naming and orthographic skills. However, they also acknowledge the role of other components that are specific to the continuous (i.e. rapid automatized) naming format. These components (such as sequential eye movements and co-ordination of information from different modalities occurring in rapid sequence) overlap with processes involved in reading connected texts, but are not involved in phonological awareness tasks. 73 Implicit in Manis et. al.’s (1999) analysis is the possibility that the relationship

between rapid naming and literacy is reciprocal - just as the relationship between phonological awareness and literacy. Processes involved in naming may contribute to reading and spelling, but also benefit themselves from reading practice. This is plausible when we consider that even very peripheral and physiologically constrained aspects of reading, such as perceptual span (i.e. the size and shape of effective visual field) are strongly affected by characteristics of the orthography and individual differences in reading skills (Rayner, 1998)^. Also, since reading skills show the strongest relationship

with naming of letters, this relationship is probably mediated through the common factor of reading experience. The possible beneficial effect of reading must operate differently for naming than for phonological awareness, however, since explicit training of naming skills does not produce generic gains (i.e. transferable beyond the trained stimuli: de Jong & Vrielink, 2000), unlike phonological awareness training. The possibility of the reciprocal causality between rapid naming and literacy has received little attention so far, and future studies in this area should explore the impact of reading experience on naming more explicitly.

2.1.3. Working memory

Working memory has been implicated in at least two aspects of reading. First, it may enable early, unskilled decoding. When conversion of graphemes to phonemes is not yet automatic and progresses slowly and sequentially (rather than in parallel) then the products of consecutive conversions have to be held in memory until they are finally blended together and lexical access can be achieved (Siegel, 1993; Baddeley, 1986). Second, at a higher level of reading proficiency, memory processes may be necessary to maintain the sequences of words being recognised or decoded and to make them available for higher-order syntactic and semantic processing. Those general predictions can be articulated within the framework of a working memory model. One particularly influential model was proposed and developed by Baddeley and his colleagues (Baddeley & Hitch, 1974; Baddeley, 1986, 1996, 1997). It

consists of three main components: a control mechanism {central executive) and two

2 e.g. for readers of the orthographies printed from left to right (e.g. English) the span is asymmetric to the right of fixation, while the reverse is the case for readers of right-to-left orthographies (e.g. Hebrew). 74 slave systems for the temporary storage of verbal and visuospatial information

{phonological loop and visuospatial sketch pad, respectively). The central executive is essentially a set of executive and attentional processes, which select and redirect short­ term storage resources to match the requirements of a given task. It also links the slave systems with long-term memory. The limited capacity of the central executive (named

working memory capacity) is measured with tasks that require simultaneous storage and processing of some units of information. Each of the two slave systems codes information in a modality specific way, stores it and actively maintains it by rehearsal. The capacities of the phonological loop and visuo-spatial sketch pad are also limited (by

trace decay and efficiency of rehearsal process) and referred to as short-term storage capacity (de Jong, 1998). Memory span (or simple span) tasks used to measure those capacities require reproduction of a sequence of items in the order they were presented (serial recall). Early, unskilled reading may require simultaneous storage of sublexical and lexical units and their deployment for higher order processes (blending, syntactic analysis, etc.). It should, therefore, directly involve working memory capacity. Since reading input is likely to be coded phonologically, short-term storage capacity of the phonological loop may also be important. Reading development should, then, depend on the functioning of the central executive and the phonological loop, but not on the visuo­ spatial scratch pad. Studies exploring working memory in the context of reading indeed revealed such a specific pattern of relationships. Digit span, word span and, most of all, nonword repetition (considered as measures of short-term storage capacity of phonological loop) were found to correlate with reading ability in children (see Baddeley, 1986; Gathercole & Baddeley, 1993; Elbro, 1996; Wagner & Torgesen, 1987 for reviews and discussions). Likewise, poor readers are consistently found to be worse on those indices than their chronological age controls (Rack, 1994). Tests of working memory capacity (tapping central executive functions) typically show even stronger correlations with reading than tests of phonological storage capacity (Leather & Henry, 1994; Swanson, 1994, Oakhill & Kyle, 2000). Phonological storage capacity and working memory capacity each predict unique variance of word decoding in normal readers (Leather & Henry, 1994; Swanson, 1994; Swanson & Alexander, 1997). Partial dissociation of those two capacities was also found by de Jong (1998) with dyslexic readers. The participants he studied were significantly worse than chronological age controls on both 75 simple span and working memory measures, yet the differences in working memory could not be explained by the differences in simple span or processing speed. Low reading achievement seems, then, linked with poor functioning of both the phonological loop and the central executive. Those two difficulties are at least partially independent, and the precise nature of their interaction remains debated (De Jong, 1998; Swanson & Alexander, 1997). It remains to be seen whether the limitation of working memory capacity associated with poor reading is of a general nature, or specific to verbal material. For the short-term storage capacity, however, there is evidence for a specific link: verbal, but not visual, span is related to reading. Although poor readers are often found to perform less well on tests that require memorising visual material (e.g. Vellutino et. al., 1996), this seems secondary to differences in strategies for memory encoding. Growth in short-term storage capacity is linked with the tendency to label visual material (pictures, geometrical figures, etc.) verbally and store it by means of a phonological code (Henry & Millar, 1993; Hitch, 1991). Verbal-phonological encoding of visual information makes it more readily available for rehearsal and reproduction (Hicks, 1980). The tendency to encode visual information verbally is delayed in poor readers (Rack, 1994). When differences in efficiency of verbal encoding are controlled (verbal encoding is eliminated by articulatory suppression, or enhanced by explicit teaching) then differences in visual memory span tend to disappear (Hicks, 1980). Also, good and poor readers of the same age usually do not differ on memory span for visual stimuli that are hard to label verbally (Crispin, Hamilton & Trickey, 1984; Vellutino, 1979). Although the association between simple verbal span, working memory span, word decoding and recognition has been demonstrated, attempts to prove a direct causal role of memory in reading give ambiguous results. Factorial analyses of phonological processing skills show that tests of short-term phonological storage and working memory usually load on the same factor as tests of phonological awareness (Wagner & Torgesen, 1987; Wagner et. al., 1993). Even when memory emerges as a distinct factor it remains strongly correlated with phonological awareness (de Jong & van der Leij, 1999), particularly with measures of phonological analysis (Wagner et. al., 1993). Since correlations of memory and reading are usually weaker than those between reading and phonological awareness, memory often fails to predict any variance in word decoding and recognition over and above that explained by phonological awareness (Wagner et. al., 1994, Torgesen et. al., 1997). Longitudinal studies that found independent 76 contributions of both verbal working memory and phonological awareness to later reading achievement (e.g. Naslund & Schneider, 1996; Rohl & Pratt, 1995) failed to control for some possible confounds (like concurrent reading level and nonverbal intelligence). Once such additional controls were introduced, memory ceased to predict any significant variance of reading, while both phonological awareness and rapid naming continued to make their significant (albeit reduced) contribution (de Jong & van der Leij, 1999). Studies involving poor readers also showed that their memory capacity, although significantly smaller than in the chronological age controls, can be greater than predicted by reading age (Stanovich & Siegel, 1994; de Jong, 1998). The type of reading disability may be critical, however: phonological, but not surface, dyslexies were found to have smaller working memory capacities than their reading-matched peers (Stanovich, Siegel & Gottardo, 1997). No clear conclusions can be drawn from studies that explored the use of phonological codes in short-term storage. Normal people typically show a reduction of memory span when visually presented stimuli (letters or words) have phonologically similar (rhyming) names (e.g. Conrad, 1964). This ‘phonetic confusability effect’ indicates the strength of phonologically based storage and rehearsal in the phonological loop (Baddeley, 1986). Dyslexic children sometimes show a reduced phonetic confusability effect, which suggests that they use phonological codes to a lesser extent than normal readers. However, the size of the phonetic confusability effect is usually the same in dyslexies and younger normal readers matched for memory span or reading level (Rack, 1994). This, again, suggests a delay in line with the observed reading problem, but probably not a direct cause of that problem. A large-scale study of Stanovich & Siegel (1994), however, found the phonetic confusability effect to be smaller in poor readers than in reading-age controls, although simple span and working memory capacity were similar in both groups. One hypothesis that may account for those ambiguous findings says that working memory (in particular, the central executive) exerts an indirect causal influence on reading, as it constrains the development of phonological awareness and other metalinguistic skills. Such an indirect causal path was proposed by Tunmer and Hoover (1992). In a number of longitudinal studies they found a direct unique contribution of phonological and syntactic awareness to reading success. These metalinguistic skills, were, in turn, dependent on working memory capacity (see also section 2.2.). Other data are consistent with this model. Working memory is a strong predictor of phonological 77 and syntactic awareness task performance (Gottardo, Stanovich & Siegel, 1996), the main constraint being working memory capacity, rather than simple memory span (Leather & Henry, 1994; Oakhill & Kyle, 2000). However, the conclusion: “linguistic awareness cannot develop without good working memory” may be misleading. We can imagine a child who fails an awareness test as she cannot cope with its memory demands, yet is, in fact, aware of linguistic structures. Her result is qualitatively (though not quantitatively) different from that obtained by another child who lacks phonological awareness, yet has good memory skills. As in the case of naming skills, the analysis of distinct task demands and components may be the best way of understanding the observed relationships. Tests of reading and phonological awareness both share a similar requirement for working memory capacity. Hence, the tests of working memory usually fail to predict any additional reading variance over and above that explained by tests of phonological awareness, as the latter already capture the variance due to differences in memory skills. However, measures of reading and phonological awareness also share additional, specific variance of the ability to become aware of sound structures. Thus, tests of phonological awareness can explain some variance in reading over and above that predicted by the tests of working memory. Such a formulation implies that efficient working memory is a requisite of reading success but its contribution may be masked once other measures of phonological skills are taken into account. A somewhat different account is given by the phonological representation hypothesis mentioned before (section 2.1.1.3) which says that phonological awareness and phonological working memory are both ultimately dependent on the quality of the phonological representations of words (e.g. Shankweiler et. al., 1992; Fowler, 1991; Elbro, 1996, Brown & Hulme, 1996; Goswami, 2000). An efficient phonological loop is contingent on having highly specified, segmentalised phonological word representations. This implies that, regardless of the role of memory for literacy, becoming literate causes memory to develop. Learning to read and spell is one of the forces (the other being vocabulary acquisition) that trigger segmental re-structuring of phonological word representations (Brown & Hulme, 1996; Goswami, 2000). Availability of phoneme-level representations will improve the efficiency of the phonological loop - which, in turn, will increase the rate of learning new vocabulary (Brown & Hulme, 1996).

78 Good working memory skills are also implied as a prerequisite of reading comprehension. This is based on the assumption that higher-order cognitive processes (such as syntactic parsing) would not be possible unless the substrates of those processes were maintained in working memory. Some authors, particularly Oakhill and her collaborators (e.g. Yuill & Oakhill, 1991) have tried to explain difficulties with comprehension as a direct result of limited working memory capacity. They observed a robust correlation between reading comprehension and working memory capacity and, a reduced capacity in poor comprehenders. Oakhill et. al. concluded that reading comprehension relies on a general working memory capacity for simultaneous storage and processing of information, which is domain-independent. However, such a conclusion seems premature, as the working memory tasks used by Oakhill and her colleagues involved only verbal or verbally encodeable stimuli (such as digits). Others (Liberman, et al., 1992) have also agreed that working memory directly constrains comprehension, yet explained working memory difficulties as the result of a general phonological deficit, in line with the phonological representation hypothesis. Low-level difficulties with processing phonological information could limit working memory capacity, creating a ‘bottleneck’ for higher-level processes of syntactic and semantic analysis. Other authors, however, particularly Snowling and her colleagues (e.g. Nation, Adams, Bowyer-Crane & Snowling, 1999) do not find working memory problems to be a direct cause of reading comprehension failure. They also found that working memory capacity correlates with reading comprehension, yet they provided some evidence that this association is specific to the verbal domain (contradicting Oakhill’s hypothesis of general processing capacity limitations) and that poor comprehenders have problems with semantic, but not phonological coding in memory (reduced span for abstract words, but normal sensitivity to phonological manipulations). That led them to conclude that poor comprehension co-occurs with some memory limitations because both are a direct result of a core deficit within the semantic subsystem of language.

2.2. LITERACY AND OTHER LINGUISTIC SKILLS

Although the processes that connect phonology and literacy have been researched extensively and from different angles, the same is not true of other language domains: morphology, syntax, semantics, pragmatics or discourse. According to some theoretical accounts, this imbalanced research focus is justified, as far as word-level literacy skills 79 are concerned. Word recognition, decoding and spelling depend primarily on the functioning of the phonological module, and other aspects of language are not directly relevant - however important they may be for reading comprehension (Shankweiler et. al., 1992; Gottardo et. al., 1996). Other authors, however (e.g. Tunmer & Hoover, 1992; Bryant, 1995) maintain that other language domains - and especially metalinguistic control over them- also make a direct independent contribution to basic word-level reading and spelling skills. The discussion is also fraught with some conceptual and methodological inconsistencies. There seems to be a consensus as to what constitutes phonology, yet other domains of language are not so clearly delineated. This is especially the case with semantic, pragmatic and discourse skills, the definitions and operationalizations of which vary widely between authors (Krasowicz-Kupis, 1999; Gombert, 1992; Tunmer & Hoover, 1992). Likewise, the measures used in this area often compound different aspects of language, making the assessment of their independent contribution difficult. Moreover, some controversies exist as to how metalinguistic skills (or linguistic awareness) of morphology, syntax, etc. should be operationalized in contrast to ‘ordinary’ (tacit) competence (see also section 2.2.1.). In my review I shall focus on the awareness of grammar (taking ‘grammar’ as an umbrella term for syntax and morphology: Bryant, 1995) and its relationship to word decoding, recognition and spelling. As the predictions regarding the role of syntactic and morphological awareness are somewhat different, I will try to discuss each of them separately, as far as possible.

2.2.1. Syntactic awareness.

Awareness of syntactic structures has been investigated with a variety of tasks requiring

operations on sentences. These include: correction of word order (jumped Jack the log: Tunmer & Hoover, 1992), judging syntactic acceptability of sentences and correcting

the errors (One of the children are sick: Gottardo et. al., 1996) and cloze tasks, where a

child is asked to supply a missing word in a sentence (It ___ very cold outside yesterday: Stanovich & Siegel, 1994). Longitudinal and cross-sectional studies that have tried to quantify the independent contribution of metasyntactic skills to reading have brought mixed results. Some found that metasyntactic skills could explain significant (albeit usually small) 80 word decoding variance, which was independent of the variance explained by phonological awareness (see Roth et. al., 1996; Snyder & Downey, 1997 for review). The overall number of studies which included separate tests of syntax and phonology is, however, very small, and they have tended to confound several language domains (syntax, morphology, semantics) into a single measure. Differences related to age and literacy subskills (decoding vs. comprehension) also make the interpretation of the results difficult. A systematic research programme which tried to disentangle those ambiguities was pursued by Tunmer and his colleagues (Tunmer, Pratt & Herriman, 1984; Tunmer, Herriman & Neasdale, 1988; Tunmer & Hoover, 1992). In a series of longitudinal studies they employed path analysis to predict second grade reading comprehension from first grade decoding, listening comprehension and language awareness skills. They consistently found that listening comprehension and word decoding each made independent contributions to reading comprehension. Word decoding was, in turn, explained by the independent effects of phonological and syntactic awareness. Syntactic awareness also contributed directly to listening comprehension. The independent role of syntactic awareness was further confirmed in a study which showed that dyslexic 4*^ graders were significantly worse than their reading-age controls on two measures of syntactic awareness (oral cloze and word order correction tasks: Tunmer, Nesdale & Wright, 1987). The model of literacy acquisition proposed by Tunmer and his colleagues was built around the central notion of metalinguistic skills - the ability to reflect on and manipulate the elements of spoken language (Tunmer, Pratt & Herriman, 1984; Tunmer & Hoover, 1992). Phonological awareness constitutes only one aspect of metalinguistic ability, others being word, syntactic and pragmatic awareness. Each makes its unique contribution to reading success. Awareness of words requires a grasp of the basic distinction between sound and meaning, and thus is a prerequisite of phonemic awareness. Phonological awareness is crucial for learning letter-sound correspondences and applying them for word decoding. Syntactic awareness also contributes to word decoding, as it enables a beginning reader to use sentence context. This is beneficial in several ways. First of all, taking context into account supports self-correction of decoding errors. Moreover, it allows for plausible guessing. A combination of guessing and rudimentary decoding helps to identify unfamiliar words, and growth in the knowledge of letter-sound correspondences is a by-product of this process. The ability to take context into account while reading is also beneficial for identification and 81 learning of homographs and exceptional words. Efficient decoding and recognition skills are, then, a product of interaction between phonemic and syntactic awareness. Syntactic awareness also makes its direct contribution to listening skills and, in this way, supports reading comprehension (see also Share, 1995, for similar considerations). Tunmer et. al. also analysed pragmatic awareness, which they defined as the ability to monitor larger messages - notice one’s own lack of understanding, detect missing information or between-sentence inconsistencies. They found little evidence for a significant role of these skills in beginning reading (or for their existence at this early stage), and speculated that they develop later and contribute directly to reading comprehension (Tunmer & Hoover, 1992). Tunmer et. al.’s conclusion that syntactic awareness affects reading through the use of context was confirmed by Rego (1991, discussed in Bryant, 1995). In her longitudinal study she found that alphabetic decoding (which was measured with an invented spelling task) was predicted by phonological, but not grammatical, awareness skills. Additionally, she measured the magnitude of contextual facilitation as she gave each child words which he or she had not been able to read in a single-word reading test (different words for different children) embedded in meaningful sentences. Here, the results reversed: context-related improvement was predicted by grammatical, but not phonological, awareness. This outcome is consistent with the hypothesis that syntactic skills provide indirect support for decoding, as they help a reader to take sentence context into account. The reliability of Rego’s conclusions is strengthened by the fact that she first collected her grammatical and phonological data before children entered school, which was not the case with the studies discussed previously. In contrast to this multi-component view of the relationship between linguistic awareness and basic literacy, other authors have proposed more ‘minimalist’ models, which have highlighted a primary (or exclusive) role of phonological skills in learning to decode, recognise, and spell words. The prominent proponents of this view have been the Haskins group (e.g. Shankweiler & Crain, 1986; Shakweiler et.al., 1992). They emphasise the modularity of language domains and insist that the acquisition of basic decoding and recognition skills is exclusively linked with the functioning of the phonological module. Difficulties with phonological processing are, however, bound to result in secondary problems in other language domains. This is because all linguistic input must first be analysed phonologically, before it is passed into syntactic parsers and semantic processing (with working memory relaying information through the system). 82 Phonological impairment limits working memory capacity, which creates processing limitations (a ‘bottleneck’) leading to a variety of higher-level linguistic difficulties, such as problems with comprehension of long sentences. Higher-order language processes are, then, not causally related to alphabetic and orthographic skills, but only associated via an underlying variable of phonological processing ability. This interpretation is consistent with the results of studies which found non­ significant (or small) contributions of syntactic awareness to word decoding and recognition, once phonological awareness was partialled out (Gottardo et. al., 1996; Warren-Leubecker & Carter, 1988). It is also compatible with the results of Stanovich and Siegel’s (1994) large scale study of dyslexies and garden-variety poor readers, which found them to perform in line with their reading age, or even better, on syntactic awareness tasks. Data on children with comprehension problems are also relevant here. Some children show selective impairment of comprehension, despite intact (or superior) word decoding and recognition. This profile of hyperlexic reading skills can be accompanied by wide-ranging linguistic and metalinguistic deficits. Phonological skills, however, are selectively spared (Stothard & Hulme, 1995; Nation & Snowling, 1998), which suggests that good phonological skills on their own are quite sufficient for the acquisition of word decoding and recognition. These results seem to contradict the studies discussed earlier, which found that both syntactic and phonological awareness make independent contributions to reading, and dyslexic readers are impaired on syntactic awareness (Leong, 1984; Tunmer et.al., 1987; Tunmer & Hoover, 1992). However, the findings can possibly be reconciled if we assume that syntactic awareness (and contextual facilitation) contribute to decoding only indirectly, providing support and compensation that is most important when decoding is originally poor (Nation & Snowling, 1998; Rego, 1991, in Bryant, 1996). Part of the difficulty in drawing conclusions about the role of meta-syntax in reading may also be methodological. Measures of “syntactic awareness” often compound syntax with semantics and morphology, and also vary the requirements for conscious, deliberate (meta-) control. Cloze tasks, in particular (which require insertion of the missing word) may rely more on automatic language processing than deliberate control, and thus not involve metalinguistic processing (Roth et. al., 1996). They should probably be understood as measures of sensitivity to grammatical structures, tapping into the epilinguistic level of language development (Gombert, 1992) - which, in any case, may be the highest level of grammatical control available to a pre-literate child. 83 2.2.2. Morphological awareness

There is a degree of overlap between the debates on the role of syntactic and morphological awareness and literacy. In both cases, the central problem is establishing the limits of the phonological processing account of literacy acquisition; that is, checking whether (and how) other language domains may contribute to this process, independently of phonology. Since morphology operates on the word level, the predictions regarding the role of morphological awareness focus on reading and spelling single words, rather than sentence or text comprehension. English orthography provides a fertile ground for testing those hypotheses, as it often represents the morphological structures directly (see chapter 3). It is, then, plausible that insight into morphological structures should support attempts at word recognition and spelling, particularly when spelling is morphologically constrained. Until quite recently, very few studies tried to quantify the independent contribution of morphological awareness to reading (for review and discussion see Roth et. al., 1996, Bryant, 1995). Carlisle and Nomanbhoy (1993) found that morphological awareness could account for significant, if small (4%) variance in U' grade word decoding over and above phonological awareness. Among different morphological measures the oral cloze task, requiring the completion of a sentence with a correct word form (e.g.: Help. My father says I am a good ) appeared most predictive. Another study carried out by Mahony and Mann (1992) employed rather ingenious methods. Second grade good and poor readers were told a number of linguistic riddles, whose appreciation required insight into different levels of linguistic representations: phonology (e.g.: What goes oom, oom? A cow walking backwards), morphology (What is the longest word in the language: ‘smiles’ or ‘trains’? ‘Smiles’, because there is a mile between two s’s.) and semantic, syntax or pragmatics (What should you do if you met a blue monster? Try to cheer him up! ). Poor readers appeared significantly worse at understanding phonological and morphological riddles, but not those invoking other levels of linguistic representations. Regression analysis found that only phonological/morphological riddles accounted for the unique variance of word reading. However, since phonological and morphological tasks were not analysed separately, it was impossible to assess their independent contribution. Some studies, especially those carried out by the Haskins group (Fowler & Liberman, 1995; Shankweiler et. al., 1995, both reported in Mann, 2000) called the 84 independent role of morphological competence in reading into question. They showed that reading-related differences in morphological awareness were most pronounced when a test required producing base or derived forms in which suffixes phonologically alter the base. This is consistent with the phonological bottleneck hypothesis, whereby morphological difficulties may constrain reading, yet itself is a by-product of a phonological processing deficit. However, a recent series of studies (published together in a thematic issue of the journal Reading and Writing) provided consistent evidence for at least the partial independence of morphological and phonological processes in reading. They employed a range of morphological awareness measures (administered in oral or written mode), including: tests of morphological relatedness (identification of derivationally related word pairs, e.g. person-personal, atom-atomic among foil pairs related only in spelling, e.g. ear-earth: Mahony, Singson & Mann, 2000); sentence completion task (requiring a selection, from a pair of words or nonwords, of the item with an appropriate derivational suffix, e.g. operation or operational, froodly or froodful: Singson, Mahony & Mann, 2000); stem-affix synthesis and blending (Casalis & Louis-Alexandre, 2000), or cloze tasks requiring decomposition {Dryer. Put the wash out to ) or derivation {Teach. He was a very good ; Carlisle, 2000). Although phonological and morphological awareness were found to correlate moderately or strongly, morphological skills predicted a small but unique amount of variance in word decoding (Mahony, Singson & Mann, 2000; Casalis & Luis-Alexandre, 2000). Phonological and morphological awareness also showed different developmental curves; for morphological skills, greater gains occurred in the later years of primary school. Likewise, the contribution of morphological skills to reading increased with age (Singson, Mahony & Mann, 2000; Casalis & Luis-Alexandre, 2000). This is consistent with the increase in the proportion of multimorphemic words children encounter in their reading material, and a growing sensitivity to specifically orthographic patterns and constraints that have been observed in other studies (Share, 1995). This pattern of findings cannot be fully accounted for by the phonological bottleneck hypothesis. It seems that, beyond an initial phase of decoding acquisition, morphological ability plays a direct and autonomous role in reading, providing an optimal framework for analysing and representing multi-morphemic written words (c.f. Seymour, 1997). A French study of Casalis & Luis-Alexandre (2000) provides particularly convincing evidence, as it was longitudinal and employed a range of implicit and explicit morphological awareness measures. It showed morphology to be specifically linked not only with word decoding, 85 but also with reading comprehension. The latter finding may reflect the role of morphological awareness in processing morphologically complex words, both in terms of their structure (decoding) and meaning. The relationship between morphological skills and literacy was investigated more extensively in the context of spelling. A systematic research programme in this area was carried out by Bryant and his colleagues. Their work focused on two phenomena of English orthography that reflect morphology and syntax in the most direct way; spelling of past tense endings, and the use of an apostrophe to mark the genitive case. They reasoned that the mastery of such spellings would depend on a (largely implicit) grasp of underlying orthographic rules. As these rules reflect grammar, so grammatical knowledge should help to learn the rules of the orthography. In the past tense study (Nunes, Bindman & Bryant, 1997) children from 2"*^, 3'^* and 4“’ grade were asked to spell three different categories of words, which ended with

/d/ and /t/. These were: regular verbs (e.g. called, dressed), irregular verbs (found, felt) and non-verbs (bird, belt). Additionally, children performed three morphological awareness tasks: sentence analogy (which required tense change: Tom helps Mary - Tom helped Mary. Tom sees Mary - ______), word analogy (anger - angry strength - ) and productive morphology (which tested the ability to derive morphologically correct forms from verbs, nouns and adjectives, using nonword material: This is a person who knows how to snig. He is snigging onto his chair. He did the same thing yesterday. What did he do yesterday? Yesterday he ). Nunes et. al. observed developmental progress in the spelling of past tense endings, which they described adopting a five-stage model. At first, spellings were unsystematic. Later on (stage two), endings were spelled phonetically (e.g. hist, slept, soft). After that -ed spellings occurred frequently, but were over-generalised to irregular verbs and non-verbs (kissed, sleped, sofed). At the fourth stage, -ed spellings were confined to past verbs, but still generalised to irregular verbs (kissed, sleped, but: soft).

Finally, -ed spellings were correctly confined to regular past verbs. Nunes et.al. used discriminant analysis to predict stage membership from scores on morphological awareness tests. Both word and sentence analogy tasks were positively related to spelling stage, concurrently and 7 months later, even after controlling for differences in age and IQ. The sentence analogy task could even predict the membership of the stage group 20 months later. The productive morphology task was not predictive at any point, however. The same pattern was observed with multiple 86 regressions predicting the number of correct -ed spellings after 7 and 20 months (partialling out chronological age, IQ, and spelling scores in initial session). However, the magnitude of spelling variance explained by morphological tasks was small (1-4%).

Overall, the study suggests that mastery of -ed spellings may indeed be an instance of implicit rule learning and the mastery of the orthographic rule partially depends on a grasp of corresponding morphological transformations. The same set of data was reanalysed in two further studies. In order to address the role of morphological skills more directly, Bryant, Nunez and Bindman (1997) selected poor readers from their sample and analysed their performance at different time points. Children diagnosed as poor readers at the end of the study turned out to be worse than their chronological age controls on spelling and morphological awareness measures. However, there was no evidence of primary impairment, as poor readers’ performance on spelling and morphology tests was similar to, or better than, younger children of the same reading level. Individual differences in morphological awareness could be fully accounted for by the spelling scores. The reverse was not true, however; differences in spelling performance were not entirely the product of differences in morphological skills. According to Bryant et. al., this pattern of results can be explained if we assume that the development of grammatical awareness is partially the product of learning to read and write. Poor readers have reduced experience with the written language (due to primary phonological deficits) which hampers their development of grammatical awareness. Poor grammatical awareness, in turn, leads to difficulties in spelling morphemes. However, there are no intrinsic problems with grammatical skills in poor readers. They should easily acquire grammatical awareness (given the adequate input of written language) and easily benefit from the instruction that explicitly highlights the connection between spellings of words and their grammatical structure. The second study (Bryant, Nunes & Bindman, 1998) provided additional confirmation of this model, using ‘historical’ comparisons. This involved the analysis of scores from the first testing session (i.e. 20 months before the diagnosis of a reading problem was made). The scores of future poor readers were compared with the scores of children who, at the time, had similar reading levels, yet eventually did not go on to develop reading problems. The performance of both groups was quite similar in terms of grammatical awareness as well as spelling. As both groups showed somewhat delayed reading development, they were also compared with even younger normally 87 developing readers of the same reading age. Those younger children appeared significantly worse on grammatical tasks and spelling than both older groups. This profile of differences makes it unlikely that early deficits of grammatical awareness are a primary cause of reading or spelling failure. Also, it suggests that grammatical awareness develops as a product of children’s experience with written words. There was, however, one area in which future poor readers were deficient: their spelling of past forms of irregular verbs was worse in comparison with two control groups (same age - same reading, and younger age - same reading). Bryant et. al. saw this as evidence of a primary phonological deficit, since correct spelling of irregular verbs does not invoke knowledge of grammatical rules, but straightforward letter-sound correspondences. Within this account, the causal influence of grammatical awareness on spelling is limited to later (orthographic) stages of development. Initially, children have to master decoding. Any difficulties in this area will arrest or slow down their reading progress, which will, in turn, hold back the development of explicit knowledge of grammar. Weaker grammatical awareness will make it more difficult to master grammatically based spellings. Here, again, we are dealing with an instance of a reciprocal relationship between literacy and linguistic skills. The study on apostrophe spelling (Bryant, Devine, Ledward & Nunes, 1997) confirmed these conclusions as far as it found a correlation between grammatical awareness and the correct use of apostrophes (In possessives: Boy's football, but not in plurals: Look at the boys). The grammatical task in question tapped into syntactic, rather than morphological awareness, requiring detection or transformation of genitive nouns, which could not be performed unless the whole sentence was taken into account. However, there was no evidence of reciprocal causality: gains in spelling of apostrophes (caused by experimental intervention) did not lead to improvement in syntactic awareness. Another study (Bryant, Nunes & Bindman, 2000) provided further evidence for a very selective link between morpho-syntactic skills and apostrophe spelling. Only this level of processing (analogy task, requiring verb tense, noun-verb and noun­ adjective transformations) was a predictor of apostrophe spelling, unlike phonological awareness (phoneme oddity) or syntactic- semantic processing (sentence anagrams and a cloze task). Overall, there seem to be two main pathways linking the awareness of grammar with literacy (Bryant, 1995). The first connection involves early reading and syntactic sensitivity. Good syntactic skills allow children to use sentence context to support their decoding. This may be particularly important if the decoding skills have only just started to develop (facilitation) or cannot develop (compensation). The second connection occurs during later phases of literacy development and involves morpho- syntactic sensitivity/awareness, and spelling. Insights into the grammatical structures of spoken language make it possible to learn conventional spellings by grasping the grammatically-based rules that underpin them. Morphological sensitivity/awareness may also optimise reading of novel multi-morphemic words and provide a framework for laying down their orthographic representation (Seymour, 1997, Carlisle, 2000). Quite independently, grammatical skills are probably critical for comprehension of spoken and written language, at all levels of development.

2.3. CONCLUSIONS

The review presented above assumed some fractionation of literacy skills and their cognitive prerequisites. My attempt was to identify basic components of reading and spelling, as well as the cognitive resources and mechanisms that are necessary for their successful acquisition. The data reviewed so far support a (moderate) version of a phonological primacy hypothesis: the first, and most direct constraint of literacy acquisition is phonological processing. Phonological processes are directly involved in the acquisition of recoding and orthographic skills inherent in word decoding, recognition and spelling. Arrested development of recoding and orthographic skills can be traced to phonological impairment - at least in a vast majority of cases. However, the emergence of recoding and orthographic competencies is also facilitated by other language sub-modules, namely morphology and syntax. If recoding and orthographic skills are established successfully, then further development of reading comprehension (extraction, integration and evaluation of knowledge from texts) is constrained mostly by semantic and syntactic abilities. Most of the linguistic abilities discussed here show some signs of a reciprocal relationship with literacy: they are necessary to develop some aspect of reading or spelling, yet also become restructured and enhanced in the process. The changes are not merely quantitative but lead to some unique achievements that otherwise could not be attained (like the emergence of metalinguistic skills). Such reciprocal causality may be a

89 universal model for describing the relationship between literacy and other linguistic (and, possibly, non-linguistic) skills. An important theoretical problem it to identify the most basic level of cognitive explanation for individual differences in the acquisition of recoding and orthographic skills. A near-consensus exists that those skills are constrained by phonology; however, while some authors treat phonological processes as the ultimate level of cognitive explanation (e.g. Shankweiler et. al., 1992) others try to reduce them into yet more basic functional components (such as cross-modal parsing or temporal integration), which are not specifically linguistic (e.g. Cossu, 1999; Wolf and Bowers, 1999).

Another controversy regards the notion of linguistic awareness, especially its status as a causal factor in reading acquisition. There is an intrinsic difficulty in drawing a clear distinction between any processes that are purportedly ‘conscious’ or ‘voluntary’, and those that are ‘unavailable to consciousness’ or ‘automatic’; the same problem applies to making causal inferences about the role of consciousness. Claims about the causal role of ‘being aware of linguistic structures’ must be clarified. It seems that development of at least some aspects of orthographic skills may be successfully described without referring to linguistic awareness (e.g. Bryant, Nunez & Snaith, 2000).

90 CHAPTER 3

CROSS-LINGUISTIC DIFFERENCES IN LITERACY ACQUISITION

The overview of mechanisms and processes of written language acquisition given in the previous chapter was based on a major simplifying assumption: ignoring the influence of the language-specific factors. The reported data from different languages (with English studies being massively over-represented) were used to construct a single story about the acquisition of literacy. It is time, however, to consider how language-specific features may produce variants of this single story - or, indeed, result in altogether different stories emerging in different languages. The chapter will be divided into four main parts. I will start with a formal linguistic analysis identifying those characteristics of spoken languages and orthographies that may affect the processing of written languages. I will focus particularly on the orthographic parameters: transparency, regularity, consistency and complexity. In the second part, the literature on cross-orthographic and cross-linguistic differences of written language acquisition will be reviewed. I will discuss the differences in learnability (the ease of acquisition) as well as learning mechanisms. This will be followed by a review of incidence, manifestations and mechanisms of reading difficulties. These overviews will be largely restricted to languages written alphabetically, though occasional reference to non-alphabetic writing systems will also be made. Finally, I will discuss the key Polish studies on normal and disordered reading acquisition, which were the immediate background to my own project.

3.1. SPOKEN LANGUAGE AND LITERACY

Numerous features of spoken languages have been postulated to have a potential influence on the acquisition of literacy. These will be enumerated and discussed briefly, before the empirical evidence pertaining to their importance is inspected.

91 3.1.1. Segmentai phonology

Languages differ in their total number of phonemic segments, relative frequency, and phonological categories. To give just a few examples: relative frequency of vowels is higher in Romance than Germanic languages; Slavic languages are abundant in fricatives and affricates (both in terms of number and frequency); they also make a phonological distinction between palatal (‘soft’) and non-palatal (‘hard’) consonants, not often found elsewhere. However, the complexity of the vowel system (distinction of quality, diphthongs) is greater in English than in most Slavic languages. Phonological complexity may have no direct bearing on the difficulty of learning to read and write, yet it becomes relevant when the language happens to be written with a ‘borrowed’ orthography that is tailored to a different, simpler phonology. In such cases new graphemes have to be derived, either by adding diacritics or by combining letters into digraphs (in alphabetic orthographies). As those derived forms usually show their relatedness to the canonical ones (i.e. are both phonologically and visually similar) this increases the possibility of confusion and thus the demands of the learning task.

3.1.2. Suprasegmental phonology a) Syllable structure. Languages differ in syllable complexity (presence or absence of consonant clusters), preferred syllable structure and length (open CV or VC versus close CYC, CCVC, etc.) and the overall number of permissible syllables. Those features may be related: languages with few consonant clusters (e.g. Italian, Finnish) tend to have syllables of uniform structure (mainly open CV- ones) and a smaller set of syllables overall. Such distributional characteristics may promote the awareness of syllables as sublexical units, and encourage the building of connections between orthography and phonology at the syllable level. Conversely, in languages with numerous, complex and varied syllables (Slavic, Germanic) the syllable may be a less salient and useful unit (with respect to the acquisition of the orthographic knowledge). Such languages may, therefore, encourage more segmental analysis of orthographic structures.

b) Rhymes. In the most generic sense, rhyme refers to a final part of a word, which may be of any length, and which starts with the (last) stressed vowel (Pszczotowska, 1972). In all monosyllables, and polysyllables with final vowel stress this overlaps with the 92 intrasyllabic unit of rime (e.g. /-ein/: cane, plane, main, contain..,). In other types of words, however, rhyme corresponds to a larger, suprasyllabic structure (e.g. /-ændi/: candy, dandy, brandy). Some linguists (e.g. Berg, 1989) refer to the latter as superrimes; more traditional nomenclature rooted in poetics distinguishes masculine rhymes (in words with oxytonic, i.e. final-syllable stress: pail, whale, entail), feminine rhymes

(paroxitonic, i.e. penultimate-syllable stress: liquor, quicker) and dactylic rhymes

(proparoxitonic, i.e. third-from-end syllable stress: sinister, minister) (Pszczolowska, 1972). Cross-linguistic differences in the distribution of rhyme types may be observed. Languages abundant in monosyllables may contain large and numerous families of masculine-rhyming words (e.g. English), whereas languages with few monosyllables and paroxitonic or proparoxitonic word stress pattern may be abundant in feminine or dactylic rhymes (e.g. Italian, Greek). Those rhyming structures that are most frequent in the language may be potentially most easily available to conscious processing, and recruited for the purpose of literacy acquisition. Rhyming knowledge and awareness might be promoted not only by ‘ordinary’ language use, but also by various forms of poetry and language games (e.g. nursery rhymes, limericks, rhyming proverbs, e.g. Dowker et. al., 1989). The languages that do not possess large rhyming/riming word families at all might selectively promote other structures (e.g. alliterations) instead.

c) Word stress. The distinction between stress-timed and syllable-timed languages, although sometimes criticised as an essentially subjective characteristic of language perception (Roach, 1998) seems relevant to written language acquisition. In stress-timed languages (as English) the phonological quality of vowels changes depending on whether they are stressed or not. This usually results in more ‘unstable’ letter-sound relationships for vowels (e.g. library-librarian, where stands for /o/ and /eo/, respectively). In syllable-timed languages, however, the phonemic value of a vowel stays the same, regardless of its stress. This results in more systematic correspondence between vowel sounds and letters.

93 3.1.3. Syntax and morphology.

Languages differ in the way they express the relationships between the units of meaning within a sentence. Positional languages (e.g. English) accomplish this mainly by manipulating word order; inflectional languages (e.g. Slavic ones) make more use of morphological devices (prefixes or suffixes); the syntactic role of morphology is even greater in agglutinative languages (e.g. Turkish), which tie long strings of morphemes together to express propositions (which, to an English speaker, might look like “a single word standing for the whole sentence”). Those syntactic and morphological differences may have implications for reading. In positional languages the surface word forms are relatively stable, often corresponding to a lexeme (basic, dictionary form of a word). This also implies the stability of the orthographic form. In an inflectional language, however, the same lexeme occurs in a large number of inflectional forms, dependent on syntactic context; the overall number of inflectional endings may be further increased by the existence of several inflectional paradigms. Contrasting Polish and English nouns provides a good illustration: a small number of regular English forms (singular, plural, possessive) correspond to a large number of Polish counterparts, e.g.

CAT, cat’s, cats, cats’ KOT, kota, kotu, kotem, kocie, koty, kotow, kotom, kotami, kotach DOG, dog’s, dogs, dogs’ PIES, psa, psu, psem, psie, psy, psow, psom, psami, psach

Such constantly changing visual word-forms could discourage reliance on visually- based, global word recognition strategies (the logographic strategy in Frith’s (1985) model) and push the learner towards fine-grained analysis of letter information right from the start. In particular, orthographic information about word endings, which may be superfluous for lexical access (for which partial word-stem letter cues are usually sufficient) has to be analysed if the syntactic role of the word is to be identified correctly. Moreover, if the inflectional (and derivational) morphology of the language is systematically reflected in the orthography, this may heighten the morphological awareness of its users and encourage the formation of direct orthography-morphology mappings.

94 3.1.4. Word length.

The dimension of word length is, to some extent, related to language morphology. The languages that add inflections to roots, or agglutinate morphemes together produce longer words than the languages that do not. Longer letter strings are probably harder to discriminate merely on the basis of salient visual cues, which may constitute yet another factor encouraging early and systematic use of decoding, and discourage global, visually-based strategies.

Overall, it seems that the spoken language influences written language acquisition primarily by shaping the orthography itself (e.g. when the phonology necessitates the augmentation of existing grapheme inventory, or when longer words must be rendered by longer strings of letters). In particular, the structure of the spoken language may partially determine which linguistic units (phonemes, rhymes, syllables, morphemes) are most consistently represented in a given orthographic system. Those units, in turn, are likely to play most important role in the literacy acquisition, and become most amenable to explicit (metalinguistic) processing. However, it is also possible that spoken language directly influences the development of phonological awareness. Specifically, the degree of pre-literate sensitivity to different phonological units may vary cross-linguistically as a function of perceptual salience and frequency of those units (e.g. higher sensitivity to masculine rhymes in English than Italian, but the reverse pattern for feminine rhymes and open syllables). Thus, the sensitivity resources that facilitate the eventual emergence of phonemic awareness may vary between languages.

3.2. ORTHOGRAPHY AND LITERACY.

3.2.1. Describing orthographies.

In the previous section I identified some parameters of spoken language that may influence literacy acquisition. Now the orthographic parameters will be addressed. The descriptive and classificatory framework provided here will also become useful later for establishing the place of Polish orthography within the family of alphabetic writing systems.

95 All existing orthographies work by relating some arbitrary graphic symbols to some chosen units of the language. At first glance, orthographies seem to differ mostly in terms of graphic (script) conventions, such as the shape of the symbols or direction of writing. Yet the most fundamental differences pertain to their underlying structure, i.e. the relationship between “the graphic” and “the linguistic”. This relationship can be analysed along two main lines:

• What kind of linguistic unit is represented?

• How systematic are the orthographic representations of the linguistic units?

Regarding the linguistic units represented by writing, we can talk about four basic principles: the syllabic principle: graphemic units represent syllables (e.g. Japanese Kana) the alphabetic principle: phonemes are represented (Greek, Latin and their derivatives) the morphological principle: morphemes are represented (e.g. unpointed Hebrew) the semantic principle: some chosen aspects of meaning are directly represented (e.g. semantic markers in Chinese or Egyptian hieroglyphics)

These principles and their combinations define different writing systems of the world, each system being implemented in a number of specific orthographies. Additionally, some authors talk about historical and conventional principles (Szymczak, 1975). This refers to the instances when the current orthographic rendition of a word reflects its origin, its archaic pronunciation, or (in the case of the conventional principle) some linguistically arbitrary consensus of the literate community (like spelling the name of a deity in uppercase). The historical and conventional influences, although sometimes very significant, cannot, however, be treated as true principles, since they are not productive (they do not entail any rules that could be applied to new instances). The fundamental distinctions between principles (and writing systems) should not, however, overshadow one structural invariant. Writing always codes, to some extent, the sound structure of language, using either the syllabic or the alphabetic principle. Even those orthographies commonly held to be non-phonological (e.g. Chinese) do, in fact, provide some systematic indication of the word’s pronunciation at the syllabic level (Po-Law & Caramazza, 1994). This is not surprising, as transcribing 96 some chosen phonological units is the best (if not the only) way to make writing productive, i.e. capable of recording novel words and utterances (Gelb, 1963, De Francis, 1989). However, the degree of this “phonetisation” varies considerably between systems. A linguistic analysis of any orthography has to establish, therefore, the relative importance of direct grapheme-sound mappings, as opposed to mappings based on other principles. The notion of orthographic depth explores this further (see below).

The alphabetic orthographies are essentially realised by a set of correspondence rules that tie individual phonemes of a given language to graphemes. Graphemes may be individual letters, but also letter pairs (digraphs) triplets or quadruplets that represent individual phonemes (e.g. SH, TH, IGH, HIGH; Coltheart et. al., 1993). However, morphological or even semantic principles are often incorporated into the alphabetic orthographies to a varied degree, together with historical and conventional influences. Alphabetic orthographies may keep the spelling of chosen morphemes constant despite their phonological alterations (especially in the case of bound, inflectional or derivational morphemes); use logographic symbols ($, &, e.g., %, Arabic numerals) within the stream of alphabetically decodable text; retain spellings motivated by etymology of words, or set customary rules of punctuation and capitalisation. The second main difference between the orthographies regards the degree of systematicity of mappings between the units of language and their graphemic representations. Partially overlapping notions of transparency, regularity, consistency and complexity are used to describe this co-variance.

Transparency refers to sound-symbol mappings. In a fully transparent system, there is a one-to-one correspondence between sounds and their graphemic symbols. A fully transparent alphabetic writing has each phoneme represented always (and only) by one grapheme (regardless of its position in a word). Such correspondences are called bi­ unique (Carney, 1994). Orthographies vary markedly with respect to their transparency. A paradigmatic case of a transparent orthography is the International Phonetic Alphabet (IPA). Most ‘real’ orthographies, however, contain only few correspondences fulfilling the criterion of bi-uniquess (e.g. /a/ s in Polish). Some (like English) have none. The notion of transparency can, however, still be applied to them, albeit in a weaker sense. We can call a word transparent if its pronunciation can be computed from its spelling by applying most typical grapheme-phoneme correspondences, or by using 97 letter sounds. Thus English words like CAT, NOT, CAN, CHAT may be seen as transparent, since their pronunciation can be worked out by someone with the knowledge of most typical sound values of English graphemes.

Regularity. Whenever the relationship between graphemes and linguistic units can be described in a systematic way, we can call it ‘regular’ and talk about ‘an orthographic rule’. The rules, by definition, are productive, i.e. capable of generating spellings or pronunciations of new or unknown words. Full regularity implies full predictability (i.e. no exceptions), usually, however, ‘exceptional’ or ‘irregular’ cases occur (e.g. pint or come which both break the ‘silent e’ rule). Some rules are context-sensitive (e.g. the rule for initial letter c, whose pronunciation depends on the following letter) and position specific (e.g. three different rules for the letter y, for the initial position as in yet, for the middle position as in gym, and for the final position as in sky) (Coltheart, et. al., 1993). The notions of transparency and regularity are interdependent but not equivalent. Transparency implies regularity (since transparent words conform to grapheme- phoneme correspondence rules). The reverse, however, does not follow: the features of the orthography which are regular do not have to be transparent. A good example is, again, given by the ‘silent e’ rule: although the pronunciation of the vowel letters in word pairs like mat - mate, cop - cope, tub - tube, etc. alternates (therefore, is not fully transparent) the correct choice is determined by the underlying rule. In such cases, letter-sound correspondences diverge from bi-uniquess, and break into conditioned variants. When alternative spellings or pronunciations cannot be disambiguated by any rule (i.e. are item-specific) we can talk about competing variants (Carney, 1994). Most alphabetic orthographies are also regulated by some rules that stem directly from the morphological principle. English, in particular, has rules for keeping the spelling of chosen morphemes constant, regardless of the changes in their surface phonological realisation. This is true especially for inflectional morphemes (- 5, -ed), but also lexical ones (bomb-bombard, legal-legislature). An additional category of elimination rules adapts the spelling of morphemes to the structure of complex words, by removing, replacing or adding certain letters at morpheme boundaries (eg. full but: spoonful, mouthful, cry, dry but: cries, dries) (Carney, 1994). An altogether different category of rules falls under the heading of graphotactics. Unlike all the rules mentioned above, graphotactic regularities are not concerned with any correspondences between the graphemes and the elements of 98 language, nor do they deal with any divergences from typical correspondences. They merely determine which grapheme combinations (strings) are legal. The fact that an English digraph CK never occurs word-initially (though it does in other positions) is an instance of a graphotactic rule. The arrangements of graphemes can also be expressed statistically as a frequency function of their position in the word. Graphostatistic regularities are not absolute rules, but relative statements about the likelihood of finding a particular grapheme arrangement within a given orthographic system. This allows some words (like TZAR, AMOEBA, AISLE) to be identified as orthographically “strange” or “unique”.

Some authors taking the educational perspective are interested in learners' conscious awareness of the rules. They often maintain that, from the point of view of literacy acquisition it is not the underlying linguistic regularity per se that is important, but the perceived regularity of the code (Downing, 1973). In other words, it is irrelevant whether some rules describing the orthographic phenomena can be drawn in principle, what matters is whether those rules can be easily understood and utilised by the learner. Rules that are taught explicitly in order to consolidate learners’ knowledge and help to avoid potential errors are called prescriptive. Most, however, ignore this subjective aspect of rule awareness. This is especially apparent in the connectionist literature, which quantifies the concept of regularity. A rule exists whenever a sound-spelling generalisation can be formed by the learning system (human or otherwise). Rules are not specified a priori, but re­ constructed from the input by the learning algorithm - strictly speaking, they are quasi­ regular statistical regularities. Within such an approach, the issue of conscious insight is not relevant.

Consistency. The notions of transparency and regularity are used primarily to describe individual grapheme-phoneme correspondences extracted from contextual and positional effects as far as possible. Consistency, on the other hand, deals with correspondences in a specific ‘environment’ (certain preceding and following letters, given position within a string) and can be applied to the analysis of sublexical units of any size (also larger than individual phonemes/graphemes). A grapheme, or string of graphemes is pronounced consistently if, in a given position (eg. word initially) it is always assigned one pronunciation. Conversely, any 99 phonological unit is spelled consistently if, in a certain position, it gets only one orthographic rendition. Thus, the letter sequence , although non-transparent in English (as it is pronounced differently in cat, abattoir, ate) is consistent when occurring word-finally: in that position it always corresponds to the rime /-æt/ {cat, mat, combat...). Consistency can be seen as a continuum and operationalized statistically by inspecting the whole word neighbourhood (the pool of words sharing the target graphemes or phonemes in the same position within a word) and counting the relative frequencies of alternative spellings or pronunciations. This can be done in two ways.

The type count compares the number of ‘friends’ (words sharing a particular pronunciation, e.g. /-ouv/ for -OVE: drove, alcove, grove, stove...) with the number of

‘enemies’ (words with alternative pronunciations: glove, shove, above, approve). The token count is also the ratio of enemies to friends, but weighted by the frequency of each word. Both type and token consistency counts are used in psychological studies of word recognition (e.g. Treiman et. al., 1995). Consistency and regularity are not fully equivalent: although irregular words have to be inconsistent, the reverse does not hold. This results in four word categories (Stanovich et. al., 1997; Coltheart et. al., 1993; Laxon, Masterson & Coltheart, 1991): irregular and inconsistent (exceptions): they contain some grapheme-phoneme correspondences that are atypical (rare) and thus may also have orthographic neighbours that conflict with their pronunciation (e.g. pint, steak - cf. mint, flint;

beak, leak); regular but inconsistent: they obey standard grapheme-phoneme correspondences,

but have several enemies in their neighbourhood (e.g. stove, drove - cf. love, move); regular and consensus: they obey standard grapheme-phoneme correspondences and share their pronunciation with nearly all their neighbours, but have an odd enemy

(e.g. mint - as m flint, hint, etc., but ci. pint); - regular and consistent: built of the most typical (frequent) individual grapheme-

phoneme correspondences, and having no enemies (e.g. stiff, press, blame).

Consistency may vary with the size of the unit concerned. This is most apparent in English, where pronunciation consistency for single vowel graphemes, in particular, is very low, but it grows rapidly when vowel graphemes are considered in the context of larger units: bodies and, especially, rimes (Treiman et. al., 1995). Similar discrepancies 100 are also observed in French, albeit to a lesser extent (Peereman & Content, 1997). These orthographies are, then, more predictable for the user at the level of larger, intrasyllabic units. In contrast the orthographies that are more transparent overall, show a similar, high degree of consistency for small and large units.

Reading versus spelling. Insofar as an orthography diverges from bi-uniquess, it contains two sets of mappings: for reading (spelling-to-sound, or “feed-forward”), and for spelling (sound-to-spelling, or “feed-backward”) that are not isomorphic (reversible). This fact is reflected in the distinction between homographs (different pronunciations but the same spelling, e.g. wind - (to) wind) and homophones (different spellings but the same pronunciation, e.g. their - there), which reflect feed-forward and feed-backward inconsistency, respectively. Generally, orthographies show higher degrees of transparency, regularity and consistency for reading than for spelling. This discrepancy may not be very marked in English, yet it is in a number of other orthographies (such as Greek or German), which are fully consistent for reading (only one pronunciation of every letter string is possible, no homographs) but not for spelling (different graphemic realisations of the same phoneme string are possible, homophones occur). This may be one of the factors that make spelling a more difficult task than reading.

Orthographic depth. It has been pointed out that all writing systems convey language phonology to some degree, yet they differ as to how directly this phonological information is conveyed. Regarding this, we can talk about the continuum of orthographic depth (Frost & Katz, 1992; Frost, 1992). At one end of this continuum we find systems that are purely phonological: they directly render the surface sound form of words (using the alphabetic or syllabic principle). Such shallow orthographies are, of necessity, transparent and regular. The deep orthographies, on the other hand, involve the morphological principle: they represent the underlying morphological structure of words, from which surface phonology can only be derived indirectly. The majority of existing orthographies are a mixture of deep and shallow features, and can be placed somewhere along the continuum. Orthographic depth implies lack of transparency, but not necessarily lack of regularity or consistency. Some deep orthographies (e.g. Hebrew) convey morphological information in a very regular way. However, the tendency to keep the 101 spelling of the morphemes constant is associated with another tendency to retain the spellings that reflect the history of the orthography and its conventions, but are otherwise capricious. Thus, orthographies with deep features (e.g. English) are usually loaded with exceptions, and show low degrees of regularity or consistency.

All the notions discussed so far can be seen as different facets of the more basic concept of orthographic complexity. Complexity reflects the overall amount of knowledge one has to acquire in order to master a given orthographic system, so is directly proportional to the degree of noise, ambiguity and competition within that system (see Ellis & Hooper, in press, for similar ideas). Simple orthographies are predictable, and thus regular, consistent and easy to describe. They are built from a few, highly productive and exception-free rules (usually grapheme-sound correspondences). Complex orthographies, on the other hand, are built from a large number of ‘local’, context- sensitive rules, and contain many exceptions that violate even those local patterns. They are, therefore, neither transparent, nor regular or consistent. It is assumed that complexity makes learning more difficult, as it limits the possibility for generalisation (transfer of knowledge) and may result in cognitive confusion (failure to understand the demands of the task in the face of its ambiguity) (Ellis & Hooper, in press; Downing, 1973, 1986/2000). Orthographic complexity may be operationalized by the length of description necessary to account for a given orthographic system, e.g. the length of a computer algorithm necessary to carry out grapheme-phoneme conversions, or the number of exceptional word spellings. It could even be crudely approximated by the length of linguistic treatise required to comprehensively describe an orthography. In the following analyses, I shall refer mainly to the dimension of complexity as a global indicator of how difficult an orthography may be to acquire. I shall also talk about consistency, insofar as I am specifically interested in decoding skills, and how they are affected by the degree of orthography-phonology co-variance. For alphabetic orthographies at least, complexity and consistency correlate highly. Figure 3-1 provides a crude classification of the alphabetic orthographies (those mentioned in this chapter) along these two continua.

102 / ^ English

M French C 0 N S Dutch? Polish?

1 German S T Spanish? Greek? E N Italian C Turkish? Welsh? Y Finnish, Serbo-Croatian

I PA

COMPLEXITY

Figure 3-1. Schematic classification of alphabetic orthographies on the dimensions of complexity and consistency.

3.2.2. The relationship between teaching methods and orthographies.

The choice of a method employed to teach reading and spelling seems logically independent of the specific features of language and orthography they are employed for. In fact, however, the two are closely related. High complexity of an orthography may induce some uncertainties as to the best method of teaching (Emphasising typical letter- sound correspondences? Families of analogous words? Morphological structures? Etymology of words? Relying on rote memorisation?). The persistent ‘reading wars’ over how to best teach reading to children, which divide the educational fields of the English speaking world, seem less present in countries with simpler orthographies. High orthographic consistency, in particular, makes explicit phonics instruction an obvious choice. Languages with rich inflectional structures also necessitate some phonics instruction right from the start, in order to enable readers to accurately recover the syntactic information conveyed by affixes. This is acknowledged even by those authors that generally subscribe to non-phonics (look-and-say) approaches (Dobrowolska- Boguslawska, 1991).

103 3.2.3. The impact of orthography on literacy acquisition - a summary of hypothesis.

The first group of hypotheses concerns the impact of orthographic complexity on learnability. Simple orthographies may be easier to learn for a number of reasons. Insofar as they are consistent, straightforward grapheme-sound mapping and systematic phonics teaching may facilitate the development of robust decoding skills which allow for efficient self-teaching. The decoding advantage may, then, generalise to word recognition, spelling or even reading comprehension. Simpler orthographies may also be easier to acquire as there is just less to learn (in terms of rules, exceptional spellings, etc.) and the cognitive competition or confusion that may be triggered by inconsistent patterns is eliminated. Linguistic awareness should benefit along with decoding, specifically at the unit-size level (morpheme, syllable, onset-rime, phoneme) most consistently represented in that particular orthography.

The second group of hypotheses regards processing strategies. Beginning readers of simple orthographies may rely more on alphabetic recoding - context-free activation of grapheme-phoneme correspondences that computes highly specified phonological representation during the early phase of word identification. Conversely, the initial strategy of complex orthography learners may be more context-dependent, relying on word-specific, graphotactic and graphostatistic knowledge. It may activate orthography- phonology mappings of larger size (e.g. rhymes) and generally result in only minimal computation of word phonology (unless overt naming is required). Complex orthography may also encourage top-down contextual priming and guessing. Similar “lexicalisation” and “contextualisation” of reading is also expected in children taught to read with the methods de-emphasising decoding skills (look-and-say or language experience approaches). The deep orthographies that are regular in conveying morphological structures may also encourage the formation of direct orthography-morphology connections, as well as increasing the awareness of morphological structures. Some of the differences postulated above have been found in the context of skilled reading. The extent and timing of phonological activation in lexical access varies with orthographic depth (Katz & Frost, 1992; Frost, 1992). Also, a number of studies have demonstrated the consistency effect, i.e. faster and more accurate processing of 104 consistent mappings (e.g. Treiman et. al, 1995; Peereman & Content, 1997). Such differences may plausibly be even more pronounced in the developmental phase. Differences between competent readers may be minimal, because proficient reading requires the same core competencies (accuracy and automaticity), regardless of orthography. However, the same competencies may be a product of quite different developmental histories (convergent evolution). The differences may arise with respect to timing of various developmental gains, or their sequence. Thus, the ability of context- free decoding of novel words with unfamiliar orthographic structures should occur earlier in the simple systems. Conversely, the facilitating effect of familiar orthographic patterns (evidenced, for example, by the word and nonword legality effect: Underwood & Batt, 1996) should occur earlier in reading complex orthographies. Yet both skills must eventually be included in the cognitive repertoire of a mature reader of simple and complex orthographies alike.

Finally, the third group of hypotheses pertains to the differences in cognitive resources that are pre-requisites and co-requisites of learning to read and spell. In all alphabetic orthographies, phonemic awareness is likely to be critical. Awareness of larger phonological units may appear important for those alphabetic systems where consistency of syllable-level or onset-rime level mappings is higher than consistency of basic grapheme-phoneme correspondences. Likewise, the acquisition of deep orthographies that consistently represent morphological structures may be linked more strongly with morphological awareness. As consistent orthographies should make linguistic awareness generally easier to acquire, its constraining power for reading and spelling may be relatively short-lived, limited to the very initial stages of acquisition. On the other hand, the efficiency of phonological retrieval and forming symbol-name connections (indexed by naming tasks) may play a similarly important role in all orthographies, insofar as they are necessary for the acquisition of specifically orthographic skills, and the automatization of all reading and spelling sub-processes. Finally, visual processes are likely to play some role at the earliest stage of reading acquisition whenever global (e.g. look-and-say) teaching methods are used.

105 3.2.4. Language, orthography and the acquisition of literacy - a review of data.

3.2.4.I. The relative difficulty of acquisition.

Are complex orthographies indeed harder to learn than simple ones? There are two main strains of evidence relevant to this question. The first, most direct, comes from bi- scriptural languages - those that use two (sometimes even more) different orthographies. Prime examples are Chinese and Japanese, which use an extensive set of ancient Kanji characters (based on a complex interaction of syllabic, morphemic and semantic components) and supplement them with more modern alphabetic (Chinese Pinyin) or syllabic (Japanese Kana) orthographies, which are simple and transparent. The differences in the rate of acquisition are startling and reflected in the school curricula. Children are generally expected to learn the phonetic orthography within their first school year, and, later on, use it as a tool for learning the Kanji system (and for other functions, such as transcribing foreign names). Kanjis, on the other hand, are gradually and laboriously learned throughout all school years, yet even that does not guarantee the full mastery of the system (e.g. Mason et. al., 1989 and Ohara, 1978, cited in Share, 1995; also Coulmas, 1989). A similar idea of a simple transitional orthography has also been experimentally tried out in English, especially using the Initial Teaching Alphabet (i.t.a.). I.t.a is an augmented Latin alphabet, tailored to maximise its fit to English phonology. The i.t.a. constitutes a near-transparent system, with mostly bi-unique grapheme - phoneme correspondences. I.t.a. gained some popularity in England and USA (especially between 1960 and 1980) as a method of teaching literacy, whereby children are taught to read in i.t.a. first, and only later, after becoming fluent, do they switch to the conventional orthography. I.t.a. attracted a great deal of research, concerned mostly with its validity as an instructional approach, but also with broader theoretical issues of orthographic complexity and its influence on literacy acquisition (for an overview, see Downing, 1967, 1969; Warburton & Southgate, 1969; Bond, Dykstra, 1967/1997; for a more recent investigation see Thorstand, 1991). Generally, children learning i.t.a. made better progress (e.g. as measured by their rate of transition through reading series), than similar children learning the conventional English orthography. In most studies, the robust differences were maintained even when additional controls (for teachers, instructional practices and materials) were introduced. Thus, the effect seems specific to the 106 orthography itself, with the conventional, complex English system being detrimental to reading acquisition. Some of the studies also found that the advantage enjoyed by the i.t.a. children was maintained after they switched to the conventional orthography. This may suggest that the firm grasp of the decoding skills (apparently facilitated by the i.t.a.) made it subsequently easier to learn any new alphabetic orthography. However, the data were very inconsistent at this point, with many studies showing i.t.a. children losing their advantage after the switch to the conventional orthography, or even performing worse than the children using the conventional orthography right from the start. Differences were also partially dependent on subskills being measured (word recognition, comprehension, spelling (Downing, 1967; Warburton & Southgate, 1969)). The second strain of evidence regarding the relative difficulty of different orthographies comes from cross-linguistic studies. These have usually included an English language group as a benchmark against which readers in other languages and orthographies could be compared. Relatively few studies of this kind have been published. In order to reach some general conclusions about their outcome I have attempted to collate all of them, providing they fulfilled two criteria: included normal school-age participants, and used word or nonword reading accuracy as the outcome measures. I was able to trace ten studies, reporting thirteen different experiments. Accuracy results are summarised in table 3-1 and figure 3-2. Despite the differences of sampling, matching and outcome measures the data show remarkable consistency, with the non-English children being more accurate than their English language peers on all studies (albeit not all those differences being significant). Cross-orthographic differences seem to gradually diminish with age. 9-10 year old English children no longer differ in word recognition skills from their simpler orthographies counterparts, but they are still worse at decoding. Null results for word recognition must be partly an artefact of the selection procedure (as some studies tried to match the groups on word recognition in order to test differences in nonword decoding) yet they may also reflect differences in underlying strategies and skills. English speaking children probably read in a more lexical, large-unit driven, rather than code-driven manner (see particularly Goswami, Gombert & de Barrera, 1998). The evidence from dyslexia studies presented below (section 3.3) suggests that, at least in the case of poor readers, the decoding disadvantage of the English readers is not overcome even at a later age.

107 STUDY AGE PARTICIPANTS STIMULI WORD SCORES NONWORD SCORES % correct % incorrect ENG OTHER sig ENG OTHER sig ley & Goldman American and Turkish, Nonwords; the same list in both 59 94 * 984 ) CA matched. Turkish languages. 1-3 syllable, 3-9 letter 87 94 * participants sig. better at long reading comprehension lorstad (1991) 6yrs English and Italian, CA Words: a difficult, adult text 56 55 87 * 7-9ys matched. English word long. The original in Italian, 90 93 * 10 yrs participants sig. better at English children read the non-verbal IQ translation. 98 98 ns (immer & 7yrs English and German, Words: number words 1-12 in 96 99 66 87 * joswami (1994) 8yrs 2"**, 3'‘* and 4“' graders, English and German, respectively. ? 7 63 92 * 9yrs matched on the length of Nonwords: derived from respective — * (im mer & Frith schooling. German number words by exchanging 100 100 76 91 994) children 10 months older onsets; 1-2 syllable, 3-6 letters long. on average inderi, 8yrs English and German, Words: 1-3 syllable, 3-10 letters 68 95 * 65 90 h’mmer, Frith CA-matched. Only data (Eng), 3-11 letters (Grm). 997) from normally reading Nonwords: derived from respective participants are reported words by changing onsets. 1-3 here. syllables, 3-12 letters. All items identical or very similar in both languages. oswam i, 7yrs English and French, Words: 1-2 syllable, 4-6 letters 90 90 52 80 * ombert, de 8yrs matched on reading age (Eng), 4-8 letters (Fr). 93 98 63 88 * arrera (1998) 9yrs Nonwords: derived from respective — xperiment 1 words by exchanging onsets. 99 99 88 94 ns Orthographic similarity to real words varied systematically. 1-2 syllables, 4-7 letters (English), 4-8 letters (French). loswami et. al. 7yrs English and French, Words: 1-2 syllables, 4-6 letters 62 92 31 71 * 1998) 8yrs matched on reading age (Eng), 4-8 letters (French). 81 97 38 77 * xperiment 2 9yrs Nonwords: orthographically — dissimilar to real words. 95 98 76 78 ns Phonological similarity to respective real words varied systematically. 1-2 syllables, 4-7 letters (Eng), 4-8 letters (Fr). loswami et. al. English, Spanish and Words: 1-2 syllables, 4-6 letters Sp Fr Sp Fr 1998) 7yrs French matched on (Eng), 3-7 letters (Sp), 4-8 letters 61 94 86 22 90 63 * * xperiment 3 8yrs reading age (Fr). 9yrs Nonwords: both orthographic and 94 93 98 64 87 77 * ns phonological similarity to 94 97 98 — 70 89 74 * ns respective real words varied systematically. 1-2 syllables, 4-7 letters (Eng), 3-7 letters (Sp), 4-8 letters (Fr). losw am i, 7yrs English and Greek, Nonwords: derived from real words 67 93 31 89 * 'orpodas, 8yrs matched on reading age. by changing onsets. Orthographic ? 7 64 85 * yheelwright 9yrs similarity to real words varied 9 7 — 81 93 * 1997) systematically. 2-3 syllables, 4-10 Experiment 1 letters (Eng), 4-8 letters (Greek). loswami et al. 7yrs The same as in Nonwords: 3-syllable, 18 84 * 1997) 8yrs experiment 1. orthographically dissimilar to real 40 88 * Experiment 2 9yrs words. Phonological similarity to * real words varied systematically. 6- 53 92 10 letters (Eng), 6-7 letters (Greek). iaslund (1999) grade 1 American and German Words: high frequency English 68 78 ns 48 71 * grade 2 children, matched on the words, and their German 96 98 ns 80 89 * length o f schooling? translation, respectively. 1-syllable, 2-5 letter long Nonwords: the same list used in both languages. 1 syllable, 3-4 letters long.

Table 3-1. Summary of cross-linguistic studies of early reading accuracy. Significant differences between English and other language groups are marked *. In some studies, word recognition accuracy was the control variable, and attempts were made (not always successful) to match the participants on that ability. Those studies are marked with — in the sig. column. CA - chronological age.

108 ^ STUDY AGE PARTICIPANTS STIMULI WORD SCORES NONWORD SCORES % correct % incorrect ENGOTHER sig ENG OTHER sig lis & Hooper 6-7yrs English and Welsh, Words: varied systematically on 52 61 1 press) matched on CA, reading frequency, 1-11 letters (Eng), 1-15 experience and academic letters (Welsh). achievement )encer & 6yrs English and Welsh, Words: high frequency English words 59 81 44 78 * aniey (in matched on CA and their Welsh translation. 1-2 syllable, ess) 2-5 letters (Eng), 1-2 syllable, 2-7 letters feperiment 1 (W elsh) Nonwords: derived from number words by exchanging onsets; 1-2 syllable, 3-6 letters (English), 1-2 syllable, 3-7 letters (W elsh) i>encer & 7yrs The same children Words: English words and their Welsh 47 86 62 89 * inley (in follow ed up a year later translation. 1-2 syllable, 3-7 letters pss) (Eng), 1-2 syllable, 3-8 letters (Welsh) «périment 2 Nonwords: the same as in exp. 1

Table 3-1 continued

100 ^

90 .

80 .

70 -

50 .

40 .

30 - — A — words - English ■ words - other 20 . — A — nonwords- English 10 . — ■— nonwords - other

6-7 yrs 8 yrs 9-10 yrs

Figure 3-2. The % accuracy of word and nonword reading in English and other languages. The scores are medians for the data presented in table 3-1.

Whereas the differences regarding reading accuracy are consistent and very robust,

studies reporting reading speed data have been fewer and less conclusive. Some showed English readers to be both slower and less accurate on nonword reading (Oney & Goldman, 1984; Wimmer & Goswami, 1994; Landerl et. al., 1997; Goswami et. al., 1998; Naslund, 1999) which indicates the global difficulty of decoding. However, a speed advantage for English readers was also reported (Goswami et. al., 1997; 1998;

109 Ellis and Hooper, in press), and the outcome seems to depend on language, age and orthographic characteristics of nonword stimuli. English participants were consistently slowed down by orthographically unfamiliar nonwords, but not necessarily by those analogous to real words. This indicates greater lexicalisation of decoding procedures in English readers. Conversely, the fact that some simple orthography readers were more accurate yet took longer to read (especially in Goswami et. al., 1997) is indicative of sequential decoding strategy. Age-related speed-accuracy trade-offs for real word reading were observed by Thorstand (1991), as well as Wimmer & Goswami (1994). The youngest participants reading consistent orthographies (Italian and German, respectively) were slower than their English counterparts; the difference, however, disappeared with age or (in Thorstand, 1991) gave way to the speed advantage of consistent orthography readers. Ellis & Hooper (in press) observed 2"'’ grade Welsh readers to be slower than their English counterparts; the difference, however, was limited to low-frequency words (on which Welsh children showed the largest accuracy advantage). Those patterns, again, suggest strategic differences: more analytic, detailed and sequential decoding of the consistent orthography readers gave them a huge advantage in terms of accuracy, but initially slowed them down. The reading of English learners was more global, based on fewer letter cues, which made it quicker but less accurate. Cross-orthographic studies of spelling performance, which have been even rarer, found an accuracy advantage of consistent orthography learners (Thorstand, 1991; Caravolas & Bruck, 1993; Wimmer & Landerl, 1997). Arguably the most interesting demonstration of this effect was provided by Upward (1992), who reported that English undergraduates studying German as their main degree subject made fewer spelling errors in German than in their (native!) English, during translation exercises. There is sparse and mostly negative evidence for the influence of orthography on reading comprehension. Cross-national surveys of reading comprehension or functional literacy have usually been concerned with cultural, educational and economic influences on attainment, and any possible orthography-related variance is likely to be swamped by those major factors. Two surveys, however, are worth mentioning. Elley (1992) in the largest cross-national study of school-age literacy conducted so far investigated the influence of “phonetic regularity of the language” on reading comprehension of 9-year olds. The comparison of the 10 most and 10 least regular orthographies found no significant difference once the main socio-economic variables were partialled out. It 110 may be questioned, however, whether Elley correctly classified some orthographies with respect to regularity. It can also be added that the country that performed best in the survey - Finland - was also one with the simplest orthography.

The second study. International Adult Literacy Survey (Literacy...., 1995) assessed functional literacy and numeracy in representative adult samples of eight countries. Large differences between English-speaking countries (with Britain below, USA above, and Canada well above international mean) show that, if anything, orthography is not among the most important influences on comprehension. However, all English-speaking countries were among those with the highest proportion of readers at the lowest level of literacy. It is plausible that this bottom group also includes dyslexies, whose difficulties (partially fuelled by the complexity of the orthography they happened to learn) were never properly remediated. It is important to mention that Poland performed by far the worst on all indices in all age and education groups. In experimental studies Oney & Goldman (1984) and Ellis & Hooper (in press) showed that English children were worse at decoding (in comparison with Turkish and Welsh readers, respectively) even when they were significantly better at comprehension. This suggests that the effect of orthographic consistency may be specific to decoding. However, as a consistent orthography allows successful word decoding much beyond current comprehension level (Ellis & Hooper, in press) it may facilitate the acquisition of new vocabulary. It is also possible that, as consistent orthographies facilitate the code-breaking aspect of reading, they may raise interest in reading in general, which leads to greater reading experience and subsequent improvement of vocabulary and comprehension. Circumstantial evidence for those indirect effects has come from i.p.a. studies (Downing, 1967; Warburton & Southgate, 1969). The answer to the question “Is it easier to learn a simple orthography?” is then, an unequivocal “yes”, when it comes to reading accuracy (and particularly the accuracy of reading novel words) and “not really, or perhaps indirectly”, when it comes to comprehension. For reading speed, the answer depends on the stage of acquisition and the kind of task a child deals with.

S.2.4.2. Differences in reading strategies Some cross-orthographic differences in the way writing is processed have already become apparent in the previous section. Whereas phonological recoding skills are central to the acquisition of all orthographies, their nature varies. In inconsistent

111 orthographies, recoding seems to be more constrained by existing lexical knowledge, to involve larger orthographic/phonological units, to be less systematic (only minimal identification of letter cues occurs) and to mature later. In consistent orthographies, conversely, decoding seems more ‘decontextualised’: based mostly on small-unit (grapheme-phoneme) mappings, with reduced back-up from lexical knowledge. It matures early and is applied systematically to deal with novel stimuli. Several related strains of evidence confirm these conjectures:

Reading speed. Beginning learners of consistent orthographies tend to read slowly, sometimes significantly slower than their inconsistent orthography counterparts (e.g. Thorstand, 1991; Wimmer & Goswami, 1994). This disadvantage, however, tends to disappear with age. Such a trend may be explained by an early detailed sequential decoding strategy, which gradually gives way to more direct (parallel) recognition.

Overt reading behaviour. Early readers of consistent orthographies are commonly observed to overtly sound out and blend letter sounds or syllables (e.g. Wimmer, 1993b).

Strong word length effect (significantly higher for consistent orthography learners: Oney & Goldman, 1984; Ellis & Hooper, in press; Spencer & Hanley, in press) and the effect of word exposure time (Wimmer & Hummer, 1990) observed in consistent orthographies can also be explained as a product of systematic sequential decoding.

Correlations between different literacy subskills and stimuli types (reading and spelling, words and nonwords) are very strong in consistent orthographies (Thorstand, 1991; Wimmer & Hummer, 1990). This, again, suggests a single recoding process underlying all aspects of learning, as opposed to developmental dissociations (particularly between reading and spelling) suggested for inconsistent orthography acquisition (e.g. Frith, 1980, 1985). Whether this constitutes a clear case of cross-orthographic difference is disputable, however, as a number of English studies have also reported strong correlations between early literacy subskills (Ehri, 2000).

Reading errors. Consistent orthography readers not only make fewer mistakes, but also show smaller proportions of lexical errors and reading refusals (particularly in nonword 112 reading tasks) and their errors are closer to the target in terms of the proportion of shared graphemes (e.g. Wimmer & Goswami, 1994; Thorstand, 1991; Wimmer & Hummer, 1990; Naslund, 1999; Ellis & Hooper, in press; Spencer & Hanley, in press). This indicates reduced lexical influences on reading, and greater reliance on small-unit decoding. A series of nonword reading studies carried out by Goswami et. al. (1997, 1998) point in the same direction. Readers of inconsistent orthographies (French and, particularly, English) showed a large performance impairment when they had to read nonwords whose rime structure did not resemble any familiar words (i.e. which lacked rime neighbours). This was true for orthographic neighbourhood (e.g. faip harder than fape in English) and phonological neighbourhood (e.g. faish harder than faip). Similar manipulations in more consistent orthographies (Greek, Spanish) resulted in much smaller performance impairment. This, again, points to the fact that decoding in the inconsistent orthographies may involve larger units (e.g. rime-based analogy making) whereas in the consistent ones it may be carried out predominantly at the level of grapheme-phoneme correspondences. Decoding strategy may, then, reflect orthographic consistency, which in complex orthographies is higher for larger units (especially onsets and rimes) than individual graphemes (Treiman et. al., 1995).

Early emergence of decoding. English children learning to read with a ‘look and say’ method may indeed go through an initial logographic phase (Frith, 1985) where reading occurs without phonological mediation (sight word recognition in the absence of decoding skills, absence of sounding out behaviour, lexical and visual errors: Seymour & Elder, 1986). In contrast, consistent orthographies and phonics teaching result in systematic alphabetic decoding right from the start of learning to read (Wimmer & Hummer, 1990; Wimmer et.al., 1991; Wimmer, 1990)

A quantitative cross-orthographic difference has also been found in the relative proportion of vowel and consonant errors. Whereas in English studies vowels were misread more than consonants (Fowler, Liberman & Shankweiler, 1977) the reverse was true for Italian (Cossu, Shankweiler, Liberman & Gugliotta, 1995) and Serbo-Croatian (Ognejovic, Lukatela, Feldman & Turvey, 1983). A direct English-German comparison also showed a similar trend (Naslund, 1999). Here, the pattern may result not so much from distinct reading strategies, but may be a very direct reflection of orthographic consistency. This consistency is particularly low for English vowel graphemes; 113 moreover, the phonological vowel system of English is also complex. In Italian and Serbo-Croatian, however, orthographic consistency, while generally high, is highest for vowels.

S.2.4.3. Differences in linguistic awareness.

In the preceding chapter I discussed the developmental connection between linguistic units and literacy. The ability to divide utterances into words, words into syllables, and to produce rhyming structures appeared to emerge universally before the onset of literacy (e.g. Liberman et. al., 1974; Bradley & Bryant, 1983; Mann, 1986). However, conscious control over phonemic segments (phonemic awareness) is contingent upon the knowledge of alphabetic writing. In this section I will focus on those more subtle differences of phonological skills observed between various languages written alphabetically. I have suggested, in the first part of this chapter, that differences in the mastery of phonological skills may be induced by the structure of a spoken language, the degree of orthographic complexity, and teaching methods. Diversity related to the spoken language is detectable most clearly in the pre-literate participant, whereas in children already learning to read it becomes inseparable from the influences specific to orthography and teaching. A systematic research programme investigating cross-linguistic differences in pre-literate phonological skills was pursued by Dowker. She used an ingenious methodology of analysing children’s spontaneous and elicited ability to make up poems (Dowker & Pinto, 1993; Dowker et. al., 1998). The last study is particularly interesting, as it not only simultaneously compared children speaking five different languages, but it also included a group of Polish pre-schoolers. Speakers of all languages were clearly capable of poem-like creativity, but the differences were observed in the ways poems were made. Italian and Polish children used phonological devices more frequently than the English children, who in turn used them more frequently than the French or Brazilian children. The two latter groups used, instead, semantic devices (metaphors, similes) much more often. Within the groups that made relatively frequent use of phonological devices, Italian and Polish participants made more use of alliteration than English participants, but Polish children used less rhyme than the English. Dowker et. al. pointed toward linguistic and cultural-linguistic factors (differences in stress patterns, 114 frequency and complexity of phonological clusters, overall frequency of rhyming and alliterative words in the language, exposure to certain poetic genres) as a likely explanation of the observed discrepancies. A more direct cross-linguistic analysis of phonological awareness was carried out by Cossu et. al. (1998) who tested Italian 4-, 5 -, 7- and 8-year olds on syllable and phoneme tapping tasks in a way that made the results directly comparable to the American study published previously (Liberman et. al., 1974). A basic similarity of developmental patterns was found. At pre-school age, American and Italian children alike were better at syllable than phoneme segmentation. In both language communities, dramatic improvement of performance was observed following a brief period of reading instruction, especially on the phoneme task. However, the Italian participants consistently outperformed their American counterparts at both tasks and all age levels, and reached near ceiling performance by the second grade. At school age, their performance also became better at phoneme than syllable tapping, while the American participants retained the earlier pattern of syllable over phoneme superiority. In explaining these differences the authors invoked both the phonological and orthographic simplicity of the Italian language. Importantly, although the syllabic structures were more easily accessible to the Italian speakers they did not seem to be more important for learning to read. In English and Italian alike, the acquisition of literacy was most directly linked with phonological, not syllabic awareness. The advantage of simple orthography readers on Liberman et. al.’s (1974) phoneme tapping test was replicated by Spencer & Hanley (in press) in a Welsh-English study. The samples they compared were matched very closely in terms of educational and cultural background as well as general cognitive skills, so the orthography seems to be the only plausible explanation for the observed differences. A similar study of Caravolas and Bruck (1993) compared Czech and Canadian English children on phoneme identification tasks, and generally found Czech participants to be superior on pre-school, kindergarden and first-grade phonemic awareness. However, this was observed only when the analysis of consonant clusters (found frequently in Czech) was required. On an (apparently easier) task requiring the segmentation of single consonant onsets, English-speaking children were on a par with their Czech counterparts. This pattern of differences was closely replicated with the spelling task, administered to the school-age groups. Children, therefore, seem to become easily aware of certain phonological structures not just because the structures 115 are simple (as the Cossu et. al. data may suggest) but because they are frequently exposed to them. The existing single language studies of literacy acquisition also show that good levels of phonemic awareness are easily induced, in nearly all learners, in the environment of a consistent orthography (e.g. Greek: Nikolopoulos, 1999; German: Wimmer et. al., 1991; Wimmer 1993b). This is tme not only for children, but also adults with minimal reading skills (Lukatela et. al., 1995). All orthographies, consistent and inconsistent alike, also replicate the same basic pattern: the awareness of phonemes is mastered only together with, not before, the acquisition of literacy, and the two are closely associated. This was demonstrated by Wimmer, Mann & Singson (1999) in a comparative study of kindergarten-age American and German children. Due to different educational policies in both countries, the American participants had already been receiving systematic reading instruction at the time of testing, in contrast to their German counterparts who could neither read nor knew many letter names. Likewise, the English-language learners massively outperformed the German participants on the phoneme identification test. The literacy-related differences were specific to phoneme awareness, as both groups performed similarly on a RAN task. The German-American study of Naslund (1999) also demonstrated that reading proficiency and phoneme awareness go hand in hand. As the word recognition skills were (rather atypically) similar in both language groups, so were the phonemic awareness skills (measured with the deletion and manipulation tasks). Differences in phonemic awareness that are directly attributable to teaching methods were found in the Portuguese study of Alegria, Pignot and Morais (1982). The performance on phonemic tasks was much better in children taught to read with a systematic phonics approach that in those exposed to the global method.

S.2.4.4. Predictors of literacy acquisition in different orthographies.

Despite the differences in developmental rate of reading and phoneme awareness observed between various alphabetic orthographies, the general mechanisms of acquisition seem to be broadly similar across the spectrum of analysed systems. Skills falling within the phonological processing domain (working memory, RAN and phonological awareness) are always found to be important concurrent and longitudinal predictors of word decoding and recognition. The possible cross-orthographic 116 differences in the relative importance of different phonological subskills are difficult to pin down, due to the methodological differences between the studies (such as participants’ age, task difficulty, etc.). Some consistent patterns of differences, however, can be observed. The studies of both dyslexic and normal participants suggest that, in consistent orthographies, phoneme awareness ability explains a relatively small proportion of reading variance, especially after a year or two of tuition (Wimmer, 1993b; Wimmer, Mann & Singson, 1999; Nikolopoulos, 1999). A similar steep decline in the role of phoneme awareness is not observed in English (e.g. Wagner et. al., 1994, 1997). This may be simply an artifact of ceiling effects (thus little variance) observed among older readers of shallow orthographies on most phonological awareness tasks. A cognitive interpretation, however, is also possible: phoneme awareness, once mastered, ceases to be a bottleneck in reading and spelling development. This further development may, however, be constrained by the ability to form and automatize orthography- phonology mappings. RAN tasks, supposed to be the index of this ability, explained a significant percentage of reading variance (independent of phonological awareness) in all orthographies in which they were studied. Moreover, while English studies usually observed the contribution of phonological awareness into reading to be more enduring than that of rapid naming, the reverse was usually found in more consistent orthographies (e.g. Wimmer, 1993b; Nikolopoulous, 1999; de Jong & van der Leil, 1999; for overview see Wolf & Bowers, 1999). The role of rhyme sensitivity or awareness may also vary between orthographies. English findings of a strong link between early rhyming and reading (Goswami & Bryant, 1990) have not been consistently replicated in other orthographies. The amount of variance in early reading explained by rhyming skills (as measured by rhyme oddity or rhyme identity judgement tasks) has usually been small or negligible (Cardoso- Martins, 1995; Gonzalez, 1997; De Gelder & Vroomen, 1991; Wimmer, 1993b; but see de Jong & van der Leil, 1999, for a sizeable contribution). This cross-orthographic discrepancy fits well with the findings on the small role of rhyme-based analogies in reading consistent orthographies (Goswami et. al., 1997, 1998) discussed previously. Whether the role of rhyme sensitivity is a true case of cross-orthographic difference is disputable, however, as recent studies seem to question its central importance for early reading of English, as well (see chapter 2). A German-language study (Wimmer, Landerl & Schneider, 1994) showed that rhyme processing ability becomes important

117 during later, orthographic phases of reading and spelling. This is plausibly the case with consistent and inconsistent orthographies alike (Seymour, 1997, 1998). Rather little is known about the relative role of syllable awareness for learning to read alphabetic orthographies. A comparative study of Cossu et. al. (1988) showed it to be rather secondary in both English and Italian. De Gelder and Vroomen (1991) obtained similar conclusions with Dutch dyslexic participants, who showed syllable skills comparable with their reading-age controls. However, a longitudinal study with Portugese children (Cardoso-Martins, 1995) found both phoneme and syllable (but not rhyme) skills to predict subsequent reading and spelling scores. Finally, higher-level visual processing skills (specifically, reproducing visual patterns from memory) were found to explain a surprisingly high percentage of reading variance in kindergarten and T'-grade Hebrew readers (Meyler & Breznitz, 1998), independent of variance explained by phonological processing. The replication of this finding with other orthographies would be desirable in order to establish whether the involvement of the visual factors stems from logographic reading strategies, or particularly high visual discrimination demands posed by some orthographies (e.g. those which, like Hebrew, are characterised by extensive use of diacritics and particularly high visual similarity between the graphemes). Overall, studies of cognitive resources and mechanisms involved in literacy acquisition show both cognitive invariance as well as language- and orthography- specific differences. In all languages, the conscious access to syllables, onsets and rhymes occurs, to a large extent, spontaneously and prior to the onset of literacy. Learning to read, however, enhances those pre-literate skills greatly, and is a sine qua non of phonemic awareness. Cross-linguistic differences in the level of mastery of various phonological skills are observed. These are attributable, partially, to the characteristics of a spoken language, but mainly to orthographic complexity. Orthographic simplicity and consistency facilitate the acquisition of phonological (and, particularly, phonemic) awareness, both in terms of rate of learning and eventual level of attainment. Phonemic awareness and rapid naming are two linguistic skills repeatedly shown to predict reading in different alphabetic orthographies. The cross-orthographic differences in the predictive power of those skills, as well as the possible role of other phonological abilities, remain less clear.

118 3.3. READING DIFFICULTIES IN DIFFERENT ALPHABETIC ORTHOGRAPHIES.

In the previous section I concluded that linguistic and orthographic factors are important constraints of the acquisition of alphabetic writing, affecting the level of performance and, to a lesser extent, the learning mechanisms. It seems plausible that similar influences will be observed for literacy difficulties: their incidence, symptoms, and the mechanisms of breakdown. I have already pointed to some dyslexia studies (e.g. Wimmer, 1993b) that show this is the case. I shall explore the available evidence more systematically now.

3.3.1. Simple orthographies - do they remove dyslexia?

Simple and consistent orthographies make it easier to break the alphabetic code. They should, therefore, eliminate dyslexia, insofar as it is a code-breaking difficulty. Unambiguous letter-sound mappings should be easier to learn even when phonological awareness is poor. This awareness may itself improve due to orthographic consistency. Consistent spellings may serve as a template for word phonology, somewhat analogously to the role of IP A transcript in learning foreign pronunciations. Systematic phonics teaching typically used with consistent orthographies should facilitate this process even further. Thus, the same level of pre-school phonological processing difficulties (due to poor quality of phonological word representations) may or may not lead to reading failure, depending on the orthography one happens to learn. Testing this hypothesis requires comparison of the incidence of literacy difficulties in different orthographies. Contrasting single-orthography surveys is of little use, as such studies vary widely in terms of sampling, operationalization of the reading problem and assessment measures. The existing studies of this kind suggest, however, that dyslexia may be found in all alphabetically written languages (for a review, see Tansley & Panckhurst, 1981). Conclusive evidence can only be provided by direct, cross-orthographic comparative studies, of which there are few. Yet they have found a reduced incidence of reading difficulties in consistent orthographies: Initial Teaching Alphabet compared to the standard English orthography (Downing, 1969), or Italian compared to English (Lindgren, de Renzi & Richman, 1985). While Lindgren et.al. 119 adopted discrepancy-based criteria of dyslexia using reading comprehension scores, Downing assessed a range of possible symptoms. He found that i.t.a. reduced the incidence of accuracy and comprehension problems, but did not make any impact on reading rate problems. This opens the possibility that consistent orthographies reduce some, but not all types of reading problems, or even merely convert the symptoms from poor accuracy into low speed. I shall consider those options now.

3.3.2. Simple orthographies - is dyslexia manifested differently?

As simple orthographies facilitate the code-breaking aspect of literacy acquisition most directly, they are most likely to eliminate or alleviate the symptoms of phonological dyslexia - that is, decoding and phonological awareness difficulties. Surface dyslexia, on the other hand, may not be eliminated, but its symptoms may alter. A hallmark of surface dyslexia is régularisation errors in reading exception words. Simple orthographies do not provide many opportunities for such errors, but the under­ development of the orthographic lexicon (understood to be the cause of régularisations) should also manifest itself in slow reading, marked word length effect and régularisation errors in spelling (if the orthography is not fully feed-back consistent) (Coltheart, 1978b; Zoccolotti et. al., 1999). Thus, when dyslexia occurs in a simple orthography, its dominant symptoms may be slowness of reading and phonologically plausible spelling errors. To examine these hypotheses, a simple meta-analysis was again attempted. The dyslexia literature was searched for the studies that reported data on both word and nonword reading, and which included participants with a reading age of approximately 7-9 years - similar to that of my Polish participants. This provided a benchmark against which the data on Polish dyslexies reported in this thesis will be compared later. In the case of the English studies, only those adopting reading-level matched design are reported; studies from other languages (which are far fewer) are also presented in the absence of reading-age comparison. The data on reading accuracy are summarised in table 3-2. In figure 3-3, the median results are presented: they are computed exclusively from those studies where reading age control data were available.

120 STUDY STIMULI GROUP AGE % accuracy WORDS NON- WORDS NGLISH lochnover et. al. Words: regular Dysl. 10;4 69 49 * 1983) Non words: derived from the words by changing 1-2 R.A. 8 78 62 letters. 1-3 syllables, 3-11 letters. )i Benedetto et. 3 sets: regular words, irregular words, nonwords Dysl. 10;2 69 70 * 1. (1983) matched on length, 1-2 syllables, 3-7 letters. R.A. 8 77 83 Non words derived from the words by changing onsets. looiigan, Words: regular and irregular, high and low Dysl. 8;6 51 51 * ahnson(1988) frequency, 1 syllable, 4-6 letters. R.A. 7;2 52 61 Nonwords: matched for length, 1 syllable, 3-6 letters. ^eech, Harding 3 sets: regular words, irregular words, nonwords, Dysl. 9;11 58 30 ns 1984) matched for length, 1-2 syllables, 4-7 letters R.A. 7;2 61 38 (words), 4-8 letters (nonwords). fzeszulski, Manis 3 sets: regular words, irregular words, non words Dysl. 10;4 58 33 * |1987) matched for length, 1-2 syllables, 4-8 letters. R.A. 7;2 69 48 |1anis et. al. Words: irregular only, 1-2 syllable, 4-10 letters. D(surf) 12;5 32 73 * 1996) Nonwords: varied in orthographic and phonological D(ph) 49 50 * similarity to real words, 1 syllable, 3-6 letters. R.A. 8;6 41 77 Itanovich et.al. Words: regular -1 syllable, 4-5 letters reg irr 1997) irregular - 1-3 syllables, 4-7 letters D(surf) 8;11 63 23 64 ns Nonwords: 1 syllable, 4-5 letters D(ph) 40 40 33 * R.A. 7;5 51 30 56 ^nderl et.al. Words: 1-3 syllables; 3-10 letters. Dysl. 12;3 63 48 * ,1997) Nonwords: derived from the words by changing or R.A. 8;3 68 65 deleting onsets, 3-12 letters. GERMAN .anderl et.al. All stimuli identical or very similar to those used in Dysl. ii;7 90 86 * 1997) the English study, 1-3 syllables, 3-11 letters R.A. 8;8 95 90 (words), 3-12 letters (nonwords) Vimmer (1993b) Words: various types, also compounds, 1-4 Dysl. 10;5 97-100 92 syllables, up to 15 letters R.A. 8;4 91-100 92 Nonwords: “Japanese” - dissimilar to real words, simple CV structure, 2-3 syllables, 4-7 letters. A^immer (1996a) Words: 1-2 syllables, 3-6 letters. Jap. nw. Nonwords: derived from the words by changing Dysl. 10;4 96 91 * 84 * onsets, 3-8 letters. “Japanese nonwords”: dissimilar R.A. 8;2 97 95 91 to real words, simple CV structure, 2-3 syllables, 4- 7 letters. Wimmer, Mann Words: two lists combined - short (1-2 syllable) D(surf) 9;3 97 94 & Singson (1999) high frequency items; compound words (2-4 D(ph) 9;5 92 73 [Study 1 syllables, up to 15 letters). R.A. Nonwords: two lists combined - short items derived D(surf) 9;3 97 92 [Study 2 from the words by changing onsets; longer D(ph) 9;4 86 67 “Japanese words”. R.A. VI ay ringer & Words: frequent, one page long list Dysl. 9;1 97 81 Wimmer (2000) Nonwords: one page long list R.A.

Table 3-2. Summary of dyslexia studies in English and other languages. The existence of nonword reading deficit is indicated in the last column (* - dyslexies significantly worse on nonword reading accuracy than RA controls, ns - non-significant difference). D(surf) - surface dyslexies D(phon) - phonological dyslexies.

121 STUDY STIMULIGROUP AGE % accuracy WORDSNON­ WORDS fREEK Jikolopulous Words: 1-5 syllables, 3-15 letters. D. 9 89 86 * p 9 9 ) Nonwords: 2-4 syllables, 4-11 letters. R.A. 7;3 96 94 }UTCH 'ap & Van der Words: 3-letter, high frequency CVC. D. 10;2 93 82 * ^ il (1993) Nonwords: the same length and structure. R.A. 7;1 100 93 'an den Bos not described D 11;8 80 46 1998) R.A. - - - PANISH :odrigo & Words: 2-5 syllables, 5-11 letters D 9;7 98 96 imenez (1999) Nonwords: 2-3 syllables, 4-11 letters R.A. - - - •ZECH 4atejcek Three one-minute text reading tasks: easy text. easy diff )998a,b) difficult text and nonword text. Speed and accuracy 0(2"*') 8;6 94 86 72 computed out of all words read within 1 min. D(3^“) 9;6 95 89 79 D(4'") 10;6 98 94 82 R.A. - --

Table 3.2. continued

100 -

Bwords-dyslexia □ words-ra controls ■ nonwords-dyslexia □ nonwords-ra controls

English Other

Figure 3-3. % accuracy of word and nonword reading of dyslexies and reading age control children - comparison between English and other language studies. Each bar represents the median of the means of individual studies reported in table 3-2 (only those where reading-age control data were included).

Overall, non-English children labelled as dyslexic were indeed much more accurate than their English counterparts. The accuracy of English participants as a whole was much worse - some 30-40% on both word and nonword task - so much so that English normal control children were generally less accurate than dyslexies in other languages (the

122 pattern confirmed in a direct English-German comparison: Landerl et. al. 1997). It must be said, however, that those cross-orthographic differences may be partially an artefact of different selection criteria. When more objective criteria were used (dyslexies selected through screening of large samples of pupils, rather than identified by teachers) then inaccurate decoders could be identified among simple orthography readers, as well, although their performance was still somewhat better than typically found in comparable English studies (cf. Wimmer, 1993b and Wimmer, Mayringer & Landerl, 1999). It is also notable that most studies, English and non-English alike, found dyslexies to be significantly deficient on nonword reading in comparison with reading- age matched controls. Thus, decoding difficulty seems to be a universal feature of dyslexia in the alphabetic languages. However, the practical significance of poor decoding is generally smaller for non-English dyslexies, given their overall high accuracy. A closer inspection of table 3-2 also reveals considerable differences between non-English orthographies. In particular, the French study of Genard et. al. (1998) and one of the Dutch studies (Van der Bos, 1998) reported accuracy of nonword reading not higher than in most English studies. This is understandable, as French and Dutch are probably the most complex non-English orthographies reported here. Sparse sub typing research (Genard et. al., 1998; Wimmer, Mayringer & Landerl, 1999) also suggests that phonological dyslexia is not completely eliminated from simpler orthographies, although its incidence or severity may be reduced. Most direct evidence for this comes from the Genard et. al. (1998) study. The French orthography allowed the authors to apply standard English criteria of surface and phonological subtypes (exception word errors vs. nonword decoding errors) but, being more consistent, yielded a higher proportion of surface dyslexies, and a lower proportion of phonological dyslexies, than identified in analogous English studies (eg. Castles & Coltheart, 1993; Manis, Seidenberg, Doi, McBride-Chang & Peterson, 1996). The data regarding dyslexic reading speed are more sparse. Reading-age comparisons have usually found evidence of nonword reading speed deficit (Landerl et. al. 1997, Wimmer, 1993b, 1996a; for negative findings see Beech & Harding, 1984, Nikolopoulos, 1999; for a review of English studies on reading speed in dyslexia see Compton & Carlisle, 1994). The dyslexic deficit of decoding seems, then, to encompass both speed and accuracy. Chronological age comparisons show unequivocally that some consistent orthography readers struggle with reading, even though they are accurate. 123 The analysis of 6 available studies that looked at both accuracy and speed (Wimmer, 1993b; Wimmer, Mayringer & Landerl, 1999; Nikolopulous, 1999; Yap & Van der Leil, 1993; Matejcek; 1998a,b; Mayringer & Wimmer, 2000) and which included 15 different dyslexia - CA comparisons are briefly summarised in table 3-3.

Dyslexies Chronological age controls Median Range Median Range Word reading accuracy 94% 82 - 98% 98% 91 -100% (%) Nonword reading accuracy 83% 67 - 94% 94% 81 - 96% (%) Word reading speed 1.54 0.84 - 4.50 0.80 0.50 - 2.90 (seconds per word) slow down ratio* 1.92 1.40-3.00 - - Nonword reading speed 2.72 1.82 - 3.90 1.705 1.28 - 2.60 (seconds per nword) slow down ratio* 1.69 1 .1 7 -1 .9 4 -- Table 3-3. Reading accuracy and time of dyslexies and chronological age controls - summary of existing non-English studies. * Slow down ratio; The ratio of dyslexic reading time to chronological age control reading time.

Simple orthography dyslexies, who produced few errors, took considerably longer to read the same set of stimuli - in the case of real words nearly twice as long, on average. It is likely that such slow and non-automatic decoding will compromise reading comprehension, despite being accurate.

3.3.3. Simple orthography dyslexias: is the nature of the problem different?

If symptoms of dyslexia change along the continuum of orthographic complexity, is the same the case with their underlying mechanisms? Two main possibilities exist: The shift toward the surface (speed) form of dyslexia observed in the simple orthographies occurs merely at the level of symptoms. Dyslexia is always an impairment of phonological recoding and/or orthographic processing, which is caused by two (typically co-occurring) deficits: poor quality of phonological word representations and the inefficiency of phonological retrieval. However, greater

severity of those deficits may be necessary to induce dyslexia in a simple orthography, as it is generally easier to acquire. - A shift along the phonological-surface (or accuracy-speed) continuum corresponds to the change in the mechanisms of failure. While complex orthography dyslexies

124 may struggle with both phonological recoding and orthographic processing, simple orthography dyslexia usually involves only the latter difficulty, linked to the deficit of phonological retrieval. The most systematic research programme in this area was carried out by Heinz Wimmer and his collaborators. They showed that a typical phenotype of reading difficulties in older (grade 2+) German children (low reading speed but few errors, orthographically inaccurate spelling) was associated more strongly with rapid naming than with phonological awareness deficit (Wimmer, 1993b). When compared with reading age controls, German dyslexies did show deficits in nonword reading and phonemic awareness. However, their absolute level of performance on phonemic tasks was still very high (Landerl et. al., 1997; Landerl & Wimmer, 2000), and decoding problems were evident mainly in relation to speed, not accuracy (Wimmer, 1996a). This looked different at the early stages of learning, though: in grade 1, a majority of later ‘speed dyslexies’ exhibited a much more ‘English-like’ profile, being inaccurate on phonological awareness and nonword decoding. In a later study (Wimmer, Mayringer & Landerl, 1999) the patterns of breakdown were identified separately for surface and phonological subgroups. In the absence of an appreciable number of exception words, surface dyslexia was operationalized as low speed of reading frequent words. The phonological dyslexia was defined in a standard way, by poor accuracy of nonword reading. The phonological subgroup exhibited more severe and pervasive difficulties, including reading speed and accuracy, spelling, phonological awareness, rapid naming and phonological memory. The problems of surface dyslexies were much more selective and involved primarily reading and naming speed, as well as spelling. Thus, phonological dyslexies were characterised by a double deficit, as opposed to single (speed) deficit surface dyslexies. Wimmer et. al. was able to identify only one English-language study that applied similar accuracy-speed subtyping criteria (Lovett, 1987). It produced remarkably similar results, with the low accuracy children performing poorly on all measures of literacy and language, and the low speed children having more circumscribed problems with processing speed and sound-symbol associations. The interpretation of these findings evolved as they accumulated (cf. Wimmer, 1993b, Wimmer, Mayringer & Landerl, 1999; Landerl & Wimmer, 2000). At present, Wimmer and his colleagues claim that the “classic” account of dyslexia as a phonological awareness deficit is insufficient - even for the inconsistent orthographies - 125 as it cannot explain the persistency of dyslexic symptoms. They agree that the lack of phonological awareness indeed results in poor phonological recoding (with its secondary consequences for orthographic learning), yet maintain that the awareness and recoding difficulties diminish with age. This improvement is particularly fast in consistent orthographies, yet it occurs in English, too. Once sufficient recoding is established, normal self-teaching should, in theory, ensue, leading to the build up of the orthographic lexicon and gradual elimination of all dyslexic symptoms. This recovery may not happen, however, if orthographic learning is compromised by a different class of phonological impairments, namely inefficient phonological retrieval and learning (reflected in rapid naming, nonword repetition, and paired-associate learning tasks). These deficits are more detrimental than poor phonological awareness since they are persistent, relatively unaffected by orthography or remediation efforts. Dyslexia studies carried out in other consistent orthographies have usually generated results similar to those obtained by Wimmer et. al. In most cases naming difficulties were a more reliable indicator of dyslexia than problems with phonological awareness (see Wolf & Bowers, 1999, for review). Although deficits of nonword decoding and phonemic awareness were usually observed in reading-age comparisons, the absolute level of mastery of those segmental skills was high. There was usually no deficit in rhyme awareness, while the findings on syllable awareness and working memory were mixed (Nikolopoulous, 1999, De Gelder & Vroomen, 1991; Gonzalez, 1997; Van Bon, Van der Fiji, 1997). Overall, cross-linguistic data suggest that the difficulties with accessing and processing segmental information (phonological awareness and recoding) may be less stable characteristics of dyslexia than initially thought. These difficulties decrease (if not disappear) as reading experience accumulates. This may be particularly the case with consistent orthographies, which reduce the complexity of the recoding task. However, other types of phonological problems - inefficient phonological retrieval in particular - can compromise the processing of all orthographies at all age levels. The co­ occurrence of awareness and retrieval difficulties probably constitutes the highest risk factor for dyslexia in all languages.

126 3.4. READING RESEARCH IN POLISH

Reading and spelling research in Polish has a relatively long history, dating back to the pre-war period. It has been dominated by linguistic and educational perspectives, however, with a relatively small contribution from experimental psychology. Little experimental research focused mostly on dyslexia, rather than normal development of literacy, and it was grounded in the perceptual, rather than the linguistic, paradigm of investigating reading and writing (for a discussion of the merits and limitations of that literature see Szczerbihski, in press). The review presented here will be limited to more recent, language-oriented literature. Regarding normal development, a few studies aimed at verifying the adequacy of the phase models of reading acquisition (particularly Frith’s, 1985) to the Polish language. Maurer (1994) carried out a cross-sectional study covering the first four years of learning to read (from the reception year, so called ‘zero grade’, until grade 3‘). Children were tested on word reading, phonological recoding (nonword reading, pseudohomophone identification^), phonological sensitivity and awareness (at the syllable, rhyme and phoneme levels), working memory capacity, and syntactic awareness (cloze task). Multiple regressions identified the following unique predictors: Grade zero: memory for words (number of words recalled in the working memory test, regardless their sequence); Grade one: syntactic awareness; Grade two: syntactic awareness and nonword reading; Grade three: pseudohomophone identification. Those results were interpreted as supportive of a three-phase model of reading, whereby words are initially processed as wholes, later on analysed phonemically, and finally morphemically. However, the interpretation is very much ambiguous, as the dependent variable in the regression analyses was children’s school marks on reading, not their actual reading scores. Also, Maurer herself, as well as other authors (e.g. Sochacka, 1998, 2001 Krasowicz-Kupis, 1999) observed that the youngest readers displayed the strongest tendency to sound out and blend individual letters and syllables, which does not fit the hypothesis of early global processing.

’ A description of the Polish school system is provided in the following chapter. ^ Such as beek-feek, commick-lommick in English. 127 Frith’s (1985) model was also verified by Sochacka (1998; 2001 see also Schneider & Stengard, 2000) in a longitudinal study focusing on qualitative error analysis. She assessed children’s reading six times between the middle of zero grade (i.e. soon after the formal reading instruction had started) and the end of grade one. A number of different error types were identified, the most frequent being transposition of letters between adjacent words. The majority of errors suggested presence of decoding, but guesses based on visual similarity also occurred frequently. Most children sounded out words, and spontaneous comments that would suggest a direct recognition strategy (“I do not know this one... This one I know... ”) were rare. According to the author, this pattern falsifies the hypothesis of a unitary logographic or alphabetic phase and suggests that Polish early readers use a mixture of phonological and visual strategies at the same time. There was also evidence of a gradual change in the dominant strategy: signs of the alphabetic decoding were most apparent during early assessments (in grade zero), while signs of whole word recognition (lexical substitution errors, better performance on real words) increased with age. However, the correlation between word and nonword reading remained near-perfect (around .90) throughout the whole period covered by the study, implying a unitary (presumably decoding-based) reading strategy. The language-oriented approach to reading and dyslexia research, which has become popular in Poland since the late 80-ies, had an idiosyncratic flavour. In comparison with the English literature it was less dominated by the assumption of modularity and the hypothesis of a specific link between reading and phonological processing. Instead, it assumed multiple connections between literacy and all language domains: phonology, but also semantics, syntax, morphology and discourse (e.g. Borkowska, 1998a). An early example of this “broad language” approach was given by Borkowska and Tarkowski (1990), who compared performance of 2""" grade dyslexic children and their chronological-age controls on a wide range of linguistic tasks (Heidelberg Language Battery). The dyslexies scored significantly worse on nearly all subtests assessing syntax, morphology and communicative competence. Both linguistic processing and communicative competence correlated with reading and spelling performance; the relationships were, however, somewhat weaker for the communicative skills. The authors suggested that semantic deficits were present in some cases of developmental dyslexia. Semantic, syntactic and communicative skills were further explored by 128 Krasowicz (1994, 1998) and Borkowska (1998b) with 2"*^ and 3'^* grade dyslexies. The tasks involved describing pictures and telling stories. In comparison with chronological age controls, narratives produced by dyslexies were shorter, less informative and poorly structured. Their sentences were syntactically simpler, with more frequent hesitations, abrupt endings and occasional syntactic errors. Oszwa (in press) investigated the use of prepositions by 2"^* and 3'^* grade dyslexies. In a series of tasks she tried to elicit prepositional forms in different temporal, spatial, idiomatic and word forming contexts. Robust differences emerged between dyslexies and chronological age controls. Dyslexies’ use of prepositions was limited in variety and frequency, and generally lacked precision. Spatial descriptions were impoverished or erroneous, with occasional left-right confusions. Also, incorrect inflectional forms (especially of nouns) were sometimes matched on prepositions, which violated the syntactic rules of agreement and government. Forming derivations - a task often involving using prepositions as prefixes - was also impaired. These findings, however interesting, are open to alternative interpretations. The authors saw them as the evidence of core dyslexic deficits in the domains of semantics, syntax, morphology and communicative skills. The mechanism by which those deficits impact on literacy were, however, not specified, nor was it ruled out that they could stem from a third, underlying cause. It is likely that semantic and communicative problems were a consequence, rather than a cause of persistent reading failure, or that they resulted from lower-level deficits with word finding or working memory (which were not controlled for). Also, in the absence of well standardized reading tests in Polish no ‘sharp’ psychometric criteria for dyslexia could be applied. It is thus possible that the dyslexic samples contained a high proportion of garden variety poor readers, which exhibited more general language impairment. Dyslexic difficulties with syntax may, however, be stated with more confidence, since dyslexic children made more syntactic errors than controls, even though they produced shorter utterances (Krasowicz, 1997). The most comprehensive investigation so far of reading acquisition, reading difficulties and their relationships with linguistic skills has been carried out by Krasowicz and Bogdanowicz (Krasowicz-Kupis, 1999; see also Krasowicz & Bogdanowicz, in press; Krasowicz, Bryant & Bogdanowicz, in press; Schneider & Stengard, 2000). Children were administered a large battery of linguistic awareness tests at the start of zero grade (before the formal reading instruction began). The tests 129 investigated the awareness of phonology (at syllabic, intrasyllabic and phonemic levels), syntax and morphology. The battery (with some age-appropriate alterations) was again administered twice, at the end of zero grade and T‘ grade, together with reading tests. WISC-R test was also administered in grade 1. Finally, reading was assessed again at the end of 2"^* grade.

Pre-literate linguistic abilities were used to predict reading levels 6, 18 and 30 months later, using hierarchical multiple regressions. The best predictors of rate and accuracy of word and nonword reading were: most of the phonemic tests (analysis and blending, alliteration detection and production) and some of the syllabic ones (syllable deletion), each accounting for some 5-15% of reading speed variance in grade 0 and 1, over and above that explained by IQ, memory (nonword repetition) and the child’s social background. Tests of rhyme processing and morpho-syntactic processing (sentence completion, grammatical acceptability judgement and grammatical correction) were weaker and inconsistent predictors. It was much more difficult to predict reading accuracy than speed, probably because of ceiling effects. Predictability of pre-school measures diminished with age, and practically disappeared in grade 2. However, more difficult tests of phonemic processing, which were first administered only in grade 1 (spoonerisms, explicit identification of minimal pair differences) were strongly predictive of grade 2 word and nonword reading. It was generally difficult to predict reading comprehension - contrary to expectations, morpho-syntactic skills were only minimally contributing there, once IQ has been controlled. Correlational analyses predicting reading in grade 0 and 1 from concurrent levels of linguistic skills brought broadly similar results. Krasowicz (1999) accounted for her data by proposing a phase model of reading acquisition. An initial (phase 1) reading strategy that is predominantly analytical- phonological (i.e. alphabetic) develops into a whole-word and whole-phrase processing (phase 3) through an intermediate, mixed phase 2. The phases are supposed to correspond to formal levels of learning, that is, grades 0, 1 and 2, respectively. The evidence for this transition was sought in the changes in the cognitive predictors of reading and in the quality of reading errors. The relationship between reading and morpho-syntactic skills, although generally weak, seemed to increase with age, together with the proportion of lexical errors (substitutions based on semantic or visual similarities). On the other hand, errors implying failure of segmental analysis (“timing errors”: pauses within a word, repetition of individual phonemes or other sublexical 130 elements) decreased. For the analysis of reading difficulties (Krasowicz & Bogdanowicz, 1999) children were divided into poor, normal and very good readers subgroups using reading rate score at the end of the first grade; the cut-off point for the poor readers group was one standard deviation below the mean. When the three groups were compared on their pre-literate language awareness skills, the largest differences emerged on: alliteration recognition and production, phoneme analysis and blending, and phoneme and last syllable deletion. For those variables both poor and normal, as well as normal and very good group contrasts were usually significant. The less marked, but still significant differences appeared in: the word syllable analysis task, the nonword blending task, rhyme production and the first syllable deletion task. Mainly poor and very good reader contrasts were significant there. Moderate yet significant differences were also found on a cloze task and sentence grammatical acceptability judgements. Syllable blending, syllable analysis (of nonwords), rhyme recognition and open-ended sentence completion did not differentiate the groups. It was, therefore, mainly the phoneme-level awareness that was problematic for children with future reading difficulties; their problems with rhyme, syllable and syntax awareness were less pronounced. When the same comparisons were carried out on language tasks administered later, concurrently with the reading test, many more significant differences were observed. All the tests were able to discriminate the groups, with syllable analysis (of nonwords), phoneme analysis and alliteration production being the most powerful indicators of reading group membership. Although the absolute level of performance grew for all children and for all measures, the distances between the groups remained similar or even grew. Only the discrepancies on alliteration and rhyme oddity and phoneme tasks were reduced over time (in the case of the alliteration oddity and phoneme blending tasks this was probably due to a ceiling effect). The authors also used discriminant analysis which established that first grade poor reading corresponded to the following pre-school language profile:

- very low scores in first phoneme deletion task (around 0) low scores in syllable deletion task (below 33 percentile) low scores in alliteration detection and production, as well as phoneme blending tasks (equal or below 40 percentile) average scores in other phoneme tasks and rhyme oddity task (around 50-60 percentile) 131 By far the most robust predictor of reading failure at the end of grade 1 was reading level itself measured a year earlier (end of grade 0), which correctly identified 92.9% of poor readers. This indicates that very early differences in reading ability are highly stable. Overall, Krasowicz et. al., established that phonemic-level awareness is closely linked with reading acquisition in Polish, whereas rhyming and morpho-syntactic processing play some, but only a secondary, role. This is consistent with the pattern observed in other simple orthographies. Syllable-level awareness (specifically, syllable deletion) also emerged as very important. This may be explained by the phonological properties of Polish: a high proportion of polysyllabic words (at least in comparison with English) and greater salience of syllables due to the syllable-timed nature of the language. Long-term follow-up studies of Polish poor readers (Bogdanowicz, 1985, 1991, 1997; Jaklewicz, 1980, Wszeborowska-Lipihska, 1995, 1996; see also Schneider & Stengard, 2000) showed age-related changes in the manifestations of their difficulties. Symptoms observed during early school years included reading and spelling errors as well as low reading speed, coupled with a stubborn tendency to overtly sound out and blend sublexical units (a behaviour which persisted at least until grade 4). Reading accuracy improved with age, however, so that older dyslexies were characterised, first of all, by orthographically inaccurate spelling, and also slowness of reading. In fact, poor spelling is frequently used as the main criterion for identifying dyslexia in Polish. Gradual disappearance of reading errors (but not other symptoms) is consistent with data from other simple orthographies, though this age related shift in symptoms of dyslexia seems to be relatively slow in Polish (for a more detailed overview of Polish dyslexia studies see Szczerbihski, in press).

132 CHAPTER 4

POLISH LANGUAGE, ORTHOGRAPHY AND LITERACY TEACHING

In this chapter I want to outline the charaeteristics of spoken and written Polish, and the way literacy is taught to Polish children in the first four years of formal education. This is not intended to be a general overview, but a highly selective comparative analysis. I want to highlight the features that are specific to the Polish linguistic and educational environment, and thus may shape the acquisition of reading and spelling in a unique way.

4.1. THE LANGUAGE

Together with Czech and Slovak, Polish belongs to the group of Western Slavic languages. It is more distantly related to the Eastern Slavic (Russian, Ukrainian) and the Southern Slavic (Bulgarian, Serbo-Croatian) groups of languages. With around 39 million speakers in the country, and possibly another 5 million worldwide, it is ranked among the 30 most widely spoken languages of the world (Webster, 1981; Ethnologue, 1996).

4.1.1. Morphology and syntax

4.1.1.1. Inflections

Polish is an inflectionally rich language. Inflectional suffixes are the prime carrier of syntactic information, which in English is conveyed mainly by function words and word order. Nouns, but also pronouns, adjectives and numerals are declined in Polish. A declination suffix carries joint information about case, number and (grammatical) gender of a word. A number of declensional paradigms exist. The assignment of declension to a word is governed by a set of conditional rules; it depends on the lexical category (different declensions for nouns, adjectives, etc.) and the grammatical gender, but the phonological properties of the word stem may also play a role. Some

133 declensional paradigms have variants (which may depend on the semantic properties of the word) and a number of idiosyncratic patterns exists, as well. The declensional system is, thus, very complex, as the examples below illustrate.

Nominative Jeden mal-y chlopiec Jedn-a mal-a dziewczynk-a One-Nom little-Nom boy-Nom One-Nom little-Nom girl-Nom

Genetive Szukamy jedn-ego mal-ego chlopc-a jedn-ej mal-ej dziewczynk-i fVe are looking fo r one-Gen little-Gen boy-Gen one-Gen little-Gen girl-Gen

Dative Przygl^dalem siç jedn-emu I mal-emu chlopc-u jedn-ej mal-ej dziewczync-e I w as lo o k in g a t one-Dat little-Dat boy-Dat one-Dat little-Dat girl-Dat

Accusative Widzç jedn-ego mal-ego chlopc-a jedn-% mal-q dziewczynk-ç le a n se e one-Ace little-Acc boy-Acc one-Acc little-Acc girl-Acc

Instrumental Rozmawialem z jedn-ym mal-ym chlopc-em jedn-% mal-^ dziewczynk-q. /w a s ta lk in g to o n e-In str little-Instr boy-Instr one-lnstr little-Instr girl-Instr

Locative Rozmawialem o jedn-ym mal-ym chlopc-u jedn-ej mal-ej dziewczync-e I w as ta lk in g a b o u t one-Loc little-Loc boy-Loc on e-L oc little-Loc girl-Loc

Vocative Witaj mal-y chlopcz-e! mal-a dziewczynk-o! W elcom e little -V o c boy-Vo cl little-Voc g irl-V o c l

Characteristically, the word stem may undergo some phonological alterations while taking on an inflectional suffix, e.g.

pies ps-a nog-a nodz-e nog

/pjes/ /ps-a/ /noga/ /nodze/ /nuk/ efog-Nom e/og-Gen /eg-N om /eg -D a t /egs-G en

Most of these alterations can be grouped into consistent families, and they reflect historical changes in the phonological system.

Verbs in Polish are conjugated. Several suffixes can be attached to a verb at the same time, specifying number, person, gender, tense and (sometimes) aspect, e.g.

134 prac-uj-ç / H^é?rÆ/am yvorking pracow-al-e-m I worked/was working (Masc.) prac-uj-esz You work/are H>orking praCOW-al-a-m I worked/was working (Fem.J prac-uj-e ffe/she yrorks/is working praCOW-al-C-S You worked/were working (Masc.J prac-uj-emy We work/are working praCOW-al-a-S You worked^were working (Fern.) prac-uj-ecie You work/are working (Ti.J pracOW-al He worked/was working pracuj-4 They work/are working praCOW-al-a She worked/was working

In verbs, as in nouns, we may find phonological alterations within the word stems of inflected words, e.g.

nos-ic nios-l-y nies-l-i wlec wlecz-esz wl6k-l

/noçitç/ /jioswi/ /peçli/ /vlets/ /vletjej/ /vlukw/ to carry they carried they carried to drag you drag/are he dragged (Fern.) (M asc.J d raggin g

The different inflectional forms do not occur independently, but are co-ordinated within the sentence, forming syntactic relations of agreement and government. Agreement occurs between nouns and their modifying adjectives, which have to share the same gender, number and case, e.g.

- gender: ladn-a dziewczyn-a ladn-y chlopiec ladn-e dzieck-o

pretty g iri p r e t t y b o y pretty chi id [both words Fern.] [both Masc.] [both Neutr.]

- number: ladn-a dziewczyn-a ladn-e dziewczyn-y

pretty g iri pretty gir/s [both words Sing.] [both PI.]

- case: ladn-a dziewczyn-a ladn-ej dziewczyn-y land-4 dziewczyn-ç

pretty girl [A smile o f a] pretty girl [To see a] pretty girl [both words Norn.] [both Gen.] [both Ace.] 135 There is also agreement between the subject and its predicate, in person and number, and in some instances also in gender, e.g. chlopiec posz-edl chlopcy posz-l-i dziewczynki posz-l-y b o y w e n t b o y s w e n t g ir ls w e n t [both 3"^ sing, masc.] [both 3"^ pi. masc.] [both 3''' pi. fem.]

Government occurs between the governing word (a verb or an adjective) and its object. The case of the object is fixed by the governing word and remains the same regardless of the form of the governing word, e.g.

n a p r â w iC [object always in Acc.] TZUCiC [object always in Loc.]

Naprawic krzesl-0 Repair a chair. Rzucic krzesl-em Throw a chair

Naprawila krzesl-0 she repaired a chair RzUClla krZCSl-em She threw a chair.

Naprawi krzcsl-o Ne/she wH/repair a chair. RzUCi ICTZCSl-Cm H e /s h e wi/Ithrow a c h a ir.

Polish verb morphology aptly illustrates the difference between positional languages (where syntactic information is carried by a whole clause) and inflectional ones (where it is conveyed mostly by inflectional suffixes). A whole clause in a positional language often translates into a single word form in the inflectional one, e.g.

We would do/have done Zrobilibysmy

I would do/have done Zrobilbym

They w ill do Zrobi^

They did/have done Zrobili

This ‘synthetic’ tendency of Polish syntax is reflected in the quantitative properties of utterances. Recent analysis of a small Polish-English parallel corpus (Szczerbihski & Coleman, 1999) established that fewer words (tokens) are required to express the same proposition in Polish than in English (12-26% difference). However, as Polish words tend to be somewhat longer (1 letter on average) the differences in overall length of propositions (operationalised as a number of letters used to record it) are small and inconsistent (from 3% longer in Polish to 7% longer in English, depending on the text).

136 A speaker and reader of Polish may deal with few word tokens (all other things held constant) but given the richly inflectional nature of the language, she must process a far greater number of unique wordforms, e.g.

The headword Possib/e word forms form f/emmaj ENG cat cat cats cat’s cats PL kot kot kota kotu koty kota kotem kotom kotow kotami kotach kocie

ENG beautiful beautiful PL piçkny piçkny piçkna piçknq piçkni piçkne piçknego piçknej piçknemu piçknego piçknym piçknych piçknymi

As pointed out in chapter 3, these characteristics are likely to affect early reading strategies. As each individual word (lemma) occurs in a large variety of forms (many of which appear as long strings of letters), the reliance on global, visually based recognition strategy seems even less viable in Polish than in English. Conversely, the role of morphological and syntactic skills in supporting elementary decoding may be greater in Polish. It is so since the ability to rely on morpho-syntactic context seems likely to be more important for decoding inflectional suffixes than word stems.

4.1.1.2. Derivadona/morpho/os^.

As in English, new words in Polish may be derived within and across lexical categories by adding prefixes and suffixes; the process that is sometimes accompanied by phonological alterations within the word stem. Some specific types of derivation are characteristic of Polish and other Slavic languages. A very productive set of rules, for example, derives new verbs by adding prefixes (e.g. {od-}, {do-}, {pod-}, {nad-}, {prze-}, {za}, {w-}). This sometimes marks a difference in aspect, e.g.

Imperf. pisalem list czytalem ksiqzkç I was writing a ietier I was reading a book

Perf. na-pisalem list prze-czytalem ksiqzkç / wro/e/bave written a letter /read/have read a book

137 Most often, however, the structure: prefix+verb functions similarly to English phrasal verbs, allowing for the expression of a variety of meanings clustered around the same root, e.g.

p iS â C w r ite rZUCiC th r o w

Z a - p is a C w r ite d o w n o d -rZ U C ic throw away; reject; turn down prze-pisac copy W y -rZ U C ic throw away/out

o d - p i s a C copy down; crib Z a-rZ U C ic abandon; accuse

The functional similarity between Polish prefixed verbs and English phrasal verbs is most apparent in those (frequent) cases when a prefix can be identified with a preposition, e.g.

od od-rzucic od-pisac fr o m th r o w a w a y c o p y d o w n

Forming diminutives and augmentatives is another very characteristic and productive derivational process. Two (or even more) distinct diminutive forms (different in ‘degree of smallness’) may be produced with many nouns. Using a diminutive may convey merely the difference in size, but also emotional attitude, and sometimes different meaning, e.g.

a b ig booh, a to m e k s iq z k a a booh ksiqzOCZka a/little/booh

Stol a ta b le Stolok a s to o l StoloCZCk a/sm all/stool

Derivational or inflectional relatedness between words is often “masked” by their surface phonological realisation, yet remains apparent in spelling, which operates on the morphological principle. I shall return to this issue in section 4.2.2.

4.1.2. Phonology

4.1.2.1. Segments.

138 Polish phonology is characterised by the contrast between a relatively simple system of vowels and a complex system of consonants. Different accounts of the Polish vowel phonology have been proposed (e.g.

Stmtyhski, 1997), yet none of them distinguishes more than 8 vowel segments. Six of them are oral vowels, which can be described with the following set of phonemic features (Puppel, Nawrocka-Fisiak & Krassowska, 1977; Bartnicka & Satkiewicz 1990):

/i/ front, close, spread e.g. /pitç/ pic /i/ front, half-close, spread /riba/ ryba Is/ front, half-open, spread /ten/ ten /a/ central, open, neutral /mama/ mama h i back, open, rounded lokol oko /u/ back, close, rounded /bul/ bol /mur/ mur

The two nasal vowel in Polish, /5/ and /ê/, correspond to the oral /o/ and /e/, respectively:

/o/ /vos/ w^s /ê/ /gês/ gÇS

/kostitutsja/ konstytucja /bëzina/ benzyna

Nasal vowels have a very weak status in the phonological system of contemporary Polish; from a historical perspective they are gradually disappearing. The original distribution of nasal vowels, now fossilised in spelling (graphemes and <ç>) became confined to two positions: before fricatives and in word-final position. In other contexts, the nasal element of the vowel became assimilated with the following consonant. Before plosives and affricates, it splits into an oral vowel and a nasal consonant having the same place of articulation as the following obstruent, e.g.

/om/ before bilabial plosives/p//b/ /kompatç/ k^pac /em/ /dembi/ dçby

/on/ before dental plosives /t/ /d/, alveolar and palato- /kont/ k^t

Zen/ alveolar affricates/ts/,/dz/,/tJ/,/d 3/ /(gndi/ tçdy

139 Before résonants /I/ and /w/ (past tense suffixes {- 4I} {-çla} {-çli}) the nasal element disappears altogether, e.g.

/o/ /v^ow/ wzi^l /e/ /v^ewa/ wziçta /v^eli/ wziçli

Even in those contexts where nasal vowels still occur, their realisation varies considerably across accents and dialects (Wierzchowska, 1980, Roclawski, 1981, 1976; Rothstein, 1993; Karas & Madejowa, 1977), e.g. idç [idê] [idew] [idew] chodz^ [xodzD] [xodzow] [xodzow] [xodzom]

A phenomenon of spelling pronunciation is also apparent here. Nasal vowel pronunciation is more likely to occur in native or well-assimilated words, which are spelled with or <ç>. More recent loan words, however, which retained their original spelling , or may be pronounced accordingly: w^s [vos] rzçsy [^êsi] konstytucja [kostitutsja] or [konstitutsja] pensja [pêsja] or [pensja]

Historical changes in nasal vowel phonology and the current variety of their realisation are largely responsible for making the spelling of nasal vowels the least consistent area of Polish orthography. In contrast to English, Polish does not differentiate vowel quantity (length). Being a syllable-timed language it does not reduce vowels: their phonemic status remains the same regardless of stress'. Likewise, no neutral vowel element (analogous to English ‘shwa’ /o/) sound appears. This is one of the major factors contributing to the much greater consistency of vowel grapheme-phoneme correspondences in Polish than in English.

' This is true for the standard pronunciation; in some local dialects there are phonological differences of vowel quantity, and the phonemic status of vowels may be affected by stress (B. Kaczmarek, personal information, May 1997). 140 The consonant system of Polish is presented in table 4-1. Polish and English consonantal phonologies are much more similar than their vowel counterparts. The main difference involves the category of palatality. Polish (along with other Slavic languages) makes a phonemic distinction between ‘soft’ (palatal) and ‘hard’ (non-palatal) consonants. This results in a series of palatal phonemes: /ç, tç, d^, ji, c, j/, e.g.

Nos /nos/ dzwon /dzvon/ cala /tsawa/

n o se a â e // w h ole nos /noç/ dzwon /dzvoji/ ciala /tçawa/

carry (i/J /im peraiive/ ring (a dei/J /im peraiive/ h o d ies

There are few other differences. English dental fricatives /0/ and / 6/ do not occur in Polish. The reverse is true about alveolar fricatives /ts/ and /dz/, which in English

occur only in few borrowings (e.g. /ts/ in pizza). A velar nasal /g/ has phonemic status in some regional dialects of Polish; in others, it is a conditioned variant of /n/ (Stmtyhski, 1997). Other consonants may be considered partially equivalent (they take the same place in the phonological system, but are realised differently in terms of place or manner) or fully equivalent in the two languages (Kopczyhski, 1977).

Bilabial Labio­ Dental Alveolar Palato- Alveolo- Velar Glottal O dental alveolar palatal B & S palatal T Plosives p b* t t* C k k* R p b* U d d* J g 9* E Fricatives f f* 0* s s* J 5* Ç X h* N V V* Ô* z z* 3 3* T Affricates ts S tj t r tç dz d3 d3* d^ R Nasals m m* n n* g* E S o Laterals 1 1* N A Trills r N T S Semi­ r* j j* w w* vowels

Table 4-1. Polish consonantal phonology. English consonants are also mapped on the same chart and marked with asterisks. If Polish and English phonemes are placed in the same box, they may be considered hilly equivalent in the two languages. Adapted with alterations from Kopczyhski, 1977, p. 24.

141 There are 3.5 times more consonant than vowel segments in Polish. This ratio suggests a strong consonantal quality of Polish - the analogous figure for standard British English is only 1.2 This seems to support the auditory impression, often reported by foreign listeners, that Polish is spoken with ‘no vowels’. However, when we compare the frequency of usage, rather than the number of segments, we find nearly identical figures for English (39% of vowels), Polish (40%) and French (41%). Those three languages may be contrasted with more consonantal German on one hand (vowel frequency only 36%), and with Italian and Finnish on the other (48% and 51% frequency of vowels, respectively) (Fry, 1947 in Crystal, 1991 p. 166; Roclawski, 1976, p.87; Kyostio, 1980). What gives Polish its specific acoustic consonantal quality is, then, probably not the high relative frequency of consonants, but their arrangement in clusters (see the following section) The distinct „hissing” or „rustling” acoustic impression of the language comes from a big family of “hissing consonants” - alveolar and palatal fricatives and affricates. They are not only numerous (12 phonemes), but also used frequently, accounting for approximately 15% of all phonemes (Roclawski, 1976, p. 87) compared to only 9% frequency of analogous sounds in southern British pronunciation (Fry, 1947 in Crystal, 1991,p.l66).

4.1.2.2. Suprase^mentûlphono/o^v

Svllable structure Polish allows for a very wide variety of syllable structures, although open syllables seem to be most typical (Bethin, 1992). A number of different consonant clusters (up to four phonemes long) is permissible in onset and coda positions, although, as syllables tend to be open, the onset clusters predominate, e.g. pstra /pstra/ panstw /pajistf/ obstrzal /opjtjaw/ chrzqszcz /xjoxjtj/

High frequency and complexity of consonantal clusters is a very characteristic feature of Polish phonology, shared with its closest relative - Czech - where it is perhaps even more pronounced.

^ Following Logman Dictionary of Contemporary English (1995), which specifies 20 vowels (including 8 diphtongs) and 24 consonants. 142 Certain types of clusters are subject to assimilations and reductions; orthographically this results in silent letters corresponding to “potential” phonemes that occur only in slow, careful speech (see section 4.2.2.1)

Stress Polish is characterised by stable paroxytonic (penultimate syllable) word stress:

'mrowka sta ro'zyt.ny lo ko m o'ty wa

There are few exceptions to this general rule and they are regular (predictable). Consequently, stress in Polish never serves a lexical function, as it does in English (eg. ' object vs. object) or in Russian.

Word length and rhvmes Compared to English, Polish lexis seems to contain a smaller proportion of monosyllables (although I am aware of no study that has tried to quantify this difference)^ This results largely from the ubiquitous presence of inflectional and derivational prefixes, which are usually syllables on their own, e.g.

kot - ko ty ko-pac - wy-ko-pac pi sac - na pi sa la cat cats (Nom.) dig digout write she has written

As a result of the small number of monosyllables and paroxytonic stress pattern, masculine rhymes are relatively less frequent than feminine rhymes (in contrast to English, where the reverse is the case)f A cursory screening of a large Polish dictionary enabled me to identify 52 families of rhyming monosyllables that have ten or more exemplars each (the largest having 42). This is an underestimate (the analysis involved only lemmas, not word forms, and ignored smaller families or pairs of rhyming monosyllables) but, in any case, the feminine rhyming families are more numerous and larger, sometimes having even thousands of exemplars. The reasons for this abundance are partially grammatical: polysyllables may rhyme when they share the same suffix (or suffixes), or sometimes a suffix and the final part of the stem. Thus, phonological identity (rhyming) partially overlaps with morpho-syntactic identity, e.g.

^ Our own study (Szczerbinski & Coleman, 1999) established that Polish words are longer on average (in terms of letters), but did not explore the syllabic structure.

143 Nouns Nouns Verbs Nom. Sing, (diminutives) Nom. PI. Past, 3'^'’ person Sing. Fem.

/ - u f k a / /oti/ /-awa/

glow-ka (sma/lj head kot-v pojech-ala sh e w en t pocztow-ka piot-v zbudow-ala makow-ka mlot-v napis-ata zasuw-ka robot-v odd-ala

/ - u j e k / / - a t k i / /- e w a /

kwiat-uszek (small)/lower matk-i m others stan-gla sh e sto o d up pal-uszek statk-i "" zdi-çla koz-uszek kwiatk-i stukn-çla lahc-uszek obiadk-i klepn-ela

rhe differences in the relative frequency of the two types of rhymes are reflected in poetic instrumentation. Verse created for children or by children (nursery rhymes, counting-rhymes, verbal mockery, etc.) is abundant in rhymes, most of which, however, are of the feminine type (Cieslikowski, 1991; 1974)^

Assimilations and reductions As many other languages, Polish is subject to assimilation processes, which harmonise the articulatory features of consonants within a cluster. Voice assimilations are most common: they affect mostly obstruents, which have to agree on the feature of voice (all obstruents in a cluster must be either voiced or voiceless). Another related process leads to the devoicing of all final obstruents and clusters. Assimilations of place and manner

‘’For the definition of masculine and feminine rhymes see section 3.1.2. ^ Comparing the opening lines of Dr. Seuss’s “Horton Hatches the Egg” with their Polish translation illustrates this nicely. Whereas all rhymes of the original are masculine (_), all but one in the translation are feminine (_).

Sighed Mayzie, a lazy bird hatching an egg Westchn^l ptak Grzebielucha “I’m tired and I’m bored Zwany tez Podouszczaika: And I’ve kinks in my leg Wysiadywac wci^z jajko - taki los nie jest baika! From sitting, just sitting here day after day. Drugi tydzieh juz siedzç - co za nuda, na Boga! It’s How I hate it! Czujç bezsens istnienia, I zdrçtwiala mi noga. I’d m u cA rather play! Z Jakiej racji wlasciwie mam zamçczac siç PRACA?! I’d take a vacation, fly off for a rest Czy mi chociaz za pracç przyzwoicie zanlaca? If I could find s o m e o n e stay on my nest! Bardzo wqtpiç, bo wszyscy przerazliwie s^ skani If I could find someone. I’d fly away free...” Moze raczej - wzi^c urlop? Ale kto mnie zastani? Then Horton, the Elephant, passed by her tree. Kto na jajku usi^dzie, kto pomocn^ da dlon?... Tu przerwala, albowiem pod jej drzewem stal slon.

144 can also be observed. The majority of assimilations are historical (i.e. they have already become obligatory for all speakers) yet some are live (i.e. observed only in some regional dialects). In certain phonological contexts, assimilations may eventually lead to cluster reduction (consonant deletion) or articulatory splitting (when two segments are produced in place of one). Most reductions and splittings are live, depending crucially on the speech tempo, among other factors. The most typical reductions observed in Polish are very different from those observed in English. Whereas English stress-timed phonology allows for the reduction of unstressed vowels and, subsequently, syllable deletion (e.g. /laibrori/ /laibri/), consonant deletion and cluster reduction are characteristic of syllable-timed Polish phonology. The phenomena mentioned here are of central importance for reading and spelling. It is in the context of assimilations and reductions where the morphological principle of Polish orthography becomes most apparent, resulting in marked (albeit predictable) spelling-sound divergences (see section 4.2.2.).

4.2. ORTHOGRAPHY

Poland emerged on the scene of written history relatively late, after the adoption of the Western (Roman) Christianity in the 10'*' century. It was, however, not until the late medieval times that the first sizeable texts were written in Polish. The Renaissance saw rapid development of native literature, flourishing printing industry, and several attempts to systematise the spelling. Late 16'*' century orthography already broadly resembled the present one. In the 19'*' and the early 20'*' century several corrections of the system were proposed (by lexicographers and various academic bodies) and some of them were successfully implemented. The most important changes involved vowel spelling. The reformers took into account a considerable simplification of the vowel phonology that had occurred over previous centuries and abolished the practice of marking old (now neutralised) vowel contrasts with diacritics. The relatively short history of Polish orthography and the successful attempts at its reform may be responsible for its relative transparency in comparison with the ‘old’ orthographies, such as English and French. In the family of Slavic languages, however, Polish is relatively non-transparent and ‘historically loaded’. This is so since other Slavic nations (like Czech or Serbo-Croatian) largely re-created their literary culture (after a period of dormancy) in the 19'*' century; which was accompanied by a re­

145 creation, or a radical reform, of the orthography. No such discontinuity occurred in Polish.

4.2.1. The alphabet

The Roman script was adopted to the phonological structure of Polish both by using diacritics and combining letters into digraphs. The contemporary Polish alphabet incorporates 23 letters of the Roman script (all except q, v and x) and supplements them

with 9 unique diacritised graphemes: . Two Roman letters have different sound values assigned to them compared to most of the other Latin-derived

orthographies: represents /v/ (/w/ is represented by < 1>), and stands for an alveolar affricate /ts/ (/k/ is represented by ). There are less than 20 possible digraphs and trigraphs; 7 of them, representing fricatives and affricates are usually treated as distinct Tetters’ and taught as such to the first grade children. All letter names contain the letter sound (unlike English or ); in the case of vowels, letter names and sounds are identical.

4.2.2. Transparency, regularity, consistency

4.2.2.1. Reading

Polish orthography may be characterised as moderately transparent. There are very few correspondences that would meet the stringent criteria of bi-uniquess (assuming standard pronunciation, is equivalent to /a/, = /i/, <1> = /I/). However, many correspondences are perfectly, or near perfectly transparent in feed-forward (grapheme- to-phoneme) direction. Many graphemes may represent just one sound value, or take up another one only in highly specific, constrained contexts. That is the case with most

graphemes denoting oral vowels , voiceless obstruents and resonants . Other graphemes can stand for two sound values: , for example, each represent voiced or voiceless obstruent, depending on the context. Rarely more than two phonemic realisations of a grapheme are possible (the graphemes being the most notable exception). A large percentage of Polish words is, then, transparent in a weaker sense (see chapter 3, section 3.2.1.): their pronunciation can be directly assembled from individual letter sounds (or digraph sounds).

146 Wherever feedforward correspondences are not transparent, they are still fully regular and consistent. Although the sound value of individual graphemes may be context dependent, every letter string (word or nonword) always has only one possible pronunciation. There are neither reading exceptions (e.g. have, pint, yacht) nor homographs (e.g. lead: /li:d/ vs /lead/)\ Alternative sound values of individual graphemes usually reflect the morphological principle, which keeps the spelling of lexical roots, inflectional and derivational affixes constant, regardless of the changes in their surface phonological realisation. Sometimes the different possible pronunciations of individual graphemes may also reflect the historical principle: tendency to retain the original spelling of loan words, regardless of the phonological alteration they undergo when adapted to Polish phonology. However, these alternatives are disambiguated by the context. The rules that govern this disambiguation may be described as orthographic (the sound value of individual graphemes changes depending on the preceding and the following graphemes). However, these rules are ultimately morpho-phonological: they reflect default phonological processes of assimilation and cluster reduction occurring in the spoken language, e.g.:

/s/ and /z/ ^ /s/ > /z/ or /s/ LASY LAS GAZY o GAZ /Iasi/ /las/ /gazi/ /gas/ obstruent (final) forests forest gases gas devoicing

/J/ and ly /J / < Z > - I y or /J/ SZYSZEK SZYSZKA LYZEK ^ LYZKA obstruent (regressive) /Mek /JiJka/ /wi^ek/ /w ijka/ devoicing cones (Gen.) cone spoons (Gen.) spoon

/w/ /w /o r/#/ PLOTLA o PLÔTL sonorant deletion /pbtw a/ /plut/ she blabbered he blabbered

A few examples of such processes are listed below. They have been chosen as they are most characteristic of the language or most productive (thus explaining the most frequently occurring grapheme-phoneme correspondences).

^ Barring a handful of exceptions, which are mostly the cases of non-assimilated foreign loans. 147 Final devoicing: voiced obstruents are devoiced in word-final positions, e.g.

/d/ /t/ SAD /sat/ /dz/ /ts/ WÔDZ /vuts/

Regressive devoicing: voiced obstruents are devoiced when followed by a voiceless obstruent e.g.

/d/ /t/ BRÔDKA /brutka/ /z/ /s/ LEZKA /weska/

Regressive voicing: voiceless obstruents become voiced when followed by a voiced obstruent (except for /v/ and /g/), e.g.

/ç/ ^ /?/ PROÉBA /prozba/ /tj/ /d^/ LICZBA /lid]ba/

Progressive devoicing: /v/ and /^/ become de voiced when preceded by a voiceless obstruent, e.g.

/v/ /f/ TWÔJ /tfuj/ /3/ /J/ PRZED /pjet/

Regressive palatalisation: non-palatal consonants become fully or partially palatalised when followed by a palatal consonant, e.g.

/z/ /z/ ROZDZIELlé /rozdzelitç/ /J/ -> /ç/ WRESZCIE /vreçtçe/

Nasalisation and denasalisation: addition, deletion or transposition of the nasal elements in the vowels h! /e/, /5/ /e/, depending on the following consonant, e.g.

Zen/ -* ZêZ PENSJA /pêsja/ /on/ /3/ KONFITURA /kofitura/

148 m /en/ P^TO /pento/ loi /on/ K^T /kont/ <ç> <4>

Combined assimilations of place and manner of articulation (and sometimes also voice), often leading to a simplication of consonant clusters, e.g.

STRZELAé /s.t.J/ /J.tJ/ /s.t.J.e.l.a.tç/ /j.trf.E.l.a.tp/ /J.tJ.E.l.a.tç/

PRZEDSZKOLE /t j .k / /tj.k/ /p.j'.E.t.j'.k.o.I.E/ -* /p.J'.e.tJ'.J'.k.a.l.e/ /pJ.E.tJ.k.a.I.E/

SZE^léSET /ç.tç.s/ -» /j.s/ /J.E.ç.tç.s.E.t/ -» /J.E.ç.s.e.t/ -» /j.E.j.s.e.t/

n.b. Dots separate individual phonemes

Partial devoicing of sonorants (occurring in certain combinations with voiceless plosives and other sonorants) may result in sonorant deletion, e.g.

RZEMIEÉLNIK /çlji/ /çji/ /^emjeçljiik/ /^emjeçjiik/ ORGANIZM /-sm/ /s/ /orgajiism/ /organis/

It is important to remember that the assimilation and reduction rules just listed play essentially a phonetic role, and the phonemic identity of any letter string is already uniquely specified by the individual sound values of its constituent graphemes. Thus, ignoring the rules of assimilation and reduction and simply blending sounds of individual graphemes together can result in “artificial” (hypercorrect) pronunciation, but not in misidentification of the lexical target, e.g.

D^B /d/ + /5/ + /b/ = /dob/ -> /domp/

hypercorrect assimilation, product of devoicing blending

149 4.2 .2.2. S p e //in ^

In contrast to the almost-perfect feed-forward (grapheme-to-phoneme) consistency, Polish is characterised by a rather low feed-backward (phoneme-to-grapheme) consistency. For every written word, only one pronunciation is conceivable, but for many spoken words, several spellings are conceivable, e.g.

row /tromba/ /jezik / trunk tromba* tongue jenzyk* /ruf/ ditch ruw bomba benzyna /bomba/ /bezina/ ruf Aomh p e tro l bçzyna Asterisks denote an incorrect spelling

Even if the spelling is inconsistent, it is usually still regular (i.e. predictable). There are a number of ways in which the correct spelling option may be determined among the competing alternatives. Most often it is based on a morphological principle. A number of examples have already been provided in the preceding sections. This type of spelling rule can be formulated in terms of morp/io-p/iono/ogica/ alternations, whereby the correct spelling of any particular sound is contingent on whether (and how) that sound changes in different forms of the target word, e.g.

PHO­ RULES EXAMPLES NEMES spell as , if it remains /u/ in all cud cuda cudowny (inflectionally and derivationally) related forms /tsut/ /tsuda/ /tsudovni/ / u / of the target word mirac/e miracles miracuious spell as <6>, if it changes to /o/, /e/ or /a/ in any przod [do] przodu [na] przedzie (inflectionally and derivationally) related forms /pjut/ /pjodu/ /pjed:?e/ of the target word fro n t forw ard at thefront spell as , if it remains /f/ in all (inflectionally traf trafu trafic and derivationally) related forms of the target /traf/ /trafu/ /trafitç/ / f / word iuck luck (Gen.) to h it (the target) spell as , if it changes to /v/ in any staw stawu stawy (inflectionally and derivationally) related forms /staf/ /stavu/ /stavi/ of the target word pond pond (Gen.) ponds

Even if a word has several phonologically plausible spelling alternatives (e.g. /ruf/: ), the correct version is usually specified uniquely by morpho-phonological alterations (/ruf/ [ditch] - /rovi/ [ditches]). 150 Another category of spelling rules concerns palatal consonants, and is based on the pkonotactic, rather than morpho-phonological principles. Palatal consonants /ç/, /^/ /tç/, /d^/, /ji/ are marked with diacritics (, , , , , respectively) if they occur before another consonant, or word-finally. If, however, they are followed by a vowel, palatality is marked with , e.g.

konca koh koniec konia koni /kojitsa/ /koji/ /kojiEts/ /kojia/ /kojii/

Baska los Basia Basi losie /baçka/ /WDÇ/ /baça/ /baçi/ /woçe/

Similar considerations apply to the spelling of the semivowel /j/. It is spelled as /j/ if it follows a vowel, or marks the beginning of a morpheme. However, if it follows a consonant which is a part of the same morpheme, it is spelled as , e.g. jajko odjechac obiad diabel /jajko/ /odjexatç/ /objat/ /djabew/

A very complex set of morpho-syntactic rules determines whether certain particles are spelled jointly with or separately from other words, e.g.

me me moze memoznosc niedaleko Nie daleko, lecz blisko /n o / he cannot Impossibility nearby N otfa r, bu t close by ia bvm bvlbvm moze bvsmv moglibvsmv /conditional /would / wouldhave maybe we could we could p a rtic le/

The spelling of most phonemes is fully regular. In minority of cases, however, the rules are violated by exceptions, or no spelling rule (which is grammatically based) can be provided at all. Unpredictable (exceptional or irregular) spellings are always historically motivated: they may ‘fossilize’ the old pronunciation of the native word, or reflect a word’s foreign origin, e.g.

151 ZoZ, ZomZ, ZonZ Spelled in native words Spelled in loan words (retaining their original spelling) wqsy trqba kqt konserwa bomba front ZvôsiZ ZtrombaZ ZkontZ ZkoservaZ ZbombaZ ZfrontZ ZkonservaZ

ZiZ as genitive case suffix of certain feminine nouns spelled <-i> in native words and well Spelled <-ii> in more recent foreign loans assimilated loans skrobi kani Arabii unii ZskrobiZ ZkaniZ ZarabiZ ZuniZ

Independently of the rules listed above (which are underpinned by phonology, morphology and syntax) the choice between competing letter patterns is sometimes facilitated by grapho-tactic and grapho-statistic constraints. Some grapheme combinations are rare or illegal within the system, although they would be phonologically plausible, e.g.

-szka approx 100 exemplars /-Jka/ -zka approx 50 exemplars -rzka no exemplars

The most productive constraint of this type (taught prescriptively to children) involves the spelling of the fricatives /J/ and Z^/ when the follow the consonants ZpZ, ZbZ, ZtZ, ZdZ, ZkZ, ZgZ, ZxZ, ZjZ, ZvZ. If such a sound sequence occurs within morpheme boundaries, then it is nearly always realised as + , e.g.

default /tj/ illegal < t z > illegal

default /93/ < g Z > rare

default mi rare illegal

152 4.3. TEACHING LITERACY

Polish children are required by law to begin their primary education in September of the year of their birthday. However, a vast majority of children (95 - 99%)’ are enrolled at non-compulsory reception classes (named ‘zero grade’) a year earlier, where reading and numeracy are also taught. Thus, Polish children typically start learning to read in the second half of their sixth year of life. This is much later than in most English- speaking countries (where teaching of reading starts at the age of 4 or 5) yet similar to most countries of continental Europe (where it starts at the age of 6 or 7). The first three grades of compulsory primary school (when children are 7-10 years old on average) are called the period of ‘initial education’. Learning is then focused on basic skills of literacy and numeracy. These are taught by one teacher, who looks after the class throughout the whole three-year period. Later on, learning diverges into specialised subject areas taught by several teachers; at this point reading and spelling gradually shift from being the main focus of learning into becoming a tool for acquiring knowledge. Systematic, explicit phonics is typically used to teach reading and writing. Its backbone (in pre-school grade zero and grade one alike) is the gradual introduction of the extended alphabet (i.e. all individual letters and most digraphs), one grapheme at a time, starting with most transparent and most frequent ones. This does not, hoverer, imply exclusive focus on letter names or even sounds. A typical reading lesson may involve introducing the target letter, detailed discussion of its graphic structure, finding sounds in spoken words corresponding to the letter sound, reading isolated syllables and, finally, reading whole words containing the target letter combined with other previously introduced letters. Teaching makes extensive use of the alliterative principle, that is, linking new letters with the alliterations of highly familiar words ( as /d/ in /dom/ [house]; as /k/ in /kot/ [cat], etc.). All these activities are supported by a chosen reading primer and a set of complementary materials. Different primers suggest somewhat different variants of phonics, yet most combine the synthetic phonics (converting letters into sounds and then blending them) with the analytic one (‘unpacking’ letter-sound relations in previously learned words). Characteristically, several primers want to prevent children from pronouncing letter sounds in isolation and encourage syllable-level analysis and blending. Elements of global approach

’ According to Maty Rocznik Statystyczny [Small Statistical Yearbook], 1998, p. 196

153 (memorising non-analysed words) may also be used (to a limited extent) in the very beginning. The zero grade curriculum requires the introduction of 22 basic Roman letters (without J, digraphs and letters with diacritics), and all the reading materials are composed of these letters only. The curriculum aims at making children independent in word decoding skills (within the basic 22 letter set) by the end of grade 0. In practice, however, the skills achieved vary widely from mere letter name knowledge to fairly fluent reading. Importantly, teaching of writing in grade zero is minimal: typically, it does not go beyond a drill in handwriting of isolated capital letters. The first grade curriculum again introduces all the letters from the beginning using a different primer*. However, the instruction is faster, more extensive and better integrated: all letters and most digraphs are eventually introduced, and reading, writing and spelling are all taught together. Cursive script is used (and explicitly taught) from the start. Spontaneous, emergent spelling is usually not encouraged, and the importance of spelling accuracy is stressed from the outset^ Explicit teaching of spelling rules also plays an important part; some morphologically-based alteration rules (e.g. those that disambiguate the spelling of homophonie graphemes u-6, r-rz) are already introduced in the first grade. Teaching and consolidation of spelling rules (accompanied by appropriate drill exercises) is an important part of the curriculum until the 5"" grade, if not longer. The curriculum generally expects children to become independent readers by the end of r* grade. Second grade reading activities should focus on fluency and comprehension, rather than basic decoding skills. However, a number of children still struggle with decoding beyond grade one. The minimum requirement is, certainly, to read independently by the end of the third grade, since from then on a child must use her reading skills extensively as a tool for extracting information in a number of specialised subject areas. Phonological awareness training features prominently, both as part of the kindergarten ‘reading readiness’ curriculum (where it occurs without any reference to

* This (arguably peculiar) repetition reflects the history of pre-school education: zero-grade instruction was introduced relatively recently (in 1979) and never fully integrated with the following compulsory education. Also, as zero grade instruction is not compulsory, the first grade curriculum is set to provide for all children, also those who did not receive any instruction before.

^ A strict approach to spelling accuracy is maintained throughout the entire period of schooling. Poor spelling can seriously compromise chances in all formal assessments involving Polish language and literature, up to and including matura (A-level) exam. There is some trend towards relaxation of this approach recently. 154 letters) and later on in grades 0 and 1 (where it is integrated with letter knowledge and reading). Phoneme and syllable analysis and blending as well as alliteration recognition are employed most often. However, the very term ‘phonological awareness’ rarely occurs; concepts such as ‘phonematic hearing’ or ‘auditory analysis and synthesis’ are used instead, betraying the underlying assumption of phonological processes being a subset of general auditory-perceptual processing. Formal teaching of grammar is also an important part of the primary school curriculum. During the period of initial education children typically learn to identify the basic parts of speech (noun, verb, adjective, adverb, numeral), and some inflectional forms (number and gender of nouns; number, person and tense of verbs; number, gender and degree of adjectives), as well as to differentiate between indicative, interrogative, imperative and exclamatory sentences. Since most spelling rules are grammatically motivated, the teaching of grammar and orthography partially overlap. The general features of the Polish reading and writing instruction may be, then, summed up as follows: - use of systematic and explicit synthetic-analytic phonics - largely normative approach - using the same materials for the whole class, predominance of whole class activities and focus on accuracy from the start; - high expectations (at least for the majority of children) in terms of speed of learning and level of mastery; - focus on grammatical/orthographic rules and their application.

The picture just sketched is certainly a simplification insofar as it fails to acknowledge recent changes in early literacy teaching. A general trend from uniformity to variety of provision may be observed. This includes teaching aids (greater variety of primers, integrated multi-book reading schemes), classroom practices (a wider range of activities, apart from traditional primer-centred and teacher-centred ones) and teaching approaches (experiments with global or language experience methods). My description, however, reflects the mainstream approach.

155 CHAPTER 5

THE STUDY

5.1. RESEARCH PROBLEM AND HYPOTHESES

The scope of the study was to investigate early phases of reading and spelling acquisition in Polish, focusing particularly on the development of phonological recoding and orthographic processing. There were two distinct aims beyond this investigation. The first one was descriptive. Given the scarcity of studies on literacy acquisition in the Polish language it seemed worthwhile to investigate a wide range of literacy-related variables, and use these data to build a normative model of how Polish children learn to read and write. Such data would also have an applied value, since they could be used as a first step towards developing clinically useful measures of reading, spelling and phonological skills. The applied aspects are, however, beyond the direct scope of this thesis, and I have tried to follow them elsewhere (Szczerbihski, 1999). The second, and the most important aim was the comparative one; trying to tease apart the eognitive invariants from language- and edueation-speei/ic constraints of literacy acquisition. Studying Polish children seemed to provide a fertile ground for investigating this problem, given the unique characteristics of the Polish language and educational environment outlined in the previous chapter. My first set of hypotheses was concerned with the characteristics of early reading and spelling, especially the rate at which those skills are acquired and the cognitive strategies used by the learners. Both were expected to be highly constrained by the specific characteristics of the language and teaching. The ability to decode words should develop rapidly, given the high feed-forward consistency of Polish orthography and systematic phonics instruction. The initial reading strategy was expected to be predominantly alphabetic, characterised by an overt, systematic, sequential and slow grapheme-to-phoneme conversion. Later emergence of the orthographic strategy (parallel processing of larger orthographic units: syllables, morphemes and whole words) would be reflected in a marked increase in reading speed and near-perfect accuracy. Alphabetic decoding in reading and recoding in spelling should follow a similar, steep developmental curve. The development of orthographic skills (manifested in high-speed word recognition and orthographically accurate spelling) should be slower

156 and more protracted. Orthographic spelling, in particular, should lag very much behind reading, given relatively low consistency of phoneme-to-grapheme (feed-backward) mappings. These hypotheses are developed and tested in chapter 6. The second set of hypotheses was concerned with cognitive pre-requisites and co-requisites of literacy acquisition. These were expected (unlike the rate of learning and the processing strategies) to be largely universal for all (at least alphabetic) languages, including Polish. The prime constraints should come from two independent phonological factors: one being the ability to access and manipulate the sublexical phonological units (phonological awareness); the other being the ability to retrieve phonological codes efficiently (operationalized with naming and fluency tasks). Cross- linguistic differences were expected to emerge mainly with respect to the absolute level of mastery of specific phonological awareness tasks and the relative importance of different levels of phonological representations (phonemic, intrasyllabic, syllabic). Given the characteristics of the Polish language and literacy instruction it was expected that the Polish learners would show a very high mastery of the phoneme-level skills (such as detection, analysis, blending and deletion). In contrast, the ability to process rhyme structures was expected to be low. Likewise, the strong connection between reading and phoneme-level, but not rhyme-level phonological ability was predicted. It was also expected that the ability to manipulate the morphemic structure of words (morphological awareness) should play an increasingly important role beyond the earliest decoding phase, particularly in the context of orthographic spelling, given its consistent morphological underpinning. The constraints coming from purely visual factors were expected to play a minor role, perhaps emerging most clearly in relation to processing of diacritics. These hypotheses are developed and tested in chapter 7. The third and final group of hypotheses regarded written language disorders. It was expected that their manifestations and mechanisms would be the same as in other moderate-to-high consistency orthographies (particularly German: Wimmer, 1993b, 1996a, b; Wimmer, Mayringer & Landerl, 1999). Problems with accuracy of decoding were expected to be rare and mild, at least beyond the initial period of learning (grade one). Typical and persistent problems should include low reading speed and orthographically inaccurate spelling. In terms of mechanisms of breakdown, support was anticipated for the double deficit hypothesis, deriving most reading and spelling difficulties from a combined deficit of phonological awareness and phonological retrieval. However, the retrieval deficit was predicted to play a much more important role than the awareness deficit, since the consistency of Polish orthography and phonics

157 instruction should alleviate the latter. Those hypotheses are developed and tested in chapter 8.

5.2. PARTICIPANTS

Participants were recruited from one state primary school located in the central borough of Krakow. As a typical state school it enrolled children of widely varying backgrounds, living mainly in close proximity to the school. Being located in a relatively affluent neighbourhood, however, it had an above average proportion of pupils from middle- class families, with parents holding a degree'. This factor was probably responsible for the above-average performance of the sample on the standardised measures of intelligence (see below). The choice of that particular institution was mainly practical; the school co-operates with the Department of Psychology of the Jagiellonian University and is a traditional ‘venue’ of psychological research and training, supporting it logistically. The school houses a small psychology clinic, which is an outpost of the Department of Psychology. The clinic has two employees working with the pupil population (dyslexia screening, dealing with challenging behaviour, etc.), who are occasionally involved in academic teaching (with psychology undergraduates and teacher trainees) and also facilitate research activities. Parents enrolling their children at the school are infomied about the possibility of them participating in psychological studies and are asked for written consent. Refusal is sporadic, so practically the whole school population is available for research. The pupils, parents and teachers are accustomed to the situation of psychological testing and good testing facilities exist.

the span of the study

grade 0 grade 1 grade 2 grade 3

> < > )re-school period period of initial education later primary education

Figure 5-1. The study and its relation to the primary education system.

' More specific information about parental education is provided for the dyslexic children and their reading-age and chronological-age controls (see chapter 8).

158 The study involved 108 children who were in the period of initial education, that is, T' to S'"" grade (see figure 5-1; see also section 4.3 for information on the Polish educational system). Nearly all of the children attended a reception class (“zero grade”) for a year before entering grade 1; this took place either at the school or at another nursery school. My study did not involve “zero graders”. The first part of testing was completed between January and May 1998, which corresponded roughly to the second semester of the school year. Six different classes (groups) were involved, two at each grade level. Testing continued during the first semester of the next school year (from September to December 1998); at this point the two most senior classes that progressed from grade 3 to 4 were dropped from the study, but two newly formed T' grade classes were added. Each grade was sampled throughout most of the school year; there was no difference between the grades regarding the time of testing (F[2,105]=.l 18, p>.50). Consecutive children were drawn from class registers, starting from the beginning or the end of the list, or working alternately toward the middle (different procedures were used in different classes). This inadvertently resulted in boys being over-represented in grade two (see table 5-1). This overrepresentation makes the analysis of the combined data set problematic, insofar as sexes differ in their performance. As it turned out, however, very few significant gender differences emerged, and none with respect to reading (word and nonword, accuracy and speed). No exclusion criteria of any sort were applied while recruiting participants.

GRADE r ‘ 2"d 3 rd overall boys 20 26 17 63 girls 17 10 18 45 overall 37 36 35 108 mean age 7;7(0) 8 ;6(8 ) 9;7(9) min - max 6;ll(8)-8;4(28) 7;7(25) - 9;6(27) 8;8(18)- 10;8 (20) Table 5-1. Age and gender characteristics of the sample.

Children were taught by 6 different teachers, each teacher leading one class throughout the whole period of initial education and being responsible for most classroom activities, apart from specific subjects (like religious studies or foreign languages). Initial reading instruction (grade one) was fairly uniform across the classes, being a mixture of analytic and synthetic phonics typical of Polish schools. Instruction was based on a primer book, although many additional materials were also used. Among the

159 eight classes involved in the study, three different primers were used when the children were in grade 1. Grapheme names and sounds were systematically and explicitly taught in the context of word analysis and blending. The grapheme-phoneme correspondences that are most frequent and transparent were introduced first, while more complex problems (letters with diacritics, digraphs, morphologically-motivated conditional correspondences) were introduced later during the first grade, or even in subsequent grades. Reading and writing instruction were closely synchronised.^ Three standardised measures used in the study showed that my sample performed above the national average in terms of general reasoning skills (Columbia Mental Development Scale) and productive vocabulary (WISC-R Vocabulary subseale), but below average on short-term memory (WISC-R Digit Span), all differences being significant (p<.005) on one-sample t-tests (see table 5-2). Superior general cognitive skills were in line with the parental socio-economic and educational background of the sample. However, there is no apparent explanation for a large and significant discrepancy (one standard deviation; p<.001) between good Vocabulary and poor Digit Span performance. Two-way Sex by Age ANOVAs showed that boys outperformed girls on Vocabulary (p<.05), while no sex differences were observed with respect to reasoning skills and Digit Span.

1** grade 2"^* grade 3*^** grade Overall WISC-R Vocabulary 12.34 (2.54) 12.74 (2.80) 12.29 (2.39) 12.46 (2.57) min - max 7 - 18 6 - 17 8- 16 6 - 18 N 35 35 34 104 WISC-R Digit Span 9.20 (2.46) 9.14(2.81) 9.6 (2.42) 9.13(2.55) min - max 4 - 16 3 - 14 4 - 14 3 - 16 N 35 35 34 104 Columbia 108.57 (8.46) 106.66(11.01) 109.11 (8.27) 108.4 (9.36) min - max 93 - 125 83 - 132 89- 123 83 - 132 N 35 35 34(281* 104(981*

Table 5-2. Participants’ performance on standardised measures. WISC-R Vocabulary and Digit Span scaled scores; mean=10, SD=3 Columbia standard scale: mean=100, SD=15 * Figures in brackets indicate the number of children within the age range covered by the test norms, standard scores are based on that group only.

^ No systematic information was available regarding reading instruction at the reception (“zero grade”) level. It did not, however, differ very much from grade one instruction, except that simpler primers were used, teaching was less intensive, and not all graphemes were introduced. The initial months of the 1" grade reading instruction essentially recapitulated what children were supposed to know already from grade zero. 160 5.3. METHODS

All tests discussed here are presented in the appendix (apart from the standardised measures of general ability).

5.3.1. Control measures

These included tests of reasoning and vocabulary knowledge.

1. Columbia Mental Development Scale. This was a test of nonverbal reasoning based on the “odd one out” principle. A participant is presented with a series of large plates, each bearing four or five drawings and is requested to point to the drawing that ‘does not flf in each plate. Verbal responses are not required and are actively discouraged. The drawings present common objects or abstract shapes. The test items become progressively more difficult (moving from perceptual distinctions into object classification, matching by function, and inductive reasoning) and a discontinuity rule is applied. The test, originally developed in the USA, was adapted and standardised nationwide for the Polish population of 3;6 - 9; 11 years old (Ciechanowicz & Szurek, 1990). The test was chosen as it is a reliable and valid measure of reasoning (Ciechanowicz & Szurek, 1990) and can be administered easily and quickly (in around 20 minutes). A potential drawback lay in the fact that the test was relatively easy for the 3"'* grade group. Also, as six of my participants were already 10 years old standard scores could not be computed for them. However, no child performed error-free, and it was perfectly possible to identify participants with below average ability. The possible range of (raw) scores was 0-67.

2. Vocabulary. This was the subtest of the Polish version of the WISC-R battery, which is standardised nationwide. The administration and scoring was carried out as prescribed by the test manual. The possible range of (raw) scores was 0-64.

161 5.3.2. Verbal memory

3. Digit Span. This subtest of the Polish version of the WISC-R battery was administered and scored as prescribed by the test manual. The possible range of (raw) scores was 0-28.

4. Nonword repetition. This was a test based on an existing nonword repetition instrument (Zetotest: ICrasowicz, 1997), but using different, more difficult stimuli, which allowed for better discrimination among my older participants. 30 test items were between 5 and 15 phonemes long, polysyllabic (2-6 syllables) and contained consonant clusters (up to three phonemes long) that are very frequent according to the existing cluster frequency list (Dunaj, 1985). The participants were requested to repeat each ‘funny word’ following my oral presentation. The items could be presented twice and corrective feedback was given whenever I felt it was necessary (e.g. to encourage the participant or remind her to be exact), yet only perfect repetitions after the first presentation were scored as correct. The (few) participants with apparent articulation problems evident in their spontaneous speech (misarticulation of /l/-/r/, /s/-/J/) were not penalised for their difficulties: their responses were counted as correct if the only errors were misarticulations observed in spontaneous speech. The possible range of scores was 0-30.

5.3.3. Phonological sensitivity

The “odd one out” task paradigm was chosen to test phonological sensitivity. Three tests were constructed, which shared the same format, but systematically varied the target phonological unit (alliteration, masculine rhyme, feminine rhyme). Each test consisted of 16 four-word trials administered orally. These were preceded by 3 demonstration trials, during which the odd unit was explicitly identified. The odd words were placed with equal frequency in the first, second, third and fourth position of a four-word trial. Word frequency was not controlled, though most words were likely to be familiar to 7-year old children. A participant received 2 points for an immediate correct response. A trial was repeated only if the participant requested one, or if she/he did not provide a response after 5 seconds. 1 point was given for the successful performance after the second presentation. The possible range of scores was 0-32 for each test.

162 5. Alliteration oddity. Two-syllable words were used here. A participant was required to make four different types of categorisation: - word-initial vowel - 4 trials, e.g.: /ekran/ - /afij/ - /alarm/ - /ajiow/

- single consonant onset - 6 trials, e.g.: /letçetç/ - / npka/ - /ramje/ - /rotjek/

- multiple consonant onset - 2 trials, e.g.: /tjaskatp/ - /g 3ontki/ - /tjista/ - /trepak/

- initial consonant within a multiple consonant cluster - 4 trials, e.g.: /droga/ - /krulik/ - /drevno/ - /drapatç/

Thus, only half of the alliteration trials tapped into the onset level of phonological representations, others required categorisation of syllables (initial vowels) or phonemes (initial consonants within clusters).

6. Feminine rhyme oddity. Two syllable words were used again. The odd word differed by one phoneme within the rhyme unit. Four different distinctions were made: - first syllable vowel (4 trials), e.g.: /dajie/- /lajie/ - /zdajis/ - /kojie/

- second syllable vowel (4 trials), e.g.: /d^awo/ - /pawa/ - /stjawa/ - /skawa/

- middle consonant (4 trials), e.g.: /dugitç/ - /kugitç/ - /nud^itç/ - /zmugitç/

- final consonant (4 trials), e.g.: /zgajiit^/ - /rajiitg/ - /krajiik/ - /xjajiit^/

7. Masculine rhyme (rime) oddity. Closed monosyllables were used. The odd word differed by one phoneme within the rime unit. Two different distinctions were made: - middle vowel, i.e. nucleus (8 trials), e.g.: /tjâs/ - /Ios/ - /nos - /kps/

163 - final consonant, i.e. coda (8 trials), e.g.: /vur/ - /dvur/ - /bu^ - /xur/

5.3.4. Phonological awareness

8 . Phoneme analysis (segmentation). The test consisted of 18 common words, whose length varied between 3-11 phonemes (1-5 syllables). Half of them had simple CVCV- structure, the other half contained two-consonant clusters. All words were fully transparent orthographically, but two were spelled with a digraph. The words were provided orally and a participant had to utter each consecutive phoneme with the help of tokens. She could either lay down one token at a time, uttering a phoneme simultaneously, or point to the tokens already lying on the table and pronounce consecutive phonemes. Since a pilot study indicated very accurate performance, a discontinuity rule was applied: testing started with 7-phoneme words and continued until children made 3 consecutive errors. Performance on shorter (3-6) phoneme items was investigated only if children the made errors on 7- and 8-phoneme words, otherwise it was assumed to be correct. Two demonstration items were given before testing. Although the children were explicitly instructed to segment the sounds, not the letters, some did respond with letter names. This was not penalised, however: it was anticipated that given the high degree of overlap between letter names and sounds in Polish (see chapter 4) the distinction may be difficult to explain, and the responses difficult to score unequivocally. Only in the case of digraphs was it always evident when children counted letters rather than phonemes. In such case they were reminded of task requirements, but the letter responses were still scored as correct. Children were generally allowed one attempt at each word, but if they ‘got lost’ mid-way through the word and stopped, they were encouraged to start from the beginning. If the second attempt was successful, the response was scored as correct. Only correct identification of all segments in a word (consonants as well as vowels) was scored as correct. The possible range of scores was 0-18.

9. Phoneme blending. Children were required to identify the word which I uttered “like a robot”, phoneme-by-phoneme, approximately one sound per second. To avoid lipreading cues I spoke with my mouth covered. Otherwise the test matched the phoneme analysis task (the same discontinuation rule, stimuli of the same length and phonological complexity with transparent spellings, 5 sounds that would have to be

164 spelled with digraphs). Two demonstration trials were given before the testing. Children could request the repetition of any test item, but only correct responses after the first presentation were scored. The possible range of scores was 0-18.

10. Phoneme deletion. The children were asked to remove consecutive phonemes in words. The first three test trials (following three demonstration trials) required the removal of a single consonant constituting the word onset, e.g. /tak/ /ak/. In the following 8 trials the children were required to remove consecutive phonemes from an onset consonant cluster, until it was deleted altogether. Clusters of increasing length were used:

CC- (3 items), e.g.: /sto/ —> /to/ —> /o/

CCC- (3 items), e.g.: /strax/ /trax/ /rax/ /ax/

CCCC- (2 items), e.g.: /pstronk/ /stronk/ /tronk/ ->/ronk/ ->/onk/

The children were always prompted to ‘subtract yet another’ sound from the beginning of the word. When they ‘got lost’ in the middle of the analysis they were reminded of the steps they had already been through and encouraged to carry out yet another subtraction. One point was given for each correct subtraction. Children lost a point for removing more than one phoneme at a time, e.g. /strax/ /trax/ —> /rax/ /ax/ - 3 pts.

/strax/ /trax/ /ax/ - 2pts. /strax/ /ax/ - 1 pt

The possible range of scores was 0-26.

11. Consonant replacement. The participants were required to replace word-initial consonant phonemes with /f/. After three demonstration trials, the children were orally presented with 8 words and asked to replace single-consonant word onsets (e.g. /kotek/ /fotek/). 2 points were given for each correct replacement. Another three demonstration trials and 8 test words followed; this time participants were required to replace the first consonant of a CC- cluster (e.g. /plama/ /flama/). The children were given four points for each correct replacement, and two points if they replaced a whole

165 onset cluster rather than the initial consonant only (e.g. /plama/ /fama/). The products of the replacement were always nonwords. Each test word was repeated if the child requested so, or if she/he did not provide a response after 5 seconds. If the child succeeded on the second trial she was given half of the points she would have received if she had responded within the first 5 seconds. Unlike on most of the other tests, corrective feedback and additional instructions were given during testing if a child failed several items in succession, and gave an impression of not understanding task requirements. The possible range of scores was 0-48.

12. Vowel replacement. This was a development of the test originally designed by Wimmer et. al. (1991). Words containing the vowel /a/ were orally presented, and children were asked to replace /a/ with /u/. 8 initial trials involved monosyllables; nucleus /a/ had to be replaced in word-initial, middle and final positions (e.g. /as/ /us/; /rak/ /ruk/; /gra/ /gru/). 8 two-syllable words followed where two /a/ vowels had to be replaced (e.g. /anka/ -» /unku/; /brama/ /brumu/). Otherwise the format, administration and marking procedure were the same as in the consonant replacement test: points were taken away for delayed responses and for replacing only one vowel in a bi-syllabic word; corrective feedback was given if a child gave the impression of not understanding task requirements. The possible range of scores was 0-48.

5.3.5. Naming

13. Grapheme naming. The test consisted of two A4 pages, each displaying all 32 letters of the Polish alphabet together with 7 digraphs (those which are always taught at school as separate orthographic units). The graphemes were printed in lowercase in four rows, in a different pseudorandom order on each page. A short demonstration trial with 6 letters familiarised the children with the requirement to name all stimuli quickly and accurately. The f grade children only, whose knowledge of all graphemes could not be assumed, were instructed to respond ‘don’t know’ to an unfamiliar grapheme and move on to the next one as quickly as possible. The number of correct responses and overall naming time was summed across both lists; these scores were used to compute the % accuracy and mean naming time per grapheme.

166 14. Picture naming. The task was an adaptation of the Picture Naming subtest of the Phonological Assessment Battery (PhAB: Frederickson, Frith & Reason, 1997). The tests consisted of two A4 pages, each displaying (in different pseudo-random order) multiple copies of drawings of 5 common objects, presented in five rows, 40 drawings in total. The testing was carried out as prescribed in the original test manual: a child was given a familiarisation trial, and asked to name both sets of pictures quickly and accurately. However, the interval between two trials (prescribed as 30 seconds in the test manual) was shortened, however. Also, 4 out of 5 of the original pictures were replaced to match the phonological characteristics of the Polish and English stimuli as closely as possible^ As few errors occurred, only naming times (summed across both trials) were analysed.

15. Digit naming. This was a literal translation of the Digit Naming subtest of the PhAB battery. The stimuli were 5 digits repeated 10 times in a pseudorandom order, all displayed in a single row on an A4 page. The task was repeated with a different arrangement of digits, and the overall naming time was summed across two trials. As in the case of picture naming, the interval between two trials was less than prescribed 30 seconds. Since Polish digit names are nearly always longer than their English counterparts, no word length match was attempted across the languages.

5.3.6. Verbal fluency

All four fluency tests were modelled on the respective subtests of the PhAB battery, and shared the same format. After two short demonstration trials two test trials were given (each 30 seconds long), during which children had to produce words in response to a specific cue (semantic, alliteration or rhyme). If the children paused for several seconds they were encouraged to generate more examples and the cue word was repeated. The results of both test trials were summed to obtain a composite score.

16. Semantic fluency. Participants were asked to produce names o f animals (30 seconds) and names o fthings you can eat if ^ seconds). The same semantic categories were used in the original English PhAB semantic fluency task. Genus names (e.g. bird^ species names (e.g. robin) and brand names (e.g. Fanta) were all scored as correct.

’ Original: ball, hat door table and box were replaced with /las/, /dom/, /xak/, /stuw/, /mij/, { fo r e s t, house, hooh, labie, mouse, respectively).

167 Varieties on the same word, however, (e.g. cream cheese, cottage cheese.. were treated as a single example.

17. Alliteration fluency. Participants were asked to produce words beginning with /t/ and /m / (30 seconds each). The sounds were chosen as they are very frequent alliterations, each having only one possible spelling. Following the PhAB manual, only real word responses were scored as correct.

18. Feminine rhyme fluency. Participants were asked to produce words rhyming with „ hrdwha ” Mvà „ ma/owac ” seconds each). This was the only fluency test without a direct counterpart in the PhAB battery. Children had practically infinite possibilities of generating examples here, as rhymes /-ufka/ (marking some noun diminutives) and /-ov atç/ (marking some verb infinitives) each have type frequency of several thousand. Only polysyllabic real word responses were scored as correct: nonwords or monosyllabic words sharing a rime with the cue word (e.g. "'stac'\ '"dac'' in response to “malowac”) were rejected.

19. Masculine rhyme (rime) fluency. Participants were asked to produce words rhyming with „bo/c” and „stac”. These words were chosen because they represent probably the largest families of masculine rhymes in the Polish language: the type rhyme frequency is 27 for /-ok/ and 41 for /-atç/"^. Only monosyllabic word responses were scored as correct: nonwords or polysyllabic words sharing the final syllable rime (e.g. '’'’ma/owad' in response to “dac”) were rejected.

5.3.7. Morphological processing

Four tests were constructed to investigate the processing of those aspects of Polish morphology that are most directly reflected in the orthography. Every test was composed of two parts (16 items each), requiring contrasting operations (e.g. adding vs. deleting a prefix), and each part was preceded by a separate instruction and three demonstration items. For two of the tests (diminutives and comparison of adjectives) pictures were used to aid explanation.

This includes only lemmas (i.e. basic, dictionary form of a word). Even more exemplars could be generated, however, as some words rhymed with the cue words only when occurring in certain inflectional forms. The number of such exemplars was difficult to specify, however. 168 Two points were given for each correct (and immediate) transformation. If children requested repetition, or did not respond within 5 seconds, the test item was repeated. Half a mark (i.e. 1 point) was given for a correct performance at the second attempt. As in the case of the two phoneme replacement tests presented above, corrective feedback and additional instructions were given if children failed several items in succession, giving the impression that they did not understand the task requirements. The scores were summed across two parts to form the composite. The possible range of scores was 0-64 for each test.

20. Derivative forms. Children were first required to find the derivatives of orally presented words (“Find the word’s children”, e.g. czytac czytan/e [read reac/m^ and then their root forms (“Find the word’s parents”, e.g. kierowca —> h'erovuac\&['\vQX

é/r/vé\). Most derivations went across word classes (verbs to nouns, nouns to adjectives, etc.) but within class derivations were also possible (e.g. popielniczka

/?op/o/[dishtmy ash]). For many items, several answers could be given, any of which would be scored as correct.

21. Diminutives. In the first subtest children were asked to form diminutives of the orally presented nouns (“big to small”, e.g. drzewo drzewko [tree sma//treé^, in the second subtest the opposite transformation was required (“small to big”, e.g. jabluszko Jablko [small apple applé^. There are several different ways of forming diminutives in Polish, and most of them were covered in the test. The word pairs were sometimes semantically identical (except the feature of “smallness”) and sometimes different (e.g. droga drozka [road pa/b]).

22. Comparison of adjectives. In the first subtest children had to derive the comparative (or superlative) form of orally presented adjectives (e.g. cieply -» cieplejszy [warm warmer^. In the second subtest the opposite transformation was required (e.g. drozszy drogi [more expensive^ expensive^). There are several different ways of forming comparative forms of adjectives in Polish and most of them were covered in the test.

23. Prefixes. In the first subtest children were asked to strip prefixes off orally presented verbs and pronounce the remaining root (“finding little words hidden in the big ones”).

169 In the second subtest they had to add prefixes to verbs. Adding a prefix sometimes changed the aspect of the verb (imperfective to perfective) and sometimes derived a new word in a way analogous to English phrasal verbs (e.g. drukowac -> fvvdruko wac I print

prmt 014î\\ rzucic rozrzucic [throw -^scatter (around/^. Each verb could take on several different prefixes and the children were encouraged to use different ones. Often (but not always) prefixes constituted a syllable.

5.3.8. Visual-motor processing

Speeded visual discrimination. Two tasks of identical format were developed, each using a different type of stimuli (letters vs. non-letter symbols)

24. Letter discrimination. 16 non-pronounceable strings of letters (4-7 letters long) were arranged in pairs, so that they formed two columns on a single A4 page. Children were asked to treat a left-hand side string as a template and compare it with its right- hand side counterpart, which should be crossed off if different, e.g.

nstulyr nstulyr mzgir mzyir

Half of string pairs contained an alteration, which involved visually similar letters (e.g. differing only in diacritics). The test was preceded by a short (6 pairs) familiarisation trial. Children were asked to perform quickly as well as accurately. Older children completed a longer version of the test, consisting of two subtests (each printed on a separate page) with 32 test letter string pairs altogether. Due to time limitations, the T‘ grade children were tested only with the first page. The times and scores of the older children were averaged across two subtests to allow a direct comparison with the results obtained by younger children on the shorter version.

25. Symbol discrimination. The testing and scoring procedure was the same as in the letter discrimination test, but non-letter symbols were used, e.g.:

& !"# & !"#

.%=>?

170 The r* grade group, again, completed the shorter version of the test.

26. Visual memory (“Chinese letters”).This test was developed to assess immediate and delayed visual recognition. It was introduced to participants as Teaming and remembering Chinese letters’. An abstract geometrical design, resembling Chinese script (approximately 2-3 cm in diameter, printed on a small card) was presented to a child for 4 seconds, and immediately replaced with a horizontal array of 10 similarly- looking designs, among which the target pattern had to be recognised. 12 trials of this type were given. Immediately following this, a child was asked to recognise the original designs once more; this time, however, only two distractors were introduced. Correct recognitions were summed across two subtests. The possible range of scores was 0-24\

27. Copying Rev-Osterrieth figure. This procedure of reproducing a complex geometrical design directly and from memory has originally been developed in the context of adult neuropsychological assessment. Performance accuracy as well as drawing strategy are indicative of executive processes and right hemisphere visuo- spatial functions (Lezak, 1995; Grant & Adams, 1996). The test has also been adopted for developmental diagnosis as a measure of visual-perceptual organisation, memory and visual-motor co-ordination. Standard testing procedure involves both direct copying and delayed reproduction. Only direct copying was requested here, as the reproduction from memory would be too difficult for 7-10 year old children. The scoring scheme provided by the Polish handbook of the test (Strupczewska, 1990) was used. It evaluated accuracy only, not the performance strategy. The time taken to perform the task was also recorded. The possible range of scores was 0-36.

All designs were developed by Agnieszka Klaczak, MA. 171 5.3.9. Reading and spelling measures fVord reading. Children were asked to read lists of unconnected words. Two word characteristics were systematically manipulated:

Orthographic compiexity. ‘Simple’ lists included only words that are fully transparent for reading and spelling, did not contain any letters with diacritics and only one digraph (, which occurred twice). These words are, thus, composed of graphemes that are introduced relatively early (most of them already in zero grade). The ‘complex’ lists included many digraphs, diacritics, and morphologically-motivated orthographic patterns. By the nature of Polish orthography, all words in the complex lists were still fully consistent for reading (i.e. they could have only one legal pronunciation); some of them were even fully transparent (they could be decoded by sounding out and blending individual letters). All these words, however, were inconsistent for spelling: they posed spelling alternatives, so that each word could have its pseudohomophone.

Spoken freguency. Frequency counts of the spoken vocabulary of 6-year-olds (Zgotkowa & Bulczyhska, 1980) were used to select the frequent words (frequency between 13 and 268 per 100,000; median 63.5) and the infrequent ones (9 or 10 per 100,000; median 9).

By counterbalancing, eight 5-word lists were constructed: 2 frequent and simple, 2 non- frequent and simple, 2 frequent and complex, and 2 non-frequent and complex (40 words altogether). Each list contained one monosyllable, three 2-syllable words, and one 3- or 4-syllable word. An attempt was also made to match lists on overall letter and phoneme length, but an exact match was not obtained. Mean word length per list varied between 5.2 and 6.6 letters, and 5.0 - 6.2 phonemes. Complex words were longer on average than simple ones (6.0 versus 5.45 phonemes; 6.3 versus 5.6 letters in the complex and the simple series, respectively), but the difference was not significant on a t-test comparison (p>.10).

Each list was printed as a column on a separate A5 page using 20-point font size.

172 Nonword reading. Nonwords were constructed from the same “letter material” as words by re-shuffling individual graphemes or whole syllables within each list. The length, CV structure and orthographic complexity of word and nonword items were matched as closely as possible; otherwise, there was little similarity between word and nonword stimuli, e.g.: fVORDS M 4TCJIÆ D NO N fVO U D S

film rolm ladny fîdny rower lewer cztery cztaga kolega kotery

non-/requent - dij/icu/t

rog POg s^siad s^siol podrzec drzeroc dziçciol dziçciad konduktor rokondukt

The whole set of reading stimuli (16 lists, 8 for words and 8 for nonwords, 80 items) was administered to and 3'*^ grade children. T’ graders read only half of this material (the first four word and nonword lists). Words were always read first, and nonwords followed during the next session (at least a day later). Children were asked to read as “nicely and quickly” as possible. Nonwords were introduced as “funny, make-believe words you have never heard or seen before”. Additionally, T* grade children only were instructed to reply “don’t know” to any items they were unable to read and to quickly move on to the next one.

173 Eight counterbalanced orders were used to present the lists. Seores were averaged across the lists to compute time and accuracy indices, separately for words and nonwords.

Spe//ing. The same stimuli wer used in a group spelling test (administered to whole classes). Some classes were tested twice, but only data from the June 1998 testing, which involved most children, are reported. Words again preeeded nonwords, but all were administered within the same session (separated by a short interval). Children spelled the same stimuli they read during individual sessions: 80 items in 2"** and grade, and 40 items in grade. At the time of eolleeting the spelling data (June), the younger group of T’ graders to be involved in the study had not yet entered school (they were still in grade 0). These children were tested in December. Their handwriting skills were poor, and unlike their older T' grade peers they were unable to spell 40 items during a single testing session. These ehildren were tested on 20 items only (frequent-easy and infrequent-difficult words, and corresponding nonwords). Given the limitation of this data set (i.e. a small set of stimuli and a different time of testing) I eventually decided to exclude the spellings of this younger T' grade cohort from the analyses.

5.4. Procedure

All the measures (exeept for a group spelling test) were administered individually in a quiet room at the school premises. The length of testing varied considerably depending on the ehildren’s age and ability. The average testing took approximately three 45- minute school lessons (ranging from less than 2 to more than 4 lessons). This was divided between 2-4 separate sessions (median 2 sessions), scattered over the period of 2-12 days (median 3 days). Breaks were taken during longer sessions at least every 45 minutes. The whole battery of tests was arranged so that similar measures (e.g. phoneme analysis and blending) were separated by at least two other tests. The whole set was then administered in eight counterbalanced orders, with the exeeption of oddity and verbal fluency measures, which followed one fixed order: alliteration, feminine rhyme, masculine rhyme oddity, semantie, alliteration, feminine rhyme, masculine rhyme fluency. Those seven tests were, however, not blocked but interspersed with other measures. 174 Some children had missing data on some variables, due to sporadic refusal, long illness or absence after the initial testing session, my errors during test administration, or missing records (I decided, in order to minimise ‘measurement noise’ that the maximum span of individual testing would be 2 weeks). However, the incomplete data sets were included into the following analyses, as far as possible. As mentioned before, spelling was assessed with a group test. Group testing created a number of problems: increased drop-out rate, possibility of cheating, as well as a variable time gap between the group assessment of spelling and individual assessment of other skills. However, time limitations did not allow for individual testing of spelling.

The descriptive statistics for all the experimental measures (mean, median, standard deviation, range, skewness and kurtosis) computed separately for each grade and for the combined sample, are presented in the appendix.

5.5. Reliability of tests

Reliability coefficients were computed for all the measures developed especially for this study (i.e. those whose psychometric “goodness” could not be known from published sources). They are presented in table 5-3. Reliabilities varied widely between the tests. They were very good for the indices of performance speed (above .90 in all but one case) but typically poorer for accuracy. A number of tests fell short of .70 reliability often recommended as a requirement for a good research tool (Nunnally, 1978, in Hammond, 2000). Tests with the lowest reliability typically showed the floor or the ceiling effect (rhyme fluency, “Chinese letters” visual memory test; grade accuracy of word reading, phoneme analysis, letter naming and visual discrimination, diminutives). The main exception to this pattern was the fluency tests, whose reliability was usually low regardless of whether they were affected by a small variability of scores (rhyming fluency) or not (semantic and alliteration fluency).

175 SKILLS TASK RELIABILITY COEFFICIENT fSt 2nd 3rd overall grade grade grade reading word-accuracy .77 .65 .46 - a-Cronbach a) word-time .95 .98 .95 - a-Cronbach b) nonword-accuracy .89 .86 .80 - a-Cronbach a) nonword-time .96 .98 .95 - a-Cronbach b) spelling word-accuracy .65 .84 .79 - a-Cronbach a) nonword-accuracy .58 .81 .64 - a-Cronbach a) memory Nonword repetition .74 .78 .52 .74 a-Cronbach, 30 items Alliteration oddity .77 .78 .66 .80 a-Cronbach, 16 items phonolo­ Feminine rhyme oddity .66 .76 .76 .76 a-Cronbach, 16 items gical Masculine rhyme oddity .81 .79 .68 .80 a-Cronbach, 16 items Phoneme deletion .77 .90 .61 .86 Guttman split-half c) sensitivity Vowel replacement .92 .92 .66 .87 Guttman split-half c) & Consonant replacement .84 .88 .73 .84 Guttman split-half c) awareness Phoneme analysis .90 .72 .07 .87 Guttman split-half c) Phoneme blending .89 .91 .62 .88 Guttman split-half c) morpholo­ Comparison of adj. .86 .87 .82 .89 a-Cronbach, 32 items gical Verb prefixation .92 .80 .87 .93 a-Cronbach, 32 items awareness Diminutives .61 .71 .37 .72 a-Cronbach, 32 items Derivative forms .76 .80 .76 .82 a-Cronbach, 32 items rapid Picture naming .76 .90 .92 .86 Guttman split-half d) naming Digit naming .99 .88 .96 .98 Guttman split-half d) Letter naming - speed .92 .93 .92 .95 Guttman split-half d) Letter naming - accuracy .98 .89 .36 .98 Guttman split-half d) verbal Semantic fluency .48 .58 .49 .59 Guttman split-half d) fluency Alliteration fluency .78 .67 .12 .71 Guttman split-half d) Feminine rhyme fluency .78 .22 .24 .46 Guttman split-half d) Masc. rhyme fluency .40 .66 .19 .41 Guttman split-half d) visual “Chinese letters” .49 .68 .64 .62 Guttman split-half d) processing Letter discrim, accur. - .81 .56 .77 Guttman split-half e) Symbol discrim, accur. - .41 .58 .48 Guttman split-half e) Letter discrim, speed - .87 .94 .91 Guttman split-half e) Symbol discrim, speed - .92 .97 .94 Guttman split-half e)

Table 5-3. Reliability coefficients of non-standardised measures used in the study. a) Based on 20 items (individual words) in T' grade, 40 items in older grades. As the number of item changed between the grades, no overall reliability index was computed. b) Based on 4 items (five-word-long lists) in T' grade, 8 items in older grades. c) Odd items against even ones. d) First part of the test against the second part. e) No reliability could be computed for T' grade children, as only one number (time of reading the first part of the test) was available from them. Overall reliability was based on 2"^ and 3"^ grade scores only.

176 CHAPTER 6

READING AND SPELLING DEVELOPMENT

The following chapter will be focused on the analysis of literacy skills of my participants. Their literacy ability will be looked at from four different angles. Firstly, I want to examine the absolute levels of reading and spelling performance and their age- related growth. Secondly, correlation and factor analyses will be used to explore the relationships between different sub-components of literacy. Thirdly, I will use analyses of variance to explore the influence of stimulus properties (lexical status, orthographic complexity, frequency) on accuracy and speed of performance at different age levels. Finally, error analyses will reveal most typical patterns of misreading and misspelling. The overarching aim of all those explorations is to identify dominant reading strategies of Polish early readers, changes over time, and to provide a normative mode/ of early reading acquisition in Polish.

6.1. COMPONENTS OF LITERACY - THEIR ORGANISATION AND GROWTH.

Throughout previous chapters I highlighted the distinction between phonological and orthographic skills. The former denote the ability to use information about phonological structure of words in order to process their written forms. They are most directly detectable in reading and spelling of unfamiliar words. The latter denote the use of orthography- spec ific knowledge, primarily in recognition and production of orthographically accurate (or at least orthographically plausible) written word forms. Although the distinction between the phonological and orthographic skills is largely agreed upon (e.g. Share, 1995; Vellutino, Scanlon & Tanzman, 1994), there are some important differences in conceptualising their interaction, as well as developmental timing and sequencing. Phase models of reading acquisition (eg. Frith, 1985; Ehri, 1992) emphasise developmental succession: phonological recoding skills (especially phoneme-based recoding, i.e. alphabetic skills) are acquired first, and enable further orthographic development. Connectionist models, on the other hand, stress the unitary nature of the acquired competence: ‘the phonological’ and ‘the orthographic’ processes are just different aspects of the same learning network. Both types of models predict robust correlations between alphabetic and orthographic skills. However, they diverge in

177 predicting their developmental trajectories. The phase framework implies a degree of asynchrony: the period of most dynamic growth in alphabetic skills precedes the respective period for orthographie skills. This is beeause some decoding competence is a precondition of normal accumulation of orthographic knowledge. The connectionist framework, on the other hand, implies that alphabetic and orthographic skills develop very much in parallel, from the beginning of aequisition. This study gave only limited possibilities for checking these contrasting predictions, since it did not include any direct measures of orthographic skills (such as homophone choice or word-pseudohomophone choice). Also, the optimal way of exploring developmental trajectories involves following individual participants longitudinally and observing when and how rapid spurts, decreases, plateaux and slow gradual increases in performance occur (Frith, 1985); the very information that is not available in a cross sectional study. In our case, however, word spelling could be treated as a good proxy of orthographic skills, whereas nonword reading and spelling provides a direct index of phonological recoding skills. Also, given the intensive, highly structured and uniform teaching programme all my participants went through, it is plausible that their individual developmental trajectories will be similar, and discernible even in cross-sectional group average data.

6.1.1. Change between the grades.

Descriptive statistics (table 6-1) show the development of different aspects of literacy between grades 1 and 3. When interpreting the results, it is important to bear in mind the different quality of reading and spelling data (see chapter 5). Reading data came from individual assessments carried out throughout the school year, whereas spelling data arose from a group test administered once to each class. As a consequence, some participants did not complete the spelling test because they were absent on the day of testing. Also, spelling data from ehildren tested in the semester of the T‘ grade were very limited, thus not included in the subsequent analyses. All those factors added some “noise”, whieh may lead to the extent of true eorrelation between reading and spelling being underestimated. '

' Additionally, the division into grades was different for reading than for spelling tasks. It was so because some participants had their spelling assessed earlier, and reading later; in the meanwhile, they progressed to the next grade. As each score is classified according to the time it was collected, the same child may contribute to T‘ grade spelling mean, but 2"*' grade reading mean, or 2"'' grade spelling, but grade reading.

178 Large discrepancies in the mastery of different tasks are apparent. Adopting some (moderately strict) operational criteria of group mastery of a task (average accuracy exceeding 80%, fewer than five percent of participants performing with less than 50% accuracy) we find that: r ' grade children had already almost mastered word reading (79% average accuracy, 5'^ percentile at 49%); 2"^* grade children showed near-perfect reading accuracy (average 94%, 5"’ percentile at 80%), but did not master any other skill; 3'^* grade children additionally mastered word spelling. Accurate recognition and reproduction of familiar written words did not imply the full mastery of the decoding skills, however. Reading and spelling of nonwords lagged some two years behind word recognition, and were not fully mastered even in the grade (when their average accuracy still fell short of 80%).

Variable Grade N Mean Median SD Range Reading words - 1 36 79 83 16 45-100 accuracy 2 36 94 96 6 8 0 -1 0 0 % correct responses 3 33 96 98 4 8 5 -1 0 0 Reading words - 1 37 5.85 4.70 3.98 1.15-15.75 time 2 36 1.77 1.27 1.19 .57-6.48 seconds per item 3 34 1.14 .96 .48 .55-2.53 Reading nonwords - 1 34 53 50 27 0-100 accuracy 2 34 70 70 17 28-95 % correct responses 3 33 77 78 13 38-98 Reading nonwords - 1 35 6.31 5.85 3.60 1.65-14.45 time 2 33 2.49 2.17 1.28 1.02-7.33 seconds per item 3 35 2.09 2.03 .70 1.08-4.20

Spelling words - 1 29 71 70 13 40-95 accuracy 2 27 77 83 14 33-93 % correct responses 3 16 89 90 9 65-100 Spelling nonwords - 1 29 70 70 14 40-95 accuracy 2 27 59 60 16 13-85 % correct responses 3 16 79 78 8 65-93

Table 6-1. Reading and spelling measures - descriptive statistics.

Measures of central tendency presented in table 6-1 show that, in absolute terms, speed increases much more than accuracy. An average 3'^' grader read words five times faster, and nonwords three times faster, than his T' grade peer, while improvement in accuracy (of reading and spelling) ranges only between 1.13 and 1.45. However, absolute ratios

179 may misrepresent the true dynamic of growth, as they do not take into consideration the variability of scores at each grade level. More reliable indices of developmental progress are given by effect sizes of change between the grades.

3 -

2.5 0.76 0.4 0.4

0.76 0.94 1.17 1.5 0.21 1.21 □ 2nd grade - 3rd grade

1.04 1.66 □ 1st grade 2nd term - 2nd grade

0.5 □ 1 St grade 1 st term - 1 st grade 2nd term 0.44

0.73 -0.5< (A

-1 J

Figure 6-1. Relative gains in reading and spellings skills, expressed as effect sizes of change between grades.

When effect sizes are computed- (with the 1" grade sample divided into first and second semester subgroups) the dynamic of growth looks rather similar for all aspects of reading, despite striking differences in absolute levels of performance (high accuracy, low speed) (Figure 6-1). The biggest developmental gains occurred up to grade 2; later on the progress became slower. Some subtle asynchronies, however, are also observable. The beginning of the 1st grade brings the most dynamic development of decoding acci/racy, whereas the following year brings relatively the largest gains in decoding and recognition speed. This asynchrony may suggest sequential development of phonological and orthographic skills: rudimentary ability to translate letters into sounds must be acquired before more automatic (parallel?) processing of letter strings can be established.

- i.e. difference between mean scores of two adjacent grades, divided by their averaged standard deviation

180 spelling skills, on the other hand, showed a different developmental curve, growing most dynamically between grades 2 and 3. This is most apparent in the case of nonword spelling which, unexpectedly, dwindles between the second half of grade 1 and grade 2, and recovers only later\ It seems, therefore, that the development of spelling is more protracted. Overall, we observe only minor asynchronies between decoding accuracy and decoding (and recognition) speed, yet quite different developmental trajectories for reading and spelling. Reading- spelling dissociations should be interpreted with caution, however, since they may be an artifact of testing procedures discussed above. The decrease in nonword spelling accuracy between grades one and two is unexpected and does not have an apparent explanation. It cannot be attributed solely to low test reliability: nonword spelling was actually most reliable (.81) in grade two, while less so (below .65) in grades 1 and 3 (see section 5.5.). Sampling bias appeared as a possibility: since boys were over-represented in the 2"^* grade sample (see section 5.2) and they performed significantly worse on spelling (but not on reading) than girls, so, as a consequence, spelling performance of the entire grade sample could decrease. If this explanation was valid, however, then the drop in performance should be observed for word and nonword spelling alike, which was not the case. The other explanation could invoke progressive lexicalisation of spelling strategies: as children move from the alphabetic to orthographic phase, they may be biased towards substituting target items with real words. Error analysis revealed that this was not the case, either: lexical substitutions constituted a small fraction of nonword spelling errors at all age levels (see section 6.3.2.). It seems most plausible that the group-administered nonword spelling test has a low validity as a measure of phonological recoding, being strongly influenced by the factors specific to the testing situation (like the level of noise in the classroom) and putting high demands on attention. The real word spelling task was less demanding on the input side, thus also less affected by those confounds.

6.1.2. Internal structure of literacy skills.

Given a hypothesis of partially dissociable alphabetic and orthographic skills, two separate (albeit highly correlated) factors were predicted. The first (representing decoding skills) would include nonword reading and spelling; the second (orthographic)

^ We have no reliable spelling data from 1" semester of the T‘ grade, but spelling skills apparently develop rapidly during that period, since they reach mean 70% accuracy in semester 2.

181 would involve word reading speed and word spelling accuracy. The remaining subskills (nonword reading time, word reading accuracy) should load on both factors. All aspects of reading turned out to be strongly intercorrelated (table 6-2). This was particularly the case with reading speed (r=.947 between word and nonword tests}* and reading accuracy (r=.824 between word and nonword tests). Word spelling showed moderately strong correlation with various reading indices. However, the test of nonword spelling appeared to be unrelated to other measures, except for word spelling and nonword reading.

Reading- Reading- Reading- Reading- Spelling- Spelling- word- word-time nonword- nonword­ word- nonword- accuracy accuracy time accuracy accuracy

Reading-word- - -.///*** accuracy Reading-word­ -.778*** - -.461*** time Reading-nonword- .824*** -.734*** - accuracy Reading-nonword­ -.772*** .947*** -.690*** - time

Spelling-word- .393** -.566*** .483*** - 469*** - accuracy Speliing-nonword- .150 -.159 .339** -.064 .508*** accuracy

Table 6-2. Correlations between reading and spelling measures. Time scores were log-transformed before the analyses. Figures below diagonal express zero-order Pearson correlations. Figures above diagonal are partial correlations, controlling for chronological age, WISC Vocabulary (raw scores), Columbia (raw scores). * p<.05; ** p<.01; *** p<.000

A factor analysis (Principal Component extraction. Direct Oblimin rotation) showed that the observed pattern of correlations could be reduced to two factors (table 6-3). The first received high loadings from all reading measures, and a weak loading from word spelling. It accounted for 63.4% of overall variance. The second factor encompassed both spelling tests, and explained 20% of overall variance.

^ Descriptive statistics revealed that the distributions of all time-based measures showed strong negative skewness (see appendix). To improve their fit for the subsequent analyses, word and nonword time scores were log-transformed. All correlation, factorial and regression analyses reported in this and following chapter are based on log-transformed time scores.

182 Factor 1 Factor 2 Reading-nonword-time -.973 Reading-word-time -.949 Reading-word-accuracy .921 Reading-nonword-accuracy .801 Spelling-nonword .971 Spelling-word .351 .673

Table 6-3. Pattern matrix of the factor analysis of reading and spelling measures. Time scores were log- transformed before the analysis. Values represent factor loadings and are sorted by size. Only factor loadings higher than .30 are displayed.

The first (general reading) factor was not decomposable any further. The second factor analysis, carried out on reading measures only (both speed and accuracy), identified just one factor which accounted for 84% of overall variance. Generally, the results suggest a very strong relationship between different aspects of reading, those which are apparently phonological as well as those which are orthographic. Spelling constitutes a partially separate dimension. The latter conclusion should be treated cautiously, however, as it probably reflects differences in testing procedure. It is important to add, however, that word spelling accuracy did load on the same factor as reading indices; it is only nonword spelling that truly stood out. That last variable also showed an atypical pattern of development, with scores decreasing between T' and 2"*^ grade level (figure 6-1). Different patterns of correlations for word and nonword spelling cannot be accounted for by differences in testing procedure (since both tasks were carried out during the same group session), but they may reflect low reliability of the nonword spelling task in grades 1 and 3 (see section 5.5.), and its generally low validity as a measure of phonological recoding (see previous section). Nonword spelling was expected to correlate particularly strongly with nonword reading, since both are considered to be relatively pure measures of recoding skills. The correlation turned out to be significant, but weak (table 6-2), despite the comparable level of difficulty of both tasks (table 6-1). As pointed out before (sections 5.5. and 6.1.1.), a group administered nonword spelling test was not very reliable in grades 1 and 3, and may have generally low validity as a measure of phonological recoding. In the case of reading, a single factor account of its different aspects and sub­ components suggests a uniform processing strategy. It is likely to be decoding-based: observation made during testing showed some (more or less overt) sounding out and

183 blending in most children, especially in grades 1 and 2. That analytic strategy involved single letters or graphemes, but most often occurred in the form of reading syllable-by- syllable. Systematic sounding out and blending behaviour explains extremely slow reading speed, observed in the T* grade. On the other hand, words are processed quicker and much more accurately than nonwords which suggests strong ‘top-down’ lexical influences on decoding (for further discussion, see the following section). Although correlational and factorial analyses suggest a unitary nature of reading skills at this early stage, there are also some signs of developmental asynchrony between ‘the phonological’ and ‘the orthographic’. Children seem to improve their decoding accuracy before they go on to make large progress in the automaticity (speed) of decoding and recognition. Longitudinal data, however, are necessary to approach the problem of developmental trajectories more directly. Relatively low accuracy of nonword processing also suggest that the consistency of the Polish orthography must be rather low after all, since several years are required to master the system fully, even in case of children that (like my sample) showed above- average intelligence. I shall return to this issue in the following section.

6.1.3. Age-related changes in the structure of literacy skills.

The correlations suggesting a uniform reading strategy were computed across all three age groups. It is plausible, however, that reading strategies change over three-year period covered by the study. Substantial growth in the absolute level of performance (table 6-1) may be accompanied by a gradual diversification of reading strategies. The initial phase of acquisition may indeed be dominated by explicit, sequential alphabetic or syllabic decoding. This uniform strategy would be reflected strong relationship between different aspects of reading (words and nonword, accuracy and speed), as well as between reading and spelling. Once basic decoding skills are established (which would normally happen by the end of first grade) differentiation and specialisation of strategies should occur to fit different kinds of tasks (reading, spelling) and stimuli characteristics (familiar, unfamiliar). Empirically, that would correspond to a gradual decrease in the correlation between different reading and spelling, as well as word and nonword, tasks. This divergence could already be occurring during the period covered by the study. Table 6-4 presents selected reading and spelling correlations, separately for each grade.

184 Grade 1 Grade 2 Grade 3 word reading accuracy - nonword .833*** 693*** .789*** reading accuracy N=33 N=34 N=31 word reading time - nonword reading .921*** .906*** .776*** time N=35 N=33 N=34 word reading accuracy - word reading -.679*** -.516** -.517** time N=36 N=36 N=33 nonword reading accuracy - nonword -.689*** -.419* -.475** reading time N=34 N=33 N=33

word spelling - nonword spelling .403* .608** .730** N=29 N=27 N=16

Table 6-4. Intercorrelations between various indices of reading and spelling, presented separately for each grade.

Indeed, an age-related decrease in the strength of correlations is observed for most tasks. Its magnitude is usually small, however, and may reflect ceiling effects more than any definite change in the relationships between the tasks. Only the correlations between two spelling measures increase in strength between grade 1 and 3. It seems, therefore, that the overall structure of literacy subskills remains largely the same throughout the period covered by the study, with possible exception of spelling, which becomes more integrated. Such a description can be treated only as a working hypothesis, however, as it is based on apparent changes in the pattern of correlation between grades, without examining the significance of observed differences. More sensitive way of exploring age-related change in reading strategies may be provided by ANOVA analyses, which explore the influence of stimuli characteristics (their lexical status, frequency, orthographic consistency) on performance speed and accuracy at different age levels.

6.2. ANOVA ANALYSES.

The design of the reading and spelling tasks allowed me to systematically explore the role of three stimuli characteristics: lexicali/y (words versus nonwords), orthographic complexity (fully transparent strings built of ‘basic’ letters versus strings including diacritics, digraphs and morphologically-motivated correspondences) and spoher word frequency versus moderate; for more detailed characteristics see chapter 5). It was anticipated that the effects of those stimuli characteristics would change with age. If Polish 1 " graders do indeed apply a systematic sequential decoding strategy to all types of written material, their performance should be relatively unaffected by the lexical status or frequency of stimuli. With gradual accumulation of lexical knowledge, however, a distinction between recognition and decoding should emerge: words should

185 increase their “superiority” over nonwords, and familiar words over non-familiar ones. Statistieally, this would be reflected in signifieant interaetions of lexieality and frequency with grade. The importanee of orthographic complexity, on the other hand, should diminish with age. grade readers are first introduced to “basic” letter-sound correspondenees in the context of transparent words. Consequently, they may find it particularly difficult to decode morphologically motivated spellings, digraphs or “rare” letters. Such disadvantages should disappear by the 2"^* grade, however, as children become familiarised with the full alphabetie structure of Polish. This would be observable as complexity by grade interaetion. The effeet of complexity was expected to operate somewhat differently for spelling than for reading. As indicated previously (chapter 4) orthographic complexity in spelling implies not only the presence of ‘rare’ letters (diaeritics or digraphs), but also a /ack o f consistency, alternatives which cannot be resolved on the basis of recoding skills alone, but whieh require item-speeific knowledge or mastery of conditional, morpho-phonological rules. This problem does not oceur for reading (which is consistent) or for nonword spelling (where only phonologieal plausibility and not orthographie aecuracy is scored). Orthographieally accurate spelling of eomplex words should, then, be the hardest task, lagging behind reading aecuracy as well as phonological spelling accuraey (indexed by nonword spelling). In my spelling test, this would be reflected as an interaetion of lexieality with complexity. There was a methodological problem for all ANOVA analyses stemming from the fact that T‘ grade children read and spelt only half of the items that older ehildren dealt with (see ehapter 5). I decided, therefore, to earry out two sets of analyses: first, including all children (grades 1-3) yet restricted to a shorter list of stimuli read or spelled by all; seeond, based on the full set of stimuli, but restricted to 2"^* and 3'^* graders. Both analyses were expeeted to bring consistent results; the latter should be more sensitive to weak main effects and interactions due to higher possible range of scores. All analyses followed the same by-subjects repeated measures design, with a between-subjeets faetor of grade, and within-subject factors of lexieality, orthographic complexity, and frequency. It should be remembered that the frequency factor had a straightforward interpretation only in case of real words. For nonwords it was a dummy variable merely coding the ‘origin’ of a nonword item (i.e. whether derived from high or low frequency

186 word). All the effects of frequency should, therefore, occur for words only; i.e. frequency was expected to interact with lexieality.

6.2.1. Reading accuracy.

The first ANOVA analysis explored reading accuracy in grades 1-3, and was based on a set of stimuli read by all children (40 items, 5 in each condition). Descriptive statistics are presented in table 6-5 and illustrated in figure 6-2.

Grade 1 Grade 2 G rade 3 N=33 N=34 N=32 Mean SD Mean SD M ean SD lexieality complexity frequency words simple frequent 4.33 .82 4.97 .17 4.94 .y.f non-frequent 4.39 4.71 4.69 . y /

complex frequent 3.3() 4.62 .JTf 4.78 .42 non-frequent 3.48 /._V 4.68 4.91 nonwords simple frequent 3.09 /.Af 3.91 yyy 4.25 y.A? non-frequent 2.76 3.82 3.97

com plex frequent 2.33 /.jy 3.47 yjy 3.53 y./^y non-frequent 2.24 y j y 3.76 y /r f 4.40

Table 6-5. Accuracy of reading of diffemt types of stimuli (the short list). Maximum possible score = 5.

3rd grade

cr (U X cr g C 0) cr cr 5 cr 2 Q. 6- ^ 2 i 2 Q. 2 « 2 Ô. 2 0)X c E 2 E c E C CL c Q. o '(/) o o o o E o E c u C Ü 1 c| i o c o 5 Ü c c

Figure 6-2. Mean accuracy of reading different types of stimuli (the short list). Bars with diagonal pattern (marked nw) represent nonword scores.

187 Three significant main effects were obtained. The effect of lexieality (F[l,96]=202.558, p<.001) showed that the response accuracy was higher for words (89.8%) than for nonwords (69.3%). The effect of complexity (F[l,96]=46.977, p<.001) showed that orthographically simple items were easier than more complex ones (83.1% and 76%, respectively). A between-subject factor of grade (F[2,96]=26.289, p<.001) showed age- related improvement in overall accuracy (65.1%, 84.9% and 88.7% in V\ 2"^' and 3"'* grade, respectively). The main effects were qualified by a number of two-way interactions. Complexity interacted with grade (F[2,96]=18.158, p<.001) and frequency (F[l,96]=14.722, p<.001). Interaction with grade arose since only T* and 2"^* grade participants found orthographically complex items more difficult than the simple ones, whereas 3'^* graders performed equally well on both types (t[32]=7.368, p<.001 in grade one; t[33]=2.750, p<.05 in grade two; t[31]=0.705, p>.10 in grade three). Interaction with frequency showed that simple items were easier than complex ones only in the case of frequent words and nonwords derived from them (t[98]=7.470, p<.001), but not in the case of the non-frequent subset (t[98]=1.676, p>.05). Marginal lexieality by grade interaction also occurred (F[2,96]=4.080, p<.05), although paired samples t-test revealed that the advantage of words over nonwords was similar at all three age levels (t[32]=9.285; p<.001 in grade one; t[33]=7.710, p<.001 in grade two; t[31]=7.805, p<.001 in grade three). One three-way interaction of lexieality by frequency by grade was also significant (F[2,96]=4.981, p<.01). Two-way ANOVAs carried out separately for each grade revealed that frequency interacted with lexieality only in grade 3, where no difference was observed between high and low frequency words (t[32]=1.044, p>.10), but, unexpectedly, nonwords derived from low frequency words were read more accurately than those derived from high frequency words (83.8% and 76.5%, respectively, t[33]=2.973, p<.01). The analysis confirmed the major impact of the lexical and orthographic status of stimuli on reading accuracy. The accuracy advantage of words over nonwords was substantial (around 20%) and (contrary to my expectations) strongest in grade 1. Complex, conditional letter-sound mappings compromised the performance until grade 2, which was longer than expected. Interactions involving the frequency factor are more difficult to interpret. Stimulus frequency seems to modulate the impact of other factors, orthographic complexity in particular. The effects are paradoxical insofar as they also

188 involve nonwords, for which the frequency category only refers to the real words they were derived from. The results of the full reading test (10 items per condition, 80 items altogether), administered to 2"‘‘ and 3'** graders only, are presented in table 6-6. Grade 2 Grade 3 N=34 N=31 Mean SD Mean SD lexieality complexity frequency words simple frequent 9.88 .33 9.87 non-frequent 9.35 9.42 complex frequent 9.38 9.77 .y? non-frequent 9.09 9.48 nonwords simple frequent 7.94 8.29 /// non-frequent 7.26 7.55 y .z f complex frequent 5.97 6.81 y;%r non-frequent 6.82 8.16 y y ^

Table 6-6. Accuracy of reading different types of stimuli (the long list). Maximum possible score = 10

The ANOVA carried out on the longer reading list brought significant main effects of lexieality (F[l,63]=207.745, p<.001) and complexity (F[l,63]=32.846, p<.001. A between-subjeets effect of grade (F* vs 2"*^) fell short of significance (F[l,63]=3.600, p=.062). Words were read better than nonwords (95.3% and 73.5%, respectively), and orthographically easy items better than the complex ones (87% vs 81.9%). Complexity interacted with grade (F[l,63]=10.198, p<.005): orthographically simple items were easier in grade two (t[33]=5.796, p<.001), but the difference almost levelled off in grade three (t[30]=2.049, p=.049). Two-way interactions of lexieality with complexity (F=9.450, p<.005), lexieality with frequency (F=12.128, p<.005) and complexity with frequency (F=30.498, p<.001) were further qualified by three-way interaction of lexieality, complexity and frequency (F=18.216, p<.001). In order to understand the source of those interactions, separate two-way ANOVAs were carried out for words and nonwords. In the case of words, the main effects of frequency (F[l,68]=29.608, p<.001) and complexity (F[l,68]=9.884, p<.005) were observed. Frequent words were easier than non-frequent ones (97.2% vs 92.8%, respectively) and simple easier than complex (96.3% vs 93.7%). For nonwords, only the

189 main effect of complexity was significant (F[l,66]=24.225, p<.001) and interacted with frequency (F[l,66]=30.142, p<.001). Orthographic complexity played a significant role for the nonwords derived from high frequency words (80.9% and 63% for simple and complex items, respectively, t[66]=7.261, p<.001), but not for the nonwords matched on low frequency words (74.2% vs 74.8%, t[66]==.248, p>.50). Those results partially confirmed the previous analysis. There was a consistent 20% difference between word and nonword reading accuracy. The negative effect of orthographic complexity was (mostly) overcome by grade 3. Additionally, a small effect of frequency was detected for words: it was the same at both age levels (no frequency by grade interaction). As overall accuracy of performance already neared the ceiling in grade two, no significant age-related improvement was observed.

6.2.2. Reading time.

Analysis of accuracy data was largely limited by ceiling effects. Reading time scores, however, while substantially co-varying with accuracy (see section 6.1.2.), showed better spread. Consequently, they should allow more sensitive analysis of reading performance. Descriptive statistics for the shorter reading test are presented in table 6-7 and figure 6-3.

Grade 1 Grade 2 Grade 3 N=35 N=34 N=35 Mean SD Mean SD Mean SD lexieality complexity frequency words simple frequent 5.13 1.39 .91 .y?

non-frequent 5.14 1.89 1.24 .<$y

complex frequent 6.01 1.90 1.15 ./ y

non-frequent 7.00 1.85 y.4(/ 1.21 .S3 nonwords simple frequent 5.49 1.92 y.y/ 1.73 . 66

non-frequent 6.05 2.38 y.44/" 1.99 .7^

complex frequent 6.41 2.72 y^(^ 2.05

non-frequent 7.31 2.46 y y / 2.18 . y /

Table 6-7. Reading times (in seconds per item) of different types of stimuli (the short list).

190 7 3 7

1 st grad e

2 8 ft 4 !

Figure 6-3. Mean reading times (secs/item) for different types of stimuli (the short list). Bars with diagonal pattern (marked nw) represent nonword times.

ANOVA based on log-transformed time scores from the shorter list read by all participants showed significant main effects of all factors; lexieality (F[l,101]=189.158, p<.001), complexity (F[l,101]=165.739, p<.001), frequency (F[l,101]=66.019, p<.001), and grade (F[2,101]=55.405, p<.001). Words were read faster than nonwords (average 2.90 and 3.56 secs, per item, respectively); orthographically simple stimuli faster than the complex ones (2.93 vs 3.52 secs.); frequent words and nonwords derived from them faster than matched non-frequent stimuli (3.07 vs 3.39 secs, respectively). Also, overall the speed of reading improved dramatically with age (6.07, 2.07 and 1.56 secs, per item in grade 1, 2, and 3, respectively). Those effects were qualified by a number of interactions. Lexieality interacted with grade (F[2,101]=18.057, p<.001) as the relative difference between word and nonword reading time increased with age (t[34]=3.279, p<.005 in grade 1, t[33]=7.683, p<.001 in grade 2; t[34]=l3.683, p<.001 in grade 3). Complexity interacted with grade (F[2,101]=5.978, p<.005) and with frequency (F[l,101]=20.207, p<.001), which was further qualified by a three-way interaction between grade, complexity and frequency (F[2,101]=16.115, p<.001). Two-way ANOVAs were carried out separately for each grade in order to explore this pattern. They revealed significant (p<.005) main effects of complexity and frequency at each grade level; yet the effect of complexity decreased steadily with age (F[l,34]=91.799 in grade 1; F[l,33]=67.186 in grade 2; F[l,34]=31.868 in grade 3), while the effect of frequency showed the opposite, increasing trend. Complexity and frequency interacted only in grades two and three. In

191 both grades, the speed advantage of simple over complex stimuli occurred only for the frequent items (t[33]=10.518 in grade two; t[34]=5.480 in grade three, p<.001), but not for the non-frequent ones (t[34]=.081 in grade two; t[34]-1.633 in grade three, p>.10). The outcome is largely, yet not fully, consistent with the results of earlier accuracy analyses. In both cases, lexieality and complexity emerged as the strongest within-subjects constrains of performance. Speed advantage of words over nonwords grew with age, as originally expected: this may reflect the emerging distinction between recognition and decoding. Interestingly, however, the accuracy advantage of words over nonwords showed an opposite trend, decreasing with age. The deleterious effect of complexity of letter-sound mapping decreased with age for speed as well as accuracy, though the impact on speed was more persistent (until grade three and possibly beyond) than on accuracy (only until grade two). For speed and accuracy alike, complexity was modulated by frequency of items, but not their lexical status: it occurred for frequent real words as well as nonwords derived from them. Descriptive statistics for the full reading test are given in table 6-8.

Grade 2 Grade 3 N=33 N=34 Mean SD Mean SD lexieality complexity frequency words simple frequent 1.37 .92 .91 .38 non-frequent 1.91 1.38 1.23 .54 complex frequent 1.77 1.28 1.09 .54 non-frequent 2.12 1.42 1.34 .61 nonwords simple frequent 2.07 1.22 1.84 .67 non-frequent 2.37 1.25 2.00 .70 complex frequent 2.82 1.41 2.29 .83 non-frequent 2.70 1.42 2.27 .78

Table 6-8. Reading times (in seconds per item) of different types of stimuli (the long list).

ANOVA on log-transformed time scores of the full test (2"^* and 3'^* graders only) replicated the main effects of lexieality (F[l,65]=263.891, p<.001), complexity (F=193.402, p<.001), frequency (F=l 15.509, p<.001) and grade (F=4.586, p<.05). Words were read more quickly than nonwords (1.47 vs 2.3 seconds per item.

192 respectively), orthographically simple stimuli more quickly than the complex ones (1.71 vs. 2.05 secs/item), and frequent stimuli quicker than non-frequent ones (1.77 vs. 1.99 secs/item). Average reading speed grew from grade two (2.14 secs/item) to grade three (1.62 secs/item). The effect of lexieality was qualified by frequency, grade and complexity. Lexieality by frequency interaction (F=50.730, p<.001) reflected the fact that the frequency effect was large in case of words (1.28 and 1.65 secs for high and low frequency words, respectively, t[69]=l 0.604, p<.001) but small for nonwords (2.23 and 2.31 secs for nonwords derived from high and low frequency words, respectively, t[67]=2.653, p<.05). Lexieality by grade interaction (F=l 1.219, p<.005) arose since the relative advantage of words over nonwords in terms of reading time was greater in grade three (1.14 vs 2.10 secs/per word and nonword, respectively, t[33]=14.796, p<.001) than in grade two (1.79 vs 2.49 secs/item, t[32]=8.673,p<.001). Finally, the marginal interaction between lexieality and complexity (F=5.160, p<.05) reflected the effect of complexity being somewhat stronger for nonwords (2.06 vs. 2.51 secs per simple and complex nonword, respectively, t[67]=l 1.285, p<.001) than for words (1.35 vs. 1.57 secs per simple and complex words, respectively, t[69]=8.291, p<.001). Interaction also occurred between complexity and frequency (F=25.113, p<.001). The facilitatory effect of simple orthographic structure was somewhat stronger for frequent stimuli (1.53 and 1.98 secs per simple and complex items, respectively, t[67]=l2.902, p<.001) than non-frequent ones (1.86 vs 2.08 secs, t[68]=7.226, p<.001). The analysis confirmed a large advantage of words over nonwords, which increased with age. The inhibitory effect of complex letter-sound mapping was also robust and, in this analysis, did not diminish with age. The facilitatory effect of frequency was also apparent and occurred mainly for words, although it was also detectable in case of nonwords.

193 6.2.3. Spelling accuracy

The results of the shorter spelling test (40 items) administered to all children (except for the first term 1" graders) are presented in table 6-9 and figure 6-4.

Grade 1 Grade 2 G rade 3 N=29 N=27 N=16 Mean SD Mean SD M ean SD lexieality complexity frequency words simple frequent 4.69 . 66 4.74 5.00

non-frequent 4.66 .66 4.74 .46 4.81 .64 complex frequent 2.38 3.26 y.vLf 4.25 .7 7

non-frequent 2.41 /.4 (f 3.52 4.19 nonwords sim ple frequent 3.62 3.89 /.Z 7 4.31

non-frequent 3.72 3.22 4.50

com plex frequent 3.07 3.1() / . / ^ 4.00 .^ 7

non-frequent 3.59 2.81 / ./ c f 4.06 .96

Table 6-9. Accuracy of spelling different types of stimuli (the short list). Maximum possible score = 5.

3rd grade

0> <1> g Q. 1Q. $ 1Q. E i c E c c E 1 1 « o « II c 11 2 8

Figure 6-4. Mean spelling accuracy of different types of stimuli (the short list)

The ANOVA which was carried out on the spelling test that was administered to all participants (40 items) showed a main within-subjects effect of complexity

194 (F[l,69]=l 18.074, p<.001) and lexieality (F[l,69]=16.630, p<.001), as well as a between-subjeets effeet of grade (F[2,69]=l 1.782, p<.001). The easy items were spelled mueh more aeeurately (86.5%) than the eomplex ones (67.9%). Words were slightly easier than nonwords (81.1% and 73.3%, respeetively). Overall aeeuraey also improved with age (70.3%, 73.4% and 87.8% in V\ 2""* and 3'^* grade, respeetively). Both signifieant within-subjeet effeets interaeted with grade (lexieality: F[2,69]=7.954, p<.005; eomplexity: F[2,69]=6.446, p>.005). An interaetion also oeeurred between lexieality and eomplexity (F[l,69]=50.650, p<.001). These were further qualified by a three-way interaetion between lexieality, eomplexity and grade (F[2,69]=l 1.860, p<.001), as well as lexieality, frequeney and grade (F[2,69]=5.197, p<.01). In order to explore this pattern further, separate three way ANOVAs were earried out at eaeh grade level. In r ' grade group only one main effeet of eomplexity was observed (F[l,28]=81.619, p<.001), whieh interaeted with lexieality (F[l,28]=81.041, p<.001). In the ease of the simple stimuli, aeeuraey of word spelling (i.e. their orthographie eorreetness) was higher than aeeuraey of nonword spelling (i.e. their phonologieal plausibility) (93.4% vs. 73.4%; t[28]=6.075; p<.001). The reverse, however, was the ease with the eomplex subset, where orthographie aeeuraey of words was lower than phonologieal aeeuraey of nonwords (47.9% vs. 66.6%; t[28]=4.896, p<.001). In grade two, both main effeets were signifieant (eomplexity: F[l,26]=69.938, p<.001; lexieality: F[l,26]=18.533, p<.001) and they interaeted (F[l,26]=9.755, p<.005). Simple words were again spelled better than their matehed nonwords (94.8% vs. 71.1%; t[26]=5.588, p<.001), while there was no differenee between eomplex words and nonwords (67.8% vs. 60%, t[26]=1.668, p>.10). Additionally, lexieality marginally interaeted with frequeney (F[l,26]=5.420, p<.05). The effeet of frequeney oeeurred, paradoxieally, for nonwords (70.7% vs 60.4% for frequent and non-frequent ones, respeetively; t[26]=2.152, p<.05) but not for words (80% vs 82.6%, t[26]=.851, p>.10). In grade three, only weak main effeets of lexieality (F[ 1,15]=12.692, p<.005) and eomplexity (F[l,15]=8.618, p<.05) were observed. I hypothesised that the ehildren would find it partieularly diffieult to learn orthographieally legal spellings of eomplex words, sinee they are not eonsistent. This seleetive diffieulty was eonfirmed, in grade one and two, with a lexieality by eomplexity interaetion. T‘ grade ehildren aetually found it harder to produee an orthographieally eorreet spelling of a familiar non-transparent word, than a phonologieally plausible spelling of a matehed nonword. This seleetive diffieulty is gradually overeome with age,

195 however, so that, in grade 3, simple and complex words alike gained advantage over their matched nonwords. The effect of orthographic complexity, although strongest in case of words, also occurred for nonwords. This was expected: while the problem of inconsistency was limited to the spelling of words only, the problem of complex letters (digraphs and diacritics) affected complex words and nonwords alike, making them harder than the simple stimuli. The results of the full spelling test (80 items) administered to 2"'^ and 3'"^ grade children only, are presented in table 6-10.

Grade 2 Grade 3 N=27 N=16 Mean SD Mean SD lexieality complexity frequency words simple frequent 9.11 9.69 non-frequent 8.89 9.44 .2 / complex frequent 6.59 8.69 non-frequent 6.26 2 7 / 7.69 2 / 2 nonwords simple frequent 6.93 8.63 / ^ non-frequent 6.07 2 / 2 8.44 / ^ complex frequent 5.81 2 ^ ^ 7.50 non-frequent 4.78 y.2f 6.94 y< ^

Table 6-10. Accuracy of spelling different types of stimuli. Max. possible score=10.

An ANOVA carried out on spelling accuracy scores of the full test found all the main effects to be significant. The effect of complexity (F[ 1,41]=107.205, p<.001) reflected greater accuracy on simple items (84%) than the complex ones (67.8%). A lexieality effect (F[l,41]=60.766, p<.001) described the advantage of words (82.9%) over nonwords (68.9%). A frequency effect (F[l,41]=10.810, p<.005) reflected better spelling of frequent stimuli (78.7%) than non-frequent ones (73.1%). Finally, a between-subjeets effect of grade (F[l,41]=17.452, p<.000) reflected overall greater accuracy of spelling in grade three (83.8%) than in grade two (68.1%). Lexieality interacted marginally with complexity (F[l,41]=5.537, p<.05) and grade (F=5.093, p<.05). Both interactions were qualified by a three-way interaction

196 between lexieality, complexity and grade (F=4.613, p<.05). Separate two-way ANOVAs carried out for each grade showed that, in grade two, significant effects of complexity (F[l,26]=101.541, p<.001), lexieality (F=49.116, p<.001) and an interaction between them (F=l 0.868, p<.005) could all be observed. The advantage of words over nonwords was stronger in case of simple stimuli (90% vs 65% t[26]=8.153, p<.001) than the complex ones (64.3% vs 53%, t[26]=3.176, p<.005). In grade three, only main effects of lexieality (F[l,15]=36.226, p<.001) and complexity (F[l,15]=27.987, p<.001) occurred, with words being spelled more accurately than nonwords (88.8% vs 78.8%) and simple items more accurately than the complex ones (90.5% vs 77%). This outcome essentially replicated the pattern obtained in the previous analysis. Children performed generally worse on orthographically complex items and on nonwords. Orthographic complexity had significantly stronger impact on real words than on nonwords in grade two, yet this difference disappeared in grade three. However, a general facilitatory effect of frequency, not found with the shorter spelling list, was also observed. As was the case with most reading analyses reported above, this effect extended to words as well as nonwords.

6.2.4. Summary of ANOVA analyses

The results of ANOVA analyses were only partially consistent with my initial predictions. The most robust constraint of performance, observed in all analyses, were the lexical status of the stimuli and their orthographic complexity. The unexpectedly large superiority of words over nonwords needs to be interpreted in the light of earlier findings, which showed that both types of stimuli were approached in similar way. There was a strong correlation between word and nonword reading, and overt signs of sounding out and blending were observed in both tasks. Participants, then, seem to apply a systematic sequential decoding strategy to all types of written stimuli, and even imperfect decoding skills are usually sufficient to identify a word. This pattern can be accommodated by a model of reading which suggests strong interaction between rudimentary sequential decoding and existing lexical knowledge. Decoding seems to provide only partial phonological cues, which, however, activate phonological word representations, one of which is eventually selected. An age-related increase in superiority of words over nonwords was observed for reading time and spelling accuracy (the corresponding decrease in word superiority for

197 reading accuracy may be an artefact of ceiling effects). This effect was expected, reflecting the emergence of orthographic word representations, and thus an increase in the role of retrieval, and a decrease in the role of assembly, in processing real words. It must be remembered that my study did not cover the first few months of reading acquisition (in pre-school grade 0), so that even the least experienced readers tested had had an opportunity to acquire some orthographic word representations, which could have contributed to the superiority of words over nonwords observed in grade one. Reading in grade zero is likely to rely on a more pure alphabetic decoding strategy, with reduced facilitation from lexical knowledge (thus small word-nonword difference). The existence of a limited logographic lexicon cannot be ruled out, either, given the fact that the teaching of reading in grade zero, although predominantly code-oriented, also incorporates some elements of global methods (see chapter 4). The effect of orthographic complexity was very strong in grade one, but gradually diminished with age. This was expected to occur, primarily as a function of the curriculum: more complex alphabetic knowledge (alternative grapheme-phoneme mappings, digraphs, diacritics, etc.) is introduced later in T* grade. However, the deleterious effect of orthographic complexity lasted longer than expected, until grade two in reading accuracy, and possibly beyond grade three in spelling accuracy and reading speed. This was the case even though the complex orthographic structures used in the tests were not in any way rare or atypical: they represented highly productive orthographic rules. It suggests that the orthographic system of Polish is generally more complex and difficult to master than initially suspected. It must be noted that the complexity effect reported here is only partially equivalent to the consistency effect that is usually discussed in the word naming literature. Reading in Polish is consistent (every grapheme has only one legal pronunciation, given the context in which it is embedded) whereas spelling is not; yet the magnitude of the complexity effect was broadly similar for reading and spelling. Also, the scoring procedure of the nonword spelling task effectively removed spelling inconsistency (any phonologieally accurate response was accepted, regardless of its orthographic plausibility), yet the effect of complexity remained, albeit markedly reduced (strong complexity by lexieality interaction). The effect of complexity is, then, only partially accounted for by consistency. It seems that the alternative letter-sound mappings are problematic even if the tasks allows for either of the alternate mapping options to be selected. The complexity effect is also partially generated by digraphs and diacriticed letters. The latter are particularly problematic (see error analyses below),

198 possibly because they compound visual and phonological similarity. The effect of frequency turned out to be weak and not consistent across different analyses. It did not show clear age-related growth, as expected. This weak effect may be partially explained by the low validity of the only available frequency counts. The frequency of productive vocabulary of pre-school children (Zgolkowa & Bulczyhska, 1980) is not equivalent to word frequency in written materials used by T’ - graders. Even more importantly, the frequency range was rather limited: as no word was produced with a frequency smaller than 9 in 100,000; all must have been rather familiar. High familiarity may explain unexpectedly good spelling accuracy observed even for orthographically ‘tricky’ words in grade three. Sampling words from the higher range of written frequencies would probably demonstrate more clearly that orthographic spelling skills lag behind other components of literacy. In some analyses, we also observed a facilitatory effect of frequency on nonwords. This is surprising since nonwords bore little visual resemblance to their real word counterparts (see the task description in chapter 5). Yet, they were constructed from the same letter material, and often preserved syllables, onsets or rhymes of the original words, combining them in new ways. It suggests that the frequency effect may reflect early orthographic sensitivity to frequently encountered letter strings, which operates not only at the level of whole words but also sublexical units. This conclusion must be treated cautiously, however, as the observed effect was weak and inconsistent, and one analysis brought the opposite outcome (nonwords derived from /ow frequency words were read more accurately, see section 6.2.1.).

6.3. ERROR ANALYSES.

Error analyses were applied as a complementary way of exploring processing strategies. In reading, I expected to observe mostly nonword errors, typically representing only minor divergences from the target (single phoneme deletions, additions or replacements) rather than gross distortions or reading refusals. This should happen if children used a systematic alphabetic decoding strategy from the start and typically mastered it rather quickly. Growth in reading experience should correspond to gradual lexicalisation of reading strategies, leading to an increase in the proportion of lexical errors (word substitutions) in older grades. Such lexicalisation should remain limited only to real word reading tasks. Nonword lists should still be decoded sublexically, though with increased accuracy.

199 In spelling, early mastery of basic recoding skills should also be evidenced by errors that are phonologically close to the target. The majority of errors should violate only the orthographic, and not the phonological structure of target stimuli. The category of orthographic errors would include, first of all, pseudohomophone spellings of real words, most of which would be régularisations (i.e. spellings based on basic, one-to-one sound-letter correspondences, which disregard morphological rules). It would also include using letter combinations that are orthographically ‘illegal’ (i.e. violating graphotactic constraints of the system), whilst remaining faithful to the target phonology. This latter error type (which can occur in words and nonwords alike) is a particularly sensitive indicator of mastery of more generic orthographic knowledge. Combining letters in an illegal (or atypical) way should, therefore, drop rapidly after grade one, when growing reading and writing experience should result in increased sensitivity to graphotactic and graphostatistic constraints of the Polish orthography.

6.3.1. Reading errors.

The following categories of reading errors were identified:

1. Reading refusals - a child omits the word, or replies “don’t know” [ref]. 2. Single nonword errors - a single phoneme is deleted, added or substituted, resulting in a nonword response [nw-sing]. 3. Multiple nonword errors - more than one phoneme of the target item is changed, resulting in a nonword response. This often results in a gross target distortion, where the syllabic ‘skeleton’ of the target is changed [nw-mult]. 4. Single lexical substitution - a real word is produced, which differs by only one phoneme (deletion, addition or substitution) from the target [lex-sing]. 5. Multiple lexical substitution - a word is produced, different by more than one phoneme from the target [lex-mult]. 6. Unsuccessful repetition - fragments of the target item are blended and repeated, but no full synthesis is reached (cg.jpsj/... psycho... psycho... hog}) [rept]. 7. Failure of blending - separate letters or phonemes are uttered, and no full blending occurs (e.g. ca... t\ s... c... /) [blend].

Relative frequencies of different types of word reading errors (expressed as a percentage of overall number of errors made at a particular grade) are presented in figure 6.5.

200 60.00% ^

50.00% H list grade (N=153) □2nd grade (N=87) 40.00% - □3rd grade (N=51)

30.00% -

20 .00% -

10.00% -

0.00% I ï k nw-sing nw-mult lex-sing lex-mult rept blend

Figure 6-5. Relative frequencies of different types of word errors in grades 1-3. Ns denote the overall number of errors at each grade level.

Chi-square analysis of error type by grade was significant (chi-square[12]=112.188; p<.001) suggesting that the relative frequencies of error types indeed changed with age. Separate chi-square analyses carried out for each error type (i.e. its frequency in relation to overall number of errors at every grade level) found a significant decrease in the proportion of reading refusals (p<.001) and an increase in the frequency of unsuccessful repetitions (p<.001), single lexical substitutions (p<.005) and multiple lexical substitutions (p<.005), with other differences being non-significant. Refusals were a dominant error category in the f grade (nearly half of all errors), yet practically ceased to occur later on. This must be, largely, an artefact of the instruction (only f graders were told they can refuse to read the words they find too difficult). However, reading refusals are also a sign of grossly inadequate decoding skills (Frith & Wimmer, 1994). Here this inadequacy probably stemmed from limited letter-sound knowledge. Spontaneous comments and requests made by some participants (“I don’t know this letter”; “What is this letter?”) showed that they refused to read words containing letters which had not yet been ‘introduced’ to them. A letter- centred teaching approach seems, then, reflected in a way children themselves approach the reading task. Those comments also imply a systematic decoding strategy, where children attend to individual letters in order to identify the word. An increase in the proportion of lexical substitutions (both similar and dissimilar to the target) is consistent with the hypothesis of progressive lexicalisation of reading

201 strategies (gradual build-up of orthographic representations of words and their activation during reading). Lexical substitutions were the most frequent error category after grade

1. The growth in the relative frequency of unsuccessful repetition errors was unexpected, since the rapid growth of reading speed and fluency (see section 6.1.) should reduce repetitions and hesitations. They may, however, reflect only minor imperfections of word decoding and accuracy monitoring (repeated attempts at word analysis, self-corrections). Error data for the non word reading test are presented in figure 6.6. The main difference in comparison with word reading was the frequency of lexical errors. Whereas word reading tended to elicit more lexical substitutions, nonword reading led to more nonword errors; the tendency discernible already in grade 1. This indicates that children adjusted their reading strategies in line with the instruction (which primed them with respect to the lexical status of stimuli) and the nature of stimuli. This strategic flexibility is consistent with the strong lexicality effect observed in the ANOVA analyses reported previously. Relative frequency of error types again changed with age, as confirmed by chi- square analysis (chi-square[12]=290.024, p<.001). A significant decrease was observed in the proportion of reading refusals (p<.001) and multiple nonword errors (p<.05), while there was an increase in the proportion of single nonword and single lexical substitution, as well as repetition errors (all three significant at p<.001). This pattern is consistent with the improvement of alphabetic decoding skills: as children get better at decoding, errors become minimal deviations from the target (two ‘single’ categories), or attempts at self-correction (unsuccessful repetition category). The same improvement is also evidenced by an inerease in overall decoding accuracy (see section 6.1.1. and 6.2).

202 60.00% ^

50.00% . list grade (N=318) □2nd grade (N=408) 40.00% . □3rd grade (N=310)

30.00% .

20.00% -

10.00% .

0 .00% Jj MH nw-smg nw-mult lex-sing lex-mult rept blend

Fig.6-6. Relative frequency of different types of nonword reading errors in grades 1-3.

6.3.1.1. Errors c/s t/ie o f o/Z/iosrap/i/c conip/ex/ty.

In chapter 3, I reviewed cross-linguistic evidence showing that reading and spelling errors are indueed most easily wherever letter-sound mappings diverge from transpareney, regularity and consistency. The pattern of errors appeared to vary considerably between languages, since eaeh orthography has its own partieular islets of complexity. Those differenees are often refleeted in the proportion of vowel and consonant errors. In Polish, letter-sound mappings are near-transparent for vowels (with the exeeption of nasal vowels); but not for consonants, where alternative correspondences exist, contingent on morphologieal properties of words, graphotactic constraints, etc. As a consequence, more consonant than vowel errors may be expected. To test this hypothesis, I searched the whole corpus of reading errors for all instances of s/ng/e grop/ie/?ie si/bst/ti/Eo/i (i.e. providing a wrong sound value of one grapheme; the target and the error making a minimal pair) and classified them as either vowel or consonant replacement. Substitutions of single letters or graphemes constituted only a fraction of all errors. This specific category was chosen, however, since it allowed me to identify directly what graphemes are most vulnerable to misidentification. Other types of errors (deletions, additions, gross word distortions) are ambiguous in this respect. In the case of word reading, very few single substitutions occurred. Nine of them involved vowels, and 18 consonants. A trend in the predicted direction was, therefore.

203 observed. Numerous replacements occurred in nonword reading: 150 vowel, and 139 consonant graphemes were misidentifled. Here, the pattern was reversed: vowel graphemes turned out to be more vulnerable, even more so when the opportunities for making vowel errors were considered (vowel graphemes triggered more than half of the errors, although they constituted less than half of all graphemes). A large proportion (more than one third) of all vowel errors involved diacritics. Children produced pronunciation corresponding to a letter differing only by a diacritic (<6> misread as , as <ç>, etc.). One particular error of this type ( read as ) occurred 32 times. The analysis confirms that diacritics create a special problem in reading Polish, particularly in the context of nasal vowel graphemes <^> and <ç>. The particular vulnerability of nasal vowels was expected: as I indicated previously (chapter 4) they are a clear instance of overlap between phonetic and orthographic complexity. However, the proportion of vowel mis-readings remained high, even after discounting the nasal vowels, especially given the lower overall frequency of vowels. Orthographic representation of the vowel system seems, then, no more robust than the representation of the consonant system. This conclusion, however, needs to be corroborated with an error corpus based on a larger set of stimuli, which would better secure against skewing the results by some idiosyncratic patterns (such as , in this case).

6.3.2. Spelling errors

In case of spelling, the following categories of errors could be identified: 1. No response - nothing is written down. This category is as analogous to refusals in reading. 2. Single nonword errors - a single grapheme of the target is deleted, added or substituted, resulting in a nonword response [nw-sing]. 3. Multiple nonword errors - more than one grapheme is changed, resulting in a nonword response (which is often a gross distortion of the target) [nw-mult]. 4. Single lexical substitutions - a word is produced, differing by only one grapheme from the target [lex-sing]. 5. Multiple lexical substitutions - a word is produced that is different by more than one grapheme from the target [lex-mult]. 6. Orthographic errors - a pseudohomophone is produced (i.e. a spelling that is orthographically incorrect, but phonologically accurate). This error type was

204 assigned to real words only, as nonword spellings were assessed only for their phonological, not orthographic, plausibility (however, see a separate analysis of illegal letter combinations in section 6.3.2.1. below). Whereas other error types were mutually exclusive, orthographic errors could co-occur with other error categories (for example, a child could substitute a target word with a different one, and misspell the latter orthographically). However, only ‘pure’ pseudohomophone errors are classified here [orto].

Relative frequencies of different error types are presented in figure 6-7.

80.00% -, ■ 1st grade (N=171) 70.00% . □2nd grade (N=252) □3rd grade (N=73) 60.00% .

50.00% .

40.00% .

30.00% -

20.00% .

10.00% .

0 .00% ._^£1 no response nw-sing nw-mult lex-sing lex-mult orto

Figure 6-7. Relative frequencies of different types of word spelling errors in grades 1-3.

Purely orthographic misspellings (pseudohomophones of target words) were by far the most frequent error category, accounting for approximately half of errors in each grade. The frequency of orthographic problems was in fact even higher, considering that erroneous responses classified under other types (nonwond and lexical errors) were sometimes also orthographically unacceptable. Among written responses that distorted target phonology single grapheme misspellings resulting in a nonword response were by far most frequent. In contrast to word reading, relatively few lexical substitutions occurred. This suggests that the auditory input was usually identified correctly, and problems occurred mostly on the output side, in assembling and executing the written response. Since the target phonology was usually preserved (orthographic errors) or altered only minimally (deletions, additions or substitutions of a single grapheme), basic grapheme-to-phoneme conversion skills also seem to have been mastered. Most of the minor alterations

205 observed could be divided into very few distinct categories. Substitutions usually involved phonologically and/or visually similar graphemes (e.g. -, -). Some substitutions probably reflected peripheral problems with cursive writing (omission of transposition of sub-graphemic elements, e.g. realising as , <1> as , omission of diacritics). Deletions often involved dropping of the final letter. Additions frequently took a form peculiar to the Polish orthography: grapheme was inserted after soft (palatal) consonant. Although superficially being a phonological distortion, this is likely to reflect a lack of orthographic knowledge, specifically knowledge of conditional rules for writing palatal consonants (palatality is marked with a slanted diacritic < > or letter , depending on phonological context, see section 4.2.2.2). The relative frequency of different type of errors changed with age, as confirmed by chi-square analysis (chi-square[10]=24.989; p<.005). Significant differences were observed with respect to orthographic errors (p<.001), no responses (p<.05) and multiple nonword errors (p<.05). Grade 2 children produced the smallest proportion of orthographic errors, and the highest proportion of no responses and multiple nonword errors. This suggests 2"‘^ graders experienced more problems with basic phoneme-to- grapheme recoding that the other two groups. The error type data for the nonword spelling task (responses analysed only according to their phonological, not orthographic plausibility) are presented in figure 6-

80.00% n

70.00% .

60.00% - ■ 1st grade (N=177) □2nd grade (N=423) 50.00% . □3rd grade (N=142)

40.00% .

30.00% -

20 .00% .

10.00 % -

0.00% no response nw-sing nw-mult lex-sing lex-mult

Figure 6-8. Relative frequencies of different types of nonword spelling errors in grades 1-3.

206 The pattern is very similar to that obtained with real word stimuli. The vast majority of errors were nonword responses, well over half of which were very close to the target (single errors). This, again, suggest a grasp of basic grapheme-to-phoneme translation. The same types of deletions, additions and substitutions were often observed in the word and nonword error corpus, suggesting common mechanisms. However, it is likely that a higher proportion of nonword than word errors (both single and multiple) arose due to mishearing of the target stimuli (the possibility we already discussed in section 6.1.1.). Chi-square analysis of error type by grade was of borderline significance (chi- square[8]=l5.202; p=.055), thus providing no strong evidence for the age-related change in the overall error pattern. Analyses of individual error types found significant change for multiple nonword errors (p<.01) and single nonword errors (p<.05). graders produced a higher proportion of the multiple errors than the other two groups (as they also did in the real word spelling) and the lowest proportion of the single type errors. This pattern suggests that graders experience the highest degree of recoding difficulties, which is consistent with the fact that they showed lowest overall accuracy of nonword spelling (see section 6.1.1.). It is difficult to explain why recoding ability in spelling did not show linear increase with age. This may be an artefact of the group testing procedure.

6.3.2.1. Sensiiiviiy to orthographic conventions.

In both spelling tasks, children occasionally used letter combinations that were orthographically illegal (they violated the graphotactic constraints of the system) or atypical (i.e. rarely used to express a given combination of sounds). Such errors seem to indicate lack of specifically orthographic skills: their disappearance marks the internalisation of positional and statistical constraints of the orthographic system. Table 6-11 presents the frequency of such errors (as the percentage of all spellings produced). r* grade 2"** grade 3*^** grade words illegal responses 4.5% 2.4% 1.6% illegal and atypical 8.3% 2.9% 2% responses nonwords illegal responses 5.9% 2.4% 3.4% illegal and atypical 11.4% 4.9% 4.7% responses Table 6-11. The frequency of orthographically illegal and implausible renditions of the target stimuli.

207 The frequency of orthographically illegal and implausible responses decreased with age, most rapidly between grades 1 and 2. The trend is even more apparent when one considers such responses as the proportion of the overall number of errors (rather than a proportion of all spellings produced). In the word spelling task, orthographically illegal responses constituted 27.1%, 11.5% and 6.1% of all errors in grades one, two and three, respectively. For the illegal and atypical responses combined, the figures are 50%, 14% and 7.9%, respectively. It is notable, however, that although the incidence of such responses and their share in the overall pool of errors decreased, they were not completely eliminated even in grade three. Apparently, some children need more than three years to fully internalise the orthographic conventions of Polish. Illegal and atypical spellings were elicited more frequently by nonword stimuli. It seems that nonword spelling taps into a more generic form of orthographic knowledge (sensitivity to grapho-tactic and grapho-statistic constraints of the system), whereas word spelling is a better measure of ‘crystallised’, item-specific orthographic knowledge.

6. 4. SUMMARY AND CONCLUSIONS.

The analyses presented above allow me to describe the guant/iat/ve aspects of literacy acquisition (typical accuracy and speed of reading and spelling at different grade levels; rate of improvement between the grades), and also explore mechanisms o flearning and representing knowledge, as well as cognitive strategies applied by apprentice readers and spellers. Changes in performance accuracy, speed, and error quality suggest that the developmental period covered by the study may be divided into two broad phases. The first - elementa/y alphabetic - corresponds to the acquisition of rudimentary recoding skills. It is characterised by a very fast rate of learning, but still low accuracy and lack of true independence in reading and spelling attempts (reading refusals). This phase corresponds to the early period of the curriculum, when children are gradually “introduced” to all the letters of the Polish alphabet and taught the “mechanics” of reading; it extends approximately till the end of grade 1. The second phase - advanced alphabetic and orthographic - is characterised by elaboration, consolidation and automatization of the recoding skills and the build-up of orthographic knowledge (both word-specific and system-general). It extends until grade three and beyond. In reading, greatest gains occur with respect to complex, conditional sound-symbol mappings

208 (which were not assimilated at the previous phase) and also processing speed in general. Big improvements occur in spelling, both quantitatively and qualitatively, as children start to respect orthographic constraints and regularities. This two-phase framework is chiefly a descriptive, not explanatory, device. “Phases” refer primarily to overt reading behaviour (rather than to underlying mechanisms of learning and representing knowledge); they denote directly observable improvements that are most apparent during a given period of time. Transition between phases is gradual and quantitative, rather than qualitative. In particular, the framework should not be taken to imply that the orthographic (knowledge, skills, mode of processing, etc.) emerges only after the decoding skills have been fully mastered. Although there was some evidence that the orthographic skills (as measured by reading speed and the quality of errors) developedafter basic decoding ability had been established, there was also strong evidence for inseparability and parallel development of the two: word and non word skills correlated strongly at all times (at least in reading) and the finer aspects of decoding were only mastered at the later phase, together with sensitivity to orthographic constraints. Regarding cognitive strategies of processing print, explicit and sequential decoding played a central role. Children’s overt reading behaviour (sounding out, blending), reading errors (typically failed attempts to apply the code) or refusals (“I don’t know this letter”) showed that children generally approached reading as a decoding and not as a recognition task. Strong correlation between word and nonword reading also suggested a unitary decoding strategy. In the beginning of grade 1, this decoding was alphabetic, i.e. it operated on individual grapheme-phoneme correspondences. However, overt reading behaviour would suggest that later on decoding moved onto the level of syllables. Other authors (e.g. Krasowicz-Kupis, 1999) also raised this possibility and presented some evidence for the role of syllable-level phonological awareness in learning to read Polish. Syllable-level decoding seems a viable option for the Polish language, given the high proportion of polysyllabic words even in early acquired and highly familiar vocabulary (see chapter 4). There were also clear signs of early strategic flexibility, over and above the core decoding process. Strong superiority of words over nonwords shows that children were able to support their insufficient decoding skills with their pre-existing oral vocabulary knowledge. Tendency to make more lexical substitution errors in word than in nonword reading also reflects children’s understanding of the contrasting demands of the two

209 tasks. There was no sign, during the period covered by the study, of ‘pure’ subiexical decoding of real words. The mastery of the orthographic system of Polish took a surprisingly long time. More than a year was usually necessary to become able to decode new words with more than 50% accuracy (it must be remembered that children were already systematically taught to read in the preparatory ‘0’ grade). Full mastery of the system was often not achieved even in grade three, as evidenced by still far from perfect average accuracy of nonword reading and spelling, and occasional spelling errors that violated basic orthographic conventions. When the accuracy of scores obtained by my participants (table 6-1) are compared with the results of similar studies carried out in other languages (chapter 3, table 1 and figure 1) the Polish children fall in between inaccurate English readers and highly accurate simple orthography readers, usually somewhat closer to “the English side”. Such outcome suggests that the Polish orthography may be more complex than I originally thought (see chapter 4). Slower than expected growth of decoding skills among my Polish participants is rather unlikely to be the result of poor instruction, although this possibility cannot be completely ruled out, either. Close similarity of reading and spelling performance was also surprising. The analysis of the Polish orthographic system (chapter 4) highlighted the contrast between consistency of reading (all written words can have only one pronunciation) and inconsistency of spelling (alternative possibilities of rendering the same spoken word in writing). This suggested that reading, unlike spelling, should be relatively unhindered by alternative letter-sound mappings (since those alternatives are effectively neutralised in letter-to-sound direction), thus much easier to acquire. This prediction was only partially fulfilled. Spelling indeed seemed to lag behind reading (stringent comparisons were precluded by differences in testing procedure) yet it was the nonword rather than the word spelling that took longest to develop, which was inconsistent with the prediction (see table 6-12). Moreover, ANOVA analyses showed that the deleterious effects of mapping complexity were strong and persistent in reading and spelling alike. Complexity of sound-symbol mappings seems, then, to affect reading and spelling in much the same way. This suggests that reading and spelling rely on the same system of orthographic representations, or on separate systems but with a very similar internal organisation.

210 % accuracy 2"** grade 3'^'* grade on: th’o easiest reading simple frequent words 99% reading simple frequent words 99% su b te sts reading complex frequent 94% reading simple non-frequent 98% words words tH’o barc/est spelling complex nonwords 48% reading complex nonwords 66% su b te sts (derived from non-frequent (derived from non-frequent words) words) spelling complex nonwords 58% spelling complex nonwords 69% (derived from frequent words) (derived from non-frequent words)

Table 6-12 Easiest and hardest tasks and stimuli (in 2"'' and 3''' grade).

The nature of instruction seems by far the most important factor that shapes the course of literacy acquisition between grades 1 and 3. Very rapid progress in reading during grade one, as well as early bias towards a subiexical decoding strategy are primarily the product of educational experiences (intensive, systematic drill in letter-sound correspondences). Some other characteristics of the learning process seem to be more contingent on the orthography itself. Problems with complex letter-sound mapping, and slow development of spelling would probably affect Polish children taught with any method. However, those features were probably made even more prominent by a curricular regime that introduced reading before spelling, and drilled simple (transparent) mappings before the more complex ones.

211 CHAPTER 7

LITERACY AND OTHER COGNITIVE FACTORS

In the previous chapter I analysed the development of literacy skills, focusing on cognitive strategies adopted by children reading and spelling single words. The analyses were limited to measures of reading and spelling, so only those cognitive structures and processes that are themselves intrinsic to literacy (like alphabetic recoding, orthographic sensitivity, etc.) could be explored. In this chapter I adopt a complementary perspective and focus on the interaction between the development of reading and spelling and other cognitive competences. The analysis will examine two general hypotheses I initially adopted (chapters 1 and 2). First is the hypothesis of reciprocity: progress in literacy depends on some pre-existing cognitive competencies, yet it also radically restructures and improves these competences. The second is the hypothesis of specificity: literacy is composed of distinct functional sub-components, the development of each is dependent on its own unique set of cognitive prerequisites.

7.1. DEVELOPMENT OF COGNITIVE SKILLS.

The battery of tests employed in the study investigated a number of specific skills falling into three broad domains: phonological processing, morphological processing and visual skills. More general aspects of cognitive functioning (vocabulary, reasoning) were also tested (see chapter 5). All skills were expected to show age-related improvement. However, the magnitude of growth should vary considerably. Reading and spelling should be the fastest developing skills, since they are subject to explicit, intensive tuition. All skills that are a direct product of literacy, or remain in reciprocal relationship with it (phonemic awareness in particular) should develop in line with reading. Skills that relate more loosely to literacy, on the other hand, may show a different (probably much flatter) growth curve. As can be seen from table 7-1, the performance on nearly all measures improved with age. A series of one-way ANOVAs (not reported here) showed that only three tests failed to show age-related improvement (p>.05). These were: masculine rhyme (rime) fluency; feminine rhyme fluency, time of copying Rey figure, and accuracy of symbol

212 discrimination. The first two tests turned out to be very difficult, whereas the last test very easy, in all grades. Speed of copying Rey figure showed large individual variation, but also no clear age trend.

Gra N Mean Median SD Range Max. -de possible score General Nonverbal reasoning 1 36 50.39 50 4.18 42 -58 67 cognitive (Columbia) 2 36 51.75 53 5.51 3 9 -6 5 functioning 3 35 55.14 55 4.47 4 5 -6 4 Vocabulary 1 36 21.56 21 5.82 1 4 -3 8 64 (WISC) 2 35 27.83 28 7.62 1 5 -4 5 3 35 31.43 33 7.07 1 9 -4 2 Phonological Digit span 1 36 7.03 7 2.02 3 - 12 28 memory (WISC) 2 36 7.86 8 2.24 3 - 12 3 35 8.77 9 1.80 5 -1 3 Nonword repetition 1 35 18.06 18 3.57 1 1 -2 5 30 2 34 16.97 18 4.48 4 - 2 8 3 35 20.51 21 3.20 1 2 -2 7 Phonological Alliteration oddity 1 36 21.53 23 6.48 8 - 3 2 32 sensitivity 2 36 25.28 26 5.70 10 -32 & awareness 3 35 28.03 29 3.90 15 -32 Feminine rhyme 1 35 14.97 16 5.67 5 -2 3 32 oddity 2 36 18.89 19 6.67 6 - 3 0 3 35 20.49 20 6.32 1 0 -3 2 Masculine rhyme 1 35 16.80 16 7.34 4 - 3 0 32 (rime) oddity 2 36 21.03 22 6.65 0 - 3 2 3 35 22.51 22 5.52 1 2 -3 2 Phoneme deletion 1 35 15 16 4.67 4 -2 5 26 2 34 19 20.50 5.39 1 -2 6 3 35 22.23 23 3.13 1 4 -2 6 Vowel replacement 1 35 29.49 32 12.04 2 -4 8 48 2 36 33.28 36.50 12.65 2 - 4 8 3 35 38.94 40 6.83 2 1 -4 8 Consonant 1 35 26.26 26 7.28 1 4 -4 3 48 replacement 2 34 28.06 28 9.91 6 - 4 8 3 35 33.09 34 7.56 1 7 -4 8 Phoneme analysis 1 36 14.83 16 3.53 6 - 1 8 18 2 36 16.61 17 1.74 9 - 18 3 33 17.42 18 .71 1 6 -1 8 Phoneme blending 1 35 13.14 15 5 2 - 1 8 18 2 36 15.03 16 3.49 5 - 18 3 35 16.06 17 1.95 11 -18 Morphological Comparison of 1 35 35.51 37 12.43 6 -5 8 64 awareness adjectives 2 35 40.26 43 12.04 8 - 5 9 3 35 50.51 52 9.01 2 4 -6 2 Verb prefixes 1 36 31.72 26.50 16.23 5 -6 1 64 2 35 38.74 45 16.42 0 - 6 2 3 35 51.97 54 10.24 1 5 -6 3 Diminutives 1 35 50.34 51 6.29 3 6 -6 0 64 2 34 54.88 56 6.38 3 2 -6 3 3 35 59.06 60 3.35 51-64 Derivative forms 1 35 29.34 30 9.92 1 0 -4 9 64 2 35 33.77 34 10.54 6 - 5 4 3 35 40.83 42 8.49 2 3 -5 6

Table 7-1. Descriptive statistics for the cognitive measures used in the study.

213 Gra N Mean Median SD Range Max. -de possible score Naming Rapid picture 1 34 111.65 108.50 23.83 72 - 177 - naming 2 36 94.86 92.50 16.39 69 - 150 (time in seconds) 3 35 91.31 89 18.54 67 - 130 Rapid digit 1 35 83.20 74 39.69 46 - 290 - naming 2 35 62 62 11.21 3 9 -8 5 (time in seconds) 3 35 56.86 55 13.10 3 1 -9 4 Grapheme naming 1 35 1.09 1.06 .38 .47 - 2.01 - time 2 35 .71 .67 .17 .45 -1.33 (secs, per grapheme) 3 35 .68 .67 .14 .44 -1.03 Grapheme naming 1 34 81 84 13 51 - .99 78 accuracy 2 34 95 97 05 78 - 100 (100%) (% correct) 3 34 98 98 02 94 - 100 Verbal fluency Semantic fluency 1 35 17.49 17 4.94 9 - 2 8 - 2 35 20.14 21 5.04 1 1 -3 5 3 34 22.47 22.50 4.40 1 1 -3 0 Alliteration fluency 1 35 8.80 9 3.57 2 - 1 7 - 2 35 11.14 11 3.90 6 - 2 2 3 35 13.94 13 2.59 1 0 -2 1 Feminine rhyme 1 34 2.32 2 2.27 0 -9 - fluency 2 33 3.12 3 2 0 - 8 3 35 3.40 3 2.06 0 - 8 Masculine rhyme 1 32 2.66 2 2.19 0 - 8 - (rime) fluency 2 33 2.33 2 2.01 0 - 8 3 34 2.88 3 2.03 0 - 9 Visual Visual memory test 1 34 20.38 21 2.07 1 5 -2 3 24 processing (“Chinese letters”) 2 35 20.89 21 2.31 1 4 -2 4 - accuracy 3 35 21.83 22 2.02 1 6 -2 4 Copying Rey figure 1 35 25.09 24.50 3.68 17.50 - 33 34 accuracy 2 34 25.90 26.25 4.43 16.50 - 32 3 35 28.16 29 3.76 1 8 -3 4 Accuracy of letter 1 36 94.79 93.75 4.84 81.25-100 16 (100%) discrimination % a) 2 34 90.99 93.75 9.22 93.75-100 32 (100%) 3 35 95.45 96.88 4.81 81.25-100 32 (100%) Accuracy of symbol 1 34 93.01 93.75 5.71 81.25-100 16 (100%) discrimination % a) 2 36 89.67 90.63 6.67 75-100 32 (100%) 3 35 90.80 90.63 6.29 68.75-100 32 (100%) Visual Time of copying Rey 1 34 253.41 221.50 111.85 104 - 541 - processing figure (secs.) 2 34 238.44 209.50 90.90 138 - 523 - speed 3 32 247.56 228 134.49 1 1 9-888 Time of letter 1 34 8.64 7.50 3.88 3.31-22.50 - discrimination 2 36 5.33 5.08 1.48 1.94-8.63 (secs/item) a) 3 35 5.27 4.84 1.86 2.41-12.56 Time of symbol 1 35 7.11 6.00 4.83 3.63-32.50 - discrimination 2 34 5.80 5.52 1.49 3.19-8.53 (secs/item) a) 3 35 5.56 5.56 1.59 3.44-11.38

Table 7-1 continued.

a) r' grade children completed only one half of each visual discrimination task. Scores were transformed to '

correct to make them comparable across all three grades.

214 Table 7-2 lists individual measures that showed the largest relative improvement, as measured by effect sizes. During the T' grade (T‘ to 2"*^ term), the largest improvement was observed in all aspects of reading: accuracy and speed of naming words, nonwords and individual graphemes. Between the second half of grade 1 and grade 2 the largest gains occurred predominantly in performance speed (reading, letter discrimination, grapheme, digit and picture naming) and vocabulary. The largest gains between grade 2 and 3 involved spelling and most aspects of morphological awareness. The observed pattern of growth is partially consistent with the initial prediction. The rate of literacy acquisition (reading and grapheme naming skills in particular) indeed set the limits for the rate of progress in other areas. This was particularly the case with the youngest, T‘ grade group. It was unexpected, however, to find that the developmental rate of phonological awareness lagged far behind. None of the skills tapping into that domain were among the five fastest developing skills, and only some (masculine rhyme oddity, phoneme blending and deletion) were among the first ten. Conscious control over the phonological system of language was, then, developing much slower than reading ability, at least among school age children (i.e. after ‘zero’ grade). This pattern is compatible with the view that some (relatively low) level of phonological awareness skills is already sufficient for normal reading progress, as long as those ‘threshold level’ skills are acquired within a ‘critical window’ of the first few months of instruction. More fine-grained analyses, however, are necessary to confirm this suggestion; ones that would take individual participants, rather than tests, as the units of analysis; and explore not only relative growth, but also absolute level of performance. They will be carried out in the latter part of this chapter (section 7-5).

1®‘ grade 1®‘ term - 1®‘ grade 1®‘ grade 2"^ term - 2"^ grade 2"** grade - 3'^^ grade 2"** term Grapheme naming accuracy 1.36 Word reading time 1.21 Nonword spelling accuracy 1.67 Nonword reading accuracy 1.32 Nonword reading time 1.16 Word spelling accuracy 1.04 Word reading accuracy 1.21 Visual discrim, time - letters 1.08 Morphology-prefixes .99 Nonword reading time 1.09 Vocabulary 1.05 Morphology-adjectives .92 Grapheme naming time 1.06 Grapheme naming accuracy 1.00 Nonword repetition .86 Word reading time .86 Grapheme naming time 1.00 Morphology-diminutives .86 Visual discrim, time - letters .84 Word reading accuracy .94 Grapheme naming accuracy .86 Digit naming time .80 Phoneme deletion .88 Fluency-alliteration .86 Masculine rhyme oddity .78 Digit naming time .76 Phoneme deletion .76 Phoneme blending .71 Picture naming time .65 Word reading time .75

Table 7-2. Ten tests showing largest developmental gains between the grades. Growth is expressed in terms of effect sizes.

215 In terms of absolute-level performance gains over the whole period covered by the study, the largest progress was observed for: word reading time (more than a sixfold increase between the 1" term of grade and grade 3), nonword reading time and accuracy, letter discrimination time, grapheme naming time. All these measures were directly related to literacy, and nearly all indexed processing speed. Comparison with speed of copying Rey figure (which did not show any age-related growth) suggest that it is not processing speed in general, but rather automaticity of processing alpha-numeric stimuli that improved so dramatically over the three years of initial education.

7.2. PHONOLOGICAL, MORPHOLOGICAL AND VISUAL SKILLS - INTERNAL STRUCTURE.

In chapter 2 1 reviewed studies that employed factor analyses in order to investigate the organisation of phonological skills. One finding was consistently reported: measures of phonological awareness and rapid naming form two largely independent aspects of phonological processing. 1 expected this finding to be replicated with my data. Whether the domain of phonological awareness is further decomposable is less clear. It could remain unitary, or break down according to the size of phonological unit represented (rimes vs. phonemes: Muter et. al., 1998); complexity of the required operation (Yopp, 1988), or between analysis and synthesis (Wagner et. al., 1993). Moreover, the measures of morphological and nonverbal (visual) skills should also emerge as separate dimensions. At least a four factor solution was, therefore, expected: phonological awareness, rapid naming, morphological awareness and visual skills. The first factor analysis 1 carried out included all cognitive measures, except the nonverbal reasoning test (Columbia), WISC Vocabulary, grapheme naming speed and accuracy. These were excluded as 1 wanted to investigate the organisation of potential predictors of literacy that were specific (unlike vocabulary and reasoning) and did not constitute an apparent attribute of literacy (like grapheme knowledge).

216 The Principal Component factor analysis with Oblimin rotation yielded a six factor solution (see table 7-3)’.

FACTORS

Morphology - comparison of adj. .757

Nonword repetition .747 Morphology - derivative forms .744

Morphology - diminutives .732

Consonant replacement .718 Morphology - prefixes .655 alliteration oddity .564 vowel replacement .512 .378 phoneme deletion .503 masculine rhyme (rime) oddity .443 alliteration fluency .374 -.356 letter discrimination speed .845 -.321 symbol discrimination speed .749 picture naming time .723 digit naming time .660 semantic fluency .437 phoneme blending .971 phoneme analysis .924 symbol discrimination accuracy -.755 letter discrimination accuracy -.679 .338 digit span -.332 -.352 masculine rhyme (rime) fluency .756 copying Rey figure time .649 feminine rhyme fluency .369 .468 visual memory: “Chinese letters’ .755 copying Rey figure accuracy .698 feminine rhyme oddity .472

Table 7-3. Pattern matrix of the first factor analysis. Values represent factor loadings, and are sorted by size. For clarity of presentation, values below 0.30 are deleted.

' The test battery involved a number of speed measures, whose distribution turned out to be negatively skewed. For the purpose of this and all subsequent analyses those variables were log-transformed. These were: picture, digit and grapheme naming time; letter and symbol discrimination time; time of copying Rey figure.

217 The obtained solution could be described as follows:

1. A ‘General Linguistic’ factor, including nonword repetition, all four tests of morphological processing and some of phonological processing (consonant and vowel replacement, phoneme deletion, alliteration and masculine rhyme oddity). Alliteration and feminine rhyme fluency were weakly related. It explained 34.2% of total variance.

2. A ‘General Speed and Fluency’ factor: digit and picture naming time, visual discrimination speed (both symbols and letters). Semantic and alliteration fluency, and digit span were weakly related. It explained 9.6% of variance.

3. A ‘Phoneme Analysis and Blending’ factor: tests of phoneme analysis and blending. Vowel replacement was weakly related. 6.6% of variance.

4. A ‘Visual Discrimination’ factor: accuracy of visual discrimination (both symbols and letters). Digit span and letter discrimination speed were weakly related. 5.5% of variance.

5. An ‘Additional Speed and Fluency’ factor: Time of copying Rey figure and masculine rhyme fluency. Feminine rhyme fluency was weakly related. 5.2% of variance.

6. A ‘Visual Analysis and Memory’ factor: Recognition of abstract shapes (“Chinese letters”) and accuracy of copying the Rey figure. Feminine rhyme oddity was weakly related. 4.5% of variance.

The results were somewhat different than expected. The first factor joined together the domains of phonology and morphology, which were expected to emerge separately. The second factor broadly corresponded to the hypothetical speed of language processing domain, although it also included non-linguistic indices of performance speed (visual discrimination speed). Phoneme analysis and blending skills, which were supposed to belong to a broader phonological awareness domain, emerged as a separate factor. Visual skills appeared to be decomposable into two factors. The first of them involved accuracy of speeded visual discrimination, whereas the second indexed visual processes carried out with no time constraints. The analysis was repeated including tests of vocabulary and reasoning (Columbia). The overall structure was unaffected. Vocabulary loaded highly (.758) on

218 the first factor, thus further justifying its label of ‘general linguistic’. The reasoning test (Columbia) loaded on the last, 6‘^, factor, together with the measures of visual analysis and visual memory. It suggests that those higher-order visual skills share substantial variance with general intelligence. Since I was most interested in the linguistic skills, another factor analysis was carried out on them only (excluding the visual tests). A four-factor solution was obtained (see table 7-4):

FACTORS 1 2 3 4

Nonword repetition .867

Consonant replacement .777 Morphology - comparison of adj. .751 Morphology - prefixes .693 Morphology - derivatives .655 Vowel replacement .651 .342 Alliteration oddity .578 -.341 Morphology-diminutives .550 -.382 Digit span .540 -.415 Phoneme deletion .512 -.311 Masculine rhyme (rime) oddity .510 -.360

Phoneme blending .946 Phoneme analysis .912

Picture naming speed .889 Digit naming speed .855

Semantic fluency -.698 Alliteration fluency -.564

Feminine rhyme fluency -.509 .396 Feminine rhyme oddity .325 -.412

Masculine rhyme (rime) fluency .784

Table 7-4. Pattern matrix of the third factor analysis, which included only linguistic measures.

1. A ‘Linguistic Awareness^ factor: all four measures of morphological awareness, most measures of phonological awareness (replacement of vowels and consonants, phoneme deletion, alliteration and masculine rhyme oddity), phonological memory (nonword repetition, digit span). It explained 42.8% of variance.

2. A ‘Phoneme Analysis and Blending^ factor: 8.6% of variance.

219 3. A "Verbal Speed and Fluency* factor: picture and digit naming speed, semantic, feminine rhyme and alliteration fluency. Feminine rhyme oddity, and some other phonological tests were weakly related. 7.8% of variance.

4. An ^Additional Phonological* factor: masculine rhyme fluency. Digit span and feminine rhyme fluency were weakly related. 6.1% of variance

This new analysis was broadly consistent with the previous ones. The linguistic skills investigated in the study can be described by three major latent variables: linguistic awareness, processing speed, and phonemic analysis and blending. These results confirmed that phonological awareness and processing speed are generally dissociated. Phonological awareness, on the other hand, was found to be neither decomposable, nor separable from morphological processing. This finding suggests a unitary model of linguistic awareness - the ability of conscious control over different (sub)lexical elements. This single skill can be measured by a wide variety of tasks. Phonemic analysis and blending are clearly an exception, however, forming a robust separate factor. This type of dissociation was not previously reported in the literature. The reason for this may be educational: analysis and blending were probably taught explicitly and exercised extensively during the very first months of reading and spelling instruction - much more than any other phonological awareness tasks used in the study. Analysis and blending may, then, be overlearned and reflect literacy instruction (or experience) more than phonological awareness as such (for further analyses and discussion, see sections 7-4 - 7-5 and chapter 8). Most measures of verbal and nonverbal processing speed loaded on the same factor. This outcome is very interesting, as it suggests the existence of a general, cross- modal, dimension of processing speed (cf. Kay & Hall, 1994). It is also consistent with Wolf & Bowers (1999) suggestion that rapid naming involves general, cross-modal aspects of processing speed, apart from specifically phonological sub-processes. Equally interesting are the results regarding verbal fluency tests, as measures of this type have rarely been included in earlier factorial analyses of phonological processing. It could be expected that verbal fluency would load on the same factor as rapid naming, insofar as both require speeded processing of phonological codes. This expectation was largely confirmed: alliteration and semantic fluency were related to rapid naming (table 7-4) but also nonverbal processing speed (table 7-3). This pattern of results suggests that rapid naming and verbal fluency share not only linguistic

220 components (like retrieval of a phonological label, articulation) but also some general, cross-modal aspects of processing speed. However, it could also be expected that alliteration and rhyme fluency (but not semantic fluency) would also share substantial variance with phonological awareness measures, since both types of tasks require explicit attention to phonological structure of words. The evidence for this was less compelling: loadings of fluency tests on the 'general linguistic’ factor (which encompassed phonological awareness measures) were weak and not consistent across the analyses (compare tables 7-3 and 7-4). Fluency tests should not, in themselves, be regarded as good measures of phonological awareness. This conclusion is consistent with the results of the factorial analysis of the original Phonological Assessment Battery, from which the fluency tests were adopted (Frederickson et. al., 1998). There, measures of phonological awareness and of fluency clearly loaded on different factors. The results regarding the four fluency tests should be treated with caution, however, as the pattern of their factor loadings varied between the analyses. This could be an artefact of floor effects on the two rhyming measures, and of low reliability of all four fluency tests, especially in the 3''^ grade (see section 5.5.). The data also need to be interpreted in a developmental perspective. The structure of linguistic skills (linguistic awareness in particular) may change with age. Within this sample, factor analyses failed to differentiate distinct size-levels of linguistic representations (rhymes versus phonemes) or distinct degrees of conscious control over them (sensitivity versus awareness). These may, however, be discernible at the pre­ school age. After literacy instruction starts, all pre-literate sensitivity skills may be gradually 'recaptured’, becoming accessible to conscious reflection and manipulation. Such cognitive restructuring is reflected as a single linguistic awareness factor. As my study did not extend to the pre-school phase, limited possibilities of testing this hypothesis exist. Some insights, however, may be given by exploring the developmental course of phonological skills during the period covered by the study, especially at its beginning. This will be the focus of the following section.

221 7.3. DEVELOPMENT OF PHONOLOGICAL AWARENESS.

A battery of eight phonological tests used in the study allowed for some predictions regarding the developmental course of phonological awareness. In chapter 2 a general hypothesis was advanced that control over phonological structures progresses through a series of stages, and a basic distinction proposed between early, implicit, phonological sensitivity and later, explicit, phonological awareness. This implies that, at the onset of literacy acquisition, tests of phonological sensitivity (oddity tests in this study) should be performed better than any tests of explicit awareness. Phonemic analysis and blending skills should be acquired next, whereas more complex aspects of phonemic awareness (manipulation, deletion) only last. Language-, orthography- and teaching-specific influences may influence the speed of transition through the stages, and the final degree of achieved mastery. Polish children may be good at detecting alliteration and feminine rhymes, and at analysing and manipulating consonant clusters, since these structures are typical for the phonological system of Polish. By the same token, sensitivity to masculine rhymes (rimes) may be poor. Relative consistency of the orthography and phonics teaching should facilitate the performance on all phoneme-level tasks. Finally, the phonics teaching may bring selective benefits to some (highly exercised) tasks: phoneme analysis, blending and alliteration oddity. No such benefits are expected for rhyming skills. A comparison of the absolute levels of task mastery was difficult due to differences in test materials and procedures. Only certain pairs or triplets of tasks could be compared directly, as they shared the same testing paradigm, number of items, and other characteristics. These were: three oddity tests, analysis and blending tests, and two phoneme replacement tests. To provide some degree of comparability across all eight tasks, all scores were converted into the percentage of maximum score possible on each test. The results are presented in figure 7-1. It shows that the order of task difficulty remained the same between the grades, although the overall level of performance grew steadily (which was accompanied by reduction in performance variability). Phoneme analysis and blending were the easiest tasks, followed by alliteration oddity, phoneme deletion, and vowel replacement. Repeated measures 8 x 3 ANOVA with a within- subject factor of task and between-subject factor of grade confirmed these impressions. A strong effect of task (F[7,679]=55.544, p<.001) indicated significant differences in

222 test difficulty. The effect of grade (F[2,97]=20.556, p<.001) showed overall age-related improvement. Lack of interaction between task and grade (F[14,679]=1.081, p>.10) indicated that this improvement was similar for all eight tests. Differences in test difficulty turned out to be partially accountable for by the uneven demands they put on phonological memory. When two memory tests (digit span, nonword repetition) were entered into the ANOVA as covariates, the main effect of task was markedly reduced (F[7,665]=13.027, p<.001). Both measures of memory interacted with task (digit span: F[7,665]=3.465, p<.005; nonword repetition: F[7,665]=2.542, p<.05) indicating varying degrees of association between memory measures and different tests of phonological awareness. Using the criteria of task mastery we adopted previously when analysing reading performance (average accuracy exceeding 80%, fewer than five percent of participants performing with less than 50% accuracy) we find that: • no tasks were mastered in the U grade (although the phoneme analysis was approaching the criterion) • one was in the 2""* grade (phoneme analysis) • five were in the 3'"' grade (phoneme analysis, blending, alliteration oddity, phoneme deletion, vowel replacement).

Accuracy on phonological awareness tests was, then, quite similar to reading and spelling accuracy (see section 6.1.1), with none of the tasks mastered fully in the first grade, only one in the second grade, but more in the third grade.

223 100

GRADE 1

I [GRADE 2

GRADE 3 odd-allit odd-rhyme ph-blend repl-c odd-rim ph-anal ph-del repl-v

Figure 7-1. Accuracy on phonological awareness lests in F' - 3"^ grade (boxplol). Raw scores are converted into % of maximum possible score on each test. Solid boxes represent interquartile range, which contains half of all observed values. Circles represent outliers (cases more than 1.5 box lengths from the upper or lower edge of the box). Stars represent extreme cases (more than 3 box lengths from the edge).

These results point toward the primary role of education-specific constraints in shaping the development of phonological awareness during the first three school years. There is little evidence for sequential progress from sensitivity to awareness proper, or from large units (rhymes) to small ones (phonemes). Several small unit skills are mastered early and best - analysis, blending, alliteration detection - and these are either explicitly taught to children, or implicitly enhanced in the context of word decoding. Rhyme detection skills, on the other hand, are probably less exercised and thus mastered poorly, even among 3'"’ graders. The comparison between small unit and large unit skills could be made most clearly on three oddity tasks (alliteration, rime and rhyme), since they shared the same format. Repeated-measures 3 x 3 task by grade ANOVA found a large main effect of task (F[2,206]=84.799, p=.0()0), the effect of grade (F[2,l()3]=11.80i, p=.()()()) and no interaction between them (F[4,206]=0.327, p=.722). Pairwise task comparisons revealed that alliteration oddity was easier than both the rhyming oddity tasks (masculine rime: t[105]=38.996; feminine rhyme: t[105]=37.910; p<.0()l). Moreover, the masculine rime was easier than the feminine rhyme (t[105]=3.995, p<.001). This latter finding was rather surprising: given the phono-statistic constraints of Polish (high frequency of multisyllabic rhyming words) children should be well sensitised to feminine rhymes.

224 One explanation of this unexpected result could invoke unequal task demands. Adopting the description of rhyme structures provided by Pszczolowska (1972) we can say that both rhyme oddity tasks required the detection of an ‘imprecise’ or ‘approximate’ rhyme in a series of ‘exact’ or ‘precise’ ones; the imprecision being based on a single phoneme assonance. The same single-phoneme difference, however, is much more salient in the case of a masculine rhymes (rimes), where the target structure is composed of two phonemes only (eg. / n ^ los - tja s/; /kot pwot - rok/), than in the case of feminine rhymes, where it is much longer (e.g. /zgapitç rajiitç xjapitç - kranik/). Single phoneme alteration of a feminine rhyme may even leave the whole final syllable unchanged (e.g. /kotek pwotek - statek/). A subtler distinction is, then, required, making the feminine rhyme task harder. This ‘perceptual’ explanation was not, however, corroborated by the results of verbal fluency tests. Although fluency tests measured primarily processing speed (which was found in factor analyses), they also involved the same phonological units (alliterations, masculine and feminine rhymes) as the oddity tests, and can be seen as output measures of alliteration and rhyming. Children should produce most responses to the structures they found most accessible, showing the expected advantage of feminine over masculine rhymes. This was not observed, however, and the performance profile found with oddity tests was replicated instead (figure 7-2). 3x3 repeated measures ANOVA found the main effect of task (F[2,190]=583.252, p<.001) and grade (F[2,95]=8.822, p<.001) as well as the interaction between them (F[4,190]=12.255, p<.001). Post-hoc tests revealed that, unlike alliteration fluency, the two rhyming fluency tests showed no age-related improvement. Pairwise task comparisons showed the advantage of alliteration over masculine rhyme (t[98]=23.026) and feminine rhyme (t[101]=25.156, each significant at p<.001), but no significant difference was found between the two rhyming tasks (t[97]=1.628, p<.107)1

^ Additional analysis also found semantic fluency to be superior to all other fluency tasks (p<.001), suggesting that attending to semantic, rather than phonological properties of words may be a default strategy.

225 ■ 1 st g rade □ 2nd grade □ 3rd grade

sem antic alliteration rime rhym e

Figure 7-2. The number of correct responses per minute generated in four verbal fluency tests at each grade level.

Combining the results of oddity and fluency tests we may conclude, therefore, that Polish children are considerably better at processing words according to their alliterations than rhymes. Differences between two types of rhymes (masculine, feminine) are minor or non-significant. Educational factors seem to be the most plausible explanation of this pattern: rhyming skills receive less attention in Polish kindergartens and schools than syllabic and phonemic competences. Even more importantly, perhaps, rhyming activities, whenever brought in (e.g. in the form of poems children listen to, learn by heart, or read) are not explicitly tied to literacy: there are few attempts to show that rhyme (as a sound structure) may co-vary with a word’s spelling. In the case of phonemic awareness, there is also some evidence for the role of task complexity. The tasks requiring only segmentation of a phonemic string (phoneme analysis, blending and deletion tests) were generally easier than those requiring its manipulation (vowel and consonant replacement). T-tests showed that five out of six critical differences were significant (p<.0()l) and only one (between phoneme deletion and vowel replacement) was not. Task complexity may also explain why consonant replacement was the hardest of all phonemic tasks, significantly more difficult (p<.0()l) than (apparently similar) vowel replacement. The initial sections of both tasks, which required simpler operation (replacing single vowel, e.g. /ptak ptuk/ and single consonant onset, e.g. /miska fiska/) were performed with similar accuracy and speed (74.3% and 76.6% of maximum possible score, respectively, p>.10). However,

226 replacing two vowels, e.g. /wata -» wutu/ was easier than replacing a single consonant embedded in an onset cluster, e.g. /krul frul/ (68.6% and 53.5% respectively, p<.001). Children tended to replace the whole onset, rather than the initial consonant

(e.g. /Jkowa fowa/, instead of /fkowa/). It was probably the combined requirement of splitting the consonant cluster and replacing its initial phoneme with /f/ that made replacing the initial consonant of onset cluster so difficult, since both component skills (replacing single consonant onset, deleting phonemes from onset cluster) were significantly easier (p<.001).

7.4. CROSS - LINGUISTIC COMPARISONS OF PHONOLOGICAL SKILLS.

The extensive body of findings on phonological awareness that has been accumulated in different languages enabled me to assess the relative competence of Polish participants on a number of phonological awareness tasks. The prime purpose of such comparative analysis was to quantify the role of language, orthography and teaching-specific factors in developing conscious representations of phonology. Given the relative consistency of the Polish orthography and systematic phonics teaching, one can expect Polish children to perform relatively well on the measures of phonemic awareness (though perhaps fall short of perfection exhibited by the readers of fully transparent orthographies). Phoneme analysis and blending, as well as the ability to detect and produce alliterations, should be developed particularly well, since these particular skills are frequently exercised. Receptive and productive rhyming skills, on the other hand, should be mastered poorly. We have already noted such discrepancies in the previous section, while analysing the absolute level of performance. Here, I expect the similar pattern of strengths and weaknesses to occur in comparison with same-age or same-grade peers from other countries.

7.4.1. Phoneme analysis and blending

Phonemic analysis skills are usually operationalized with the tasks that require phoneme counting (where the participant has to indicate the number of segments in a word by tapping, laying down tokens, etc.) or phoneme segmentation (where consecutive segments have to be uttered). Those two procedures may be combined. Table 7-5 presents the results of all such studies which I was able to trace, and which fulfilled two

227 additional criteria: provided a detailed description of the task (especially the length of stimuli) and included T' or 2""^ grade school children, whose school experience would be comparable to that of my participants. Analyses employing word and nonword stimuli are presented separately. We can notice a number of apparent trends. Performance generally improved with grade. Familiar words were easier to analyse than nonwords. English participants performed poorly in comparison with readers of other, more consistent, orthographies. Finally, Tunmer & Neasdale (1985) as well as Perfetti et. al. (1987) found that children confounded phonological and graphemic structures of words, making a number of ‘overshot’ errors (i.e. reporting more phonemes than there really were) in words which were spelled with digraphs, or nonwords that had to be spelled with digraphs.

MATERIALS & PROCEDURE fSt grade 2nd grade mean mean mean mean ENGLISH WORDS age error % age error % Liberman et. al. 42 items, 1-3 phoneme long, randomly assorted. One-phoneme items were 6;11 33% (1974) nonwords. Tapping Backman Subset of Liberman et. al. (1974) stimuli, 21 items. Tapping 7;3 22% (1983) Blachman Original Liberman et. al. (1974) stimuli and procedure. Children of low 7;1 52% (1984) socio-economic status. Tunmer & 12 items, 1-3 phoneme long (letter-sound correspondences varied 6;3 17% a) Nesdale (1985) systematically) randomly assorted. Tapping. 41% b) Wagner et. al. 15 items, 2-5 phoneme long. Uttering consecutive phonemes. 8;1 61% (1994) OTHER WORDS LANGUAGES Cossu et. al. Italian. 45 items, 2-4 phonemes long, randomly assorted. Tapping. 7;0 7% 8;1 6% (1988) Wimmer et. al. German. 12 items, 1-3 phoneme long, randomly assorted. Counting (laying 7;2 8% (1991) down tokens and uttering consecutive phonemes). Nikolopoulos Greek. 20 items, 2-5 phoneme long. Counting (laying down tokens and 7;1 12% (1999) uttering consecutive phonemes). Krasowicz Polish. 6 items, 3-8 phoneme long. Uttering consecutive phonemes. 8;0 12% (1999) CURRENT Polish. 18 words, 3-11 phonemes long, assorted in ascending order of 7;7 17.6% 8;5 7.7% STUDY length. Phoneme counting (laying down tokens and uttering consecutive phonem es) ENGLISH NONWORDS

Treiman & 30 items, 1-3 phonemes long. Counting (laying down tokens). 6;6 58% 7;11 42% Baron (1981) Tunmer & 12 items, 1-3 phoneme long (letter-sound correspondences varied 6;3 25% c) Nesdale (1985) systematically) randomly assorted. Tapping. 33% d) Perfetti et. al. 16 items, 8 words and 8 nonwords, 2-4 phoneme long. Tapping. Only the 6;9- 35-57% (1987) results of the last test (April) are presented here. 7;0 OTHER NONWORDS LANGUAGE Krasowicz Polish. 8 items, 3-10 phoneme long. Uttering consecutive phonemes. 8;0 17% (1999)

Table 7-5. Summary of phonemic analysis studies. a) words spelled with one-to-one letter-sound correspondences b) words spelled with digraphs c) nonwords that can be spelled with one-to-one letter-sound correspondences d) nonwords whose orthographic rendition must include digraphs.

228 At first glance, the participants in the present study showed poor performance when compared with consistent orthography readers. Quite the opposite is the case, however, when one considers the length of the stimuli. No foreign language study used strings longer than 5 phonemes. In contrast, participants of my study were tested according to a discontinuation rule: they started with 6-phoneme long words and proceeded towards longer stimuli; shorter items were employed only if some errors occurred at the 6- phoneme level (see Methods section, chapter 5). Such demanding stimuli were adopted following a pilot study, which showed that performance accuracy on shorter words was very high. 6- and 7-phoneme long words (on which all participants were tested) elicited 11% of errors in grade 1, and 2% in grade 2. This was much higher accuracy than observed in all other studies. The performance was, then, even better than expected. It was likely to be partially the product of stimuli characteristics and the scoring procedure. All test items were frequent, transparent words, spelled almost exclusively with one-to-one letter sound correspondences (only two digraphs occurred). Even more importantly, confusions of letter names with letter sounds were not penalised. They were allowed since I anticipated that children may find the distinction between letter sounds and names confusing, due to their high degree of overlap in Polish. Such scoring leniency, however, effectively turned the phonemic analysis into an oral spelling task, and probably overestimated phonemic analysis skills. Fortunately, however, my participants also performed a phoneme blending task, which, while employing similar stimuli (high frequency transparent words, only four digraphs) did not allow for confusion of letter names and sounds. Both tasks appeared largely equivalent, as they correlated strongly (r=.769) and loaded highly on the same factor. The blending task, could, then, provide a more accurate estimate of phonemic skills. The accuracy of blending was indeed lower than the accuracy of analysis. When only 6- and 7- phoneme long words were considered, then 24% and 10% of errors were noted in T‘ and 2"*^ grade, respectively. Notably, these scores are still better than reported in the two comparable English blending studies (table 7-5).

229 2"d P ‘ g rade grade WORDS mean mean mean mean age error % age error % Wagner et. al. English. 15 items, 2-6 phonemes long. 8;l 24% (1993) K rasowicz Polish. 8 items, 3-10 phoneme long. g;Q 7% (1999) THIS STUDY Polish. 18 words, 3-11 phonemes long, assorted in ascending order of 7;7 27% 8;5 16.5% length. NONWORDS Perfetti et. al. English. 16 items, 8 words and 8 nonwords, 2-4 phoneme long. 6;9-7;0 29-43% (1987) Wagner et. al. English. 15 items, 2-6 phonemes long. 8;1 40% (1993) Krasowicz Polish. 8 items, 3-10 phoneme long. g-Q 30% (1999)

Table 7-5. Summary of phoneme blending studies.

My results were largely consistent with those obtained by Krasowicz (1999). Her large sample of Polish children was tested on the analysis and blending of words and nonwords, whose length varied between 3-8 phonemes (word analysis) or 3-10 phonemes (other tests). Spelling of her stimuli was also orthographically transparent, involving mostly one-to-one letter sound correspondences (only three digraphs occurred in the word blending task). Unlike in my study, however, letter-name responses were not allowed, and no discontinuation rule was used (all participants were tested on all stimuli). Given these constraints, 12% and 7% of errors occurred in word analysis and blending, respectively, at the end of T‘ grade. Corresponding error rates in my sample (items of the same length) were 7% and 21%, respectively. Thus, my participants were better at analysis (presumably because their performance was scored more leniently) but poorer at blending. Despite these discrepancies, both studies showed overall high accuracy of the Polish participants, compared to the learners of other orthographies. Consistently with my results, Krasowicz also reported substantial correlation between phonemic analysis and blending (around 0.5 after controlling for IQ and working memory) and found both tasks load on the same factor. Another interesting observation regarded the comparative difficulty of the two phonemic tasks. English studies consistently found blending to be easier than analysis, regardless of the type of stimuli (e.g. Perfetti et. al., 1987; Wagner et. al., 1993). However, my word tests and Krasowicz’s (1999) nonword tests showed the reverse. Only the word tests used by Krasowicz was consistent with the English data showing some (albeit small) advantage of blending. Such atypical pattern of difficulty may be an artefact of orthographic transparency of the stimuli used in both Polish studies. It is

230 plausible that the tendency to confuse phonemic word structure with its orthographic form is more prominent in the case of analysis (where children have to retrieve their own representations) than in blending (where the specification of a word’s phonological structure is provided). Consequently, using fully transparent stimuli that remove the orthographic confusability effect should benefit analysis more than blending. Overall, both studies suggest relatively high level of phonemic segmentation in grade Polish learners, in comparison with children from other countries.

7.4.2. Oddity tests.

The sound categorisation (oddity) paradigm required a child to pick the odd word out of four. The critical difference involved one phoneme only; it could occur word-initially (alliteration oddity), centrally or finally (rhyme oddity). The results of studies sharing this format are presented in table 7-6 and ordered according to the age of the participants. Of the three oddity tasks used in this study, only the masculine rhyme oddity was directly comparable to the English and German tasks reported in the literature. The feminine rhyme oddity test found no exact counterpart in other language studies, so I do not consider it here. The alliteration oddity test differed with respect to some phonological properties of the stimuli. It employed two-syllable words and tested consonant as well as vowel oddity (e.g. /oçow/ - /objat/ - /utjeji/). Sometimes it also required a single consonant distinction within a consonant cluster (vwosi vwa?itç - swijetç) thus tapping into the phoneme-level, rather than the onset-level, representations. Moreover, unlike most English studies, it did not keep the post-onset vowel constant (cf. gig, gin - hi I - 30W JIE3, ^ebratç - zupo). My oddity tests were previously scored according to the algorithm that combined accuracy and response time (see chapter 5). Here, however, only accuracy data are provided to facilitate comparisons with other studies. Both “strict” scores (accuracy at first attempt) and the “lenient” ones (second attempt allowed) are provided.

231 AGE STUDY PARTICIPANTS, MATERIAL & PROCEDURE % accur acy Diffe­ rence allit rime !;6 Bradley, Bryant ENGLISH . Items blocked by 3 conditions: initial C vs. middle V vs. final C, 53.6 67.8 -14.2 (1983) 10 items per condition. i;0 Wimmer, Landerl, GERMAN . Items blocked by 3 conditions: initial C vs. middle V vs. final C, 6 44 72.5 -28.5 Schneider (1994) items per condition. Distracters introduced (shared alliteration in rhyming test, shared rhyming in alliteration test). >; 1 Nation, Hulme ENGLISH. Items blocked by 2 conditions: initial C vs. final C, 12 items per 45.7 50 -4.3 (1997) condition. ); 10 Bradley, Bryant ENGLISH . Items blocked by 3 conditions: initial C vs. middle V vs. final C, 6 8&8 95.5 -6.7 (1978) items per condition. >; 11 Wimmer, Landerl, GERMAN . Items blocked by 3 conditions: initial C vs. middle V vs. final C, 6 41.7 60 -18.3 Schneider (1994) items per condition. Distracters introduced (shared alliteration in rhyming test, shared rhyming in alliteration test). j/;0 Goswami (1990) ENGLISH. Items blocked by 3 conditions: initial C vs. middle V vs. final C, 83 67 16 10 items per condition.

THIS POLISH Items blocked by 2 conditions: alliteration vs. rhyming (middle V or 63.3 a) 50 13.3 final C), 16 items per condition. r STUDY 71.2 b) 55 16.2 S;0 Nation, Hulme ENGLISH. Items blocked by 2 conditions: initial C vs. final C, 12 items per 6 2 8 60.7 2.1 (1997) condition. B;5 THIS POLISH Items blocked by 2 conditions: alliteration vs. rhyming (middle V or 76 a) 6 2 9 12.1 STUDY final C), 16 items per condition. 81.9 b) 67.2 14.7 P;0 Nation, Hulme ENGLISH. Items blocked by 2 conditions: initial C vs. final C, 12 items per 79 6 2 9 10.1 (1997) condition. ?;6 THIS POLISH Items blocked by 2 conditions: alliteration vs. rhyming (middle V or 85.5 a) 67.3 18.2 STUDY final C), 16 items per condition. 91.1 b) 73.4 17.7 10; 4 Bradley, Bryant ENGLISH, POOR READERS. Items blocked by 3 conditions: initial C vs. 56.3 78 -21.7 (1978) middle V vs. final C, 6 items per condition.

Table 7-6. Summary of sound categorisation studies. Rhyme detection accuracy % is averaged across middle V and final C conditions.

a) Strict scoring criteria: accuracy at first attempt only.

b) Lenient scoring criteria: second attempts also considered.

Polish children showed both alliteration and rhyme accuracy within the range obtained by other language speakers. Characteristic of the Polish participants, however, was a large discrepancy between the two skills, in favour of the alliteration. Most studies found children to perform better in the rhyme condition (especially if participants were younger) or show moderate alliteration superiority. In my sample, however, the alliteration superiority was substantial. Similar results were obtained by Krasowicz (1999). Using oddity tasks of a slightly different format (odd one out of three, some feminine rhymes included) she reported rhyme detection accuracy of 59%, 81% and 74% in 6- 7- and 8-years old Polish children, respectively. The corresponding figures for the alliteration condition were 77%, 91% and 90%, thus 10-18% higher. Both studies, then, suggest that Polish learners find onsets much more accessible than rhymes. The results should be treated as preliminary, however, until they are replicated with other oddity tasks that match the properties of rhyme and onset stimuli (their length, frequency, phonological complexity) more closely.

232 7.4.3. Vowel replacement test

My task of substituting a vowel /a/ with /u/ in mono- and bi-syllabic words was based on the test originally developed by Wimmer et. al. (1991). In a series of studies (which required /a/ - /i/ substitution), a rapid growth in performance accuracy was reported, from 38-47% in pre-literate children, to 88% - 97% in grade one. This was associated with the improvement in decoding skills. When my data were re-scored using Wimmer's et. al. (1991) original (more lenient) criteria, the following results were obtained: THIS STUDY WIMMER et.al., study 2

before reading instruction

(beginning of T‘ grade) 40% (S D = 3 6 .7 ) T’ grade (first term) 69.5% (17.8) T' grade (second term) 71.7% (21.3)

end of r ‘ grade 88% (2 0 ) 2"^* grade (first term) 75.9% (28.6)

Polish children, then, seem slower at acquiring vowel manipulation skills than their German-speaking counterparts. Although this may partially be an artefact of task difficulty (my test was longer and used words of more varied syllabic structure), it was consistent with the rate of decoding skills acquisition, which also seemed slower in Polish than in German (see chapter 6). As the ability to manipulate vowels correlated significantly with decoding in German and Polish alike (see section 7.5.) so the Polish children lagged in both areas.

7.4.4. Speed and fluency tests.

Most tightly controlled cross-linguistic comparisons could be made in the case of verbal fluency and naming speed tests. Three out of four fluency measures used in the study (except feminine rhyme fluency) exactly replicated the testing and scoring procedure of the Phonological Assessment Battery (PhaB: Frederickson et. al., 1998). Its nationwide English standardisation allowed me to compare the raw scores of the Polish participants directly with the English norms. In the case of the picture naming task, the phonological properties of the stimuli (CV structure, number of segments) could be matched very

233 closely across the languages (see section 5.2). No such match could be obtained in the case of the digit naming task, since Polish digit names are nearly always longer and phonologically more complex than their English equivalents. English norms were, however, still applied, with the realisation that they would underestimate the performance of the Polish children. Raw scores on all five tests and their English standard score equivalents are presented in table 7-7 and figure 7-3.

TASK grade 2"** grade 3"^"^ grade

Raw score Standard Raw score Standard Raw score Standard score score score

Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD) Mean (SD )

fluency (per minute) semantic 17.49 (4.9) 101.3(13.7) 20.14 (5.0) 103.5 (12.6) 22.47 (4.4) 103.9 (11.7) alliteration 8.80 (3.6) 97.6 (14.2) 11.14 (3.9) 102.6 (12.9) 13.94 (2.6) 108.6 (7.2) rhyme (masculine) 2.32 (2.3) 8 4 .2 (1 1 .9 ) 3.12 (2.0) 79.8(11.1) 3.40 (2.1) 80.2 (9.1) rhyme (feminine) 2.66 (2.2) - 2.33 (2.0) - 2.88 (2.0) -

Rapid naming (time in secs, per task) pict. naming 111.6 (23.8) 101.6(15.6) 94.86 (16.4) 108.6 (12.6) 91.31 (18.5) 105.3 (14.4) digit naming 83.2 (39.7) 94.9 (12.5) 62.00 (11.2) 101.9 (10.5) 56.86(13.1) 9 9 .7 (1 1 .2 )

Table 7-7. Performance of the Polish children on verbal fluency and rapid naming tasks, compared to English norms. English standard score equivalents of the Polish raw scores are taken from the PhAB

manual (Frederickson et.al., 1998).

With the exception of the rhyme fluency test, Polish children generally performed within the range that would be considered typical for their same-age English peers. This was even the case with digit naming, despite the fact that a Polish child had to utter several more syllables to name the same string of 50 digits. grade scores were relatively lower - indeed, poor, considering above average intelligence of the Polish sample (see chapter 5). This may be explained by the fact that Polish T‘ graders had less experience of formal schooling than their English counterparts matched on chronological age.

234 108.6 108.6

1 0 3 .^ 0 3 .9 101.0 10 1 .9

SEMANTIC FL. ALLlTERAi lON FL. RIME FL PICTURE NAMING DIGIT NAMING

Figure 7-3. Results of verbal tluency and rapid naming tests transformed to PhAB English standard scores (mean =100, SD = 15).

A clear-cut discrepancy between Polish and English data occurred on one task only. Rhyming fluency scores in my sample were very poor, consistently more than one standard deviation below what would be expected of an average English child of a similar age.

Overall, in comparison with their English counterparts, Polish children demonstrated strong phoneme analysis and blending, very weak rhyming (particularly rhyme fluency), and were similar on other phonological skills (alliteration oddity and fluency, naming speed). This pattern is generally consistent with expectations, and can be accounted or by phonological, orthographic and - particularly - instructional factors. It is perhaps surprising, though, that the Polish children were not better than their English peers on all phonemic tasks (e.g. alliteration oddity and fluency). In fact, when compared to other shallow orthography readers (German) they showed rather poorly on untrained phonemic tasks (vowel replacement) as well as decoding. Perhaps (as speculated at the end of the previous chapter) the Polish orthography is less consistent than I initially assumed, making it difficult to attain decoding proficiency, including its core element - full control over the phonemic structure of language.

235 7.5. COGNITIVE PREDICTORS OF LITERACY.

In the previous sections of this chapter I described the development of different cognitive skills in Polish children, focusing on phonological processing abilities, their cognitive-universal and language-specific characteristics. 1 would now like to turn to the central problem of my thesis: the role of these different cognitive skills in reading and spelling acquisition. Several causal relationships between literacy and cognitive skills were predicted. Performance on all literacy tasks should rely on two, largely independent aspects of phonological processing: phonological awareness and efficiency of phonology retrieval. Phonological (particularly, phonemic) awareness should enable children to form systematic letter-sound connections, and thus be most important in the context of decoding skills (operationalized with accuracy of nonword reading and spelling). Processes underlying efficient phonology retrieval (operationalized with rapid naming and fluency tasks) should also underlie the ability to automatize print-sound mappings, whether they are systematic or arbitrary. The performance on rapid naming and fluency tasks should, therefore, be specifically associated with the orthographic skills (operationalized with reading speed and orthographic accuracy of spelling). A specific role may also be played by morphological awareness and rhyming skills. Control over the morphological structure of language should be most important for the acquisition of orthographic skills, particularly conventional spellings of words, which are often conditioned by language morphology. Good rhyming skills may encourage a shift from sequential grapheme-phoneme translation to processing of larger phono-graphic units. This may particularly benefit orthographic spelling and reading speed. The role of rhyming should be minor, however, given relatively small benefits one can gain from preferring rhyme-level over grapheme-level regularities in reading and spelling Polish (chapter 4), and also considering a generally low level of rhyming skills in my sample. Although the cross-sectional, correlational paradigm of the study precluded direct testing of causal hypotheses, it allowed - by the means of statistical control - to pinpoint specific connections that are likely to be causal. In order to do this, a series of multiple regression analyses was first carried out. All correlations under scrutiny were controlled for variables that are likely to be predictors of learning success in every

236 domain: reasoning ability (Columbia, raw scores), vocabulary (WISC Vocabulary, raw scores) and chronological age. For each variable, these predictors were entered as the first three steps in a fixed order hierarchical regression analysis. A variable of interest constituted the fourth step. R squared change was examined after each step.

7.5.1. Predicting word reading and spelling.

7.5.1.1. Contribution of individual variables.

The analyses with word reading and spelling as outcome measures are summarised in table 7-8.

Skills task reading reading spelling measured accuracy speed accuracy step general nonverbal reasoning .081** .090** .110** 2"“ step predictors vocabulary .084** .136*** .075* 3"' step Chronological age .102*** .215*** .043 4“’ step df=89-95 df=9]-97 dM3-67 phonological W ise digit span .007 .034* .009 memory Nonword repetition .005 .029* .057* Alliteration oddity .065** .118*** .109** Feminine rhyme oddity .058** .072*** .021 phonological Masculine rhyme oddity .060** .057** .000 sensitivity & Phoneme deletion .060** .088*** .021 awareness Vowel replacement .071** .115*** .048* Consonant replacement .048* .036* .051* Phoneme analysis .109*** .129*** .019 Phoneme blending .106*** .053** .000 morpholo­ Comparison of adj. .011 .006 .001 gical Verb prefixation .005 .030* .064* awareness Diminutives .026 .011 .004 Derivative forms .026 .008 .003 rapid Rapid pict. naming .067** .095*** .032 naming Rapid digit naming .156*** .176*** .043 Semantic fluency .023 .009 .001 verbal Alliteration fluency .097** .090*** .032 fluency Feminine rhyme fluency .023 .041** .004 Masc. rhyme fluency .010 .010 .027 Visual memory test .000 .002 .009 visual skills - Copying Rey figure .002 .001 .021 accuracy Accuracy of letter discr. .004 .001 .104** Accuracy of symb. discr. .000 .001 .066* visual skills - speed of copying Rey .008 .007 .006 speed Speed of letter discr. .020 049** .002 Speed of symbol discr. .006 .014 .005

Table 7-8. Multiple regression analyses predicting word reading and spelling skills from individual tests.

237 The general pattern of correlations was similar for both aspects of reading (speed, accuracy) but somewhat different for spelling. Looking at reading first, we can notice that the three general predictors explained a substantial amount of variance of the outcome measure - 29% in case of accuracy, and 44% in case of speed. Rather surprisingly, it was chronological age that contributed most to this prediction. The variable of age is probably a collective index of all those cognitive skills that are related to literacy, but unrelated to general verbal and nonverbal intelligence. The tests that contributed most to the prediction of reading came from three categories: rapid naming, verbal fluency, and phonological awareness. The following five tests were the strongest predictors of the outcome measures: reading accuracy reading speed spelling accuracy

rapid digit naming rapid digit naming alliteration oddity phoneme analysis phoneme analysis accuracy of letter discrimination phoneme blending alliteration oddity accuracy of symbol discrimination alliteration fluency vowel replacement verb prefixation vowel replacement rapid picture naming nonword repetition

In terms of input skills, both phoneme-level and intrasyllabic-level awareness contributed significantly. However, output rhyming skills (as measured by verbal fluency tests) could not predict reading accuracy, and little of reading speed. This could be an artefact of the floor effect on both rhyming fluency tests. Little effect of morphological awareness was observed. A small contribution came from only one task that required deletion and addition of verb prefixes. The role of phonological memory also turned out to be small or even negligible (in the case of reading accuracy). Finally, visual processing skills did not contribute any unique variance into reading. The only exception was speed of letter discrimination, which showed a specific connection with speed of reading. Spelling was generally harder to predict. The reasons for this are likely to be methodological, and I discussed them before (smaller number of participants, their more restricted age range, group testing condition, a long and varied time gap between the

238 assessment of predictors and the outcome). Like reading, spelling was explained by general predictors (23%) and some phonological awareness measures (alliteration oddity, vowel and consonant replacement). Some role of working memory (nonword repetition) was also discernible. Apart from that, the patterns of correlations for reading and spelling were different. Phonemic analysis and blending, which were among the most powerful predictors of reading, were not associated with spelling. Against expectations, word spelling was not linked with rhyming, either, and received only minimal contribution from rapid naming, which fell short of significance (p=.052 for digit naming speed). Two predictors that were, conversely, strongly and specifically associated with spelling yet not reading, were the visual tasks: accuracy of visual discrimination of letters and (non-alphabetic) symbols. However, this result could be an artefact of the ceiling effect on the visual discrimination accuracy (see section 7.1.). To see whether that was the case, an alternative, non-parametric, analysis was carried out. For each outcome measure (reading accuracy, reading speed, and spelling accuracy) the best and the worst subgroup of participants was selected using a cut-off criteria of 90‘^ and 10“’ percentile, respectively. These subgroups were then compared on the accuracy of visual discrimination using a Mann-Whitney test. No differences were found on either visual discrimination measure between subgroups contrasted on reading accuracy and speed (all p>.10) - the outcome consistent with the null results of multiple regression analyses. Very good spellers were different from the very poor ones on letter discrimination (Z=2.994, p<.005) but not symbol discrimination (Z=1.676, p>.10) accuracy. The outcome was confirmed with whole sample Spearman correlations: the association was significant for spelling and letter discrimination (rho=232, p<.05), but not for spelling and symbol discrimination (rho=.125, p>.10).This partially confirmed the multiple regression results, suggesting that visual discrimination accuracy does relate to spelling accuracy insofar as the stimuli to be discriminated can be encoded verbally. Interestingly, both letter and symbol discrimination tasks produced a speed- accuracy trade-off: faster performance was associated with a higher number of errors (p<.01). This suggests that high visual discrimination accuracy may indicate certain strategic preferences: attention to details, tendency to monitor one’s performance carefully, or even overall importance attached to accuracy as such. These preferences may be beneficial for learning conventional spellings, hence the observed relationship.

239 Overall, the ability to spell words in the orthographically legal way was related to some aspects of phonemic awareness and visual processing.

7.5.1.2. Unique contribution of latent factors.

Multiple regression analyses presented above explored the predictive power of individual tests of linguistic and visual skills. From a theoretical point of view, however, it is more revealing to explore the contribution of underlying latent dimensions that were identified in factor analyses. A series of hierarchical regression analyses was again carried out (table 7-9). Initially, each one of six latent factors (identified in the factor analysis presented in table 7-3) was entered individually into the regression equation after the three general predictors (reasoning, vocabulary, age). This allowed me to establish which factors explained unique variance in reading or spelling over and above the variance accounted for by the general predictors (table 7-9, steps 1 and 2a). In the case of reading, three factors made their unique contribution: General Linguistic (1), General Speed and Fluency (2), as well as Phoneme Analysis and Blending (3). A quite different pattern was obtained for spelling accuracy: only Accuracy of Visual Discrimination (factor 4) contributed into its prediction. The following analyses tried to quantify the unique contribution of each of the three factors that turned out to be significant predictors of reading. Each factor was entered at the last step of the regression analysis, after the general predictors and the other two factors (table 7-9, steps 2b and 3). It turned out that each factor maintained its independent contribution into reading over and above all the others. The highest percentage of reading variance was uniquely explained by General Speed and Fluency (12% of accuracy and 13% of speed), followed by Phonemic Analysis and Blending (9% and 12% of accuracy and speed, respectively). The contribution of the General Linguistic factor was smaller (5% and 3%, respectively).

240 reading reading spelling accuracy speed accuracy step 1 general predictors (Columbia, Vocabulary, age) .266*** .442*** .228**

step 2 a individual latent predictors (factors) d M 8 df=80 df=54

1 - general linguistic .069** .049** . 0 1 0

2 - general speed and fluency .127*** .140*** .008 3 - phoneme analysis and blending .106*** .137*** .019 4 - visual discrimination .005 .024 .123**

5 - additional speed and fluency .004 . 0 1 2 .006

6 - visual analysis & memory .025 .006 . 0 1 1

4f=73 d/=75 step 2 b all significant latent predictors except factor I .227*** .270*** step 3 factor 1 (general linguistic) .051** .032**

step 2 b all significant latent predictors except factor 2 .161*** .172*** 118*** step 3 factor 2 (general speed and fluency) .130***

step 2 b all significant latent predictors except factor 3 .192*** .185*** step 3 factor 3 (phoneme analysis and blending) .086*** .117***

Overall R squared .5 4 5 . 744 .351 Adjusted R squared .5 0 9 .7 2 4 .3 0 3

Table 7-9. Multiple regression analyses predicting word reading and spelling from six latent factors. Overall and adjusted R squared changes are based on the significant predictors only.

The combined effect of the three general predictors and the three significant specific factors could explain over 70% of reading speed variance, and 50% of reading accuracy variance. In the case of spelling accuracy, only around 30% of its variance could be explained by the combined effects of age, reasoning, vocabulary and the only significant factor of visual discrimination. Using factor loadings as the independent variables had certain limitations. It allowed one to identify the factors that contributed uniquely to the prediction of reading and spelling, but did not specify what individual tasks (loading on their respective factors) were mostly responsible for correlations between these factors and the outcome measures. The last set of analyses was carried out to identify these tasks. First of all, stepwise regression analyses identified (separately for each factor) tasks that captured all variance shared between that factor and the outcome measures. Unique predictability of each factor for reading or spelling could, in most cases, be accounted for by just one task out of many that loaded onto that factor (table 7-10, steps 1 and 2a). Overall, reading accuracy was predicted by five variables, which represented four different

241 factors; reading speed was predicted by eight variables (out of six factors). Spelling accuracy could be explained by two variables, each loading on a different factor. Variables selected this way were then subjected to hierarchical regression analyses, with the order of entry varied systematically (table 7-10, steps 2b and 3).

reading accuracy reading speed spelling accuracy step 1 general predictors .266*** .422*** .228** (Columbia, Vocab., age)

df =96-97 df=93-95 df=66 step 2 a factor 1 alliteration fluency alliteration oddity alliteration oddity vowel replacement vowel replacement alliteration fluency .135*** ISO*** .109**

factor 2 digit naming speed digit naming speed - .156*** .176***

factor 3 phoneme analysis phoneme analysis - .109*** 129***

factor 4 - digit span letter discr. accuracy .034* .104**

factor 5 - femin. rhyme fluency - .041*

factor 6 feminine rhyme oddity feminine rhyme oddity - .058** .072***

Table 7-10. Results of multiple hierarchical regression analyses predicting reading and spelling from selected variables (best predictors in each factor).

242 reading accuracy reading speed spelling accuracy

df^93 df=88 df=65 step 2 b all significant predictors .241*** .284*** .104** except those from factor 1 step 3 factor 1 predictors .019 .023* .069** step 2 b all significant predictors .190*** .238*** except those from factor 2 step 3 factor 2 predictors .070*** .069*** - step 2 b all significant predictors .215** .262*** except those from factor 3 - step 3 factor 3 predictors .046** .046*** - step 2 b all significant predictors .307*** .109** except those from factor 4 step 3 factor 4 predictors - .001 .063* step 2 b all significant predictors .307*** except those from factor 5 step 3 factor 5 predictors - .000 - step 2 b all significant predictors .259*** .306*** except those from factor 6 - step 3 factor 6 predictors .001 .001

Overall R squared .526 749 .400 Adjusted R squared .486 .718 .354

Table 7-10 continued

The analyses revealed that all variance in reading accuracy that could be predicted by our large set of tasks was essentially captured by only two of them: rapid digit naming and phoneme analysis. They represented factors 2 and 3, respectively. Reading speed was uniquely predicted by three tasks from factor 1 (alliteration oddity, vowel replacement, alliteration fluency), rapid digit naming (factor 2) and phoneme analysis (factor 3). Spelling accuracy was explained by alliteration oddity and letter discrimination accuracy, representing factors 1 and 4, respectively. Selected individual tests could predict reading speed and accuracy just as well as did factor scores; in case of spelling the regression model based on individual test scores provided a slightly better fit than the model based on factor scores (compare overall R squared changes in

243 table 7-9 and 7-10). This was due to the specific contribution of the alliteration oddity task, which could not be detected when latent factor scores were analysed. The most important outcome of the above analyses is the confirmation of the “double underpinning” hypothesis. All analyses showed consistently that reading is predicted by phonological awareness as well as the efficiency of phonological retrieval, each making its independent, unique contribution. Analyses carried out on factorial scores suggested that contribution coming from phonological awareness can be further broken down into two independent components: phoneme analysis and blending, as opposed to other awareness skills. When combined together, these two aspects of phonological awareness predicted a bigger share of variance in reading accuracy and speed than did the retrieval (naming and fluency) skills, although the role of the latter was also substantial. Spelling accuracy seems to be related primarily to alliteration oddity and accuracy of letter discrimination. This result requires replication in a better controlled study with an individually administered spelling test and the letter discrimination tasks where the ceiling effect is eliminated (e.g. by limiting the duration of the stimuli exposure).

7.5.2. Predicting nonword reading and spelling

The analyses presented above were also carried out with nonword reading and spelling tasks. As indicated earlier a similar, yet not identical, pattern of predictors was expected to emerge for words and nonwords. Insofar as nonword reading and spelling are the index of decoding ability, they should be most strongly associated with phonological awareness, especially at the phonemic level. If other linguistic abilities (rapid naming, morphological skills, rhyming skills) are indeed linked primarily with orthographic skills, not decoding, they should turn out to be weaker predictors of nonword reading and spelling.

244 7.5.2.I. Contribution of individual variables.

Table 7-11 presents the results of multiple regression analyses with individual cognitive tasks.

Skills task nonword nonword nonword measured reading reading spelling accuracy speed accuracy r ‘ step general nonverbal reasoning .126*** .088** .068*

2 "'^ steppredictors vocabulary .080** . 1 0 1 ** . 0 0 1 3'" step Chronological age .039* .163*** .007 4"" step df=91-94 dM2-95 df=63-66

phonological WISC digit span .037* .017 . 0 0 0

memory Nonword repetition .049* . 0 1 0 .050

Alliteration oddity .1 2 0 *** . 1 0 0 *** .090** Feminine rhyme oddity .053** .078** .064* phonological Masculine rhyme oddity .064** .066** .049

sensitivity & Phoneme deletion .082** .087** . 0 0 0

awareness Vowel repl. .140*** .073** . 1 0 2 ** Consonant repl. .099*** .037** .049

Phoneme analysis .090** .1 0 2 *** .052 Phoneme blending .072** .044* .064*

morpholo­ Comparison of adj. .035* . 0 0 2 .016

gical Verb prefixation . 0 2 1 . 0 2 0 . 0 2 1

awareness Diminutives .014 .013 . 0 0 2

Derivative forms .038* . 0 0 1 .048 rapid Rapid pict. naming .063** .132*** .003 naming Rapid digit naming .154*** .233*** .006

Semantic fluency . 0 1 1 .017 .007

verbal Alliteration fluency .042* .093*** . 0 1 2 fluency Feminine rhyme fluency .024 .053** .033

Masc. rhyme fluency . 0 0 0 . 0 1 2 .064*

Visual memory test . 0 0 0 .003 .041

visual skills - Copying Rey figure . 0 1 2 . 0 0 0 .005

accuracy Accuracy of letter discr. . 0 0 1 . 0 0 0 .029

Accuracy of symb. discr. . 0 0 0 . 0 0 2 . 0 0 1

visual skills - speed of copying Rey . 0 0 2 . 0 1 1 . 0 2 0

speed Speed of letter discr. .009 .086*** . 0 0 1

Speed of symbol discr. .004 . 0 2 2 .014

Table 7-11. Multiple regression analyses predicting nonword reading and spelling skills from individual tests.

Looking at reading first, we notice strong similarities across all analyses. Nearly the same pattern of correlations held for nonword accuracy and speed. Both were related to general predictors (which accounted for 24% and 35% of accuracy and speed variance, respectively) and showed the strongest specific associations with measures of rapid naming, phonological awareness, and verbal fluency:

245 strongest specific predictors reading accuracy reading speed spelling accuracy

rapid digit naming rapid digit naming vowel replacement vowel replacement rapid picture naming alliteration oddity alliteration oddity phoneme analysis feminine rhyme oddity consonant replacement alliteration oddity phoneme blending phoneme analysis alliteration fluency masculine rhyme fluency

The outcome was also very similar for word and nonword reading (compare tables 7-8 and 7-11). Contrary to expectations, there were no apparent differences in the relative importance of rapid naming and phonemic awareness in predicting word and nonword performance. The results were quite different for nonword spelling, however. It was weakly predicted by only one out of three general variables (reasoning); among the remaining measures only four tests of phonological awareness and one of verbal fluency made their significant contribution. There was some similarity between word and nonword spelling accuracy insofar as both were predicted by the phonemic skills. However, only word, but not nonword spelling was also associated with visual discrimination skills.

7.5.2.2. Unique contribution of latent factors.

The analyses that explored the contribution of individual latent factors to the prediction of nonword reading and spelling are presented in table 7-12. In the case of nonword decoding accuracy, three factors: General Linguistic, General Speed and Fluency, and Phoneme Analysis and Blending each contributed uniquely. The same outcome was obtained for the word reading accuracy (table 7-9). However, in the case of words the largest share of variance was explained by the General Speed and Fluency (12%); in the case of nonwords by the General Linguistic factor (10%). This weak differential trend suggests partial dissociation, whereby phonological awareness links most strongly with sublexical decoding, and rapid naming with recognition of familiar words. In the case of nonword reading speed only two factors: General Speed and Fluency, as well as Phoneme Analysis and Blending, accounted for significant variance.

246 Like in the case of word reading speed, the largest contribution came from the general speed factor (20%). Unlike in the word task, however, no contribution was received from the General Linguistic factor after controlling for three general predictors. It was so despite the fact that most individual tasks that loaded onto that factor correlated significantly with nonword reading speed. Those correlations were probably ‘diluted’ by the remaining few tasks that loaded highly on the General Linguistic factor, but did not correlate with reading (nonword repetition, four morphological tests). A similar situation occurred in the case of nonword spelling: it was predicted only by factor 3 (Analysis and Blending) although it also correlated significantly with some tests that loaded on other factors. Overall predictability was somewhat weaker for nonword than word skills. Nonword spelling, in particular, could not be predicted significantly by the latent factor scores derived from my test battery.

Nonword Nonword Nonword reading reading spelling accuracy speed accuracy step 1 general predictors (Columbia, Vocabulary, age) .244*** .353*** .076

step 2 a latent predictors df=77 df=78 df=54 1 - general linguistic .124*** .026 .054 2 - general speed and fluency .061* .229*** .014 3 - phoneme analysis and blending .095** .095*** .085*

4 - visual discrimination .033 . 0 2 2 .016 5 - additional speed and fluency .003 .023 .061

6 - visual analysis & memory . 0 2 1 . 0 0 0 .051

4f=75 df=77 step 2 b all significant latent predictors except factor 1 .152*** step 3 factor 1 (general linguistic) .102***

step 2 b all significant latent predictors except factor 2 .200*** .095*** step 3 factor 2 (general speed and fluency) .054** 221***

step 2 b all significant latent predictors except factor 3 .181*** .229*** step 3 factor 3 (phoneme analysis and blending) .073** .087***

Overall R squared .499 .669 .162 Adjusted R squared .458 .647 .100 Table 7-12. Multiple regression analyses predicting nonword reading and spelling from six latent factors.

In the last set of analyses, I tried to identify a minimal set of tasks capable of capturing all variance shared between the whole test battery and each outcome measure (table 7-

247 13). This was done using the two-step selection procedure described previously (section 7.5.1.2, table 7-10), which combined factor analysis with regression analyses. All predictable variance in nonword decoding accuracy was accounted for by scores of four tests, which represented three different factors: General Speed (rapid digit naming). General Linguistic (vowel and consonant replacement) and Analysis and Blending (phoneme analysis). Only two tests captured all accountable variance of nonword reading speed: rapid digit naming (General Speed factor) and phoneme analysis (Analysis and Blending factor). In the case of spelling, four tests representing four factors (vowel replacement, phoneme blending, masculine rhyme fluency, feminine rhyme oddity) were largely equivalent, as they cancelled out their respective contribution. Numerically, the largest input came from the test of vowel replacement (General Linguistic factor).

Nonword reading Nonword reading Nonword spelling accuracy speed accuracy

df=95 df=96 df=66 itep 1 general predictors 244 *** 353*** .076 (Columbia, Vocabulary, age) itep 2a factor 1 alliteration fluency

vowel replacement phoneme deletion

consonant replacement masculine rhyme oddity Vowel replacement

1 7 6 * * * .167*** .102 **

factor 2 digit naming speed digit naming speed -

154*** 233 ***

factor 3 phoneme analysis phoneme analysis Phoneme blending

.090*** 102*** .064*

factor 4 digit span --

.037*

factor 5 - feminine rhyme fluency Masculine rhyme fluency

.053** .064*

factor 6 feminine rhyme oddity feminine rhyme oddity Feminine rhyme oddity

TG3** .078** .064*

Table 7-13. Results of hierarchical multiple regression analyses predicting reading and spelling from

selected tests (best predictors in each factor).

248 Nonword reading Non word reading Nonword spelling accuracy speed accuracy

df=89 df=89 df=62

step 2 b all significant predictors except those from factor 1 .230*** .311*** .124*

^tep 3 factor 1 predictors .067** .012 .048t

^tep 2 b all significant predictors except those from factor 2 Î .224*** .2 2 1 *** -

^tep 3 factor 2 predictors 073*** .103*** - step 2 b all significant predictors except those from factor 3 .271*** .277*** .152* step 3 factor 3 predictors .027* .046** .020 step 2 b all significant predictors except those from factor 4 .296*** - step 3 factor 4 predictors .001 - step 2 b all significant predictors except those from factor 5 - .323*** .158** ptep 3 factor 5 predictors - .000 .014 step 2 b all significant predictors except those from factor 6 .297*** .323*** .153** step 3 factor 6 predictors .000 .000 .019

Overall R squared .541 .676 .249

Adjusted R squared .495 .639 .164

Table 7-13 continued.

It is clear from all the analyses presented above that the predictors of reading are quite similar for word and nonword tasks. Both receive independent contribution from phonological (particularly phonemic) awareness and the measures of phonological retrieval (particularly rapid naming). Generally, however, measures of phonemic awareness tend to be better predictors of accuracy, whereas rapid naming tests account best for reading speed. Spelling accuracy is (weakly) connected with phonological awareness skills, in the case of words and nonwords alike. A major difference between the two outcome

249 measures regards the role of visual discrimination accuracy, which is significant for word spelling only.

7.5.3. Reading and phonological awareness - analysis of individual cases.

In preceding paragraphs, the relationship between literacy and linguistic skills was explored with correlational analyses. Intrinsic limitations of this approach in pinpointing a causal relationship can be partially overcome with a case-by-case analysis, whereby a causal hypothesis is formulated, and individual cases that would falsify it are sought. The hypothesis of a reciprocal link between literacy and phonological skills I test here implies bi-directional causal influences. On the one hand, phonological skills are a necessary (although perhaps insufficient) condition of reading progress. On the other hand, learning to read is also a necessary (if insufficient) condition for the development of phonological skills (phonological awareness in particular). These two predictions are logically independent and would be falsified by a different set of conditions. We should reject the first hypothesis (phonological awareness necessary for reading) if we observed any children that are poor at phonological awareness, but good at reading. Conversely, the second hypothesis (reading necessary for phonological awareness) should be rejected in the face of participants that are poor at reading, yet good at phonological awareness. The operationalization of the critical conditions was carried out as follows:

Phonological awareness as a necessary Reading as a necessary condition for condition for reading phonological awareness

no children poor at phonological awareness, but no children poor at reading, but good at good at reading phonological awareness specifically specifically

1. no children very poor at phonological awareness 3. no children very poor at reading (below 10 percentile) (below 10 percentile) but above average (50 but above average (50 percentile) on phonological percentile) on reading. awareness.

2. no children very good at reading (above 90 percentile) 4. no children very good at phonological awareness but below average (50 percentile) on phonological (above 90 percentile) but below average (50 percentile) awareness. on reading.

The hypothesis of reciprocity implies, in its strong version, that no cases fulfil the critical conditions 1-4, so there is an overlap between extreme cases (children scoring

250 very high or very low on reading perform likewise on phonological awareness, and vice versa). Less than perfect overlap can be allowed, however, if we assume that compensatory factors play a role. I also anticipated that reading progress would be more strongly constrained by phonological awareness than phonological awareness would be constrained by reading mastery. The hypothesis was tested with the nonword decoding test as the measure of reading, and alliteration oddity and vowel replacement as the measures of phonological awareness. Nonword decoding was considered more appropriate than word recognition, since the relationship between phonological awareness and word reading is supposed to be mediated by decoding. The two tests of phonological awareness were chosen since the regression analyses showed them to be the most strongly associated with reading. Individual cases selected on the basis of extreme decoding scores (corresponding to conditions 2 and 3 specified above) are presented in table 7-14. Cases of extreme phonological awareness scores (conditions 1 and 4) are given in table 7-15.

alliteration number of cases vowel number of cases oddity replacement decoding decoding

1 0 “’ prc or less 90 prc or more 1 0 ’“ prc or less 90 prc or more

1 0 ^ prc or less 5 1 0 “’ prc or less 2 more than 1 0 '^ prc 4 more than 1 0 “’ prc 4

> 2 0 “' prc 1 > 2 0 “’ prc 2 1

> 30“’ prc 4 > 30’“ prc 2 > 40“’ prc 1 > 40’“ prc 2 > 50“’ prc 1 3 > 50’“ prc 1 4

> 60'^ prc > 60’“ prc 2

> 70’^ prc 2 > 70’“ prc 2

> 80'^ prc 2 > 80’“ prc 1 90“’ prc or more 2 90’“ prc or more 2

Table 7-14. Cross-tabulation of reading and phonological awareness scores (children selected for extreme reading scores).

251 decoding number of cases decoding number of cases

alliteration oddity vowel replacement

1 0 '“ prc or less 90 prc or more 1 0 '“ prc or less 90 prc or more

1 0 “’ prc or less 5 1 0 '“ prc or less 2

more than 1 0 “’ prc more than 1 0 '“ prc 3

> 2 0 '“ prc 3 2 > 2 0 '“ prc 5 1 > 30'“ prc 2 > 30'“ prc 1 > 40'“ prc 1 > 40'“ prc 3 > 50'“ prc 1 > 50'“ prc 2 > 60'“ prc 1 > 60'“ prc 1 > 70'“ prc 3 > 70'“ prc 3 > 80'“ prc > 80'“ prc 2 90'“ prc or more 2 90'“ prc or more 2

Table 7-15. Cross-tabulation of reading and phonological awareness scores (children selected for extreme scores on phonological awareness tests).

The cases of extreme performance on both conditions, consistent with the reciprocity hypothesis (marked with bold print) constituted 22/95 (23%) of analysed instances, the remaining ones showing various degrees of dissociation. 17 cases (18%) fulfilled my Talsificatory’ criteria, breaking down as follows:

oddity replacement c. 1. very poor at PA, but above average on reading

c. 2. very good at reading, but below average on PA 8/49 (16.3%)

oddity replacement

c. 3. very poor at reading, but above average on PA 1 1

c. 4. very good at PA, but below average at reading 3 4 9/46 (19.6%)

The observed pattern of dissociations goes against the strong version of the reciprocity hypothesis, whereby good reading is an ‘absolutely necessary’ condition of phonological awareness, and vice versa. Both relationships held in general, yet dissociations also occurred. Relatively often, a very good mastery of one skill was accompanied by mild difficulties with the other (conditions 2 and 4). It seemed more rare, however, to compensate for severe difficulty in one skill and reach average on the

other (conditions 1 and 3). Notably, no participants that were very poor on phonological awareness reached an average reading level, whereas the reverse did occur. This suggests that phonological awareness limits reading progress more strongly than reading limits the development of phonological awareness.

252 7.5.4. The role of grapheme naming.

The analyses presented previously were concerned with 'external’ predictors of reading and spelling. Hence, they deliberately excluded letter naming ability, which constitutes an intrinsic part of being literate, rather than a cognitive skill that is in any way external to it. Here I would like to investigate how the mastery of graphemes (accuracy and speed of retrieving names and sounds of single letters and digraphs) constrains reading and spelling development. At least three types of connection are possible. First of all, spelling is simply not possible without knowing letters; nor is reading if - like in case of my participants - systematic phonics instruction is applied and children are never asked to commit whole words to memory without decoding them first. In such context knowledge of the alphabet should directly constrain decoding skills and, this way, indirectly contribute to the development of sight vocabulary. Secondly, grapheme

naming reflects the ability to learn and automatize arbitrary connections between sounds and symbols; the ability considered important for reading in general, and the orthographic skills in particular. Finally, early experience of reading and spelling should also feed back into grapheme naming skills, making them more accurate and automatic. Table 7-16 presents the results of multiple regression analyses predicting reading and spelling from the accuracy and speed of naming graphemes.

WORDS NONWORDS

Reading Reading Spelling Reading Reading Spelling accuracy time accuracy accuracy time accuracy

Step 1 General predictors (Columbia, Vocabulary, .266*** .422*** .228** .244*** .353*** .076 age)

df=93 df=93 dM2 df=91 dM2 df=62 Step 2 Grapheme naming .507*** .284*** .073* .357*** .321*** .041 accuracy Step 3 Grapheme naming speed .000 113*** .047* .000 120*** .001

Step 2 Grapheme naming speed .245*** .369*** .092** .170*** .406*** .013

Step 3 Grapheme naming .263*** .028*** .028 .188*** 035*** .002 accuracy Overall R squared .774 .839 .348 .602 .794 .119

Adjusted R squared .762 .830 .295 .580 .784 .048

Table 7-16. Results of hierarchical multiple regression analyses predicting reading and spelling skills from grapheme knowledge and naming speed.

253 Grapheme naming skills appeared, on their own, to be a very good predictor of reading (better than any other specific skill analysed in the study). Multiple regressions predicting reading scores showed partial dissociation between accuracy and speed of processing. Only grapheme naming accuracy (not speed) uniquely predicted reading accuracy; conversely, reading speed was predicted much better by grapheme naming speed than accuracy. Such a pattern was observed for both word and nonword reading. It suggests that individual differences in reading accuracy are a direct product of letter knowledge, yet differences in reading speed are less so.

Inability to decode words due to incomplete letter knowledge is not the major factor that slows reading down. This outcome corroborates the results of earlier regression analyses, showing accuracy and speed as (partially) dissociable dimensions of reading. Although reading speed and accuracy correlate strongly and are, by and large, predicted by the same set of variables, each show strongest links with different domains of cognitive processing. Accuracy of reading (both words and nonwords) is most strongly linked to various aspects of phonological awareness (especially at the phonemic level) and to knowledge of letters and digraphs. Reading speed, on the other hand, is tied most strongly with speed of naming, particularly of alphanumeric stimuli. Once again, spelling was much harder to predict than reading. All predictable variance of word spelling accuracy was captured only by the speed, not accuracy, of grapheme naming. Orthographic spelling may, then, rely on some abilities and experiences linked specifically with the speed of grapheme naming (such as ability to automatize; exposure to reading and spelling activities). Neither accuracy, nor speed of grapheme naming could reliably predict encoding (nonword spelling). I proposed that letter knowledge contributes to word reading indirectly, enabling successful decoding which, in turn, helps to build sight vocabulary. If this is the case all variance in letter knowledge that contributes to word reading and spelling should be captured by nonword decoding skills. This turned out not to be the case, however: although the overlap between letter skills and nonword decoding skills was substantial, both contributed some unique variance into word reading (table 7-17). In fact, word reading accuracy correlated somewhat more strongly with grapheme naming than with nonword decoding. Combined together, grapheme naming and nonword decoding skills provided a near-perfect prediction of word reading speed, and a very good prediction of

254 accuracy.

word word word reading reading spelling accuracy speed accuracy step 1 general predictors (Columbia, Vocabulary, .266*** .442*** .292*** age)

df=89 d M 9 df^60 step 2 grapheme naming accuracy .507*** .397*** .120** grapheme naming speed step 3 nonword reading accuracy .063*** .098*** .069* nonword reading speed

step 2 nonword reading accuracy .496*** .484*** .147** nonword reading speed step 3 grapheme naming accuracy .074*** .011** .042 grapheme naming speed

R squared change .836 .936 .417 Adjusted R squared .824 .931 .349

Table 7-17. Results of hierarchical regression analyses predicting word reading and spelling skills from grapheme mastery and nonword decoding.

In the case of word spelling, some unique contribution of grapheme naming skills was also discernible (4%), but fell short of significance. Unique contribution of grapheme naming skills into word reading over and above alphabetic decoding can be explained by the complexity of the grapheme naming task. In contrast to a typical letter knowledge test (e.g. Duncan & Seymour, 2000) it included not only 23 basic Roman letters, but also 9 letters with diacritics, and 7 digraphs. Children were taught some of them only towards the end of grade, perhaps even later. For some children, the learning process took longer still: 5% and 2% of grapheme naming errors were made in grade 2 and 3, respectively. Naming the whole set of graphemes accurately and quickly probably reflected more than foundation-level skills, and required considerable reading experience. This made the task a particularly good proxy of all reading skills. Comparison of grapheme naming accuracy and reading accuracy (table 7-18) supported this hypothesis. Apart from the lower end outliers, accuracies of word reading and letter naming were remarkably similar, very good knowledge of all graphemes being a marker of good reading, rather than of basic level

255 decoding. The minimum level of grapheme knowledge required to read more than half of all items accurately was approximately 70% for words and 80% for nonwords.

grapheme N word reading accuracy % nonword reading accuracy % identihcation accuracy median minimum maximum median minimum maximum less than 70 % 6 50 45 60 15 0 35

70-79% 9 75 65 90 38 10 75

80-89% 9 85 70 100 50 40 85

90-95% 23 95 80 100 70 28 90

96-99% 38 98 85 100 79 38 100

1 0 0 % 10 98 88 100 77 55 95

Table 7-18. Accuracy of reading as a function of letter knowledge

7.5.5. Change in predictors of literacy over time.

The regression analyses presented above lacked the developmental perspective, as they pooled together the data of all T‘ to 3'^* grade children. Some crucial changes were expected over that 3-year period, however. Progress through the “elementary alphabetic” phase (which, for most children, extended until the end of grade: see chapter 6) should be directly constrained by grapheme knowledge, phoneme analysis and blending, and other phonological awareness skills. An “advanced alphabetic and orthographic” phase, on the other hand, should depend more on the processes indexed by rapid naming tasks, as well as on morphological awareness. A small number of participants limited the possibilities of carrying out separate statistical analyses for each grade. One set of hierarchical multiple regressions was carried out: word reading skills were predicted from the performance on each individual cognitive test, after controlling for the three general variables (vocabulary, reasoning and age; see table 7-19). Analysing individual tests (rather than latent factors) maximised the number of degrees of freedom, as factor scores were missing for any participant who failed to complete the whole battery of tests. Spelling scores were not analysed here: too few participants completed the spelling test at each grade level. Also, as spelling was tested separately from reading, some participants had already moved to the next grade by the time their reading and other cognitive skills were assessed individually.

256 Word reading accuracy Word reading speed

task 1*‘ grade 2 nd 3 rd 1®‘ grade 2 nd 3 rd

grade grade grade grade

T' step nonverbal reasoning .060 .013 . 0 0 1 .006 .018 .041

2 "^“ step vocabulary . 0 1 1 . 0 2 0 .032 . 0 0 1 .140* . 0 0 0

3'‘' step Chronological age . 0 1 0 .123* .016 .031 . 0 0 0 .016

4“’ step df^30-26 df=30-28 df=29-25 df^30-26 df=30-28 df=28-26

W ise digit span .005 .089t .044 .116t .130* . 0 1 1

Nonword repetition . 0 1 2 .070 .051 .109t .179* .025

Alliteration oddity .not .1 1 1 * .004 . 2 1 0 ** .284*** .127*

Feminine rhyme oddity .219** .004 . 0 0 2 .248** .097t .094t

Masculine rhyme oddity .176* .008 . 0 0 1 .216** .037 .088

Phoneme deletion .063 .067 .003 .132* .177** . 0 0 1

Vowel replacement .105t .203** .028 .421*** .096t .084

Consonant replacement .072 .242** .106t .090* .115* .109t

Phoneme analysis . 2 2 1 ** .064 .015 .388*** .004 .047

Phoneme blending .328*** .1 1 2 * . 0 0 2 .320** .032 .084

Comparison of adj. .067 . 0 1 2 . 0 0 2 .096t . 0 0 0 .033

Verb prefixation . 0 1 1 .015 .018 .064 .033 .104t

Diminutives .049 . 0 0 0 .142* . 0 0 0 .039 .058

Derivative forms .140* . 0 1 1 .062 .074 .007 .068

Rapid pict. naming .165* .019 .028 .208** .195** .186*

Rapid digit naming .258** .047 . 1 0 2 t .363*** .377*** .144*

Semantic fluency . l i l t . 0 0 2 .097t . 0 0 1 .052 .159*

Alliteration fluency .324*** .149* .1 0 2 t .279** .187** .003

Feminine rhyme fluency .232** .050 .077 .273** .080t .007

Masc. rhyme fluency .105t .005 . 0 1 0 .1 1 2 t . 0 0 1 .005

Visual memory test . 0 0 0 .007 .109t . 0 0 0 .014 .016

Copying Rey figure acc. .005 .092t . 1 1 2 t .008 .019 . 0 0 0

Accuracy of letter discr. .026 .005 .388*** . 0 0 1 .065 .062

Accuracy of symb. discr. .004 . 0 1 0 .025 .008 .059 .013

copying Rey figure spee. .068 . 0 0 1 .095 .044 .078 .013

Speed of letter discr. . 0 1 0 .034 . 0 0 0 .041 .059 .067

Speed of symbol discr. .051 . 0 0 1 .037 .119t .003 . 0 0 0

Letter naming accuracy .726*** .098t .003 .557*** .249** .005

Letter naming speed .406*** .053 . 0 0 2 .703*** .491*** .189*

Table 7-19. Results of hierarchical regression analyses predicting word reading, carried out separately for each grade. *** p<.001; ** P<.01; * p<.05; t p<10

257 It is noticeable, first of all, that the strength of most correlations decreased with grade, making it increasingly hard to predict reading reliably. This must partially be an artefact of ceiling effects on a number of measures (including word reading accuracy) after grade 1. However, there were also some exceptions to this general pattern, as well as differences between the two outcome measures (accuracy and speed). grade reading accuracy was predicted very accurately by grapheme naming skills; but their predictive power dropped precipitously in later grades. A less sharp decline was observed for rhyming skills, phoneme analysis and blending, as well as rapid naming. Two more complex phonemic tasks, however (vowel and consonant replacement), as well as alliteration oddity showed the highest predictive power in the 2""^ grade. Finally, some visual processes also appeared important (accuracy of letter discrimination, possibly also visual analysis and memory) yet almost exclusively in grade 3. For word reading speed, the predictive power of grapheme naming accuracy, rhyming skills, as well as phoneme analysis and blending was also limited mainly to the grade. Again, some complex phonemic tests (phoneme deletion, consonant replacement) and alliteration oddity increased their input in the 2""' grade. But (unlike in the case of reading accuracy) tests of naming remained significant predictors at all three grade levels, although their input decreased steadily. Among phonological awareness

measures, alliteration oddity also maintained its significant role until the 3"'^ grade, being most important in the 2"'' grade. Correlations between reading scores and the morphological test did not exhibit any clear-cut age-related pattern. The initial progress in reading was, then, constrained very tightly by the mastery of alphabet and digraphs and by phonological awareness skills (particularly analysis and blending). This outcome fits the hypothesis of an initial alphabetic phase, where reading is based on sounding out and blending of individual letters. Basic prerequisites of such sequential decoding (grapheme knowledge, analysis, blending) are typically fully mastered by the end of 2"^* grade, and cease to constrain further reading development. At this point reading probably becomes an autonomous, encapsulated process. The sizeable contribution of rhyme-level skills to first grade reading (masculine and feminine rhyme oddity, rhyme fluency) suggests that early decoding is based not only on forming and activating grapheme-phoneme mappings, but also involves larger, intrasyllabic and suprasyllabic units. As the role of rhyming skills mostly disappears

258 after the 1" grade, they are probably not involved in the development of the orthographic skills (contrary to the hypothesis of Wimmer & Hummer, 1994). As expected, rapid naming skill was the strongest predictor of reading speed at every grade level. It was also highly significant for reading accuracy, yet only at the early (grade 1) phase. This differential pattern must be interpreted cautiously, however, as it may just reflect the ceiling effect on the accuracy of word reading after grade 1. A contribution of visual skills to reading accuracy which appeared relatively late (S'"" grade) was unexpected. It is usually proposed that the role of higher-order visual processing for reading (if any) is confined to the earliest stages of acquisition (Satz et. al., 1978; Willows & Kruk, 1993). The finding is likely to be a statistical artefact; visual discrimination accuracy and visual memory (“Chinese letters” test) were at ceiling in grade 3, and so was reading accuracy. Also, none of the visual test reliably predicted reading skill in general, across-grades regression analyses reported previously. Although non-parametric analyses (which compared visual skills of the best and worst readers in each grade) brought results consistent with the multiple regressions reported above, the effect sizes of the observed differences were very small. However, accuracy of speeded discrimination of non-pronounceable letter strings clearly warrants further investigation, especially as it also emerged as a significant predictor of spelling (see section 7.5.1.1.). It is plausible that this task taps into some aspect of orthographic processing.

7.6. SUMMARY AND CONCLUSIONS

Analyses presented in this chapter supplemented earlier explorations of reading and spelling processes (chapter 6) in two ways. Firstly, they showed the impact of literacy acquisition on the development of other linguistic skills. Secondly, they identified the linguistic skills that were likely to be critical for literacy development. Factorial analyses of phonological skills showed fundamental division between two main components: ability to attend to and analyse sound structures (phonological sensitivity and awareness) and ability to retrieve verbal labels efficiently (rapid naming and verbal fluency). This division seems to be a universal property of the phonological system, since it has been consistently reported in several other languages (see Wagner & Torgesen, 1987; Wolf & Bowers, 1999 for reviews). Most tests of phonological sensitivity and awareness turned out to constitute a single dimension, which was, moreover, inseparable from other ‘analytical’ linguistic

259 skills (morphological awareness in particular). This could be seen as the evidence for a unitary (meta)linguistic ability, which encompasses different linguistic domains (phonology, morphology, syntax, etc.). I would, however, opt for an alternative interpretation: distinct types of linguistic awareness do exist, each tied with a different domain of language (phonology, morphology, syntax, semantics-pragmatics), yet they share some common prerequisites and components, such as sufficient vocabulary knowledge or ability to de-centre and objectify language (cf. Tunmer & Neasdale, 1992). The evidence for partial dissociation of phonological from morphological awareness came in two ways in my study. First of all, they showed different trajectories of growth: most phonological tasks developed most rapidly during grade 1; morphological skills, on the other hand, showed largest gains later, in grades 2 and 3. Secondly, mainly phonological, and not morphological tasks were predictive of reading and spelling. My data showed little evidence for the decomposability of phonological awareness itself, according to the type of phonological units (rhymes vs. phonemes) or the complexity and explicitness of the required mental operation (detection vs. segmentation vs. manipulation). Although task difficulty did vary as a function of phonological units and of complexity, all tests showed a similar growth curve, most loaded on the same factor and were largely equivalent as predictors of literacy success. This outcome should be interpreted from a developmental perspective. Even the youngest children in my sample had already received several months of systematic reading instruction. This should have restructured their phonological representations into a more segmental, better-specified format (Elbro, 1996). As a consequence, children probably adopted a similar, phoneme-based strategy of dealing with all phonological awareness tasks, also those involving rhymes. Had the same skills been tested in a pre-school sample, dissociations corresponding to task complexity or phonological unit-size would probably be observed. Phonemic analysis and blending did emerge as a factor separate from other phonological skills, which was unexpected. This may be an artefact of a near-ceiling effect on both measures. However, analysis and blending were also found to contribute unique variance to the prediction of reading over and above other phonemic tasks, which suggests that they tapped into a different underlying domain. It is plausible that my phoneme analysis and blending tasks measured literacy skills per se (especially oral spelling) apart from phonemic awareness.

260 Comparative Polish-English analyses consistently found my participants to perform poorly on input and (particularly) output rhyming skills, regardless of the size of the rhyme unit (masculine, feminine). This weakness was specific to rhymes and not other phonological units. Three possible explanations of this pattern may be put forward. The first invokes phono-statistic properties of the language: there are fewer rhyming words in Polish than in English. This explanation, however, would apply only to the masculine rhymes, yet the feminine rhymes (very frequent in Polish) were also processed poorly. The second explanation is socio-linguistic: Polish children are less exposed to rhyming activities than their English peers. However, Polish does possess a rich tradition of nursery rhymes, and children’s creative use of rhyme in poems, games and verbal banter (employing mainly suprasyllabic structures) is also well documented (Cieslikowski, 1974, 1991). The school curriculum of my participants also included listening to, reading and even rote-learning of rhyming poetry. Although it is plausible that the acquaintance with rhymes is less extensive for Polish than for English-speaking children, this difference (which, in any case, is difficult to quantify) is likely to account for only a fraction of the ‘poor rhyming’ effect. The third hypothesis, which emphasises the link between rhyming ability and the experience of learning to read, may account for most. Even if sensitivity to rhymes (evident in rhyme oddity tasks) emerges early and spontaneously (Goswami &, Bryant, 1990) it is probably enhanced by the experience of learning to read, especially by explicit tuition on correspondences between phonological and orthographic rhymes. Such tuition is usually not given in Polish; rhymes are generally treated as a phenomenon on its own, and not tied systematically with the teaching of alphabetic or orthographic skills.

Analyses of concurrent relationships between literacy and other cognitive skills (section 7.5) were complementary to previous analyses of literacy (chapter 6) in providing information about “cognitive underpinning” of early reading and spelling. In the case of reading (for which more reliable data are available), two sets of predictors were consistently identified: phonological awareness (particularly phoneme detection, segmentation and manipulation) and efficiency of verbal code retrieval (indexed especially by rapid naming tasks). Each was shown to account for some unique aspect of literacy. There was, however, little evidence for the original hypothesis of phonemic awareness and rapid naming as specific predictors of alphabetic and orthographic skills,

261 respectively. A simpler dissociation was observed, whereby phonemic awareness was a better predictor of reading accuracy (of words and nonwords alike) while rapid naming was better at predicting reading speed. Partial dissociation between accuracy-related and speed-related predictors was also found with the grapheme naming task. It must be remembered, however, that speed and accuracy of reading correlated very strongly, and their predictors also showed a large degree of overlap. Phonemic awareness and code retrieval abilities seemed both necessary for accurate as well as fast reading, and the observed dissociations were only a matter of degree. Between-grade changes in predictors of reading (section 7.5.4.) were compatible with the two-phase model of reading acquisition proposed in chapter 6. The first, basic alphabetic, phase (which typically covers the T' grade) involves establishing basic word decoding skills. Sequential decoding constitutes the core learning mechanism, allowing for gradual accumulation of lexical knowledge. The proximal requirements for decoding are letter knowledge together with analysis and blending skills; the distal requirements are phonological awareness and phonological retrieval processes. The second, advanced alphabetic and orthographic phase involves the acquisition of more complex rules and mappings of the orthographic system, expansion of lexical knowledge, as well as automation of lower level decoding and recognition processes. It is also characterised by growing independence of reading from its lower-level cognitive prerequisites. This last claim is proposed with caution, however, as it requires further empirical support. It is indeed possible that reading requires only certain sufficient levels of phonological awareness and retrieval efficiency. Once these are reached, reading can progress freely, becoming increasingly modular by its own specific storage and processing mechanisms. However, it is also possible that phonological awareness and code retrieval continue to constrain reading progress for ever, yet the relationship was hard to detect in my study, given the ceiling effects on my outcome measures of reading. This is likely since the grade-related decrease in predictability of reading from phonological awareness and rapid naming was greater for reading accuracy (where the ceiling effect was strong) than for reading speed (where it was much smaller). Future research may clarify this

ambiguity by using more sensitive measures of reading skill, possibly a reading rate index.

262 CHAPTER 8

THE COGNITIVE PROFILE OF DYSLEXICS AND POOR READERS

In the following chapter 1 shall investigate the performance of those participants who were identified with different forms of reading difficulties. This is intended to be a complementary way of approaching the central problem of discerning cognitive- universal and language-specific constraints of written language acquisition; the problem which in the previous chapter was analysed in relation to the whole, unselected, sample. In chapter 4 the evidence was reviewed that symptoms, and possibly mechanisms of dyslexia, are orthography-specific. Dyslexies struggling to acquire an inconsistent orthography are typically characterised by very poor word decoding skills, although their speed of reading is usually also compromised. These problems are strongly associated with a double deficit of poor phonological awareness and slow naming. Dyslexia in a consistent orthography however, is primarily the problem of low reading speed and low naming speed. Reading accuracy and phonological awareness skills are usually quite satisfactory, although they may be somewhat lower than in normal readers. These differences may be explained by a direct influence of orthographic consistency. Consistent mappings may simply provide less opportunity for reading and spelling errors (Upward, 1992) and facilitate segmental awareness, even if individual cognitive prerequisites of such awareness are poor. However, this explanation only accounts for differences of symptoms, but does not settle whether the causes of dyslexia vary between the orthographies. Two alternative views may be proposed here. The

''cognitive relativity'' view would maintain that the causes and mechanisms of reading failure differ between orthographies, even though the general requirements of good reading are always the same (breaking the code and automatizing sound-symbol mappings). The same underlying cognitive weakness may or may not lead to reading failure, depending on the orthographic complexity. This applies particularly to phonological awareness: any potential difficulty in accessing the segmental structure of speech (and bringing this knowledge into decoding) may develop and cause reading problems only in the context of the inconsistent orthography; in the consistent one it is 263 ‘worked through’ and disappears. The cognitive problems underlying poor naming ability are probably of more universal importance, affecting the automatization of reading skills in shallow and deep orthographies alike. The implication of this view is that some children starting off with the same poor ‘cognitive endowment’ would become dyslexies in one orthography, but not in the other.

The alternative “cognitive invariance’’’ view would maintain that dyslexia has the same causes in all orthographies - the deficit of either phonemic awareness or of rapid naming, and typically the combination of both. Orthographic consistency plays a more peripheral role, affecting mainly the symptoms of reading difficulties. Initial problems with phonemic awareness, even if overcome quickly, have long-term deleterious consequences for reading progress. Whether it is low accuracy or low speed that is the dominant symptom depends on orthographic consistency, but also on the “proportion” of the two basic deficits, or their severity (with milder impairments compromising reading speed, but not reading accuracy). This view implies that the same children would become dyslexic in every orthography, although their dyslexia could manifest differently. It remains uncertain whether cross-orthographic differences in dyslexic profiles observed so far are not the artifact of selection procedures. As the consistent orthography readers vary little in terms of reading accuracy, researchers tend to select poor performers using the speed criterion. This, however, may prejudge the findings. A recent study of Wimmer, May ringer & Landerl (1999) suggests that both inaccurate and slow readers can be identified in a consistent orthography - providing that the appropriate selection criteria are used - and their cognitive profiles are partially different. The present sample provides the opportunity of addressing those issues. The Polish children (unlike their highly accurate German peers investigated by Wimmer, 1993) varied on both speed and accuracy of word reading. It was, therefore, decided that low speed and low accuracy dyslexies would be independently selected and contrasted. A number of specific hypotheses were made. Firstly, it was expected that relative consistency of the Polish orthography and systematic phonics teaching should result in a good level of word decoding and phonological awareness skills, even among the poorest readers. Therefore, I expected to find rather few low accuracy dyslexies who were not deeply impaired. Two contrasting predictions were made regarding the causes of dyslexia. If the same cluster of deficits underlies most dyslexic cases, then speed and 264 accuracy difficulties should co-occur, giving high degree of overlap between low accuracy and low speed groups. Cases diagnosed as ‘low speed only’ dyslexia would represent the milder end of the same double deficit continuum. Conversely, if word decoding accuracy and speed are both contingent on different underlying abilities (respectively, phonological awareness and efficient activation of symbol-sound connections) then little overlap between the two dyslexic groups should be found, and each should be characterised by a different single deficit.

8.1. IDENTIFYING DYSLEXIC CASES.

A discrepancy-based definition of dyslexia was initially adopted: reading performance had to be poorer than one could predict given the child’s intelligence. Reading- intelligence discrepancy was operationalized in two ways. The ‘simple discrepancy’ criterion was based on absolute difference between Z-transformed reading and intelligence scores. The ‘regression discrepancy’ criterion used a regression equation predicting reading from intelligence, which allowed the identification of outliers showing exceptionally large difference between expected and obtained reading scores. As the two selection criteria differed only in secondary psychometric properties it was expected that they would identify mostly the same cases. Raw scores on three variables: word reading accuracy, speed, and WISC-R Vocabulary were transformed into Z-scores, separately for each grade. The vocabulary subscale of the Wechsler test was taken as an estimate of overall verbal intelligence and was the basis for computing the intelligence-reading discrepancies. Although a more reliable index of nonverbal IQ was available (Columbia) it was not used as it showed weaker correlations with reading indices than the Vocabulary scale (this finding is consistent with numerous studies showing reading to be more strongly linked with verbal than nonverbal intelligence). It was further assumed that dyslexia would be identified in grades 2 and 3 only, whereas the T' grade group would serve as a source of reading-age controls. Initially, rather strict cut-off criteria for dyslexia were adopted: a discrepancy of at least two standard deviations (SD) was required (based on actual or expected scores for the simple and the regression criteria, respectively); moreover, the reading score had to be at least one SD below the grade mean. The simple discrepancy identified 3 low accuracy and 3 low speed dyslexies. The regression-based discrepancy found 5 low 265 accuracy and 3 low speed dyslexies (see table 8-1). The degree of overlap between the simple and the regression-based criteria was satisfactory only for the low accuracy cases; with low speed dyslexia, different subjects were identified with each procedure. This was probably due to low reliability of regression-based discrepancies: only one out of four correlations that they were based on was actually significant.

Low accuracy dyslexia Low speed dyslexia simple regression-based simple regression-based discrepancy discrepancy discrepancy discrepancy

Criteria reading accuracy Z- reading accuracy Z-score reading speed Z- reading speed Z- score score more than 2SD more than 2SD (standard score more than more than 2SD (standard below Vocabulary errors of prediction) below 2SD below errors of prediction) Z-score the score predicted by Vocabulary Z-score below the score predicted Vocabulary Z-score by Vocabulary Z-score reading accuracy score more than ISD reading speed score more than ISD below grade mean below grade mean Identified 39 M 39 M 43 M dyslexic 49 M 49 M 87 F subjects 73 M 90 M (case number, 75 M 75 M 91 F gender) 93 M 93 M 103 F

Table 8-1. Criteria for identifying dyslexia and the list of identified children.

The small number of identified dyslexies limited the possibilities of statistical analyses. Therefore, I decided to relax the discrepancy criteria and require only ISD difference between reading and verbal intelligence scores. That not only increased the number of subjects identified as dyslexies, but also brought higher overlap between the two identification procedures (see table 8-2). As the simple discrepancy criteria appeared more conservative, only the subjects that fell within their limits were treated as dyslexies in the following analyses.

266 Low accuracy dyslexia Low Speed dyslexia simple regression-based simple regression-based discrepancy discrepancy discrepancy discrepancy

Criteria reading accuracy Z- reading accuracy Z-score reading speed Z- reading speed Z- score score more than ISD more than ISD (standard score more than more than ISD (standard below Vocabulary errors of prediction) below 2SD below errors of prediction) Z-score the score predicted by Vocabulary Z-score below the score predicted Vocabulary Z-score by Vocabulary Z-score reading accuracy score more than ISD reading speed score more than ISD below grade mean below grade mean Identified 39 M 39 M 43 M 43 M dyslexic 43 M 55 M subjects 49 M 49 M 70 M 70 M number, 52 M 73 M gender) 73 M 73 M 87 F 87 F 75 M 75 M 90 M 90 M 88 M 88 M 91 F 91 F 93 M 93 M 93 M 93 M 95 M 95 M 95 M 103 F 103 F

Table 8-2. ‘Relaxed’ criteria for identifying dyslexia, with the lists of identified children.

Overall, some 4% or 10% of subjects were identified as low accuracy dyslexies, depending on the strictness of the criteria. The incidence estimates of low speed dyslexia were very similar. The two conditions however, showed only a small degree of overlap (only one child, boy 93, met both speed and accuracy criteria). Low accuracy dyslexia occurred only in boys, whereas low speed dyslexia showed a more even gender balance. The distinctness of the two conditions was also evidenced by the fact that two low accuracy dyslexies qualified as normal controls in terms of reading speed; conversely, one low speed dyslexic was a control for the low accuracy condition. Low speed and low accuracy dyslexia groups were separately matched with chronological-age and reading-level controls. The chronological age controls (or same- grade controls, more precisely, since a very close match on chronological age was not always possible) had to exhibit average or good reading scores (no worse than half SD below grade mean); additionally, their reading scores could not fall more than half SD below their vocabulary scores. The reading-level controls were 1st graders matched on reading accuracy or speed, respectively. Since low accuracy dyslexies were all boys, only male controls were matched with them, but children of both sex were included as

267 controls for low speed dyslexies. Accuracy and speed control groups overlapped partially. The selection criteria and the basic characteristics of all groups are summarised in tables 8-3 and 8-4.

Low accuracy dyslexia Chronological-age controls Accuracy-level controls

Reading accuracy score lower than Boys only. Reading accuracy score no r ' grade boys only. Reading ISD below grade mean; reading lower than 0.5 SD below grade mean accuracy raw scores close to that accuracy Z-score more than 1 SD and no more than 0.5 SD below obtained by low accuracy below Vocabulary Z-score Vocabulary Z-score dyslexies

N =7 N =23 N =10

2"‘‘ grade: 3 2"‘' grade: 12 all 1" grade

3"^ grade: 4 3'^* grade: 11 all m ale mean min max mean min max mean min max age: 9;3(10) 8;8 9;8 age: 8; 10(5) 7;10 10;4 age: 7;8(23) 7;3 8;1

read, accur. Z score: read, accur. Z score: read, accur. Z 0.1 1.0 score: -2.1 -2.8 -1.5 0.5 -0.3 1.0 0.5 vocabulary Z score: vocabulary Z score: vocabulary Z score: 0.1 -1.5 1.5 0.0 -1.2 1.2 -1.3 2.8 0.8

Low speed dyslexia Chronological-age controls Speed-level controls

Reading speed score lower than 1 SD Reading speed score no lower than 0.5 T‘ grade children with reading below grade mean; reading speed Z- SD below grade mean and no more speed raw scores close to that score more than 1 SD below than half SD below Vocabulary Z- obtained by low speed dyslexies Vocabulary Z-score score

N =7 N =36 N =10

2"^* grade: 3 2"*^ grade: 12 all 1" grade

3'^* grade: 4 3'^* grade: 11 m ale: 4 male: 19 male: 6 fem ale: 3 female: 17 female: 4

mean min max mean min max mean min max age: 9;3(25) 7;12 9;11 age: 9;1(18) 8;2 10;9 age: 7;7(3) 7;0 8;1

read, speed Z score: read, speed Z score: read, speed Z score:

-2.1 -4.0 -1.2 0.7 0.0 1.2 0.6 -0.2 1.2 vocabulary Z score: vocabulary Z score: vocabulary Z score:

0.0 -1.5 0.9 -0.2 -1.8 1.1 -0.3 -1.3 1.1

Table 8-3. Selection criteria and basic characteristics of dyslexic and control groups. Z scores are relative to a grade level. 268 Although no attempt was made to equate all groups on verbal intelligence, a good match was actually obtained (see table 8-4). Dyslexies and controls showed very similar standard vocabulary scores, while the raw scores were, expectedly, lower in the younger reading level controls (the difference significant only for the reading speed comparison). In terms of reasoning skills (Columbia test) low accuracy dyslexies performed somewhat poorer than both control groups; this trend fell short of significance. Although almost no overlap was observed between low accuracy and low speed

dyslexia on the level of individual cases, the symptoms of inaccurate and slow decoding co-occurred to some extent. Low accuracy dyslexies tended to be somewhat slower than the same age-controls; conversely, low speed dyslexies were somewhat less accurate.

Chrono­ Low accuracy Accuracy Chrono­ Low speed Speed-level logical age dyslexia level logical age dyslexia controls controls controls controls N=23 N=7 N=10 N=7 N=36 N=10 Mean t Mean t Mean Mean t Mean t Mean (SD) (SD) (SD) (SD) (SD) (SD) Word reading 98 7.652*** 85 88 97 2 .1 19t 92 86 accuracy (%) (2) (4) (6) (5) (6) (11) Word reading 1.19 2.560* 1.87 2.690* 4.72 .88 4.864** 2.90 3.34 time (secs/word) (.73) (.79) (.22) (1.70) (1.86)

Vocabulary (raw 29.78 30.29 26.44 28.53 30.14 2.969* 19.67 score ) (5.98) (7.%0 (7.13) (6.16) (8.05) (&%%

Vocabulary a) 12.91 12.43 13.89 12.11 12.57 11.33 (standard scores) (1.63) (2.51) (2.98) (3.41) (2.92) Columbia (raw 53.74 50.43 52.00 53.17 52.00 51.30 scores) (4.13) (6.85) (4.47) (5.40) (3.68)

Columbia b) 109.2 101.3 1.836t 111.1 107.5 104.4 110.3 (standard scores) (7.70) (11.86 (9.22) (9.75) (7.11) (8.26)

Table 8-4. Word reading and intelligence tests scores in dyslexies and controls. All t-test comparisons between the dyslexies and controls significant at the level p< .10 are listed.

t p<.10 * p<.05 ** p<.01 *** p<.001 a) Vocabulary standard scale: mean=10, SD=3

b) Columbia standard scale: mean=100, SD=15

Table 8-5 presents information on the educational background of the parents of the children investigated here. A full range of possible backgrounds was observed, but the highest number of parents (33%) had degree-level qualifications. This number is higher than the national average, reflecting predominantly middle-class social composition of the school catchment area. Chi-square comparisons revealed no significant differences

269 in parental education of dyslexies and chronological-age controls (although dyslexies’ parents seemed over-represented in the lower, vocational qualification, category). Reading-level controls tended to have better-educated parents than the children from the two older groups; that difference was significant between low accuracy dyslexies and accuracy matched controls (Pearson chi-square = 6.854, p<.05). However, social deprivation as a reason for unexpectedly poor reading achievement can be ruled out at least in the majority of cases 1

Education low accuracy chronological accuracy dyslexia age controls matched controls primary only - 0% 1 3% - 0% vocational 6 43% 9 24% 1 5% secondary (A-levels) 3 21% 13 35% 6 32% higher education (a university degree) 5 36% 14 38% 1 2 63%

missing information - 9 1

N 14 46 20 low speed chronological speed matched dyslexia age controls controls primary only - 0% 2 4% - 0% vocational 4 31% 13 24% 3 21% secondary (A-levels) 5 38% 21 38% 4 29% higher education (a university degree) 4 31% 19 35% 7 50% missing information 1 17 6

N 14 72 20

Table 8-5. Educational background of participants’ parents.

It must be remembered that the criteria for identifying dyslexia I adopted were purely psychometric. Consequently, my diagnosis did not always overlap with that given by two psychologists working at the school. They used more clinical and qualitative assessment, monitoring children’s progress longitudinally from the beginning of grade one, obtaining information from teachers and analysing samples of children’s own work. Children they diagnosed with some form of reading difficulties were referred to special needs classes. 6 out of 13 children I identified as dyslexic used this form of

' School psychologists reported ‘particularly difficult home situation ’ in the case of one low speed dyslexic boy, and one chronological-age control girl. 270 provision (3 low accuracy cases, 2 low speed ones, and the only child with both difficulties). However, only two of those six cases warranted an unequivocal diagnosis of dyslexia according to the school psychologists. In the remaining four they found some degree of cognitive, perceptual or motor deficits they considered typical of dyslexia, confounded with low IQ (two cases) and a disadvantaged home background (one case). Conversely, among 43 children I treated as chronological age controls 10 were attending special needs classes and 3 were diagnosed as dyslexic by the school psychologist. The term ‘dyslexia’ I am going to use in the following analyses does not, therefore, aspire to the clinical validity, it is merely a shorthand for reading skills that (in a single assessment) turned out to be unexpectedly low, given chronological age and mental ability.

8.2. COGNITIVE PROFILE OF DYSLEXIC CHILDREN.

A series of t-tests were carried out in order to compare the performance of dyslexic and control children on all cognitive measures. Tables 8-4 and 8-6 present the descriptive and t-test statistics. The significant differences are summarised in table 8-7.

271 Chronological age Low accuracy Accuracy level Chronological Low speed Speed level controls dyslexies controls age controls dyslexies controls N=23 N=7 N=10 N=36 N=7 N=10 Mean t Mean t Mean Mean t Mean t Mean SD SD SD SD SD SD 'Jonword reading 78 5.041** 47 2.559* 70 77 65 66 (14) (13) (21) (15) iccuracy (21) (21) '^onword reading time 2.11 1.958t 2.69 2.350* 5.01 1.73 4.650** 3.80 3.71 (1.06) (.78) (2.77) (.42) (1.66) (1.47) Digit Span (raw) 8.22 7.86 7.33 8.44 8.43 7.22 (1.93) (2.41) (1.12) (1.56) (1.72) (1.09) Digit Sp. (standard) 9.14 8.14 9.44 9.14 8.86 9.56 (2.40) (1.13) (2.00) (2.27) (1.24) 'lonword repetition 20.26 2 .1 1 5 t 16.86 19.89 19.71 19.14 20.22 (3.77) (3.72) (4.40) (3.95) (4.78) (3.87) Alliteration oddity 27.78 23.57 24.10 28.17 24.86 25.00 (3.06) (7.32) (4.84) (3.64) (4.37) "eminine rhyme oddity 20.52 20.29 18.11 20.44 3.007* 14.57 1 .961t 18.78 (6.81) (7.76) (2.57) (6.04) (4.43) (4.02) Vlasc. rhyme oddity 23.39 21.14 22.56 22.08 20.71 20.67 (5.78) (3.76) (6.00) (5.23) (5.62) (5.29) ^honeme deletion 21.48 17.86 15.56 21.43 19.43 16.11 (2.83) (6.57) (3.51) (3.76) /owel repl. 38.91 2.394* 28.29 32.90 37.89 35.57 34.90 (7.84) (10.92) (11.08) (7.55) (10.49) (10.08) Consonant repl. 36.43 3.019* 26.14 27.22 31.67 31.43 26.44 (5.89) (8.41) (5.29) (8.64) (5.77) (5.55) ^honeme analysis 16.82 17.43 1.874t 14.67 16.80 17.14 16.22 (L%0 (.79) (1.66) (1.46) (2.54) ^honeme blending 15.22 ].8 2 9 t 16.86 2.0144 12.89 15.17 2.776* 17.14 1 .826t 15.00 (3.54) (1.35) (5.71) (3.26) (1.21) (3.24) Comparison o f adj. 46.78 41.57 42.00 45.56 1.867t 50.86 3.716** 36.00 (12.11) (10.47) (10.62) (12.00) (5.34) (10.36) l/erb prefixation 44.35 43.17 37.3 46.39 42.14 37.11 (16.24) (14.16) (19.77) (14.1) (17.59) (18.33) Diminutives 57.43 53.29 53.44 58.14 58.71 3.763** 47.89 (4.12) (8.28) (8.17) (3.17) (3.73) (7.52) Derivative forms 37.00 36.33 36.00 38.14 38.43 2 .0 0 9 t 28.90 (9.15) (10.56) (9.51) (9.90) (9.36) (9.99) ^apid pict. naming 93.17 97.57 101.67 85.22 2 .0 8 4 t 96.29 100.7 (17.22) (18.51) (16.90) (15.33) (13.39) (10.91) tapid digit naming 60.57 66.29 71.22 55.42 2.491 * 69.57 67.33 (14.22) (12.72) (13.18) (12.11) (15.52) (12.01) jraph. naming speed .68 .71 1.8934 .93 .63 2.790* .86 .88 (.16) (.17) (.26) (.12) (.23) (19) Grapheme naming acc. 96 97 2.691* 89 98 94 2 .1 4 6 t 86 (4) (02) (8) (2) (V) (8) Semantic fluency 21.26 18.29 20.11 22.31 20.57 17.22 (4.21) (3.95) (5.84) (4.27) (3.87) (6) Alliteration fluency 12.17 12.14 9.44 13.25 11.86 9.67 (2.53) (4.98) (2.96) (3.05) (3.67) (2.96) ^eminine rh. fluency 3.04 3.17 3.63 3.60 3.00 2.44 (1.97) (2.79) (2.88) (1.97) (2.24) (1.88) Masculine rh. fluency 2.78 2.83 2.67 2.83 2.71 3.00 (1.94) ... (2.43) (1.32) (2.06) (2.14) (2.12) Visual m em ory 21.22 20.00 21.00 21.11 21.00 20.88 (2.39) (1.41) (2.31) (1.41) (1.25) ley figure accuracy 26.65 25.50 26.00 27.00 25.86 24.61 (4.20) (5.14) (4.11) (3.61) (5.40) (3.67) .etter discrim, accur. 93.0 87.5 2.0924 94.4 94.4 90.6 93.8 (9.(0 (7.6) (4.9) (7.8) (7.4) (5.4) lymbol discrim, accur. 90.0 89.8 95.8 90.3 89.8 93.1 (6.0) (7.6) (5.4D (6.1) (8.0) (5 8) ley figure time 303.2 1.858t 214.0 246.7 247.3 205.6 195.6 (177.0) (48.96) (104.1) (138.7) (43.98) (58.51) fetter discrim, time 2.7 2.34 2.625* 4.12 2.57 2.81 4.28 (1.14) (.79) (1.48) (99) (.6% #1% ymbol discrim, time 3.07 2.54 3.24 2.87 2.75 2.92 (.91) (86) (1.0) (.8) (9 1 ) (1.17)

Table 8 -6 . Performance of dyslexies and controls on individual cognitive tests, t p<.10 * p<.05 ** p<.01 *** p<.001

272 Low accuracy dyslexies Low speed dyslexies

worse than reading level controls nonword reading accuracy 2.559* feminine rhyme oddity 1.961f letter discrimination accuracy 2.092f worse tllan chronoi'ogical age controls word reading accuracy 7.652*** word reading time 4.864** nonword reading accuracy 5.041** nonword reading time 4.650** consonant replacement 3.019* feminine rhyme oddity 3.007* word reading time 2.560* grapheme naming speed 2.790* vowel replacement 2.394* rapid digit naming 2.491* nonword repetition 2.115f rapid picture naming 2.084f nonword reading time 1.958t better than reading level controls grapheme naming accuracy 2.691* comparison of adjectives 3.716** word reading time 2.690* Vocabulary (raw scores) 2.969* letter discrimination time 2.625* grapheme naming accuracy 2.146f derivative forms 2.009f nonword reading time 2.350* phoneme blending 1.826t phoneme blending 2.014f grapheme naming speed 1.893f phoneme analysis 1.874t better than chronological age controls phoneme blending 2.014f phoneme blending 2.776* phoneme analysis 1.874f comparison of adjectives L867f

Table 8-7. Summary of significant differences between dyslexies and controls.

The two types of dyslexia exhibited a rather distinct cognitive profile. Low accuracy dyslexies showed an apparent decoding deficit: their nonword decoding accuracy was significantly lower in comparison with both chronological age controls (by 31%) and younger word reading matched controls (by 23%)\ Consistently with this outcome, low accuracy dyslexies performed poorly on some phoneme manipulation tests (in comparison with same-age controls). Although they were also slow readers for their age, they read more quickly than younger accuracy-matched controls, and showed no apparent problems on any measures of processing speed. This suggests that speed- related problems are neither a primary cause nor symptom of those readers. Instead, the

^ This statement needs to be qualified, however. Dyslexic were administered longer nonword list than younger reading level controls. When the comparison was restricted to the shared set of 20 stimuli dyslexies were still less accurate than younger controls (56% vs 70%) but the difference was no longer significant (t=1.611, p=.131). The 14% discrepancy is, however, robust enough to justify our conclusion of decoding deficit in low accuracy dyslexia; lack of significance may be attributed to low N. 273 observed cluster of problems can be characterised as developmental phonological dyslexia. An expected beneficial effect of orthographic consistency on decoding accuracy turned out to be limited. Dyslexies identified in this study were indeed relatively accurate on word reading (between 80-90%), much better than English and French dyslexies, and nearly as good as Spanish, German Dutch, Czech or Greek ones (see chapter 3, table 3-2). On the nonword decoding task, however, the Polish dyslexies performed very poorly (accuracy between 28-63%). This outcome may be slightly better than in English studies (which usually showed numerically similar levels of nonword reading accuracy, yet used easier, one-syllable stimuli) but it is clearly worse than in consistent orthography studies. German, Spanish, Greek, Dutch and Czech dyslexies typically read nonwords with 70-90% accuracy - similarly to, or better than the Polish younger reading level controls. The picture of “low speed” dyslexia was different. The difficulties lay primarily in the area of speed and fluency; no significant phonological awareness problems were observed (with the possible exception of feminine rhyme oddity). Most importantly, low speed dyslexies did not show the profile of deficiency, but of developmental lag: they were not significantly worse than the younger reading-level matched controls on any task, though they did show a number of delays in comparison with the same-age controls. The low speed group, therefore, had little in common with the syndrome of phonological dyslexia. It rather resembled the low speed dyslexies described by Wimmer (1993), although they exhibited the true decoding speed deficit (apparent in reading age, not only chronological age comparisons). Neither dyslexic group identified here showed any problems with phonological analysis and blending or grapheme knowledge. Older children (normal and dyslexic) tended to outperform younger controls on these tasks, suggesting that their mastery is constrained primarily by ‘external’ factors of learning experience. Why the dyslexies also tended to be better at phoneme analysis and blending than the same-age normal readers is less clear. Perhaps it reflects the predominant reading strategy of dyslexic children: sequential sounding out and blending of individual graphemes, instead of parallel processing of larger orthographic units. The pattern emerging from previous analyses may be difficult to discern as it involves a large number of individual comparisons. To make the similarities and differences between low speed and low accuracy dyslexia more clear, data reduction 274 was attempted. It was shown in the previous chapter (section 7-2) that a 5-factor solution could satisfactorily describe my test battery; with three factors (General Linguistic, General Speed and Fluency, Analysis and Blending) accounting for the largest share of variance. Moreover, only a few individual tests were able to capture most variance shared between the whole large test battery and the outcome measures of reading and spelling. This justified the use of composite scores. Three such scores were computed for each dyslexic child, representing the three largest factors. Each composite was an average of two or three tests that showed the highest correlation with reading among the tests loading on a particular factor. The raw scores on each test were Z- transformed (separately for each grade) and the Z-scores were used to form the composite. The results of both dyslexic groups are presented in table 8-8. Composite reading accuracy and speed scores are also given for the purpose of comparison. Figure 8-1 illustrates the differences between dyslexies and controls on all five composites.

LOW ACCURACY DYSLEXIA LOW SPEED DYSLEXIA

Mean Median Min. Max. Mean Median Min. Max. Phonemic awareness -0.54 -0.69 -1.81 1.02 -0.37 -0.38 -1.27 0.42 composite Rapid naming -0.40 -0.66 -2.02 0.71 -0.57 -0.48 -2.02 0.19 composite Analysis and 0.42 0.20 0.11 0.90 0.40 0.54 -0.75 0.90 blending composite Reading accuracy -1.96 -1.83 -2.84 -1.29 -0.73 -0.48 -2.84 0.98 composite Reading speed -0.70 -0.75 -2.01 0.55 -1.91 -1.34

Table 8 -8 . Scores of dyslexic participants on phonological processing and reading composites Phonemic awareness = mean of alliteration oddity, vowel replacement and alliteration fluency.

Naming speed = mean of picture and digit naming. Analysis & blending = mean of phoneme analysis and blending. Reading accuracy = mean of word and nonword reading accuracy

Reading speed = mean of word and nonword reading speed. All individual test scores were Z-transformed (separately for each grade) before averaging into the composite.

275 0,66 0 ,6 4 0 ,5 4 0 ,5 8 0 ,5 4 0 .5 2 0.5 0,2 0,22 0,2 4 0 ,1 7 111 03r

acv lexi I ed ( ysh xia ca controls-accuracy ca controls-speed

-0.5 -0,48 -0,46 .0 .6 9 0 .6 6 0 ,7 5 0 phonological awareness □ rapid naming □ analysis and blending -1.5 -1 8 4 □ reading accuracy □ reading speed

-2 -1.83

Figure 8-1. The median scores of dyslexies and chronological age controls on the five composites.

The composite scores showed that the cognitive profiles of the two dyslexic groups were actually quite similar; more so than the earlier analyses based on individual tests seemed to suggest. Both groups showed a double difficulty - with phonological awareness and rapid naming - while their analysis and blending skills were quite normal. The main difference seemed to lie in the severity of the difficulties: low accuracy group performed generally worse on all phonological skills composites. There were also some weak indicators of dissociation of group profiles: whereas low accuracy dyslexies performed most poorly on phonemic awareness, low speed dyslexies had lowest scores on rapid naming. The difference was minute, however. The outcome suggests that both types of reading problems tend to occur when a double difficulty - with phonological awareness and rapid naming - is present. The actual symptoms of reading failure are mainly the function of severity of that double difficulty. More severe difficulty results in poor reading that is primarily inaccurate, but also slightly

slow. The double difficulty, which is generally less severe and evident more in the rapid naming domain, results in a reverse set of symptoms (serious slowness, slight inaccuracy).

The limited explanatory power of the cognitive factors must be acknowledged,

however. It is apparent that the dyslexic difficulties in reading and spelling are more serious than the cognitive impairments that are assumed to cause them. The analysis of individual

scores also revealed that some dyslexic subjects showed perfectly normal (higher than average) performance on both phonological awareness and rapid naming composites. Some other cognitive, educational or experiential factors (e.g. reading habits) must, then, also play additional role in bringing about the observed difficulties with written language.

276 8.3. COGNITIVE PROFILE OF POOR READERS

Apart from dyslexies, backward readers (whose poor literacy skills are commensurate with their IQ) were also investigated. They were defined as children whose reading scores fell at least one SD below their respective grade means, but who did not meet the discrepancy criteria. 3 low accuracy and 2 low speed readers were identified this way. As the numbers were small, I decided to merge dyslexic and backward readers groups and rerun the analyses with the new, broader control samples. Chronological age controls had to fulfill the sole criterion of reading no worse than half a standard deviation below the grade mean. Additional subjects were also added to reading level-control groups (see table 8-9). The whole group of poor readers included 19 participants; three children (all boys) met the criteria of both inaccurate and slow reading.

Low accuracy readers Chronological-age controls Accuracy level controls

Reading accuracy score lower than Reading accuracy score no lower than T‘ grade children with reading ISD below grade mean. half SD below grade mean. accuracy scores close to that obtained by low accuracy readers N=10 N=51 N=17 2"*^ grade: 6 2"‘* grade: 25 all T‘ grade grade: 4 3"'^ grade: 26 male: 9 male: 29 male: 10 female: 1 female: 22 female: 7

mean min max mean min max mean min max age: 9;1(18) 7;11 9;8 age: 9;0(8) 7;8 10;9 age: 7;8(12) 7;3 8;3

read, accur. Z score: -2.78 -1.08 read, accur. Z score: -0.28 1.01 read, accur. Z 0.07 0.98 score: -1.86 0.48 0.48 vocabulary Z score: -1.48 1.5 vocabulary Z score: -1.76 2.25 vocabulary Z score: -0.19 -0.25 -1.3 2.82 0.34

Table 8-9. Selection criteria and basic characteristics of poor readers and control groups. Z scores are

relative to a grade level.

277 Low speed readers Chronological-age controls Speed level controls

leading speed score lower than ISD Reading speed score no lower than r ‘ grade children with reading >elow grade mean half SD below grade mean speed scores close to that obtained by low speed readers ^=9 N=48 N=ll grade: 4 2"*^ grade: 24 all 1" grade B"' grade: 5 3"^ grade: 24 nale: 6 male: 30 male: 6 emale: 3 female: 18 female: 5 mean age: 9;3(2) mean age: 9; 1(0) mean age: 7;7(19) mean min max mean min max mean min max

9 ge: 9;3(20) 7;12 9; 12 age: 9;1(18) 7; 12 10;9 age: 7;7(3) 7;0 8;1

read, speed Z score: -3.97 -1.19 read, speed Z score: -0.33 1.22 read, speed Z score: -0.23 1.16 i-1.93 0.55 0.63 vocabulary Z score: -1.48 0.93 vocabulary Z score: -1.76 2.25 vocabulary Z score: i-0.13 0.15 -0.27 -1.3 1.11

Table 8-9 continued

Adding additional subjects did not change the intelligence profile of the sample very much (table 8-10). Poor readers and controls had similar WISC-R Vocabulary standard scores; the absolute levels of vocabulary knowledge (raw scores) tended to be lower in younger controls. Poor readers tended to have lower reasoning skills (Columbia) standard scores than did controls; the difference approached significance with the low accuracy group.

Chronolo­ Low accuracy Accuracy Chronolo­ Low speed Speed level gical age readers level gical age readers controls controls controls controls N=51 N=10 N=17 N=48 N=9 N = ll Mean t Mean t Mean Mean t Mean t Mean (SD) (SD) (SD) (SD) (SD) (SD) Word reading 98 10.276*** 85 87 96 2.262* 91 87 accuracy (%) (2 ) (4) (6 ) (5) (7) ( 1 1 ) Word reading 1.24 3.230** 2.45 2.170* 4.43 1.00 3.993** 2.98 3.34 time (secs/word) (.69) (1.58) (3.16) (.35) (1.48) (1.76) Vocabulary (raw 29.84 28.00 23.56 30.79 28.78 2.945* 20.0 score ) (7.77) (7.78) (6.99) (7.09) (7.48) (5.16) Vocabulary 12.60 11.78 12.88 12.79 12.22 11.4 (standard score) (2.63) (2.82) (2.90) (2.49) (3.07) (2.76) Columbia (raw 53.16 51.70 51.56 53.77 1.819t 50.89 51.36 scores) (4.91) (6.83) (4.02) (5.41) (4.14) ^ 5 0 ) Columbia 107.6 102.6 110.3 108.8 1.875t 102.4 1.9 9 9 t 110.1 (standard scores) (9.59) (11.92) (8.65) (9.96) (9.0) (7.87)

Table 8-10. Word reading and intelligence tests scores in poor readers and control groups. All t-test

comparisons between the dyslexies and controls significant at the level p< . 1 0 are listed. 278 Chronological Low accuracy Accuracy level Chronological Low speed Speed level age controls readers controls age controls readers controls N=51 N=10 N=17 N=48 N=9 N=ll Mean t Mean t Mean Mean t Mean t Mean SD SD SD SD SD SD inword reading acc. 78 6.453*** 47 3.198** 68 76 1.827t 64 66 (12) (13) (19) (15) (18) (21) inword reading time 2.12 2.405* 3.21 4.38 1.84 4.195** 3.96 3.74 (.86) (1.68) (2.33) ( 5 9 (1.49) (L%0 git Span (raw) 8.49 7.20 7.13 8.60 7.77 7.10 (2.08) (2.25) (LMO (1.92) (2.10) (1.10) git Sp. (standard) 9.34 7.78 9.19 9.36 8.11 9.30 (2.62) (2.77) (2.34) (2.39) (2.76) (1.42) ?nword repetition 19.36 2.0351 16.33 18.60 19.60 17.78 19.70 (4.35) (4.06) (4.03) (3.75) (4.94) (4.0) literation oddity 27.12 23.10 23.75 28.13 2.286* 23.11 25.09 (4.81) (6.87) (5.03) (3.41) (6.41) (4.16) |minine rhyme oddity 20.04 19.20 18.00 20.71 2.681* 15.56 18.60 (6.62) (3.95) (6.72) (4.98) (&&4 iasc. rhyme oddity 22.18 20.60 20.87 22.85 21.44 20.40 (6.77) (3.89) (6.47) (5.42) (5.17) (5.06) iioneme deletion 20.80 17.11 15.60 21.47 18.22 15.40 (4.27) (6.72) (4.34) (14^ (6.26) (4.20) jowel repl. 37.75 2.532* 26.20 30.69 38.31 34.33 34.90 (9.40) (13.81) (13.19) (7.59) (12.68) (10.08) onsonant repl. 32.16 2.503* 25.00 27.73 31.89 30.44 26.00 (9.17) (7.65) (7.08) (8.94) (5.92) (5.42) toneme analysis 17.02 17.10 2.206* i'4.8i 16.85 i'7.ii 16.30 (1.48) (1.29) (3.82) (1.56) (1.27) (2.41) toneme blending 15.24 2.276* 16.60 2.354* 13.20 14.98 2.811** 16.77 15.20 (3.19) (1.26) (5.37) (3.26) (1.30) (3.12) omparison of adj. 46.04 40.33 38.87 47.04 47.33 2.503* 36.60 (11.93) (11.15) (11.47) (11.32) (8.75) (9.95) erb prefixation 46.53 39.22 33.69 47.92 42.00 35.5 (15.44) (16.51) (17.29) (11.09) (16.29) (18.02) iminutives 57.18 54.11 52.40 58.26 55.78 2.231* 47.90 (5.31) (7.37) (7.31) (3.70) (7.09) erivative forms 37.37 36.22 33.56 38.83 37.35 1.872t 28.90 (10.59) (9.69) (8.82) (10.01) (9.16) (.9.99) apid pict. naming 91.88 99.00 100.7 89.75 96.7 102.5 (17.70) (15.90) (14.43) (16.43) (14.1) (11.81) apid digit naming 57.80 2.660* 68.22 70.07 57.33 2.600* 69.9 67.90 (12.21) (12.70) (11.05) (12.32) (13.47) (11.46) :raph. naming speed .68 .82 .92 .65 2.666* .86 .85 (.14) (25) (.24) (13) (.22) (.20) 3rapheme naming acc. 97 94 1.853t 89 97 94 2.178* 87 (3) (7) (7) (2) (7) (8) semantic fluency 21.45 19.11 19.80 22.50 1.925t 19.78 17.50 (5.11) (5.41) (4.64) (3.73) (5.72) Mliteration fluency 12.78 11.00 10.07 13.23 10.78 9.80 (3.09) (4.90) (2.60) (3.36) (3.87) (2.82) Femin. rhyme fluency 3.30 3.13 2.86 3.49 2.87 2.60 (1.97) (2.42) (2.48) (2.05) (2.1) (1.84) Vlasc. rhyme fluency 2.59 2.88 2.53 2.85 2.62 3.00 (213) (1.64) (2.00) (2.14) (2.0) (212) Visual memory test 21.55 1.911t 2Ô.0Ô 20.40 2Ï.56 20.78 21.00 (2.24) (1.68) (2.26) (1.39) (1.22) Copying Rey figure 27.69 1.966Ÿ 23.89 25.63 27.50 25.44 24.55 (3.98) (5j5) (4.14) (3.62) CUO (3.47) Letter discrim, accur. 14.96 14.11 2 .0 9 8 t 15.13 15.10 14.44 15.10 (1.23) (1.32) (81) (116) (1.21) (88) Symbol discrim, accur. 14.41 14.25 1.816t 15.13 14.45 14.22 14.70 (1.03) (1.38) (83) (.99) (1.44) (1.06) Copying Rey fig. time 256.7 206.8 233.0 246.9 216.3 200.0 (129.2) (45.26) (97.83) (125.9) (44.15) (56.29) Letter discr. time 84.38 86.78 2.280* 120.7 81.49 92.72 136.5 (28.51) (22.73) (44.07) (28.61) (26.23) (94.03) Symbol discr. time 91.93 90.30 95.60 89.88 89.33 93.6 (23.96) (26.80) (27.66) (23.37) (33.07) (35.35)

Table 8-11. Performance of poor readers and controls on individual cognitive tasks, t p<.10 * p<.05 ** p<.01 *** p<.000 279 Tables 8-10 and 8-11 present descriptive statistics of poor readers and their controls. Significant differences are summed up in table 8-12. The pattern obtained during earlier dyslexia analyses was generally replicated, although an increase in the number of participants allowed for a larger number of significant differences to emerge. Low accuracy readers were characterised by the nonword reading deficit (they made, on average, 21% more errors on nonword decoding than younger readers matched on word reading accuracy^) and low scores on several indices of phonological processing. They were also slow on rapid digit naming (unlike the dyslexia group analysed before). Low speed readers showed mainly speed and fluency problems; the phonological problems they did show were limited to the oddity tasks.

Low accuracy readers Low speed readers worse than reading level controls nonword reading accuracy 3.198*** Columbia (standard scores) 1.999f letter discrimination accuracy 2.098f symbol discrimination accuracy 1.816f worse tllan chronoi'ogical age controls word reading accuracy 10.276*** nonword reading time 4.195** nonword reading accuracy 6.453*** word reading time 3.993** word reading time 3.230** rhyme oddity 2.681* rapid digit naming 2.660* grapheme naming time 2.666* vowel replacement 2.532* rapid digit naming 2.600* consonant replacement 2.503* alliteration oddity 2.286* nonword reading time 2.405* word reading accuracy 2.262* nonword repetition semantic fluency 1.925t visual memory (Chinese letters) 1.911f Columbia-standard scores 1.875f Copying Rey figure 1.966f non word reading accuracy 1.827f Columbia - raw scores L819f

better than reading level controls phoneme blending 2.354* comparison of adjectives 2.503* letter discrimination time 2.280* diminutives 2.231* phoneme analysis 2.206* letter naming accuracy 2.178* word reading time 2.170* derivative forms 1.872f grapheme naming accuracy 1.853f

better than chronological age controls phoneme blending 2.276* phoneme blending 2.811*

Table 8-12. Summary of significant differences between poor readers and controls.

^ As in case of dyslexic sample, this difference ceased to be significant when the analysis was restricted to the subset of stimuli read by all subjects, although it was still robust (54% vs 68% nonword decoding accuracy in poor readers and younger controls respectively; t= 1.906, p=.075). 280 To clarify the analysis, composite scores were also computed in a way described previously (section 8.2.). As very few subjects were added, no major changes in the pattern of results were expected. Descriptive statistics for the five composites are given in table 8-13 and displayed in figure 8-2.

LOW ACCURACY READERS LOW SPEED READERS

Mean Median Min. Max. Mean Median Min. Max. Phonemic awareness -0.72 -1.13 -1.81 1.02 -0.49 -038 -1.81 0.42 composite Rapid naming -0.45 -0.66 -2.02 0.71 -0.55 -OJW -202 0.19 composite Analysis and 0.31 0.22 -0.75 0.90 0.35 0.39 -0.75 0.90 blending composite Reading accuracy -1.80 -1.75 -2.84 -0.91 -0.70 -0.48 -284 0.98 composite Reading speed -1.03 -0.75 -3.87 0.55 -1.80 -1.34 -287 -0.97 composite

Table 8-13. Scores of poor readers on phonological processing and reading composites

Phonemic awareness = mean of: alliteration oddity, vowel replacement and alliteration iluency.

Naming speed = mean of rapid picture and digit naming.

Analysis & blending = mean of phoneme analysis and blending.

Reading accuracy = mean of word and nonword reading accuracy

Reading speed = mean of word and nonword reading speed.

All individual test scores were Z-transformed (separately for each grade) before averaging into the composite.

0 .5 9 0.5 2 0 .5 1 0.38 OM. 0 3 10 .0 2 Ü.11 n — eac ers rea dart ca controls-accuracy ca controls-speed

-0.48 -0.4( B phonological awareness 0 rapid naming □ analysis and blending □ reading accuracy □ reading speed

Figure 8-2. The median scores of poor readers and controls on five composites.

2 8 1 In comparison with the dyslexies, the extended group of poor readers showed a nearly identical cognitive profile, with one exception: low accuracy readers showed even greater phonemic awareness difficulties than the (more stringently selected) low accuracy dyslexies. Figure 8-2 suggests that inaccurate and slow readers differ not only

in the severity of cognitive problems (with inaccurate children being more impaired) but

also in the dominant difficulty (inaccurate readers are more impaired on phonemic awareness than rapid naming; the reverse is the case with slow readers). At the beginning of this chapter I presented two contrasting models of the relationship between underlying cognitive deficits and manifestations of reading difficulties. The observed pattern of results is generally more consistent with the cognitive invariance model, whereby all forms of reading difficulties are related to the same double impairment with phonemic awareness and rapid naming. The differences in symptoms (inaccuracy versus slowness) are primarily the function of the severity of this double impairment, and probably also some instructional and experiential factors. The connection between symptoms and underlying impairments may be specific to some degree: inaccurate readers tended to have greater problem with phonemic awareness, while slow readers with rapid naming. Low accuracy dyslexia (and poor reading in

general) seems to fit the pattern of phonological processing deficit and correspond to the syndrome originally described as the developmental phonological dyslexia (Campbell & Butterworth, 1985). The low speed subtype, while involving the same phonological difficulties, is generally more benign and can be better described as a developmental

delay.

8.4. VISUAL DEFICITS IN DYSLEXIA?

The analysis of performance on individual tests (table 8-6 - 8-7 and 8-10 - 8-11) showed that dyslexies and poor readers obtained low scores on visual as well as phonological measures. This raises an interesting (if unexpected) possibility that the impairments of higher-order visual processes of analysis, memory and discrimination contribute to reading failure. In order to explore this issue further, two visual composite scores were computed in the same way as the phonological composites had been previously. Each visual composite corresponded to the latent ‘visual’ variable identified in the factor

282 analysis (section 7.2): Visual Analysis and Memory (mean of visual memory test and accuracy of copying Rey figure) and Visual Discrimination (mean of letter and symbol discrimination accuracy).

0,31 Û a?

ca controls-speedca controls-accuracy ca controls-speedca

-0.4f

0 .66-0 6^ phonological awareness □ rapid naming □ visual analysis and memory □ visual discrimination

-1.4

Figure 8-3. Median scores of poor readers and controls on phonological and visual composites.

Phonemic awareness = mean of: alliteration oddity, vowel replacement and alliteration Ouency.

Naming speed = mean of rapid picture and digit naming.

Visual analysis and memory = mean of visual memory (“Chinese letters") and Rey figure drawing accuracy

Visual discrimination = mean letter discrimination and symbol discrimination accuracy

All individual test scores were Z-transformed (separately for each grade) before averaging into the com posite.

Comparing phonological and visual composites (figure 8-3) revealed that poor readers indeed appeared to have difficulties in both domains. Case-by-case analysis also revealed that visual impairments occurred almost as frequently as the phonological ones. Taken together, the data suggest strongly (albeit indirectly) that visual factors contribute to reading failure. A more direct test of this visual deficit hypothesis was possible. It was a “mirror image” of the analyses carried out previously. Instead of identifying children with different types of reading impairment in order to describe their cognitive profile, it identified children with different types of cognitive impairment and described their reading performance. Systematic comparison of different impairments (single and combined) allowed me to find out which were sufficient to bring about reading difficulties, and which were not. All children with cognitive impairments from grades I-

3 were sought and compared with their unimpaired same-age peers (unlike in the

283 previous analyses, which were restricted to older, and S'"* grade poor readers and which used both age-matched and younger skill-matched controls).

Since each child was described with four composite cognitive scores (two visual and two phonological) the following cases were identified:

• Children with the phonological problem only: at least one of the two phonological composites showed impairment, but there was no impairment on either visual

composite. As previously, impairment was defined as performance worse than 1 SD below grade mean. 16 such cases were identified.

• Visual problem only: at least one of the two visual composites showed impairment, but there was no impairment on either phonological composite. N=15

• Phonological and visual problem: at least one visual and one phonological composite showed impairment. N=6

• No problem: none of four composites showed impairment. N=62

Figure 8-4 presents median scores of all groups on four cognitive as well as two reading composites. It is apparent that children whose impairment(s) were limited to the visual domain showed normal reading performance, similar to unimpaired controls. Impairments limited to the domain of phonology, on the other hand, were accompanied by reading accuracy and speed problems (though, on average, these were only mild). The gravest reading problems occurred when the visual and the phonological impairments overlapped.

0.51

visual en only gical I )lei 1 pIttiioii igti al v su: I no problem only I nol Jer i

-0.60.6 @ phonological awareness □ rapid naming 1,22 Bvisual analysis and memory □ visual discrimination □ reading accuracy □ reading speed

Figure 8-4. Performance of children with different types of impairment and the unimpaired controls.

Bars represent medians of z-scores on four cognitive and two reading composites. The composites were computed identically as in previous analyses.

284 The outcome suggests a multiple deficit model of reading failure, whereby the combination of visual and phonological impairments is most likely to compromise reading development. However, it must be remembered that the multiple deficit children were not well-matched on their single deficit counterparts: they tended to have lower general ability (WISC-R Vocabulary and Columbia scores) and more severe phonological and visual difficulties. Worst reading performance of those children could, then, result from more severe phonological problems combined with lower intelligence, rather than from co-occurrence of phonological and visual difficulties. Limited number of children made it impossible to select closely matched groups. To provide some control of the intelligence confound, adjusted mean reading scores were computed after co-varying for WISC-R Vocabulary and Columbia scores (all expressed, as previously, on grade-relative Z-scale). The results are presented in table 8- 14.

GROUPS

Visual problem Phonological Phonological and No problem only problem only visual problem Reading accuracy 0.09 - 0.66 -0.64 0.15 composite 0.02 [0.04] - 0.73 [-0.60] -0.78 [-1.22] 0.20 [0.31] Reading speed 0.24 -0.73 -0.96 0.17 composite 0.14 [0.34] - 0.73 [-0.60] -1.09 [-0.88] 0.21 [0.51]

Table 8-14. Mean scores on reading composites adjusted for general ability (WISC-R Vocabulary and Columbia) z-scores. Italicised scores represent unadjusted means and medians [in brackets].

The adjustment did not change the means appreciably. It must be noted however, that the unadjusted mean and median scores were quite discrepant in the ‘visual + phonological’ problem group. Mean scores suggest that the presence of visual problems does not affect reading accuracy at all, but it may have some (minor) deleterious effect on reading speed - yet only if combined with phonological impairments. Overall, the pattern of findings was consistent with - now widely accepted - conclusion of Vellutino (1979). Reading problems are rarely, if ever, caused by impairment of visual processes - at least higher-order visual processes that require voluntary attention. This outcome is also consistent with the results of regression

285 analyses (chapter 7), which showed that the phonological, but not visual factors are unique predictors of reading performance.

8.5. TESTING THE DOUBLE DEFICIT HYPOTHESIS

The same type of analysis was also used to quantify the independent and joint effects of the phonemic awareness and rapid naming impairments. Applying earlier criteria of impairment (score worse than 1 SD below grade mean on a given composite) I identified children with the phonemic awareness impairment (N=9), rapid naming impairment (N=7), both impairments (N=6) and the unimpaired control group (N=80). Performance of these children on the criterion measures (phonemic awareness and rapid naming composites) and outcome measures (reading) is presented in table 8-15 and figure 8-5.

PHONEMIC AWARENESS RAPID NAMING DOUBLE IMPAIRMENT IMPAIRMENT N=9 IMPAIRMENT N=6 N=7

Mean Me­ Min. Max. Mean Me­ Min. Max. Mean Me­ Min. Max dian dian dian

Phonemic awareness -1.37 -1.42 -1.81 -1.00 -.12 -.25 -.63 .48 -1.36 -1.32 -1.76 -1.13 composite

Rapid naming -.27 -.36 .94 -.60 -1.53 -1.31 -2.35 -1.02 -1.82 -1.79 -2.97 -1.12 composite

Reading accuracy -.61 -.55 -1.67 .61 -.05 -.03 -.60 .98 -1.52 -1.56 -2.84 -.21 composite

Reading speed -.50 -.53 -1.28 .62 -.23 -.28 -1.49 .97 -2.02 -1.97 -3.87 -.79 composite

Table 8-15. Scores of children with single and double phonological impairments on reading and

phonological processing composites.

286 0,51 TTT

Ofphcnemic im on ng on k 0th impaired on none s o ily on'y -0.28 # -0 .5 5 -0 .5 3

/ Bphonological awareness □ rapid naming □ reading accuracy □ reading speed -1.56

Figure 8-5. Performance of children with single and double phonological deficits, and their controls.

Bars represent median Z-scores on two phonological and two reading composites.

Some differences were observed between the two single impairment groups. The phonemic awareness impairment was associated with moderately low speed and accuracy of reading. Unexpectedly, however, the rapid naming impairment appeared to have little effect on reading. The double impairment group showed by far the largest reading difficulties, suggesting a multiplicative, rather than additive effect of combined phonological impairments. The double impairment group performed worst on general ability tests (WlSC-R Vocabulary and Columbia) but the pattern was maintained even after adjusting for those differences (table 8-16).

GROUPS

Phonemic Rapid naming Double No impairment awareness impairment impairment impairment Reading accuracy -0.55 -0.05 - 1.43 0.18 composite -0.61 1-0.55J - 0.05 1-0.03] - 7.52 /-7.56y 0.20 /o.joy Reading speed -0.50 -&25 -:L02 0.22 composite - 0.25 /o. 2,sy -2.02 /-7.97y 0.22 /0.57y

Table 8-16. Mean scores on reading composites adjusted for general ability (WISC-R Vocabulary and

C olum bia) z-scores. Italicised scores represent unadjusted means and medians [in brackets].

287 The final analysis ensured even further that the observed between group differences were not the artifact of general cognitive ability (see figure 8-6). Children with low general ability, but no impairment on either phonological composite were as accurate and quick at reading as unimpaired controls. The “mirror group” (normal general ability, but impairment on one or two phonological composites) did show reading problems.

The combination of low general ability and phonological difficulties resulted in the worst reading outcome. This, however, may simply reflect the fact that the children with such a combination of difficulties are less phonemically aware than the children with phonological impairments only.

>nolog low genKBlab lity onlyinler ts no impairments rment^ otify 52

phonological awareness □ rapid naming Vocabulary □ Columbia -1 ,5 4 □ reading accuracy □ reading speed

Figure 8-6. The etlects of low general ability and phonological impairments on reading performance.

Phonological deficits only: one or both phonological composites within the impaired range (lower than -ISD below grade mean). N=I4

Low ability only: Columbia or Vocabulary (or both) scores within impaired range. N=2t

Both impairments: general ability and phonological processing impairment (at least one score from each domain falling within the impaired range). N=8

No impairments. N=59

The results of the last series of analyses strongly support the double deficit hypothesis of dyslexia (e.g. Wolf & Bowers, 1999). Serious problems with word decoding and recognition (its speed and accuracy alike) were typically associated with the combined impairment of phonological awareness and rapid naming. There was little support for the “cognitive relativity” hypothesis, which predicted that dyslexia in a (comparatively) consistent Polish orthography would be predominantly speed related in both its causes and manifestations (cf. Wimmer, 1993). Contrary to this view, it was the phonemic awareness impairment that appeared more important. This was the only deficit always

288 associated with poor reading, even in the absence of other cognitive problems. Rapid naming impairment seemed to contribute to reading problems considerably, yet only when combined with the awareness impairment. Low general ability and visual impairments played only a peripheral role (if any): they possibly aggravated reading problems, whose primary causes were phonological.

The analyses presented in this chapter were focused on identifying typical cognitive profiles of low accuracy and low speed readers, and paid less attention to individual differences within those groups. Those differences were considerable, however (examine, for example, the spread of scores reported in tables 8-8, 8-13 and 8-15). The analysis of individual cases revealed occasional dissociations between poor reading and normal phonological skills, as well as poor phonological skills and normal reading. Larger samples would be required to identify the additional vulnerability and resilience factors contributing towards those unexpected reading outcomes.

289 CHAPTER 9

SUMMARY AND CONCLUSIONS

This final chapter is divided into three parts. Initially, I will summarize the main findings of the study and synthesize them into a model that will describe the initial period of reading and spelling acquisition in Polish. Secondly, I will discuss how these findings inform the general debate about the cognitive mechanisms involved in learning to read and write. Finally, I will point out the limitations of the study that arose while collecting and analyzing the data, identify the original research questions for which no unequivocal answers were found, as well as propose some new questions for future research.

9.1. READING AND SPELLING ACQUISITION IN POLISH

9.1.1. Processing written words: ages, stages, mechanisms

The data presented in chapters 6 and 7 are consistent with the two-phase model of the development of single word reading and spelling. The elementary alphabetic phase broadly corresponds to the first two years of formal instruction (grades 0 and 1). During this time children receive systematic instruction in the “mechanics” of reading and spelling: they learn most graphemes, their basic sound values, as well as analysis and blending skills. The main cognitive achievement of this period is the acquisition of basic phonological recoding, which is alphabetic (based on single grapheme-to- phoneme correspondences), sequential, and used explicitly. This recoding constitutes the main mechanism of processing all written words (familiar and unfamiliar alike) during this phase. The effectiveness of this recoding depends directly on the number of grapheme -phoneme correspondences a child has been explicitly taught. Therefore, it increases in line with instruction. The subsequent, advanced alphabetic and orthographic phase, corresponds to the remaining two years of initial education (grades 2 and 3) and probably extends beyond. During this time, children receive intensive practice in reading and spelling. The main achievements of this period include the mastery of complex grapheme-phoneme mappings (i.e., those involving letters with diacritics and digraphs, but especially the non-transparent mappings that reflect the morphological principle), which allows for full independence of decoding. It is also the 290 period of intensive growth of specifically orthographic skills: accumulation of orthographic representations of individual words, as well as implicit and explicit learning of orthographic rules. These achievements are related to the increasing role of the processing mechanisms that rely on larger orthographic and linguistic units (syllables, morphemes and whole words).

The following results support this two-phase framework:

Quantitative change in reading: marked absolute gains in reading accuracy and speed during the grade, more asymptotic progress later on. Directly observable manifestations of reading strategies: overt sounding out and blending of individual letters, very frequent in grade 1, was diminished later on in favour of syllable-by-syllable reading or whole word naming. Reading errors: disappearance of reading refusals after grade; increase in the relative frequency of lexical substitutions (in place of nonword errors). Orthographic plausibility of spelling errors: decrease, after grade 1, in the absolute frequency of letter combinations that are illegal or atypical within the Polish orthographic system. Change in the cognitive predictors of reading. Individual differences in reading skills during the grade are explained very well by letter knowledge, phoneme analysis and blending. These are typically mastered during the 2"^ grade and fail to explain reading later on, while some other phonemic awareness skills and speed of naming (letters, digits or pictures) remain significant predictors of reading until the 3^^ grade.

The two-phase model is adopted primarily for its descriptive utility. It emphasises the age-related change in the skills being acquired and in the processing mechanisms that seem to occur most rapidly between grades 1 and 2 .1 do not, however, wish to endorse the assumption of reading acquisition as a succession of discrete stages. Instead, my data suggest gradual changes and parallel developments of processing mechanisms and strategies, which may be characterized as follows:

Sub-lexical phonological recoding is the core mechanism of processing words throughout the whole period covered by the study. The nature of this decoding changes, though, from predominantly alphabetic, sequential and explicit (overt

291 grapheme-phoneme translation) to more implicit (automatic) processes that involve parallel processing of larger orthographic units. The central and lasting role of recoding is evidenced by strong correlations between word and nonword reading at all age levels, permanent predominance of nonword reading errors, as well as sounding out and blending behaviour (which, although they diminish with age, can always be seen with more complex nonword items). Nonword reading deficits observed in low accuracy dyslexies (chapter 8) also points to the central role of recoding. Gradual lexicalisation of processing (increased reliance on stored orthographic representations of words). This is evidenced by age-related increase in the relative frequency of word substitution errors in reading, as well as the increase in the lexicality effect (performance advantage of words over nonwords) found for reading speed. Growth of orthographic skills. This process is closely related to the lexicalisation of reading and spelling mentioned above. It is manifested in gradual disappearance of orthographically implausible spelling errors, increase in reading speed and speed lexicality effects, and improved accuracy in the reading of complex, non-transparent stimuli. These effects do not occur very early (during the first semester of the grade), which suggests that some basic decoding skills (involving transparent grapheme-phoneme mappings) are a prerequisite for orthographic development.

My model was preceded - indeed, inspired by - a similar proposal of Krasowicz-Kupis (1999; see also Sochacka, 2001). There are only minor discrepancies between the two models: Krasowicz-Kupis (1999) proposed three, rather than two, phases of reading acquisition, and emphasized the role of meta-syntactic skills during the last phase. These discrepancies seem to reflect the different design of her study (a longitudinal project; inclusion of text reading and syntactic awareness measures) rather than conflicting conclusions. Both models propose that reading acquisition in Polish involves gradual transition from predominantly alphabetic decoding towards more lexicalised processing. They agree that this transition does not imply a complete replacement of one mode of processing with another, but a change in the dominant mode of processing. Alphabetic and lexical processes occur in parallel and their rudiments can be traced to the very beginning of learning to read.

292 9.1.2. Cognitive correlates of literacy

Correlational analyses presented in chapter 6 showed that individual differences in reading skills are well predicted by three types of phonological tasks: those requiring detection and manipulation of phonological units (phonological sensitivity and awareness), phonemic segmentation and blending, and efficient phonological retrieval (rapid naming). These three groups of tasks represent partially independent aspects of phonological processing, since they emerged as independent latent variables in factor analyses, and each usually accounted for unique variance of reading skills. The tasks tapping into phonemic processing were, on average, better predictors of reading than those tapping into rhyme processing. This may reflect the greater role of phonemes than rhymes in reading acquisition. Yet, it may also be an artifact of floor effects and low reliability which often affected rhyme tasks. Rhyming skills also did not fit very well into the three-factor description of phonological processing that emerged from factor analyses, showing weak and inconsistent pattern of factor loadings. Unexpectedly, phonological processing skills appeared to be weak, and often non-significant, predictors of spelling. This is likely to be an artifact of the study design (group administration of spelling tests; considerable time gap between the assessment of spelling and of other skills). Non-phonological skills predicted reading and spelling very weakly, if at all. Contrary to expectations, morphological awareness skills did not play a significant role, although they did form a single latent factor with phonological awareness skills. Possible reasons for this outcome will be discussed later. Differences in higher-order visual processing (pattern analysis and memory) were also not important, with one possible exception: accuracy of visual discrimination appeared specifically related to accuracy of word spelling. This finding must be treated with caution, however, due to the poor psychometric properties of the two measures of visual discrimination accuracy. A relationship between letter discrimination speed and reading speed was also found. This, however, is likely to reflect individual differences in letter knowledge and naming ability, rather than visual processing per se. Grapheme naming ability, which was analyzed separately from the other predictors, appeared by far the strongest correlate of reading and a significant (though not the strongest) correlate of real word spelling. Knowledge of graphemes strongly constrained reading accuracy; this was detectable until the 2"^ grade, during which the

293 knowledge of graphemes was usually becoming near-perfect. Speed of naming graphemes was a more long-term predictor of reading speed. Overall, the results of correlational analyses suggest that the alphabetic skills (learning and using individual grapheme-phoneme mappings) are central for the initial success in learning to read Polish, while other modes of processing (e.g. morphological analysis or global, visually based word recognition) play lesser or non-significant roles. The importance of naming speed measures as predictors of reading suggests that the automatization of the alphabetic skills is also crucial.

9.1.3. Written language difficulties: symptoms and mechanisms.

Poor accuracy and slowness of reading were generally associated. However, the psychometric discrepancy criteria identified two, largely non-overlapping, groups of poor readers, one impaired primarily on accuracy of reading, the other on its speed. The poor accuracy subgroup showed a nonword reading deficit (i.e. accuracy of nonword decoding that was worse even in comparison with younger children matched on real word reading accuracy) - a reading profile of developmental phonological dyslexia as described in the literature on English speakers. The slow readers, on the other hand, seemed developmentally delayed rather than deficient in their reading (i.e. similar to younger controls matched on word reading speed). However, in terms of other cognitive skills, the two groups appeared to be similar. They were both characterized by a double difficulty with phonemic awareness and rapid naming (but not phonemic analysis and blending), though poor accuracy readers tended to be more impaired on phonological awareness than on naming, while reverse was the case with the low speed group. Both groups of poor readers also tended to have lower verbal, reasoning and visual skills than the controls, yet additional analyses suggested that these played only peripheral (if any) role in poor word processing. Low general ability or visual difficulties, when occurring on their own, were usually not accompanied by poor reading - unlike the phonological awareness problem, which tended to co-occur with poor reading even in the absence of other cognitive difficulties. Interestingly (and unexpectedly) poor naming skills occurring on their own did not lead to poor reading, either. However, double impairment in phonological awareness and naming was clearly associated with, by far, the most serious reading difficulties. This showed that naming is a more important constraint of reading than other, non-phonological skills: addition of non-phonological

294 impairment to poor phonological awareness aggravated reading difficulties only little, if at all.

9.2. BROADER THEORETICAL ISSUES

9.2.1. Language-specific and cognitive-universal aspects of literacy acquisition

The main aim of the study was to analyze the interaction between cognitive-universal aspects of literacy acquisition, and its language-, orthography- and instruction-specific constraints. Although this problem could be addressed only indirectly (since the study was not a comparative one) there are a number of relevant results. It is the similarities between the findings of this study and of other language studies that are most striking. These include, fist of all, the cognitive predictors of reading. The data provide converging evidence for phonological awareness and efficient phonological retrieval (rapid naming) being the two most important (and largely independent) predictors of reading. The same ‘double underpinning’ of reading was also reported in German (Wimmer, 1993), Dutch (de Jong & van der Leil, 1999) and English (e.g. Wagner et. al., 1997). The results of the factor analyses (chapter 3) were also broadly consistent with results from other-language studies exploring the structure of phonological skills. These studies varied in terms of number and type of latent factors that appeared to describe the structure of phonological processing skills. However, they usually agreed that phonological awareness and rapid naming were separate dimensions, while phonological memory was more closely related to awareness than to naming (Wagner & Torgesen, 1987; Wagner et. al., 1993). The current study replicated that general pattern. Cloze associations between phonological and morphological awareness skills observed here (the two loaded on a single factor) were also consistent with other-language studies (e.g. Casalis & Luis-Alexandre, 2000; Singson, Mahony & Mann, 2000). The result most clearly inconsistent with findings from other languages is the emergence of phonemic analysis and blending as a factor separate both from phonemic awareness and rapid naming. This analysis and blending factor also appeared to be a unique predictor of reading. It is likely that these tasks measured the amount of reading instruction a child received and her reading experience more than phonological awareness per se. The data were also consistent with the results of Lovett (1987) and Wimmer (1999) in showing that largely independent groups of poor readers can be differentiated,

295 one characterized by poor accuracy, the other by slowness of reading. However, while other studies showed those groups to be different in terms of cognitive deficits (inaccurate readers being characterized by a double impairment of phoneme awareness and rapid naming, while slow readers by a naming impairment only), the current study found both groups to have a broadly similar double phonological impairment. Difficulties limited to rapid naming were not associated with poor reading at all (see below). Cross-linguistic differences were anticipated with respect to rate of learning. Given the high feed-forward (but not feed-backward) consistency of the Polish orthography, Polish children were expected to reach near-perfect decoding accuracy after a short period of instruction, but take much longer to become fast in their reading and, especially, orthographically accurate in their spelling. However, the Polish children acquired decoding skills slower than expected: although they probably learned faster than their English-speaking counterparts, they definitely lagged behind other consistent orthography learners (for example German-speakers, with whom most detailed comparisons could be made: Wimmer & Hummer, 1990; Wimmer, 1993b; Wimmer, 1996a, b). It is likely, therefore, that Polish orthography is more complex than originally assumed, making the acquisition of decoding more difficult. It is unlikely that the relatively poor performance of the Polish children stems from educational or social factors, given the systematic phonics instruction received by the participants in the current study, and their typically favourable socio-economic background. Further explorations of these differences would require direct comparative studies. The analyses of the relative mastery of different phonological tasks also revealed some language-related differences. Polish children seemed extremely good at phoneme analysis, even when compared with the learners of consistent orthographies. They seemed relatively good at blending, as well (though conclusions were harder to reach there, given the scarcity of comparative data). However, Polish children were worse than their German counterparts on the vowel manipulation task. Finally, they were rather poor at rhyming - definitely at rhyme production - when compared to English children. It seems that literacy instruction is a crucial factor explaining this pattern of cross-language differences, though orthographic consistency and the phonological structure of the language could also play an additional role. Polish children receive a drill in analysis and blending skills as a part of their reading instruction, hence, they master those skills. Phoneme manipulation skills are not explicitly exercised, so they develop less well, in line with decoding skills (which are worse in Polish than in

296 German children). Rhyming skills are exercised, but rarely in the context of literacy (since Polish orthography does not give many reasons to emphasize spelling-sound connections at the level of rhymes), therefore they remain implicit. It is also possible that Polish speakers find rhyme retrieval more difficult because their mental representations of rhymes are organized differently than in the English speakers (e.g. because of different distributional frequencies of phonological units, or because Polish rhymes typically show partial overlap with morphological suffixes)\ Unexpectedly, morphological skills did not generally show a specific connection with reading or spelling. This was inconsistent with the results of English, French and also Polish (Krasowicz-Kupis, 1999) studies reviewed in chapters 2 and 3, the majority of which found a small, yet significant, contributions of morphological awareness to literacy that were independent of phonological awareness. This is surprising, since the Polish orthography consistently reflects the language’s morphology (see chapter 4) and the morphological tasks used in the study were no less reliable than the phonological ones (see chapter 5). However, the contribution of morphological skills may be more important in processing connected texts containing inflected words - whereas the reading and spelling tasks used in the current study focused on isolated words in their basic (lemma) form. Secondly, morphological skills are likely to be more important for spelling than for reading, in which case the negative findings may be an artifact of study design (a group spelling test distant in time from the assessments of morphological skills). Moreover, morphological skills are more important for processing those words whose spellings are morphology-based, rather than transparent (Bryant, Nunes & Bindman, 1998; 2000). Since the set of words used in this study contained a mixture of transparent and morphologically spelled items, this could have ‘diluted’ the possible contribution of morphological processing skills to reading and spelling. Finally, the validity of the morphological tests as measures of morphological awareness can be questioned. Although all four tests undoubtedly required morphological operations (of the type directly reflected in the Polish orthography), these had to be carried out on relatively low frequency words. Individual differences in performance could, therefore, reflect vocabulary knowledge more than morphological ability per se^. Also, the general cognitive demands of the morphological tasks must have been particularly high, since the cases of apparent failure to understand the instruction seemed much more frequent

’ I owe these ideas to Dr. Marketa Caravolas and Dr. Charles Hulme ^ This is likely since WISC-RWISC-F Vocabulary scores typically correlated more highly with morphological than with phonological tests. 297 on the morphological tests (especially ‘prefixes’ and ‘derivative forms’) than the phonological ones. The results pertaining to the double deficit hypothesis of dyslexia (e.g. Wolf & Bowers, 1999) were, again, only partly consistent with other-language findings. The double deficit hypothesis was clearly supported by the data insofar as it states that the most pervasive and severe reading difficulties are linked with the co-occurrence of phonological awareness and rapid naming impairments. It was also consistent with the double deficit hypothesis that an impairment limited to phonological awareness was associated with moderate difficulties in accuracy and speed of reading. However, Polish children whose impairment was limited to rapid naming did not show any reading problems, whereas other language studies (e.g. Lovett, 1987; Wimmer, Mayringer & Landerl 1999; Compton, DeFries & Olson, 2001) consistently found such children to be very slow readers. This outcome suggests that a recent reformulation of the phonological processing deficit hypothesis of dyslexia put forward by Landerl and Wimmer (2000) may have underestimated the role of phonological awareness, and overestimated the role of naming skills in learning to read. All conclusions regarding cognitive impairments and their consequences for reading must be treated as preliminary, however, given the very small number of cases used in the analysis.

Overall, the results suggest that the language-, orthography- and instruction-specific factors play a peripheral, modulating role in the process of literacy acquisition. The core mechanisms of learning (especially the use of alphabetic decoding in order to acquire orthographic representations), as well as basic cognitive resources that subserve learning (quality of phonological representations, efficiency of name retrieval) are the same in all written languages (at least the alphabetic ones). Cross-orthographic differences (regarding consistency or overall complexity of an orthography) primarily affect the difficulty of the learning task, and less its cognitive mechanisms. Orthography, therefore, constrains the average rate of learning to read and spell, and the symptoms of written language disorders (especially the degree of reading inaccuracy). Specific instructional approaches play a crucial role (arguably greater than orthography) in shaping the conscious strategies of processing written words (e.g., tendency to rely on systematic sounding out, rather than context-based guessing). Literacy instruction is also chiefly responsible for the differences in the relative mastery of different phonological awareness tasks.

298 9.2.2. Phonological recoding versus orthographic processing

At the outset of this thesis, I invoked the distinction between phonological recoding (forming and using the mappings between orthography and phonology) and orthographic processing or skills (encoding serial order of graphemes in individual words, and distributional frequency of graphemes within the whole orthographic system). The former was operationalized with nonword reading and spelling accuracy, the latter with reading speed, orthographic accuracy (or plausibility) of spelling, as well as lexicality and frequency effects (superior performance on familiar words). I expected to find a considerable degree of dissociations between the two sets of skills. Phonological recoding was seen as a prerequisite for orthographic skills; a learning mechanism through which orthographic knowledge could be acquired. Moreover, the acquisition of orthographic skills was expected to rely on cognitive resources indexed by rapid naming tasks, while recoding predominantly on phonological awareness. These predictions were only partially fulfilled. As expected, speed of reading and the orthographic quality of spelling showed the fastest period of growth only after some rudimentary recoding had already been established (see chapter 6). However, more complex decoding (involving morphologically conditioned grapheme-phoneme mappings, digraphs and diacritics) was mastered only together with, not before, the orthographic competencies. Furthermore, the factor analysis of reading and spelling skills did not confirm the expected dissociation between phonological recoding and orthographic processing. Different indices of reading (speed and accuracy of reading words and nonwords) emerged as a single factor, suggesting that they reflect the same underlying skill. There was no clear dissociation, either, between the cognitive predictors of phonological recoding and orthographic processing. The results suggest, therefore, that these two types of processing are very closely integrated; indeed, the distinction between them may be arbitrary to some degree. A dissociation appeared, on the other hand, between reading and spelling skills. This is likely, however, to be an artifact of study design. Even more fundamental questions may be raised about my original conceptualization of orthographic processing. I assumed that a variety of apparently different manifestations: orthographic accuracy or plausibility of spellings, high reading speed, lexicality and familiarity effects, all reflected the operation of the same set of

299 processes responsible for encoding letter order and letter positional frequencies - namely, orthographic processing. This assumption requires more direct testing. The indirect evidence from my study raises doubts about the validity of that idea, however: predictors of reading speed and of orthographic accuracy of spelling (both expected to reflect orthographic processing) were quite different. Also, the study would benefit from using the letter string choice tests (e.g. “Which one looks more English - ckun or nuck^l), which is considered the purest measure of orthographic processing (Vellutino, Scanlon & Chen, 1994).

9.2.3. Reading versus spelling

Differences in the time and method of collecting reading and spelling data limited the opportunity for exploring the developmental relationships between the two skills. The same methodological factors were probably also responsible for the fact that the phonological and morphological skills appeared unexpectedly weak (and typically non­ significant) predictors of spelling. I expected that the Polish children would be accurate on reading, and phonologically accurate on spelling, but that they would make numerous orthographic spelling errors. This was expected given the structure of the Polish orthography, which may be non-transparent, irregular and inconsistent for spelling, but is always regular and consistent (even if non-transparent) for reading (see chapters 3 and 4). Most of predictions were not confirmed. Complex (non-transparent) grapheme-phoneme mappings appeared hard to use in reading and spelling alike. Also, orthographically accurate spelling of real words was not the hardest task: it was the phonologically accurate reading and spelling of complex nonwords that typically induced the highest number of errors. This suggests, first of all, a relatively high overall complexity of the Polish orthography, which makes it difficult to acquire not only orthographic spelling, but also recoding skills. Secondly, it suggests a close similarity between mental representations and retrieval processes used for reading and for spelling. My results do not directly inform the debate about the storage of orthographic representations (separate lexicons for reading and spelling versus a single one). Yet, they suggest that if separate reading and spelling lexicons do exist, they must encode orthographic information in a similar way.

300 9.3. LIMITATIONS OF THE STUDY AND FUTURE DIRECTIONS

Arguably the greatest limitation of the project was its cross-sectional, instead of longitudinal, nature. This precluded direct testing of causal hypotheses, especially the hypothesis of reciprocal causal relationship between literacy and its requisite skills. Correlational analyses allowed me to discover a number of specific relationships (i.e., independent of age, vocabulary knowledge and general reasoning ability) between reading, spelling and different cognitive skills. It was impossible, however, to ascertain whether the cognitive skills thus identified were prerequisites or products of literacy. Most likely they were both. The study was also limited in its span. It aimed at describing the initial period of literacy acquisition. Yet, it excluded grade 0 children (i.e., those in the very first months of their reading instruction). I extrapolated my grade results to hypothesize that 0 grade reading is even more overtly alphabetic (based on sequential sounding out and blending of individual letters) than grade reading. Krasowicz-Kupis (1999) and, particularly, Sochacka (2001) presented results confirming this hypothesis. However, these authors also pointed out that, at no stage was purely alphabetic reading observed (i.e. free of any whole word processing strategies, or top-down influences from the sentence context). The ecological validity of the study would have been enhanced if the general literacy ability (reading comprehension, free writing) had also been tested. While the study explored the development of word-level reading and spelling skills, it remains to be seen how these contribute to literacy in its core sense: the ability to understand written messages and express oneself in writing. Group, rather than individual testing of spelling skills (which was done because of time limitations) also limited the possibility of comparing reading and spelling development directly. It is this methodological factor that was probably responsible for the unexpectedly poor predictability of spelling skills from other cognitive abilities. One may also question the validity of some theoretical constructs adopted in the study; the operationalization of those constructs, and the validity of specific tests. Problems of conceptualization and measurement have already been discussed with respect to orthographic processing. It remains to be seen whether a single orthographic process exists (responsible for encoding letter order and letter positional

301 frequencies), which manifests itself in all diverse aspects of reading and spelling that I treated as “orthographic”. The concept of orthographic complexity that was applied to reading and spelling analyses (chapter 6) also requires conceptual and operational refinement. At closer inspection, the parameter of complexity appeared to confound three different factors. Firstly, complexity implied lack of orthographic transparency, i.e., grapheme-phoneme mappings that did not reflect basic sounds of letters, but the morphological structure of words. Secondly, it implied graphemic complexity per se: letters with diacritics or digraphs, instead of ‘basic’ Roman letters. Thirdly, complex mappings and graphemes were also those which children learned late, in the second semester of grade 1, or even in the beginning of grade 2. With the present design it is impossible to say which out of these three factors was responsible for the strong complexity effect that was found. It is plausible that each one of them made its independent contribution. The study also explored the role of word frequency on reading and spelling, which appeared small and inconsistent. However, it is the written word frequency (familiarity with a word in its written form) that is most likely to affect the performance. As no written word frequency counts were available, the data on the spoken word frequency of pre-school children had to be used instead, which could ‘dilute’ the possible frequency effects. Also, the words were sampled from a rather limited frequency range, with all items likely to be familiar to children. Some potential problems with the validity of my morphological tasks as measures of morphological awareness have been mentioned already. Although all four morphological tests undoubtedly required morphological operations, they probably depended more on good vocabulary knowledge and tacit linguistic competence than explicit, metalinguistic control. The study would also benefit from a closer liaison with classroom teachers, the special needs teacher and parents, in order to collect more information on classroom instruction, remediation and home literacy experiences. I assumed that instruction was the same in all classes, which may not have been the case. Monitoring instruction is important, given my conclusion that instruction is critical for the development of explicit strategies children use to process written words. It would be particularly interesting to check whether grade teachers who encourage syllable-by-syllable reading (instead of sounding out individual graphemes) indeed made children adopt such a strategy. Inclusion of syllable-level tests of phonological awareness would also be interesting in this context. These were excluded because the literature review

302 suggested that the syllabic awareness was typically achieved by the time children entered school, and that it was only weakly and indirectly related to reading acquisition (e.g., Cossu et. al., 1988). However, a Polish study (Krasowicz-Kupis, 1999) found considerable variability in pre-school and early school syllable awareness, which appeared a relatively good predictor of reading skills. It is possible, therefore, that the salient syllabification of Polish, the predominance of multisyllabic words (even in early reading vocabulary), and reading instruction that emphasizes syllables, may encourage Polish early readers to rely on syllabic processing. Concern may also be raised about poor consistency of identifying dyslexic cases, apparent when my own identifications (based on psychometric criteria) were compared with those made by the two school psychologists (who used a combination of formal cognitive tests and classroom information). A longitudinal study would, again, provide an optimal way of establishing the most valid criteria for dyslexia - that is, the ones that identify the most persistent and severe written language difficulties, which seriously jeopardize educational progress. The study consistently refuted the hypothesis that higher-order visual processes directly constrain early reading and spelling development. The possible exception from this pattern was visual discrimination skills, whose role (particularly for spelling) requires further study. It is still possible, however, that the higher-order visual skills directly constrain only some specific aspects of orthographic processing that are particularly visually demanding - such as processing of diacritics. This hypothesis has also been suggested for the Hebrew language (Shatil & Share, 2000) and requires further investigation.

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327 A P P E N D I X 1

DESCRIPTIVE STATISTICS

GRADE 1 GRADE 2 GRADE3 OVERALL Possible range of scores word-accuracy Valid N N=36 N=36 N=33 N=105 0-100 % Mean 79 94 96 89 Median 83 96 98 95 Std Deviation 16 6 4 13 Min. - Max. 45 - 100 80 -100 85 -100 45 - 100 Skewness -.574 -.928 -1.004 -1.783 Kurtosis -.617 -.044 .649 2.855 nonword- Valid N N=34 N=34 N=33 N=101 0-100 accuracy % Mean 53 70 77 66 Median 50 70 78 70 Std Deviation 27 17 13 22 Min. - Max. 0-100 28-95 38-98 0-100 Skewness -.184 -.760 -.649 -.953 Kurtosis -1.012 -.005 .594 .375 word-speed Valid N N=37 N=36 N=34 N=107 (secs, per Mean 5.85 1.77 1.14 2.98 word) Median 4.70 1.27 .96 1.63 Std Deviation 3.98 1.19 .48 3.22 Min. - Max. 1.15-15.75 .57-6.48 .55 - 2.53 .55 - 15.75 Skewness .929 1.948 1.185 2.126 Kurtosis -.100 5.752 .958 4.224 non word- Valid 5^ N=35 N=33 N=35 N=103 speed Mean 6.31 2.49 2.09 3.65 (secs, per Median 5.85 2.17 2.03 2.68 word) Std Deviation 3.60 1.28 .70 2.95 Min. - Max. 1.65-14.45 1.02-7.33 1.08-4.20 1.02-14.45 Skewness .717 1.916 .775 1.918 Kurtosis -.355 5.253 .659 3.335 spelling-words Valid N N=29 N=27 N=16 N=72 0-100 % accuracy Mean 70.69 77.13 88.75 77.12 Median 70 82.50 90 80 Std Deviation 13.48 14.34 9 14.60 Min. - Max. 40-95 33 -9 3 65 -100 33 - 100 Skewness -.451 -1.46 -1.048 -.827 Kurtosis .077 2.355 1.107 .522 spelling- Valid N N=29 N=27 N=16 N=72 0 -1 0 0 nonwords Mean 70 58.98 78.75 67.81 % accuracy Median 70 60 77.50 70 Std Deviation 14.45 15.88 .08 15.76 Min. - Max. 40-95 13-85 65-93 13-95 Skewness -.352 -.987 .094 -.812 Kurtosis -.502 1.590 -1.171 1.092

Table A-1. Descriptive statistics: Reading and spelling variables

328 GRADE 1 GRADE 2 GRADES OVERALL Possible range of scores Nonword Valid N N=35 N=34 N=35 N=104 0 -3 0 repetition Mean 18.06 16.97 20.51 18.53 Median 18 18 21 18 Std Deviation 3.57 4.48 3.20 4.03 Min. - Max. 11-25 4-28 12-27 4-28 Skewness .127 -.178 -.686 -.381 Kurtosis -.587 1.628 .368 .581 Alliteration Valid N N=36 N=36 N=35 N=107 0-32 oddity Mean 21.53 25.28 28.03 24.92 Median 23 26 29 26 Std Deviation 6.48 5.70 3.90 6.05 Min. - Max. 8-32 10-32 15-32 8-32 Skewness -.480 -1.221 -1.544 -1.039 Kurtosis -.678 1.186 2.626 .370 Rhyme Valid N N=35 N=36 N=35 N=106 0-32 (feminine) Mean 14.97 18.89 20.49 18.12 oddity Median 16 19 20 19 Std Deviation 5.67 6.67 6.32 6.60 Min. - Max. 5-23 6-30 10-32 5-32 Skewness -.070 -.376 -.017 -.067 Kurtosis -1.410 -.488 -.918 -.755 Rime oddity Valid N N=35 N=36 N=35 N=106 0-32 Mean 16.80 21.03 22.51 20.12 Median 16 22 22 21 Std Deviation 7.34 6.65 5.52 6.92 Min. - Max. 4-30 0-32 12-32 0-32 Skewness .166 -1.039 -.122 -.470 Kurtosis -1.047 1.556 -1.022 -.354 Phoneme Valid N N=35 N=34 N=35 N=104 0-26 deletion Mean 15 19 22.23 18.74 Median 16 20.50 23 20 Std Deviation 4.67 5.39 3.13 5.35 Min. - Max. 4-25 1-26 14-26 1 -26 Skewness -.365 -1.656 -1.316 -.967 Kurtosis .170 3.173 1.601 .683 Vowel Valid N N=35 N=36 N=35 N=106 0-48 replacement Mean 29.49 33.28 38.94 33.90 Median 32 36.50 40 37 Std Deviation 12.04 12.65 6.83 11.42 Min. - Max. 2-48 2-48 21-48 2-48 Skewness -.496 -.896 -.799 -.950 Kurtosis -.541 -.133 -.012 .203 Consonant Valid N N=35 N=34 N=35 N=104 0-48 replacement Mean 26.26 28.06 33.09 29.14 Median 26 28 34 28 Std Deviation 7.28 9.91 7.56 8.73 Min. - Max. 14-43 6-48 17-48 6-48 Skewness .467 .085 -.045 .086 Kurtosis .054 -.153 -.673 -.333

Table A-2. Descriptive statistics: Phonological and morphological variables

329 GRADE 1 GRADE 2 GRADE 3 OVERALL Possible range of scores Phoneme Valid N N=36 N=36 N=33 N=105 0-18 analysis Mean 14.83 16.61 17.42 16.26 Median 16 17 18 17 Std Deviation 3.53 1.74 .71 2.56 Min. - Max. 6-18 9-18 16-18 6-18 Skewness -1.312 -2.606 -.838 -2.407 Kurtosis .900 9.587 -.490 6.059 Phoneme Valid N N=35 N=36 N=35 N=106 0-18 blending Mean 13.14 15.03 16.06 14.75 Median 15 16 17 16 Std Deviation 5 3.49 1.95 3.85

Min. - Max. 2-18 5 -18 1 1 - 18 2-18 Skewness -1.067 -1.694 -.887 -1.721 Kurtosis -.177 2.018 -.091 2.326 Morphology: Valid N N=35 N=35 N=35 N=105 0-64 Comparison of Mean 35.51 40.26 50.51 42.10 adjectives Median 37 43 52 43 Std Deviation 12.43 12.04 9.01 12.81 Min. - Max. 6-58 8-59 24-62 6-62 Skewness -.161 -.790 -1.027 -.601 Kurtosis -.306 .088 .940 -.250 Morphology: Valid N N=36 N=35 N=35 N=106 0-64 Verb prefixation Mean 31.72 38.74 51.97 40.73 Median 26.50 45 54 46.50 Std Deviation 16.23 16.42 10.24 16.74 Min. - Max. 5-61 0-62 15-63 0-63 Skewness .295 -.671 -2.144 -.594 Kurtosis -1.181 -.665 5.572 -.955 Morphology: Valid N N=35 N=34 N=35 N=104 0-64 Diminutives Mean 50.34 54.88 59.06 54.76 Median 51 56 60 56 Std Deviation 6.29 6.38 3.35 6.54 Min. - Max. 36-60 32-63 51-64 32-64 Skewness -.570 -2.140 -.749 -1.254

Kurtosis - . 1 0 2 5.836 -.058 1.711 Morphology: Valid N N=35 N=35 N=35 N=105 0-64 Derivative forms Mean 29.34 33.77 40.83 34.65 Median 30 34 42 36 Std Deviation 9.92 10.54 8.49 10.71 Min. - Max. 10-49 6-54 23-56 6-56

Skewness . 1 0 1 -.520 -.558 -.335 Kurtosis -.676 .270 -.318 -.483

Table A-2 continued

330 GRADE 1 GRADE 2 GRADE 3 OVERALL Possible range of scores RAN - pictures Valid N N=34 N=36 N=35 N=105 (secs.) Mean 111.65 94.86 91.31 99.11 Median 108.50 92.50 89 96 Std Deviation 23.83 16.39 18.54 21.47 Min. - Max. 72 - 177 69 -150 67 -130 67 - 177 Skewness 1.109 1.161 .378 1.061 Kurtosis 1.253 2.353 -1.056 1.790 RAN - digits Valid N N=35 N=35 N=35 N=105 (secs.) Mean 83.20 62 56.86 67.35 Median 74 62 55 62

Std Deviation 39.69 1 1 . 2 1 13.10 27.27 Min. - Max. 46 - 290 39-89 31-94 31 - 290

Skewness 4.366 . 1 2 0 1.185 5.431 Kurtosis 22.682 -.242 2.324 42.651 Grapheme Valid N N=35 N=35 N=35 N=105 naming speed Mean 1.09 .71 .68 .83 (secs, per Median 1.06 .67 .67 .76 grapheme) Std Deviation .38 .17 .14 .31 Min. - Max. .47 - 2.01 .45 - 1.33 .4 4 -1 .0 3 .4 4 -2 .0 1 Skewness .893 1.374 .298 1.736 Kurtosis .678 3.315 -.457 3.684

Grapheme Valid N N=34 N=34 N=34 N=102 0 - 1 0 0 naming Mean 81 95 98 92 accuracy % Median 84 97 98 96

Std Deviation 13 5 2 1 1 Min. - Max. 51-99 78 -1 0 0 94 - 100 51 - 100 Skewness -.650 -1.883 -.825 -1.888 Kurtosis -.452 4.613 .461 3.107

Table A-3. Descriptive statistics: Naming speed and fluency variables

331 GRADE 1 GRADE 2 GRADE 3 OVERALL Possible range of scores Fluency: Valid N N=35 N=35 N=34 N=104

semantic Mean 17.49 20.14 22.47 2 0 . 0 1

Median 17 2 1 22.50 2 0 Std Deviation 4.94 5.04 4.40 5.18 Min. - Max. 9-28 11-35 11-30 9-35 Skewness .093 .607 -.339 .048 Kurtosis -.711 .940 .222 -.168 Fluency: Valid N N=35 N=35 N=35 N=105 alliteration Mean 8.80 11.14 13.94 11.30

Median 9 1 1 13 1 1 Std Deviation 3.57 3.90 2.59 3.98

Min. - Max. 2-17 6 - 2 2 1 0 - 2 1 2 - 2 2 Skewness .038 .606 1.070 .037 Kurtosis -.280 .181 .868 .017 Fluency: rhyme Valid N N=34 N=33 N=35 N=102 (feminine) Mean 2.32 3.12 3.40 2.95

Median 2 3 3 3

Std Deviation 2.27 2 2.06 2.14

Min. - Max. 0 - 9 0 - 8 0 - 8 0 - 9 Skewness 1.548 .826 .365 .819 Kurtosis 2.071 .678 -.641 .134 Fluency: rime Valid N N=32 N=33 N=34 N=99

Mean 2 . 6 6 2.33 2.88 2.63

Median 2 2 3 2

Std Deviation 2.19 2 . 0 1 2.03 2.07

Min. - Max. 0 - 8 0 - 8 0 - 9 0 - 9 Skewness .893 1.058 1.005 1.003 Kurtosis .678 .911 1.429 .747

Table A-3 continued

332 GRADE 1 GRADE 2 GRADE 3 OVERALL Possible range of scores Visual memory Valid N N=34 N=35 N=35 N=104 0-24 (Chinese letters) Mean 20.38 20.89 21.83 21.04

Median 2 1 2 1 2 2 2 1

Std Deviation 2.07 2.31 2 . 0 2 2 . 2 0 Min. - Max. 15-23 14-24 16-24 14-24 Skewness -.612 -.930 -1.179 -.811

Kurtosis -.127 1 . 2 2 1 1 . 1 2 1 .400 Copying Rey Valid N N=35 N=34 N=35 N=104 0-36 figure: accuracy Mean 25.09 25.90 28.16 26.38 Median 24.50 26.25 29 26.50 Std Deviation 3.68 4.43 3.76 4.14 Min. - Max. 1 7 .5 -3 3 1 6 .5 -3 2 18-34 16.5 - 34 Skewness .072 -.416 -.907 -.366 Kurtosis -.096 -.891 .731 -.613 Copying Rey Valid N N=34 N=34 N=32 N=100 figure: time Mean 253.41 238.44 247.56 246.45 (secs) Median 221.50 209.50 228 218 Std Deviation 111.85 90.90 134.49 112.37

Min. - Max. 104-541 138 - 523 119-888 104 - 8 8 8 Skewness 1.085 1.764 3.752 2.597 Kurtosis .430 3.477 17.161 10.452 Letter Valid N N=36 N=34 N=35 N=105 0-16 discrimination: Mean 15.17 14.56 15.27 15 accuracy Median 15 15 15.50 15 Std Deviation .77 1.48 .77 1.09 Min. - Max. 14-16 9.5 - 16 13-16 9.5 - 16 Skewness -.304 -1.437 -1.365 -1.825 Kurtosis -1.242 2.901 1.755 5.698 Symbol Valid N N=34 N=36 N=35 N=105 0-16 discrimination: Mean 14.88 14.35 14.53 14.58 accuracy Median 15 14.50 14.50 15

Std Deviation .91 1.07 1 . 0 1 1 . 0 1

Min. - Max. 13-16 12-16 1 1 - 16 1 1 - 16 Skewness -.263 -.490 -1.251 -.703 Kurtosis -.850 -.203 3.130 .766 Letter Valid N N=35 N=34 N=35 N=104 discrimination: Mean 138.17 85.31 84.26 102.75

time (secs.) Median 1 2 0 81.25 77.50 91.25 Std Deviation 62.15 23.69 29.72 48.88 Min. - Max. 53 - 360 31-138 38.5 - 201 31 - 360 Skewness 1.915 .196 1.784 2.441 Kurtosis 4.747 -.054 5.837 9.104 Symbol Valid N N=34 N=36 N=35 N=105 discrimination: Mean 113.74 92.78 88.93 98.28 time (secs.) Median 96 88.25 89 91 Std Deviation 77.26 23.81 25.52 49.15 Min. - Max. 58 - 520 51 - 136.5 55 -182 51-520 Skewness 4.681 .097 1.639 6.294 Kurtosis 24.604 -1.028 4.103 52.534

Table A-4. Descriptive statistics: Visual variables.

333 A P P E N D I X 2

TESTS USED IN THE STUDY

334 NONWORD REPETITION NONW-REP fVl4CZDYKTAF0N!

Bçdç ci teraz môwil dziwnie brzmi^ce sJowka, a ty stuchaj uwaznie 1 powtarzaj dokladnie to CO powledziaiem.

1. AREN y 16. NASKUT y

2. USZCZOSYM y 17. ZDJ^SZUTOCZ y 0

3. GDZIL^ZARY y 0 18. UCZOGURAL / 0

4. UWONDZIJACHEM y 0 19. 0Z1EYLKACZ4S y 0

5. MNOClJiJCHUBAREC y 0 20. DWOGIDZOFATUNI y 0

6. KOMRU y 0 21. CZLEWOP y 0

7. BZD4FADZE y 0 22. SNIDUGRZYCH y 0

8 . KIMOGLABER y 0 23. DZUBYJACHNl y 0

9. WÉC1CHEZYNUPAT y 0 24. CHRZCZ4S1Z0KATY y 0

10. WZMI^ZILOKACZORDZE y 0 25. WYGlTRZj^ZlDANEF y 0

11. PRZABY y 0 26 SKRACM y û

12. USLATYJ y 0 27. POLYZIK y 0

13. RWi;SlGOLESZ y 0 28. MGLOSADNICE y 0

14. KTACIDLYGUSZEF y û 29. pî;funizadej y 0

15. TADZ1EYN4SZAGUÉ y 0 30. CHESCIDZIÇZAMORA y 0

WYL4CZDYKTAFON! ALLITERATION ODDITY TEST

Teraz powiem ci kilka slow. Trzy z nich bfdq siç zaczynac tak same, a jedno bçdzie siç zaczynac inaczej.

Posluchaj: BALON, SILA, BOCIEK, BÔJKA .... BALON, BOCIEK i BÔJKA brzmi^ podobnie, bo zaczynaj^ siç tak samo (akcentujemy wymowç pierwszej gioski). SIowo SILA nie pasuje, bo zaczyna siç inaczej.

Powiedz, ktore slowo teraz nie pasuje: CALY, DZIECI, CESARZ, CÔRKA .... (dziecko podpowiada. Nawet gdy odpowiedz jest prawidlowa, wyjasniamy): Tak, CALY, CESARZ i CORKA zaczynajq siç tak samo. Slowo DZIECI zaczyna siç inaczej, wiçc nie pasuje.

Powiedz CO teraz nie pasuje: PIANA, PIESEK, ZJECHAC, PIÔRO (wyjasniamy jesli dziecko waha siç, lub zrobi bi^d): PIANA, PIESEK i PIÔRO zaczynaj^ siç na ten sam dzwiçk. ZJECHAC zaczyna siç na inny dzwiçk, i nie pasuje.

Sprobujmy jeszcze:

(slowa podajemy wyraznie, rytmicznie, w tempie ok. 1/sek., nie akcentuj^c jednakze sztucznie zadnych fragmentow)

ODPOWIEDZ OCENA 1. trzaskac grz^dkl trzysta trzepak 2. lody leciec linia roczek 3. obiad uczeh usta ukrasc 4. zupa z^bek zawias zebrac 5. ekran afisz alarm aniol 6. m eta myslec lahcuch m ostek 7. krolik drew no krakac krysztal 8. slyszec slupek wloczka slow o 9. obrac uczeh osiol obiad 10. zupa zolnierz zebrac zycie 11. echo ekran aniol etat 12. lahcuch lozko lowic m eta 13. droga krolik drewno drapac 14. w losy wlazic wloczka slyszec 15. leciec rybka ramiç roczek 16. grz^dki grzebieh trzaskac grzyby

Ü 6 FEMININE RHYME ODDITY TEST

Teraz zagramy w rymowanki.

Musimy sobie najpierw przypomniec, co to rymy. Takie slowa jak BYK, LYK, RYK, albo LAPKA, KANAPKA, CZAPKA rymuj% siç, to znaczy konczq siç tak samo.

Teraz powiem ci kilka slow. Trzy z nich bçdq siç kohczyc tak samo, czyli rymowac, a jedno nie.

Posluchaj: MAMA, SAMA, GORY, TAMA .... MAMA, SAMA i TAMA rymuj^ siç. Slowo GORA kohczy siç inaczej, wiçc nie rymuje siç.

Powiedz, ktore slowo teraz nie pasuje: KONIK, GONlé, SLONIK, TONIK .... (dziecko podpowiada. Nawet gdy odpowiedz jest prawidlowa, wyjasniamy): Tak, KONIK, SLONIK i TONIK kohczq siç tak samo. Slowo GONIÉ kohczy siç inaczej, nie rymuje siç i nie pasuje.

Powiedz CO teraz nie pasuje: TUBA, ZABA, SRUBA, GRUBA .... (wyjasniamy jesli dziecko waha siç, lub zrobi bl^d): TUBA, SRUBA, GRUBA rymuj^ siç, a ZABA brzmi trochç inaczej, i nie pasuje.

Sprobujmy jeszcze:

ODPOWIEDZ OCENA 1. zganic ranic kranik chrzanic 2. nora smola szkola kola 3. danie lanie zdanie konie 4. upic chlupac kupic zlupic 5. kreski szeiki wielki belki 6. dusic nudzic kusic zmusic 7. dzialo pala strzala skala 8 . statek bratek kotek platek 9. konie dlonie slonie danie 10. deski kreski szeiki lezki 11. dzialo smialo malo skala 12. statek kotek mlotek plotek 13. nudzic budzic dusic studzic 14. kupic tupac chlupac chrupac 15. chrzanik kranik stanik zganic 16. kora smola nora pora

ii? MASCULINE RHYME (RIME) ODDITY TEST

Teraz sprobujemy jeszcze inne rymowanki. Juz wiesz, co to znaczy, ze slowa siç rymujq. To znaczy ze kohczy siç tak samo. Na przykiad posiuchaj: WUJ, MÔJ, PARK, TWOJ.... WUJ, MOJ i TWOJ rymujq siç ze sob^, a PARK nie.

Powiedz, ktore sJowo teraz nie pasuje: PLOT, MLOT, KOT, ROK .... (dziecko podpowiada. Nawet gdy odpowiedz jest prawidlowa, wyjasniamy): Tak, PLOT, MLOT i KOT koncz^ siç tak samo. Slowo ROK konczy siç inaczej, nie rymuje siç i nie pasuje.

Powiedz C O teraz nie pasuje: LEW, STAW, SPIEW, ZLEW .... (wyjasniamy jesli dziecko waha siç, lub zrobi bl^d): LEW, SPIEW i ZLEW rymujq siç, a ST AW brzmi trochç inaczej, i nie pasuje.

Sprobujmy jeszcze:

ODPOWIEDÉ OCENA 1. ktoz gr 6b dziob ztob 2, dzien pieh dion len 3. nos pas las czas 4. dar smar hak zar 5. ruch duch zuch grzech 6. bye myc dym kryc 7. krasc pasc masc jesc 8 . prog wor wrog bog 9. czas los nos kos 10. hak smar brak rak 11. ruch mech pech grzech 12. dym Rzym rym bye 13. jesc krasd niesc czesc 14. wor dwor bog chor 15. ktoz noz stroz grob 16. koh ieh dIon bron PHONEME ANALYSIS

Teraz sprobujemy roztozyc stowa na maie kawalki, z ktorych sq zbudowane. Te kawaleczki to dzwiçki, albo, inaczej, gioski. Powiedz mi jakie dzwiçki slyszysz w slowie DOM? .... (pomagamy, jesli to konieczne) Dobrze. A teraz sprobuj mi pokazac to samo, uzywajqc zetonow (monet). Powiedz glosno kazd^ gloskç po kolei, i dla kazdej poioz na stole jeden zeton, o tak: D - O - M (demonstrujemy). Sprobuj zrobic to samo dla slowa KOSZ .... Bardzo dobrze. Môwisz kazd% gloskç po kolei, i jednoczesnie dotykasz zetonow. Teraz sprobuj slowo KORA (np. kora drzewa).... w powyzszych przyktadach wazne jest, aby dziecko - nawet jesli nie potrafi wyodrçbnic wszystkich gtosek w slowie - zrozumialo ze chodzi nam o gioski, nie svlabv ani nie literv (stqd szczegôlnie wazne sq dwa ostatnie przyklady), wymawialo dzwiçki glosno, i iednoczesnie kladlo na stole zetony w rzçdzie, albo dotykalo juz lezqcych zetonow. Badanie zaczynamy od pozycji 7 i kontynuujemy, az osoba badana popelni trzy sukcesywne blçdy. Jezeli blqd wystqpi juz w pozycji 7 lub 8, wôwczas cofamy siç "'rakiem" az do pocz^tku (nieco podobnie jak w badaniu testem Columbia).. Nie powtarzamy zadnej prôby, chyba ze osoba badana sobie tego zyczy. Powtôrn^ prôbç nalezy wyraznie zaznaczyé dwiema pionowymi kreskami //

1)ROK ______3 2)STO ______3 3)MALY ______4 4)BRAT ______4 5)ZAMEK ______5 6)DROGA ______5 7)ZAKUPY ______6 8 )SZNUREK 6 9)WYPADEK 10)TABLICA 11)CZEKOLADA 12)MROWISKO 13)NAMALOWAC 14)POWOLUTKU 15)WYKOLEJONY 10 16)WYDRUKOWA(^ 10 17)POKOLOROWAC 11 18)KRASNOLUDEK 11 PHONEME BLENDING

Teraz pobawimy siç w zgadywanie slow. Ja bçdç môwil rôzne slowa w bardzo dziwny sposôb, tak jakbym byl robotem albo jak^s maszynq, ktôra dopiero uczy siç môwic, a ty musisz zgadn^c jakie slowo prôbujç powiedziec. Na przyklad: m - a - m .... Tak, “mam”, na przyklad Mam siedem lat”. A teraz: m - a- m - a .... Tak, “mama”, na przyklad “moja mama”. Nasz robot nie ma ust, tak jak ludzie, tyiko glosnik, wiçc ja zasloniç swoje usta (zaslaniamy doln^ czçsc twarzy) zebys nie widzial CO prôbujç powiedziec. Uwaga:

Badanie zaczynamy od pozycji 7 i kontynuujemy, az osoba badana popetni trzy sukcesywne btçdy. Jezeli blqd wystqpi juz w pozycji 7 lub 8, wôwczas cofamy siç ‘’rakiem” az do pocz^tku (nieco podobnie jak w badaniu testem Columbia).. Nie powtarzamy zadnej prôby, chyba ze osoba badana sobie tego zyczy. Powtôrn^ prôbç nalezy wyraznie zaznaczyc dwiema pionowymi kreskami //

1) k - 0 - 1 3 2) d - w - a 3

3) 1” a - t - 0 4 4)p-t-a-k 4 5)b-a-l-o-n 5 6)m-I-e-k-o 5 T)p”0 ”2“0~d-a 6 8)g-r-o-sz-e-k 6 9)D-o-I-i-cz-v-c 7 101 z-a-D - a- l- k- a 7 11) n - a - D- i- s- a- n- e 8

12) 2 -a-r-n-u-sz-e-k 8 13) k-a-l-o-r-y-f-e-r 9 14) p-u-d-e-l-e - cz - k - o 9 15) z-a-cz-a-r-o-w-a-n-y 10 16) s-p-a-c-e-r-o-w-a-c 10 17) p-o-z-a-p-i-s-y-w- a - c 11

18) z - d - e-n-e-r-w -o-w -a-c 11

bho PHONEME DELETION PH - DEL

Pewnie wiesz (juz mowilismy o tym), ze wszystkie slowa skladajq siç z dzwiçkow, czyli tak zwanych gtosek. Teraz sprobujemy wyjmowac pojedyncze dzwiçki z roznych stow i zobaczymy, co zostanie. Powiedz mi, co styszysz na pocz^tku stowa MAMA? .... Tak, /m/. A teraz sprobuj powiedziec “mama” bez /m/ na poczqtku Tak, AMA. MAMA - AMA.

Stuchaj uwaznie i powiedz co styszysz na samym poczqtku stowa GRUSZKA? .... /g/. Sprobuj powiedziec “gruszka” bez /g/ na poczqtku .... RUSZKA. Jak zabierzemy /g/ z GRUSZKA to zostanie RUSZKA (akcentujemy pierwsz^ gtoskç). A jak zabierzemy nastçpny dzwiçk, to co zostanie? .... USZKA. Zostaty USZKA. Sprobuj powtorzyc jeszcze raz od poczqtku: GRUSZKA....

A teraz trochç trudniejsze stowo: MGLA - MGLA. Co zostanie, jak zabierzesz pierwszy d ^ içk? .... A drugi.... I jeszcze jeden .... Tak, mamy MGLA - GLA - LA - A.

(Jest to trudne cwiczenie, i moze wymagac wieiokrotnego powtarzania slow, i dodatkowych wyjasnien. Wazne jest aby dziecko - nawet gdy nie potrafi manipulowac gtoskami poprawnie - zrozumialo samq ideç ich kolejnego odejmowania. NIE nalezy uciekac siç do zadnych pomocy wizualnych - literek, rysunkow, klockôw, itp.). Pocz^tkowe gioski, oraz zbiegi spolgloskowe nalezy wymawiac bardzo wyraznie, z pewnq przesad^ - ale tylko w probach. We wlasciwym tescie slowa wymawiamy glosno i wyraznie, Jeez naturalnie. Dobrze. Sprobujmy zrobic to samo z innymi stowami. Ja powiem jakies stowo, a ty sprobuj zabrac z niego pierwszy dzwiçk, a jak poproszç, to tez nastçpny. Uwaga: 1) TAK ______2) JUTRO ______3) MOCNY ______

4) STO - STO Zabierz pierwszy dzwiçk ...... i jeszcze jeden ......

5)PROSTY

6)ZNACZEK

7)STRACH

8 )SKLADAé

9)ZD J4è

10)PSTR4G

11)ZD±BLO CONSONANT REPLACEMENT

ZnaSZ moze opowiadania O muminkach?... f./es7i /7ie to podajem y kro^he w}Jas'/7/enie: mumm/ci to ta k ie 777de okrqgie stH’orzonka ktore zyjq n' da/ekim kraju, / zdarzajq im si^ rozae cieÂ'awep/'zygody itp.). Jedno z opowiadah o muminkach to opowiadanie o Funku i Furice. Funiek i Funka byli par^ stworzonek, ktore pewnego dnia przyszty do doliny muminkow. Na poczqtku jednak nikt nie mogt siç z nimi dogadac, bo mowili wtasnym, dziwnym jçzykiem. Dopiero po pewnym czasie ktos ten jçzyk zrozumiat: tak naprawdç Funiek i Funka mowili tak samo jak my, tylko zamiast pierwszego dzwiçku w kazdym slowie wstawiali /f/. Czyli, zamiast “mama” mowili F AMA, zamiast “tata” - FATA, zamiast “dom” - FOM. Ja w ich jçzyku nie nazywatbym siç Marcin tylko FARCIN, a Basia nie Basia tylko..... Chcç teraz zobaczyc czy ty tez potrafisz mowic tak jak Funiek i Funka. Na przyklad, co powiedzieliby oni zamiast slowa BUT ? .... A zamiast NOC ? .... A zamiast DZEM ? .... Dobrze. Pocwiczmy jeszcze trochç jçzyk Funka i Furiki.

1) KOTEK ______2) ZACZ4C ______3)CZYSTY ______4) MISKA ______5) LUBIC ______6) RYBA ______7) JABIKO ______8) W 4SY ______Posluchaj uwaznie. Zamiast zdania “To jest maly piesek” Funiek z Funkq powiedzieliby FO FEST FALY FJESEK, czyli zamiast “piesek” powiedzieliby FJESEK. A CO powiedzieliby zamiast SZKOLA ? .... A zamiast CZTERY ? .... A zamiast PSUC ?

Wazne jest aby dziecko zrozumiato ze chodzi 0 zamianç tylko pierwszej spotgtoski, a nie catej grupy spétgloskowej. Jesli to konieczne wyjasniamy wprost ze chodzi o zamianç tylko pierwszego dzwiçku.

9) KIOSK ______10) KRÔL ______11) PLAMA ______12) C H C IE é ______13) PRZYBKi______14) STOLIK ______15) SZPITAL______16) SKALA ______VOWEL REPLACEMENT

A teraz sprobujemy pocwiczyc nasz wlasny tajemniczy jçzyk. Bçdzie siç on nazywai ATU, poniewaz zamiast dzwiçku, albo gioski /a/ bçdziemy môwic gloskç /u/. Wszçdzie gdzie slyszysz /a/ zamienisz je na /u/. Zamiast “las” bçdzie LUS, zamiast “ja” - JU, zamiast “mam” - MUM. A co powiesz zamiast HAK ? .... A zamiast DACH ? .... A zamiast PLAC ? ....

1) AS 2) RAK 3) GRA 4) PARK 5) ZART 6) PTAK 7) KRAN 8 ) STRACH

A teraz sprobuj zrobic to samo z takimi slowami, w ktorych sq dwa dzwiçki /a/. Musisz oba zamienic na /u/. Zamiast “mama” bçdzie MUMU, zamiast “tata” ..... zamiast “wata” .... a zamiast “kara” ....

9) FALA ______10) JAMA ______11) KASA ______12) ALARM ______13) ANKA ______14) ZABA ______15) LATA ______16) BRAMA ______

M NAMING SPEED - PICTURES

PV£4CZDVKrAFON/ (Pokazujemy stronç probn^) Chcialbym zebys ponazywal/a wszystkie te obrazki tak szybko, jak tylko potrafisz. Pierwszy obrazek to LAS, drugi to DOM, trzeci HAK, dalej STOL i MYSZ. Teraz powtorz ty (dziecko powtarza. Celem tego powtorzenia jest upewnienie siç, ze dziecko nazywa obrazki w dokladnie taki sposob, Jak wyzej podano. Poprawiamy w razie potrzeby). A teraz powtorz jeszcze raz, tak szybko jak potrafisz (poprawiamy ew. blçdy).

(Pokazujemy stronç 1 ) A teraz poproszç ciç, zebys ponazywal/a te wszystkie obrazki, tak szybko jak tylko potrafisz. PRZFGOTOfVAC^STOPEjR^t2iX2i\ siç tez nie robic zadnych bfçdow. Idz od lewej do prawej, i nie zatrzymuj siç miçdzy rzçdami (wskazujemy rçk^ kierunek nazywania). Ja bçdç mierzyl twoj CZas. Uwaga, START!

DOM LAS HAK LAS STOL LAS STOL MYSZ HAK DOM

STOL LAS LAS STOL MYSZ DOM MYSZ HAK STOL HAK

DOM MYSZ STOL MYSZ LAS DOM DOM MYSZ HAK STOL

DOM HAK STOL HAK LAS MYSZ HAK MYSZ DOM LAS

LAS DOM MYSZ STOL STOL HAK LAS HAK DOM MYSZ

CZAS:

Zrob ok po^mmutowcjiprzerwçprzeAnastçpnym bada/ii'em.

Teraz powtorzymy to samo cwiczenie, tylko obrazki bçdq inaczej ulozone. PPZYGOTOfVAd^ STOPEP/ Pamiçtaj, masz ponazywac wszystkie obrazki tak szybko jak tylko potrafisz, i staraj siç nie robic zadnych blçdôw. Uwaga, START!

MYSZ STÔL LAS DOM LAS STOL DOM HAK MYSZ HAK

HAK DOM STOL LAS STOL DOM HAK MYSZ MYSZ LAS

STOL DOM LAS HAK MYSZ STOL LAS HAK DOM MYSZ

MYSZ DOM HAK MYSZ LAS LAS STOL HAK MYSZ STOL

DOM MYSZ HAK HAK DOM STOL LAS LAS STOL DOM

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(pokazujemy stronç DN-1) Teraz chciatbym, abys przeczytal/a te cyferki najszybciej, jak potrafisz. Czytaj kazd^ cyferkç oddzielnie. Pierwsza cyfra to „trzy”, druga „dwa”, trzecia „piçc”, 1 tak dalej. Czytaj od lewej do prawej(wskazujemy rçk^ kierunek nazywania) 1 nie zatrzymuj slç w przerwach miçdzy cyframi. Przeczytaj cafy rzqdek do kohca, tak szybko jak tylko potrafisz, i staraj siç nie robic zadnych bfçdow. PRZVGOTUJSTOPER/^2i bçdç mierzyt twoj czas. Uwaga, START!

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CZAS:

Zrob ok. polmi/iutowqprzem ’çprzednastçpnym baZaniem.

(pokazujemy stronç DN-2) Teraz zrobimy to samo cwiczenie, tylko cyferki bçd^ inaczej utozone.

PRZYGOTUJSTOPER/czytaj tak szybko jak tylko potrafisz, i staraj siç nie robic zadnych bfçdow. Uwaga, START!

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CZAS: fn'£4CZDrKTAFOM

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DN-2 NAMING SPEED - LETTERS

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Popatrz na tç kartkç, i powiedz mi jakie to litery Dobrze. Sprobuj jeszcze raz, jak najszybciej.... Bardzo dobrze. Teraz pokazç ci drugg kartkç, na ktorej bçdzie duzo wiçcej liter (pokazujemy str. LN-l) Chcç zebys je wszystkie ponazywal/a, tak szybko jak tylko potrafisz. Niektore litery znasz na pewno, ale moze bçdq tez takie, ktorych siç jeszcze nie uczyles/as (to zdanie mozna pomin^c u starszych dzieci). Jezeli nie znasz jakiejs litery, to powiedz szybko „nie wiem” i czytaj nastçpn^. Idz od lewej do prawej, i nie zatrzymuj siç miçdzy rzçdami (wskazujemy rçk^ kiemnek nazywania). Ponazywaj wszystkie litery tak szybko jak potrafisz, i staraj siç nie robic zadnych blçdow. PRZYGOTUJ STOPER Ja bçdç mierzyl twoj czas. Uwaga, START! cz Ç j w rz s u t h P c sz y s 1 ch a z 1 f z 4 m z n r e dz h c d 0 g dz 6 i k dz b

CZAS:

Zrob ok. pobminutowqprzerwçprzednastçp/^ym bada/i/e/n.

(Pokazujemy stronç LN-2) Teraz powtorzymy to samo cwiczenie, tylko litery bçdq inaczej utozone.

PRZYGOTUJSTOPER/ Pamiçtaj, masz ponazywac wszystkie litery tak szybko jak tylko potrafisz, i staraj siç nie robic zadnych blçdow. Uwaga, START! m f cz 1 Ç u 4 s c z

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LN-2 FLUENCY TEST - SEMANTIC

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Teraz sprobujemy zobaczyc, jak szybko potrafisz wymieniac rozne slowa. Na przyklad, sprobuj szybko powiedziec jak najwiçcej rzeczy, ktore mozna zobaczyc w twoim pokoju. (zostawiamy dziecku ok. 15 sekund, zachçcamy, poprawiamy i wyjasniamy w razie potrzeby. Wazne jest, aby dziecko zrozumialo, ze chodzi o pojedyncze slowa, nie opisy rzeczy).

Bardzo dobrze. Teraz, kiedy powiem „start” zacznij wymieniac NAZWY ZWIERZ^T, tak szybko jak potrafisz, zanim nie powiem „stop”. PRZYGOTOfVAC STOPEJi Pamiçtaj, masz mowic NAZWY ZWIERZ^T. Uwaga, START! SOse/cund

W przypadku tej proby, jak i wszystkich kolejnych, naiezy przypomniec slowo-klucz, jesli dziecko milczy przez wiçcej niz 6 sek., lub jesli popeinito dwa blçdy pod rzqd. Jesli widac wyraznie, ze dziecko nie chce kontynuowac badania, mozna - po uprzedniej zachçcie - przerwac danq probç po upiywie 20 sek.

1. 11. 2. 12.

3. 13.

4. 14.

5. 15.

6. 16.

7 .______8 . __ 9. 10.

Swietnie. Teraz sprobujemy zrobic to samo z RZECZAMI DO JEDZENIA. PPZYGOTOfVAdSTOPFP Kiedy powiem „start” zacznij szybko wymieniac wszystkie RZECZY KTÔRE MOZNA ZJEÉ6 , az nie powiem „stop”. Uwaga, START! SOse/cund

1. 11. ______2. 12.______3 .______13.______4 .______14.______5 .______15.______6 . 16. ______7. ______8 . ______

9 . ______10. ______FLUENCY TEST - ALLITERATION FT - ALLIT

Dobrze. Teraz sprobujemy wymyslac slowa, ktore zaczynajq siç na jakis okresiony dzwiçk, czyli gloskç. Na przyklad, jakie slowa potrafisz wymienic, ktore zaczynaj^ siç na /a/? (dziecko wymienia przez ok. 15 sek. Pozniej, aby zachçcic do wymieniania slow nalezqcych do roznych czçsci mowy, i sprawdzic rozumienie zadania, pytamy:) Czy ANTONI bçdzie dobrym slowem? A CO powiesz o slowie ATAKOWAC? A o slowie ALBO? Co ze slowem BABA?

Dobrze. Kiedy powiem „start” zacznij szybko wymieniac slowa, ktore zaczynaj% siç na /t/, tak diugo, az nie powiem „stop” PRZFGOTOfVACSTOPER Powtarzam, wszystkie slowa, ktore zaczynaj^ siç na /t/. Uwaga, START! 30sekund

1 . ______7 .______

2. 8. ______

3. 9.

4 .______10.

5 .______11.

6. 12.

Bardzo dobrze. Sprobuj jeszcze raz, ze slowami, ktore zaczynajq siç na /m/. PRZYGOTOfVAC!^ STOPER Powtarzam, wszystkie slowa, ktore zaczynaj^ siç na Iml. Uwaga, START! SO sekund

1 . ______7 . ______

2 . 8. ______

3 .______9. ______

4 .______10.______

5 .______11.______

6 . 12.______

i 5 6 FLUENCY TEST - FEMININE RHYMES

Teraz sprobujemy wymyslac slowa, ktore siç rymujq. Pamiçtasz pewnie z naszych poprzednich cwiczen, ze takie slowa jak BYK, LYK, RYK, aibo LAPKA, KANAPKA, CZAPKA rymuj^ siç, czyli konczg siç tak samo. Na przyklad, sprobuj powiedziec jakies slowa, ktore siç rymuj^ Z WATA (podpowiadamy i pomagamy, jesli konieczne; szm a/a, chaZa, draZa, /aia, saiata - sugerujemy zwlaszcza brata i salata, aby pokazac, ze slowa ktore siç rymuj^ mog^ miec roznq liczbç sylab, i bye w roznych przypadkach). A takie ktore siç rymuj^ Z KOTEK? (podpowiadamy, jesli konieczne; kotek,pfoiek, mfotek, zwlaszcza /a s k o /e k ) .

Kiedy powiem „start” sprobuj wymienic jak najwiçcej slow, ktore rymuj^ siç ze slowem KRÔWKA, tak dlugo, az nie powiem „stop”. PRZVGOTOfVACSTOPER Powtarzam, mow slowa, ktore rymuj^ siç z KRÔWKA. Uwaga, START! Sûsekund

1 . ______5 . ______

2 . 6.______

3 .______7.______

4. 8 .______

Teraz poproszç ciç o rymy do slowa MALOWAC. PRZVGOTOfVACSTOPER Powtarzam, powiedz jak najwiçcej slow, ktore rymuj^ siç z MALOWAC. Uwaga, START! SOsekund

1 . ______5 .______

2 .______6.______

3 .______7.______

4.______8. ______

i5 9 FLUENCY TEST - MASCULINE RHYMES (RIMES)

Bardzo dobrze. To byto dose trudne cwiczenie, prawda? Zobaczymy, jak sobie poradzisz z jeszcze innymi rymami. Potrafisz powiedziec jakies siowa, ktore siç rymuj^ z KOT? (Dziecko odpowiada przez ok. 15 sek., zachçcamy i podpowiadamy w razie potrzeby: pfot, lot,pot, m iot).

Dobrze. Teraz poproszç ciç o takie slowa, ktore rymuj^ siç ze slowem BOK. FRZVGOTOfVACSTOPER. Sprobuj powiedziec jak najwiçcej slow, ktore rymuj^ siç z BOK. Uwaga, START! SO sekund

1 . ______5 . ______

2 .______6.______

3 .______7.______

4.______8 .______

Na koniec sprobuj my to samo cwiczenie ze stowem STAC. PRZYGOTOfVAC STOPER Sprobuj powiedziec jak najwiçcej slow, ktore rymujq siç ze STAC. Uwaga, START! SOsekund

1 . ______5 .______

2 . 6.______

3 .______7.______

4. 8 .______

Wy£4CZDYKTAEON/

iS 6 COMPARISON OF ADJECTIVES CAD-1

W tym cwiczeniu bçdziemy porownywac slowa ze sob%. Popatrz na ten obrazek (pokazujemy wiewiorkç). Co to jest za zwierzç? .... Tak, to wiewiorka. O wiewiorce czçsto mowimy, ze jest mala, ze to male zwierzç. Popatrz na ten rysunek - co to jest? (pokazujemy mysz). Mysz jest jeszcze mniejsza niz wiewiorka. Mamy wiçc dwa slowa: MAEY i MNIEJSZY, ktorych mozemy uzywac, aby porownywac rzeczy ze sobq.

Popatrz teraz na ten rysunek Iwa (pokazujemy). Lew jest DUZY, ale slon (pokazujemy rysunek) jest jeszcze Tak, WIJÇKSZY. Mamy wiçc nastçpne dwa slowa: DUZY i WI^KSZY, ktorych mozemy uzywac, zeby porownywac rzeczy ze sob%.

Popatrz na mo je spodnie. Kiedy je kupilem, to wydalem niewieie pieniçdzy, wiçc te spodnie byly TANIE. Ale kupilem tez drugg parç i wydalem jeszcze mniej pieniçdzy, wiçc te drugie spodnie byly ....

Jeszcze jeden przyklad. W lawce siedzi dwoch kolegow. Jeden z nich na ogol nie rozmawia na lekcji, zwykle slucha uwaznie i raczej nie przeszkadza innym. O takim uczniu nauczycielka powie, ze jest GRZECZNY. A drugi chlopak nigdy nie rozmawia, slucha uwaznie i nigdy ms. przeszkadza innym. Taki chlopak jest jeszcze .....

(Jesli dziecko mowi: „ bardziej maly, mniej drogi” itp., mowimy: „Dobrze, ale sprobuj to samo powiedziec jednym slowem”).

Ja bçdç môwil rozne slowa, i chcç zebys ty je zmienil w taki sposob jak przed chwilq cwiczylismy. JesU ja powiem MALY, to ty odpowiesz MNIEJSZY, jak ja powiem GRZECZNY to ty .... i tak dalej. Dobrze?

1. CIEKAWY______2. BRZYDKI______3. PI^KNY ______4. BLISKI ______5. BIALY ______6. W^SKI ______7. DOBRY ______8 . LEKKI ______9. SUCHY 10. SZEROKI. 11.JASNY 12. DLUGI 13. BYSTRY 14. CZERWONY 15. KRÔTKI___ 16. CIEPLY

2)59 CAD-2

Bardzo dobrze. Teraz zrobimy to samo cwiczenie jakby na odwrot. To moze byc trochç trudniejsze. Kiedy ja powiem MNIEJSZY, to ty powiesz MALY, jak ja powiem WI^KSZY, to ty powiesz .... Zamiast GRZECZNIEJSZY powiesz .... , zamiast TANSZY bçdzie ....

1. SLABSZY______2. SZYBSZY ______3. SLICZNIEJSZY ______4. NIZSZY ______5. SMIELSZY ______6. GORf^TSZY ______7. GORSZY ______8.M4DRZEJSZY ______9. NOWSZY ______

10. g l ï ;b s z y ______11. CIAÉNIEJSZY ______12. DROZSZY ______13. OSTRZEJSZY ______14. ZIELENSZY ______15. PLYTSZY ______16. ZWYKLEJSZY ______

3G0 DERIVATIVE FORMS DF-1

Nasze nastçpne cwiczenie bçdzie siç nazywalo „rodziny slow”. Moze nie wiedziales/as, ze slowa, tak jak ludzie, maj^ swoje rodziny, czyli swoich krewnych. Wezmy na przyklad slowo MALOWAC - malowac obrazek, aibo malowac scianç. Od MALOWAC pochodzq takie slowa, jak MALOWANIE, aibo MALARZ. Mozna wiçc powiedziec ze slowa MALOWANIE i MALARZ to jakby dzieci slowa MALOWAC. Jak myslisz, od jakiego slowa pochodzi OGRODNIK?

(podpowiadamy jesli konieczne) tak, od OGROD, bo ogrodnik to osoba ktora pracuje w ogrodzie, dba o ogrod.

A na przyklad PRALNIA?......

Tak, od PRAC (aibo od PRANIA), bo po to jest pralnia zeby w niej prac rozne rzeczy.

A CHUDZIELEC? Skqd moze pochodzic CHLDZIELEC?... Tak, od slowa CHUDY.

Bçdç teraz mowil rozne slowa, a ty sprobuj zgadnqc od jakich innych slow one pochodzg,dobrze?

1. APTEKARZ ______2. MYDLO ______3. ÉMIALEK ______4. LODZIARNIA ______5. LOTNISKO ______6. SLEPOTA ______7. POPIELNICZKA______8. STRZYZENIE ______9. RÔW NOSé ______10. KURNIK ______11. KIEROWCA ______12. GRUBAS ______13. GRACZ______14. SPIEWANIE ______15. CZYSCICIEL ______16. SPAWARKA ______DF-2

Bardzo dobrze. W cwiczeniu, ktore robilismy przed chwilq mielismy „stowa - dzieci”, takie jak MALARZ, OGRODNIK, i probowalismy znaiezc ich rodzicow - MALOWAt, OGROD, i tak dalej. Teraz sprobujemy zrobic odwrotnie: mamy slowo MALOWAC, i CO od niego pochodzi? .... Tak, MALARZ i MALOWANIE pochodzg od slowa MALOWAC. A CO pochodzi od slowa OGROD? ... fogrodni/cj

A od PRAé? .... fpra/nia, praniej

A od CHUDY? .... fchudzielecj

1. BRAM KA______2. SZYC ______3. GLUPI ______4. KAWA ______5. K4PAC ______6. GLUCHY ______7. SOL ______8. CHODZIC ______9. WDZI^CZNY ______10. TRAWA ______11. DOWODZié. 12. BRUDNY___ 13. PA Llé ___ 14. CZYTAé___ 15. UCZYé ___ 16. SUSZYé PREFIXES PR-1

Teraz bçdziemy siç bawic w znajdowanie schowanych slowek. Moze wiesz, ze w jçzyku polskim mamy wiele slow krotkich i prostych, tak jak pies, kot, dom, rzeka, aibo jezioro. Aie sq tez duze slowa, w ktorych schowane sq mniejsze stowka. Na przyklad, popatrz na slowo DOJECHAL, tak jak w zdaniu: „Poci^g dojechal do Krakowa”. W slowie DOJECHAL schowalo siç slôwko JECHAL; DO - JECHAL, czy slyszysz to? (Jesli dziecko zdaje siç nie rozumiec, wyjasniamy ponownie, uiywaj^c, Jesli trzeba, pokrewych przykJadow: W Y JECHAL, POJECHAL, itp.). Chcç zobaczyc, czy potrafisz znajdowac talde schowane slôwka, dobrze?

Na przyklad, co siç schowalo w slowie WYPIC? ....

USLYSZEC, na przyklad „uslyszec muzykç”? ....

DOKONCZYC, na przyklad „dokohczyc zadanie”? ....

1. NADMUCHAé ______2. ZEPSUC ______3. GBRAC ______4. ZWALIC ______5. WCHODZIC ______6. PRZESKOCZYC______7. PODRAPAé ______8. SCHOWAÇ ______9. ODDAÇ ______10. WYGRAC ______11. OBLAC______12. ZABlÇ______13. NADLAMAÇ ______14. PODPISAÇ ______15. PRZYWOZlé ______16. ROZCI4 Ç ______

héh PR-2

A teraz sprobujemy zrobic cos odwrotnego. Ja powiem proste slowko, a ty musisz dodac cos do niego na jpoczqtku, zeby powstaio nowe, diuzsze stowo. Na przyklad, kiedy ja powiem JECHAC, to ty mozesz powiedziec PRZYJECHAC aibo WYJECHAC, aibo cos podobnego (akcentujemy wymowç przedrostkow, ale wymamiamy je l^cznie z nastçpuj^cym rdzeniem).

Na przyklad, co mozesz powiedziec, kiedy ja mowiç KONCZYC? .... fDOJ aibo: SLYSZEC? .... fUJ

1. DRUKOWAC 2. 3. KROIC 4. CHOROWAé 5. DRZEé 6. JE&É 7. KLElé 8. LECIEC 9. W ALlé 10. RZUClé 11. CALOWAé 12. PALLÙ 13. KOPAé 14. GOTOWAé 15. NIEàC 16. CZESAé DIMINUTIVES DIM-1

Sluchaj, bçdziemy porownywac rzeczy duze 1 mate. Ten obrazek przedstawia zegar (pokazujemy), duzy zegar, ktory mozna postawic na stole aibo na szahe. A tutaj mamy maty zegar, czyli zegarek (pokazujemy), ktory mozna nosic na rçce. A wiçc o duzym przedmiocie mowimy ZEGAR, a o mniejszym ZEGAREK. Mozna tak mowic o bardzo wielu rzeczach. To jest oczywiscie PIES (pokazujemy obrazek), a to bçdzie maty .... Sprobujmy jeszcze parç przykladow. To jest CHAT A, czyli rodzaj domu w ktorym ludzie mieszkajq na wsi. Mata chata bçdzie siç nazywac ....

To jest RJÇKA (pokazujemy wlasn^). Mata rçka to ....

To jest PALEC. Maty palec to ....

Ja bçdç teraz mowit rozne stowa, a ty je zamieniaj w ten sam sposob, dobrze?

1. LAS ______2. SNIEG ______3. BRZUCH ______4. KLUCHA ______5. DOE ______6. SZAFA ______7. KROWA ______8. NOGA ______9. KSI^GA ______10. KOPYTO______11. PUDLO ______12. NÔZ ______13. KOZUCH 14. SERGE 15. KURCZ]^. 16. DRZEWO

3 6 5 DIM-2

Bardzo dobrze. Teraz sprobujemy zrobic cos odwrotnego: ja bçdç mowil slowa „male”, a ty bçdziesz je zamienial na slowa „duze”. Czyli, jesli powiem PIESEK, to ty powiesz PIES, jesli powiem ZEGAREK, to ty powiesz .... Zamiast CHATKA powiesz .... Zamiast R^CZKA.... Zamiast PALUSZEK....

1. PASEK______2. BRZEZEK______3. GROSZEK ______4. DESKA ______5. STOLEK ______6. LAWKA ______7. GLÔWKA ______8 . DRÔZKA______9. WST^ZKA ______10. KORYTKO ______11. SKRZYDELKO______12. HACZYK ______13. LENIUSZEK ______14. JABLUSZKO ______15. ZWIERZ^TKO______16. K Ô L K O ______CHINESE LETTERS CHIN

Pokazç ci teraz chinsk^ literkç. Przyjrzyj siç jej bardzo uwaznie i zapamiçtaj .... (prezentacja trwa 4 sek., nastçpnie pokazujemy „diug^ planszç”). A teraz pokaz, gdzie ona siç schowala ....

(Po prezentacji 12 „dlugich” plansz) Teraz jeszcze raz pokaz mi, gdzie schowala siç ta literka, ktor^ na pocz^tku miales zapamiçtac ....

^azne Jest, aby pram'dbowej odpowiedzi nie sugerowac' wzrokiem, co moze siç ztbarzyc iatwo, nawet mimowoinie/

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Insiz Insiz READING - words fV£4CZDrKTAFON/

(Pokazujemy kartç IF-E, lez%c% strong niezapisan^ do gory) Za chwilç pokazç ci napisane na kartce kilka slow. Sprobuj je przeczytac na glos, najtadniej i najszybciej jak potrafisz. (w przypadku kl. i dodajemy: Nlektore slowa mogq bye trudne. Jezeli nie mozesz przeczytac jakiegos slowa, powiedz „nie wiem” i zaraz sprobuj czytac nastçpne). Ja bçdç mierzyt twoj czas(przygotowujemy stoper, odwracamy kartkç na stronç zapisan^, wskazujemy palcem pocz^tek pierwszego slowa). Uwaga, START!

Przy wszystkich kolejnych kartach podajemy najpierw poiecenie przeczytania, potem prezentujemy slowa, i mowimy: Uwaga, START!

1. 2. 3. 4. IF E IF-D INF-E INF-D film piçc znak slad fadny jezdzic bramka grz^dka

rower obiad mokry gruszka

cztery lozko wojsko krowka

kolega piosenka koparka wieloryb

CZAS:

1. 2. 3. 4. 2F-E 2FD 2NF-E 2NF-D sklep snieg bok rog

maty duzy patac sqsiad

samolot przy nies c synek podrzec

czarny ksiqzka pirat dziçciot

diaczego oglgdac gimnastyka konduktor

CZAS:

6 5 0 READING - nonwords

Pf^£4CZDVJiLrAFON/

Teraz znowu dam ci do przeczytania kilka stow. Bçd^ to takie smieszne, zmyslone stowa, jakich nigdy jeszcze nie styszales. Przeczytaj je tak tadnie i szybko, jak tylko potrafisz (pokazujemy kartç, przygotowujemy stoper). Uwaga, START!

1. 2. 3. 4. 1 NW F-E 1 NW F-D 1 NW N F-E 1 NW N F-D rolm jçc krap szkad fidny zdzipiec kambra krqdka lewer adiob krymo grusla cztaga tenko skowoj grzowka kotery piosozka kokazna rylowieb

CZAS:

1. 2. 3. 4. 2 NW F-E 2 NW F-D 2 N W NF-E 2 N W N F-D dlep ksieg bac pog tyma zudy palok sqsiot toczamol sniniesc kenys drzeroc rysna przgzka rapit dziçciad sklagocze od^glac kistymnaga rokondukt

CZAS:

h8\ piçc film jezdzic tadny obiad rower

W lôzko cztery 00 rO piosenka kolega

1 - F - D 1 -F-E znak slad bramka grz^dka mokry gruszka

rO wojsko krowka CV rn koparka wieloryb

1-NF-E 1-NF-D sklep smeg maty duzy samolot przynlesc czarny ksiqzka 00 rf) diaczego ogl^dac

2 - F- E 2-F-D rog bok sqsiad patac podrzec synek

In dziçciot pirat oo -0 konduktor gimnastyka

2 -NF-D 2- NF - E JÇC rolm zdzipiec fidny adiob lewer tenko czlaga VD rO piosozka kotery

1 - F - D - nw 1 - F - E - nw krap szkad kambra krqdka krymo grusla

fV skowoj grzowka 00 rO kokazna rylowieb

1 - NF - E - nw I NF D-nw dlep ksieg tyma zudy toczamol sniniesc

prz^zka Op rysna Û0 rO sklagocze od^glac

2 - F - E - nw 2 - F - D - nw pog bac s ^ s i o } patok drzeroc kenys

0 7 dziçciad rapit 00 rokondukt kistymnaga

2 - NF- D - nw 2 - NF- E - nw