Predicting Patterns of Early Literacy Achievement: A Longitudinal Study of Transition from Home To School
Author Young, Janelle Patricia
Published 2004
Thesis Type Thesis (PhD Doctorate)
School School of Cognition, Language and Special Education
DOI https://doi.org/10.25904/1912/1354
Copyright Statement The author owns the copyright in this thesis, unless stated otherwise.
Downloaded from http://hdl.handle.net/10072/367304
Griffith Research Online https://research-repository.griffith.edu.au
Predicting the Patterns of Early Literacy Achievement: A Longitudinal Study of Transition from Home to School
VOLUME 1
Janelle Patricia Young DipTch; BEd; MEdSt
A thesis submitted in fulfillment of the requirements for the degree of Doctor of Philosophy at Faculty of Education, School of Cognition, Language and Special Education, Griffith University, Brisbane. July 2003 ABSTRACT
This is a longitudinal study of patterns of children's early literacy development with a view to predicting literacy achievement after one year of schooling. The study fits within an emergent/social constructivist theoretical framework that acknowledges a child as an active learner who constructs meaning from signs and symbols in the company of other more experienced language users.
Commencing in the final month of preschool, the literacy achievement of 114 young Australian students was mapped throughout Year 1. Data were gathered from measures of literacy achievement with the students, surveys with parents and surveys and checklists with teachers. Cross-time comparisons were possible as data were gathered three times from the students and teachers and twice from parents.
Parents’ perceptions of their children’s personal characteristics, ongoing literacy development and family home literacy practices were examined in relation to children’s measures of literacy achievement. Their perceptions were found to be accurate. Parents supported children’s literacy growth at home in both the prior- to-school period and throughout Year 1.
Teachers reflected on children’s characteristics as members of their classes and on their knowledge of children’s preparation for literacy. Generally, their predictions of literacy success were based on unsustainable connections with children’s ability to concentrate, follow directions and stay on task.
Abstract i Children demonstrated a broad range of understandings about literacy in the prior-to-school period and teachers failed to acknowledge the extent of these.
Children’s prior-to–school understandings relating to the alphabet, environmental print, concepts about print and phonological awareness all predicted later literacy achievements. Alphabetic knowledge and environment print were found to be the strongest predictors.
Results showed few significant school, age, home or gender effects. However, children’s prior-to-school understandings of literacy were shown to predict later literacy achievement. Those with the greater level of knowledge prior-to-school generally maintained that advantage when later literacy achievements were measured.
Abstract ii TABLE OF CONTENTS
VOLUME ONE ABSTRACT i CHAPTER ONE: INTRODUCTION 1 1.1 THE RESEARCH QUESTIONS 3
1.2 SIGNIFICANCE OF THE RESEARCH QUESTIONS 4 1.2.1 Theory 6 1.2.2 Methodology 7 1.2.3 Practice 7 1.2.4 Policy 11
1.3 PREVIEW OF THE PROJECT 13
CHAPTER TWO: LITERATURE REVIEW 19 2.1 INTRODUCTION 19
2.2 THEORETICAL MODELS AND PRACTICES IN THE EARLY YEARS 20 2.2.1 Maturational Perspective 22 2.2.2 Developmental and Nativist Perspectives 24 2.2.3 Psycholinguistic Perspective 25 2.2.4 Connectionist Perspective 28 2.2.5 Emergent Perspective 29 2.2.6 Social Constructivist Theory 32 2.2.7 Critical Theory 33
2.3 CURRENT LITERACY POLICIES AND RESEARCH 36 2.3.1 Current Literacy Practices in Parts of the Developed World 36 2.3.1.1 Australia 36 2.3.1.2 United States 44 2.3.1.3 United Kingdom 52 2.3.1.4 New Zealand 54 2.3.2 Literacy Practices in the English-speaking World: Similarities and 56 Differences
2.4 RESEARCH ON LITERACY IN THE EARLY YEARS 58 2.4.1 Emergent and Early Literacy Development 58 2.4.1.1 The Influence of Clay 59 2.4.1.2 Influences on Emergent and Early Literacy Development 63 2.4.1.3 Literacy Development in the Prior-to-School Period 80
2.5 RESEARCH QUESTIONS RESTATED 110
CHAPTER THREE: METHOD 113 3.1 SUBJECTS 113 3.1.1 Students 113 3.1.2 Parents 117
Table of Contents 3.1.2.1 Mothers 118 3.1.2.2 Mothers in Preschool A 121 3.1.2.3 Mothers in Preschool B 122 3.1.2.4 Mothers in Preschool C 122 3.1.2.5 Fathers 123 3.1.2.6 Fathers in Preschool A 127 3.1.2.7 Fathers in Preschool B 128 3.1.2.8 Fathers in Preschool C 129 3.1.3 Year 1 Teachers 130
3.2 SETTINGS 130
3.3 CONTENT AND ADMINISTRATION OF ASSESSMENT 132 INSTRUMENTS 3.3.1 Literacy Assessment Tasks: The Preschool Period 132 3.3.1.1 Environmental Print Awareness 132 3.3.1.2 Story Comprehension 133 3.3.1.3 Student Writing Own Name and Recognising Letter 135 Names 3.3.1.4. Robinson’s Test of Writing Vocabulary 135 3.3.1.5 Letter Knowledge and Identification 135 3.3.1.6 Concepts About Print Test: Version Sand 135 3.3.1.7 Canberra Word test 138 3.3.1.8 Print Knowledge Task 139 3.3.1.9 Sutherland Phonological Awareness Test 140 3.3.2 Literacy Assessment Tasks: May/June Year 1 141 3.3.2.1 Student Writes Own Name (retest) 142 3.3.2.2 Robinson’s Test of Writing Vocabulary (retest) 142 3.3.2.3 Letter Knowledge and Identification (partial retest) 142 3.3.2.4 Concepts About Print Sand (retest) 142 3.3.2.5 Canberra Word Test (retest) 142 3.3.2.6 Story Comprehension 142 3.3.2.7 Print Knowledge Task (retest) 143 3.3.2.8 Sutherland Phonological Awareness Tasks (retest) 143 3.3.3 Literacy Assessment Tasks: November Year 1 143 3.3.3.1 Ohio Word Test 143 3.3.3.2 Dictation and Spelling Test 144 3.3.3.3 Concepts About Print Test: Version Stones 144 3.3.3.4 Sutherland Phonological Awareness Tasks 144 3.3.3.5 Miscue Analysis 146 3.3.4 Surveys 147 3.3.4.1 Parent Surveys 1 and 2 147 3.3.4.2 Teacher Survey 147 3.3.5 Checklists 148 3.3.5.1 Teacher Checklists 1 and 2 148
3.4 METHODOLOGICAL CONSIDERATIONS 148
3.5 REPORTING RESULTS 151
Table of Contents CHAPTER FOUR: DESCRIBING AND CORRELATING PRESCHOOL 153 DATA
4.1 PARENT SURVEY 1 154 4.1.1 Parents’ Perceptions: Children’s Personal Characteristics and 155 Interests 4.1.2 Parents’ Perceptions of Home Literacy Practices 158 4.1.2.1.Reading to Preschool Students 158 4.1.2.2 Texts Read to Preschool Students 160 4.1.2.3 Books at Home and Use of Local Libraries 160 4.1.2.4 Preschool Children’s Writing at Home 162 4.1.3 Summary 163
4.2 LITERACY ASSESSMENT TASKS: PRESCHOOL PERIOD 165 4.2.1 Environmental Print Awareness 166 4.2.1.1 Task1: Recognition of Food Products 166 4.2.1.2 Task 2: Recognition of Product Names 167 4.2.1.3 Task 3: Recognition of the Cut-Out Labels 168 4.2.1.4 Task 4: Recognition of Words on Cards 168 4.2.1.5 Analysing Environmental Print 169 4.2.1.6 Summary 170 4.2.2 Story Comprehension 171 4.2.2.1 Comprehension Score For My Grandma 171 4.2.2.2 Comprehension Score For Oscar Got the Blame 171 4.2.2.3 Literal Comprehension Across the Two Stories 172 4.2.2.4 Inferential Comprehension Across the Two stories 173 4.2.2.5 Summary 173 4.2.3 Writing Names and Naming Letters 174 4.2.3.1 Summary 176 4.2.4 Robinson’s Test of Writing Vocabulary 177 4.2.4.1 Summary 179 4.2.5 Letter Knowledge and Identification 180 4.2.5.1 Summary 182 4.2.6 Concepts About Print Test (CAP) 183 4.2.6.1 Summary 186 4.2.7 Canberra Word Test 186 4.2.7.1 Summary 188 4.2.8 Print Knowledge Using the Rhyme, Humpty Dumpty 188 4.2.8.1 Summary 189 4.2.9 Sutherland Phonological Awareness 190 4.2.9.1 Summary 192 4.2.10 Students’ Perceptions of Reading Practices at Home 194 4.2.10.1 Summary 195
4.3 TEACHER CHECKLIST 1 196 4.3.1 Adjustment to School and Work Habits 197 4.3.1.1 Summary 198 4.3.2 Literacy Progress and Handwriting 199 4.3.2.1 Summary 202
Table of Contents 4.4 TEACHER SURVEY 205 4.4.1 Teachers’ Perceptions of Students’ Skills When Entering Year 1 205 4.4.1.1 Environmental Print 206 4.4.1.2 Students Indicate They Have Stories Read to Them 208 4.4.1.3 Book-Handling Skills 209 4.4.1.4 Students Writing Their Own Name 211 4.4.1.5 Students Who Can Read on Entering School 214 4.4.1.6.Students Who Can Write Words 215 4.4.1.7 Naming Letters of the Alphabet 217 4.4.2 Discussion 220 4.4.3 Teaching Activities Used by Year 1 Teachers 222 4.4.4 Discussion 225 4.4.5 Summary 225
CHAPTER FIVE: REDUCING DIMENSIONS: RELATIONSHIPS IN 229 THE PRESCHOOL DATA 5.1 FACTOR ANALYSES 229 5.1.1 Background Factors 231 5.1.1.1 Background Factor: Demography 231 5.1.1.2 Background Factor: Parent Perceptions of Child 232 Characteristics 5.1.1.3 Background Factor: Parents’ Perceptions of Home 233 Literacy Practices 5.1.1.4 Background Factor: Teachers’ Perceptions of Child 235 Characteristics 5.1.1.5 Background Factor: Teachers’ Perceptions of Literacy 236 Progress 5.1.2 Correlations of Background Factors 237 5.1.3 Performance Factors 241 5.1.3.1 Performance Factor: Environmental Print Awareness 242 5.1.3.2 Background and Environmental Print Factors 243 5.1.3.3 Performance Factor: Letter Knowledge 245 5.1.3.4 Background and Letter Knowledge Factors 245 5.1.3.5 Performance Factor: Concepts About Print Test (CAP) 248 5.1.3.6 Background and Concepts About Print Test Factors 252 5.1.3.7 Performance Factor: Print Knowledge Task 255 5.1.3.8 Background and Print Knowledge Task Factors 258 5.1.3.9 Performance Factor: Sutherland Phonological Awareness 259 Test 5.1.3.10 Background and Sutherland Phonological Awareness 261 Test Factors 5.1.4 Discussion 263
5.2 CLUSTER ANALYSES 266 5.2.1 Variable Set A 268 5.2.2 Variable Set B 270 5.2.3 Variable Set C 272 5.2.4 Relationships Among Variable Sets 274 5.2.5 Relationships With Variable Set A 275 5.2.6 Discussion of Variable Set A Associations 286
Table of Contents 5.2.7 Relationships With Variable Set B 288 5.2.8 Discussion With Variable Set B Associations 300 5.2.9 Relationships With Variable Set C 302 5.2.10 Discussion of Variable Set C Associations 311 5.2.11 Summary: Cluster Analyses of Literacy Assessment Task 312 Measures in Preschool VOLUME TWO CHAPTER SIX: DESCRIBING AND CORRELATING YEAR 1 316 (MAY/JUNE) DATA 6.1 LITERACY ASSESSMENT TASKS: YEAR 1 (MAY) 317 6.1.1 Introduction 317 6.1.2 Writing Own Name 318 6.1.2.1 Summary 318 6.1.3 Robinson’s Test of Writing Vocabulary 318 6.1.3.1 Summary 320 6.1.4 Letter Knowledge and Identification 320 6.1.4.1 Summary 323 6.1.5 Concepts About Print Test (CAP) 323 6.1.5.1 Summary 324 6.1.6 Canberra Word Test 324 6.1.7 Story Comprehension 325 6.1.8 Print Knowledge Task 326 6.1.8.1 Summary 327 6.1.9 Sutherland Phonological Awareness Test 327 6.1.9.1.Summary 329 6.1.10 Discussion 330
CHAPTER SEVEN: REDUCING DIMENSIONS: RELATIONSHIPS IN 332 THE YEAR 1 (MAY/JUNE) DATA 7.1 FACTOR ANALYSES: LITERACY ASSESSMENT TASKS MAY YEAR 333 1 7.1.1 Performance Factor: Letter Knowledge 2 333 7.1.2 Correlation Coefficients: Letter Knowledge 2 334 7.1.2.1 Summary 336 7.1.3 Performance Factor: Concepts About Print Test (CAP) 2 337 7.1.4 Correlation Coefficients For Concepts About Print Test (CAP) 2 339 7.1.4.1 Discussion 342 7.1.5 Performance Factor: Sutherland Phonological Awareness Test 343 7.1.6 Correlation Coefficients: Sutherland Phonological Awareness Test 344 7.1.7 Discussion 345
7.2 CLUSTER ANALYSES 347 7.2.1 Variable Set A 348 7.2.2 Summary of Variable Set A Associations 352 7.2.3 Variable Set B 355 7.2.4 Summary of Variable Set B Associations 359 7.2.5 Variable Set C 361 7.2.6 Summary of Variable Set C Associations 366
Table of Contents 7.2.7 Discussion: Cluster Analyses Literacy Assessment Tasks 367 May/June Year 1
CHAPTER EIGHT: DESCRIBING AND CORRELATING YEAR 1 370 (NOVEMBER) DATA 8.1 LITERACY ASSESSMENT TASKS YEAR 1 (NOVEMBER) 371 8.1.1 Introduction 371 8.1.2 Ohio Word Test 371 8.1.3 Dictation and Spelling Test 372 8.1.4 Concepts About Print Test (3) 374 8.1.5 Sutherland Phonological Awareness Test 374 8.1.6 Oral Reading Accuracy and Comprehension 376 8.1.7 Summary 379
8.2 PARENT SURVEY 2 381 8.2.1 Parents’ Perceptions: Child Personal Characteristics and Interests 381 8.2.2 Parents’ Perceptions: Home Literacy Practices 383 8.2.2.1 Reading to the Year 1 Children at Home 383 8.2.2.2 Texts in the Home 385 8.2.2.3 Listening to Year 1 Children Read at Home 387 8.2.2.4 Year 1 Children Writing at Home 389 8.2.3 Parents’ Perceptions of Children’s Literacy Progress 390 8.2.4 Summary 390
8.3 TEACHER CHECKLIST 2 391 8.3.1 Teachers’ Perceptions of Students’ Conduct in Class: November 392 of Year 1 8.3.2 Teachers’ Perceptions of Students’ Literacy Progress: November 393 of Year 1 8.3.3 Summary 394
CHAPTER NINE: REDUCING DIMENSIONS: RELATIONSHIPS IN 397 THE YEAR 1 (NOVEMBER) DATA 9.1 FACTOR ANALYSES: NOVEMBER YEAR 1 398 9.1.1 Background Factors: Parent Survey 2 399 9.1.1.1 Background Factor: Parents’ Perceptions of Children’s 399 Characteristics: November of Year 1 9.1.1.2 Background Factor: Parents’ Perceptions of Literacy 400 Progress 9.1.1.3 Background Factors: Parents’ Perceptions of Home 401 Literacy Practices 9.1.2 Background Factors: Teacher Checklist 2 402 9.1.2.1 Background Factor: Teachers’ Perceptions of Students’ 402 Class Conduct 9.1.2.2 Background Factor: Teachers’ Perceptions of Students’ 403 Literacy Progress 9.1.3 Correlations of Background Factors 404 9.1.4 Performance Factors: Literacy Assessment Tasks Year 1 (Nov) 410 9.1.4.1 Performance Factors: Concepts About Print Test 411 9.1.4.2 Correlations: Background Factors and CAP Test 413
Table of Contents 9.1.4.3 Performance Factors: Sutherland Phonological 415 Awareness Test 9.1.4.4 Correlations: Background Factors and Sutherland 417 Phonological Awareness Test Factors 9.1.4.5 Performance Factors: Dictation and Spelling 418 9.1.4.6 Correlations: Dictation and Spelling 419 9.1.4.7 Performance Indicator: Reading Texts 421 9.1.4.8 Correlations: Reading Texts 422
9.2 CLUSTER ANALYSES: NOVEMBER YEAR 1 423 9.2.1 Variable Set A 424 9.2.2 Discussion of Variable Set A Associations 427 9.2.3 Variable Set B 432 9.2.4 Discussion of Variable Set B Associations 435 9.2.5 Variable Set C 439 9.2.6 Discussion of Variable Set C Associations 441 9.2.7 Summary of Cluster Analyses Preschool to November Year 1 445
CHAPTER TEN: SUMMARY AND IMPLICATIONS 450 10.1 FINDINGS 450 10.1.1 The Prior-to-School Period 450 10.1.1.1 Student Data 450 10.1.1.2 Parent Data 452 10.1.1.3 Teacher Data 452 10.1.2 Reducing Dimensions in the Preschool Period 453 10.1.3 Literacy Development After Five Months at School 455 10.1.4 Reducing Dimensions in May/June of Year 1 458 10.1.5 Literacy Development After One Year at School 459 10.1.5.1 Student Data 459 10.1.5.2 Parent Data 461 10.1.5.3 Teacher Data 462 10.1.6 Reducing Dimensions in November of Year 1 462 10.2 IMPLICATIONS 464 10.2.1 Implications For Theory 464 10.2.2 Implications For Research Methodology 466 10.2.3 Implications For Classroom Practice 467 10.2.4 Implications For Policy 468 10.3 LIMITATIONS OF THE STUDY 469 10.4 DIRECTIONS FOR FUTURE RESEARCH 470 10.5 CONCLUSIONS 471 REFERENCES 478
Table of Contents
LIST OF APPENDICES
Appendix A: Longitudinal Studies 503
Appendix B: Letter to Parents 508
Appendix C: Parent Survey 1 509
Appendix D: Literacy Assessment Tasks Recording Instrument: Preschool 511
Appendix E: Sample Word Card For Food Product Recognition 518
Appendix F: Transcripts From My Grandma & Oscar Got the Blame 519
Appendix G: Comprehension Statements: My Grandma & Oscar Got the 520 Blame
Appendix H: Concepts About Print Administration and Scoring 521
Appendix I: Canberra Word Test 526
Appendix J: Text Humpty Dumpty 527
Appendix K: Sutherland Phonological Awareness Test 528
Appendix L: Literacy Assessment Tasks Recording Instrument:May/June Yr 1 536
Appendix M: Transcript For My Brother John 540
Appendix N: Comprehension Statements For My Brother John 541
Appendix O: Literacy Assessment Tasks Recording Instrument: Nov. Year 1 542
Appendix P: Ohio Word Test: List A 549
Appendix Q: Transcripts of Children’s Reading Texts: November Year 1 550 Level 1: The Farm and A Toy Box Level 6: Having a Picnic Level 12: If You Like Strawberries Don’t Read This Book Level 16: First Flight Level 24: Grandpa’s Cardigan
Appendix R: Comprehension For Children’s Reading Texts: November Yr 1 554 Level 1: The Farm and A Toy Box Level 6: Having a Picnic Level 12: If You Like Strawberries Don’t Read This Book Level 16: First Flight Level 24: Grandpa’s Cardigan
Table of Contents Appendix S: Parent Survey 2 556
Appendix T: Teacher Survey Year 1 558
Appendix U: Teacher Checklist 1 561
Appendix V: Teacher Checklist 2 562
Table of Contents LIST OF TABLES
Table 1 Summary of Results For Remaining Longitudinal Multivariate Studies 101 (1980-1989)
Table 2 Summary of Remaining Multivariate Longitudinal Studies (1990- 107 2002)
Table 3 Languages Spoken by Preschool Students 117
Table 4 Mothers’ Occupations For Each Preschool 119
Table 5 Highest Education Level For Mothers 121
Table 6 Fathers’ Occupations For Each Preschool 124
Table 7 Highest Education Level For Fathers 126
Table 8 Percentage Frequencies of Children’s Personal Characteristics and 155 Interests from Parent Survey 1
Table 9 Comparison of Means From Parental Ratings of Children’s 156 Concentration, Memory, Interest in Books and Writing by Age Group
Table 10 Comparison of Mean Scores From Parental Ratings of Children’s 157 Concentration, Memory, Interest in Books and Interest in Writing by Gender
Table 11 Percentages of Those Who Read at Home to Preschool Children as 158 Reported by Parents
Table 12 Percentages of Parents Reporting Time Frequency For Reading to 159 Preschool Children
Table 13 Percentages of Parents Reporting Periods of Daily Time Spent 159 Reading to Preschool Children
Table 14 Percentage Estimates From Parents of Texts Shared at Home With 160 Preschool Children
Table 15 Percentage Estimates From Parents of the Number of Books at Home 161 Suitable For Preschool Children
Table 16 Percentage Estimates From Parents For Use of Local Libraries 161
Table 17 Percentage Estimates From Parents of Preschool Children’s 162 Frequency of Writing at Home Other Than Writing Own Name
Table 18 Comparison of Perceptions of Frequency of Writing at Home by 162 Gender
Table of Contents
Table 19 Recognition of Selected Products (Task 1) 167
Table 20 Recognition of Product Names on the Selected Products (Task 2) 167
Table 21 Recognition of Cut-out Labels For the Selected Products (Task 168 3)
Table 22 Recognition of Selected Product Names on Cards (Task 4) 168
Table 23 Comparison of Cumulative Scores For Recognition of Environmental 169 Print Tasks
Table 24 Comprehension Scores For the Story My Grandma 171
Table 25 Comprehension Scores For the Story Oscar Got the Blame 172
Table 26 Literal Comprehension Scores For the Two Stories in Preschool 172
Table 27 Inferential Comprehension Scores For the Two Stories in Preschool 173
Table 28 Number and Valid percentages of Students Who Could Write Their 174 Name in Preschool
Table 29 Frequency and Valid percentages of Cases Used by Students and 174 Order of Letters When Writing Their Own Names
Table 30 Students’ Accuracy When Spelling Their Names in November of 175 Preschool
Table 31 Students’ Knowledge of Letters in Their Own Names 176
Table 32 Students’ Scores on Robinson’s Test of Writing Vocabulary 177
Table 33 Number of Words of Different Sizes Written by Preschool Students 178
Table 34 Comparison of Mean Scores For Robinson’s Test of Writing 179 Vocabulary by Gender
Table 35 Univariate Analysis For Robinson’s Test of Writing Vocabulary by 179 Gender For Words Longer Than Five Letters
Table 36 Preschool Students’ Knowledge of Letter Names, Sounds and Words 181 Beginning With Each Letter
Table 37 Performances For Concepts About Print Test in Preschool 184
Table 38 Scores For Canberra Word Test in Preschool 187
Table 39 Performances in Preschool For Print Knowledge 188
Table of Contents
Table 40 Scores in Preschool For Syllable Counting 190
Table 41 Scores in Preschool For Rhyme Detection 191
Table 42 Scores in Preschool For Rhyme Production 191
Table 43 Scores in Preschool For Onset Identification 191
Table 44 Scores in Preschool For Final Phoneme Production 191
Table 45 Family Members Identified by Preschool Students For Reading to 195 Them at Home
Table 46 Percentage Distributions of Year 1 Teachers’ Perceptions of Students 197 Adjustment to School and Work Habits
Table 47 A Comparison of Mean Scores For Adjustment to School and Work 197 Habits
Table 48 A Comparison of Means For Year 1 Teachers’ Perceptions of 198 Application to Tasks and Personal Organisation by Gender
Table 49 Tests of Between Subject Effects For Application to Tasks and 198 Personal Organisation With Gender
Table 50 Percentage Descriptions of Year 1 Teachers’ Perceptions of Students’ 199 Interest and Progress in Reading, Writing and Handwriting
Table 51 Comparing Mean Scores For Progress in Reading by School 200
Table 52 Comparing Mean Scores For Writing and Handwriting Progress by 200 School
Table 53 Multiple Comparisons For Literacy Progress showing School Effect 201
Table 54 Teachers’ Estimates of Students’ Knowledge of Environmental Print 206 at the Beginning of Year 1
Table 55 Students’ Scores in Preschool on Selected Items For the Recognition 207 of Labels on Products
Table 56 Teachers’ Estimates of the Proportion of Students Who Had Been 208 Read to Prior to Beginning School
Table 57 Teachers’ Percentage Estimates of Students Displaying Book- 209 Handling Skills at the Beginning of Year 1
Table 58 Students’ Book-Handling in Preschool 210
Table of Contents
Table 59 Teachers’ Estimates of Students Who Had Written their Given Name 211 With 90% Accuracy When Commencing School
Table 60 Percentage of Students Who Wrote Their Name Correctly in 212 Preschool (LAT 1)
Table 61 Teachers’ Estimates of Students Who Could Write Given Name and 213 Surname With 90% Accuracy When Commencing Year 1
Table 62 Teachers’ Estimates of Students Who at the Beginning of Year 1 216 Could Write Words Other Than Their Names
Table 63 Preschool Students’ Scores For Robinson’s Test of Writing 216 Vocabulary by Preschool
Table 64 Comparison of Teachers’ Estimates of Students’ Ability to Write 217 Other Words on Entering School Compared to Students’ Achievement on Robinson’s Test of Writing Vocabulary in Preschool
Table 65 Frequency of Teachers’ Estimates of Students Who Knew No Letter 218 Names at the Beginning of Year 1
Table 66 Teachers’ Estimates of Students Who Know the Names of All Letters 219 of the Alphabet on Entering Year 1
Table 67 Students’ Scores For Letter Naming in Preschool 219
Table 68 Teachers’ Estimates of Students’ Literacy Abilities as They Enter 221 Year 1
Table 69 Percentage Frequency of Using Shared Book Experience 222
Table 70 Percentage Frequency For Teaching Word Recognition 222
Table 71 Percentage Frequency For Teaching Phonological Awareness 223
Table 72 Percentage Frequency For the Teaching of Handwriting 223
Table 73 Percentage Frequency For Modelling the Writing of Texts 223
Table 74 Percentage Frequency For Students Writing Their Own Texts 223
Table 75 Percentage Frequency For Using Children’s Literature 223
Table 76 Percentage Frequency For Using Reading Scheme Materials 224
Table 77 Percentage Frequency For Using Materials Brought by Students 224
Table of Contents Table 78 Percentage Frequency For the Use of Teacher-made Materials 224
Table 79 Rotated Component Matrix For Two-Factor Solution on Parents’ 231 Education Levels and Occupations
Table 80 Rotated Component Matrix For a Two-Factor Solution For Parents’ 232 Perceptions of Their Children’s Concentration, Memory, Interest in Writing and Books and Enjoyment of Preschool
Table 81 Rotated Component Matrix For Parents’ Perceptions of Home 234 Literacy Practices
Table 82 Rotated Component Matrix For Year 1 Teachers’ Perceptions of 235 Students’ Characteristics
Table 83 Rotated Component Matrix For Teachers’ Perceptions of Literacy 236 Progress in March Year 1
Table 84 Significant Positive Correlations of Background Factors 237
Table 85 Significant Negative Correlations of Background Factors 238
Table 86 Rotated Component Matrix For Four Environmental Print Tasks 243
Table 87 Correlations For Environmental Print Tasks 244
Table 88 Component Matrix For Letter Knowledge in Preschool 245
Table 89 Correlations For Letter Knowledge Factor in Preschool 246
Table 90 Rotated Component Matrix For Concepts About Print Test in 249 Preschool
Table 91 Correlations of Background Factors With Preschool CAP Factors 252
Table 92 Rotated Component Matrix For Print Knowledge Task in Preschool 256
Table 93 Correlations of Preschool Print Knowledge Task Factors and 258 Background Factors
Table 94 Rotated Component Matrix For Sutherland Phonological Awareness 260 Test in Preschool
Table 95 Correlations For Sutherland Phonological Awareness Test With 261 Background Factors
Table 96 Standardised Cluster Mean Vectors For Student Groups Within 269 Variable Set A
Table of Contents Table 97 Standardised Cluster Mean Vectors For Student Groups Within 271 Variable Set B
Table 98 Standardised Cluster Mean Vectors For Student Groups Within 273 Variable Set C
Table 99 Pearson’s Chi-square Analyses For Variable Set A and Background 275 Variables
Table 100 Chi-square For Cluster A (Derived from CAP 1) With Cluster C 276 (Derived from Sutherland Phonological Awareness 1)
Table 101 MANOVA From Variable Set A With Demography, Parents’ 278 Perception and Teachers’ Perception Factors
Table 102 Significant Results For Variable Set A With Preschool Literacy 279 Task Measures
Table 103 Means and Standard Errors For Variable Set A on Contextualised 280 Reading of Environmental Print Measures
Table 104 Means and Standard Errors For Variable Set A on the Factor Score 281 For Rhyme, Onset and Final Phoneme
Table 105 Means and Standard Errors For Variable Set A on Significant Print 282 Knowledge Task Factors
Table 106 Means and Standard Errors For Variable Set A on Robinson’s Test 283 of Writing Vocabulary, Canberra Word Test and Reading Words on all Literacy Tasks
Table 107 Means and Standard Errors For Variable Set A on Literal and 285 Inferential Comprehension Measures
Table 108 Variable Set A (Based on CAP) With Significant Preschool Literacy 286 Factors and Scores Depicting the Highest and Lowest Cluster Mean Scores
Table 109 Pearson’s Chi-square Analyses For Variable Set B and Background 288 Variables
Table 110 Pearson’s Chi-square For Cluster B (Derived from Environmental 289 Print and Letter Knowledge) With Cluster C (Derived From Sutherland Phonological Awareness 1)
Table 111 MANOVA of Variable Set B With Five Background Factors 291
Table 112 Significant Results For Variable Set B With Preschool Literacy Task 292 Measures
Table of Contents Table 113 Means and Standard Errors For Variable Set B on Teachers’ 293 Perceptions – Class Conduct and Independence
Table 114 Means and Standard Errors For Variable Set B on Teachers’ 294 Perceptions of Reading and Writing Progress
Table 115 Means and Standard Errors For Variable Set B on Significant 296 Factors From Concepts About Print Test in Preschool
Table 116 Means and Standard Errors For Variable Set B With Significant 297 Phonological Awareness Factors
Table 117 Mean Scores and Standard Errors For Variable Set B With Print 298 Knowledge Task Factors
Table 118 Mean Scores and Standard Errors For Variable Set B With 299 Robinson’s Test of Writing Vocabulary
Table 119 Mean Scores and Standard Errors For Variable Set B With Canberra 299 Word Test
Table 120 Mean Scores and Standard Errors For Variable Set B With Reading 299 Words in all Literacy Task Measures
Table 121 Variable Set B (Based on Environmental Print and Letter 301 Knowledge) With Significant Teachers’ Perceptions and Literacy Factors/Scores Depicting the Highest and Lowest Mean Scores
Table 122 Pearson’s Chi-square Analyses For Variable Set C and Background 302 Variables
Table 123 MANOVA of Variable Set C With SES, Parents’ Perception and 303 Teachers’ Perception Factors
Table 124 Significant Results For Variable Set C With Literacy Tasks 304 Completed in Preschool
Table 125 Means and Standard Errors For Variable Set C With Teachers’ 305 Perceptions – Reading Progress and Writing Progress
Table 126 Means and Standard Errors For Variable Set C on Contextualised 306 Reading of Environmental Print Measures
Table 127 Means and Standard Errors For Variable Set C on Letter Knowledge 307 Measures
Table 128 Means and Standard Errors For Variable Set C on Print Awareness 307 from CAP
Table of Contents Table 129 Means and Standard Errors For Variable Set C on Print Knowledge 308 Task For ‘Read Words’ Factor and ‘Sequencing Text’ Factor
Table 130 Means and Standard Errors For Variable Set C on Robinson’s Test 309 of Writing Vocabulary
Table 131 Means and Standard Errors For Variable Set C on Canberra Word 310 Test, Reading Words in All Literacy Tests and Literal Comprehension
Table 132 Variable Set C (Based on Phonological Awareness) With 311 Significant Preschool Literacy Factors and Scores Depicting the Highest and Lowest Mean Scores
Table 133 Summary of Multivariate Analyses of Variable sets A, B and C 313 With Literacy Measures in Preschool
Table 134 Parts of Their Own Name Written by Students in May/June Year 1 318
Table 135 Scores For Robinson’s Test of Writing Vocabulary May/June Year 1 319
Table 136 Results For Knowing Letter Names, Sounds and Words For Each 321 Letter in May/June Year 1
Table 137 Univariate Analysis of Letter Knowledge and Identification 322 Performances May/June Year 1 by School
Table 138 Scores For Concepts About Print Test May/June of Year 1 323
Table 139 Scores For Canberra Word Test May/June of Year 1 324
Table 140 Scores For Story Comprehension May/June of Year 1 325
Table 141 Scores For Print Knowledge Task May/June of Year 1 326
Table 142 Univariate Analysis For Print Knowledge Task in May/June of 326 Year 1 by School
Table 143 Post Hoc Analysis of Variance For Print Knowledge Task May/June 326 of Year 1 With School
Table 144 Scores For Syllable Counting May/June of Year 1 327
Table 145 Scores For Rhyme Detection May/June of Year 1 328
Table 146 Scores For Rhyme Production May/June of Year 1 328
Table 147 Scores For Onset Identification May/June of Year 1 328
Table 148 Scores For Final Phoneme Production May/June of Year 1 328
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Table 149 Multivariate Tests For Sutherland Phonological Awareness Tests 329 May/June of Year 1
Table 150 Component Matrix For Letter Knowledge 2 May/June of Year 1 334
Table 151 Significant Correlations For Letter Knowledge 2 Factor May/June of 334 Year 1
Table 152 Rotated Component Matrix For CAP Factors May/June of Year 1 338
Table 153 Correlations of CAP Factors With Background Factors May/June of 340 Year 1 (A)
Table 154 Correlations of CAP Factors With Background Factors May/June of 340 Year 1 (B)
Table 155 Rotated Component Matrix For Sutherland Phonological Awareness 343 Test May/June of Year 1
Table 156 Correlations of Sutherland Phonological Awareness Factors With 344 Background Factors May/June of Year 1
Table 157 Significant Results For Variable Set A With Literacy Tasks 348 Completed in May/June of Year 1
Table 158 Means and Standard Errors For Variable Set A on Letter Knowledge 349 Measures in May/June of Year 1
Table 159 Means and Standard Errors For Variable Set A on Total Score For 350 Print Knowledge Task Measures in May/ June of Year 1
Table 160 Means and Standard Errors For Variable Set A on Total Score For 351 Robinson’s Test of Writing Vocabulary Measures in May/June of Year 1
Table 161 Means and Standard Errors For Variable Set A on Canberra Word 352 Test Measures in May/June of Year 1
Table 162 Variable Set A (Based on CAP in Preschool) With Significant 354 May/June Literacy Assessment Measures Depicting the Highest and Lowest Cluster Mean Scores
Table 163 Standardised Cluster Mean Vectors For Student Groups Within 354 Variable Set A
Table 164 Significant Results For Variable Set B With Literacy Tasks 355 Completed in May/June Year 1
Table 165 Means and Standard Errors For Variable Set B on Letter Knowledge 356 Measures in May/June of Year 1
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Table 166 Means and Standard Errors For Variable Set B on Print Knowledge 357 Task Measures in May/June of Year 1
Table 167 Means and Standard Errors For Variable Set B on Robinson’s Test 358 of Writing Vocabulary Measures in May/June of Year 1
Table 168 Means and Standard Errors For Variable Set B on Canberra Word 359 Test Measures in May/June of Year 1
Table 169 Variable Set B ( Based on Environmental Print and Letter 361 Knowledge) With Significant May/June Literacy Assessment Measures Depicting the Highest and Lowest Cluster Mean Scores
Table 170 Significant Results For Variable Set C With Literacy Tasks 361 Completed in May/June of Year 1
Table 171 Means and Standard Errors For Variable Set C on Letter Knowledge 362 2 Measures in May/June of Year 1
Table 172 Means and Standard Errors For Variable Set C on Onset 363 Identification, Final Phoneme Production and Rhyme Production Factor Measures in May/June of Year 1
Table 173 Means and Standard Errors For Variable Set C on Syllable Counting 363 and Rhyme Detection Measures in May/June of Year 1
Table 174 Means and Standard Errors For Variable Set C on Print Knowledge 364 Task Measures in May/June of Year 1
Table 175 Means and Standard Errors For Variable Set C on Robinson’s Test 365 of Writing Vocabulary Measures in May/June of Year 1
Table 176 Means and Standard Errors For Variable Set C on Canberra Word 366 Test Measures in May/June of Year 1
Table 177 Variable Set C (Based on Phonological Awareness in Preschool) 367 With Significant May/June Literacy Assessment Measures Depicting the Highest and Lowest Cluster Mean Scores
Table 178 Cluster Analyses With Literacy Assessment Tasks May/June of 368 Year 1
Table 179 Scores For Ohio Word Test November of Year 1 372
Table 180 Scores For Dictation and Spelling Tests November of Year 1 373
Table 181 Scores For Concepts About Print Test November of Year 1 374
Table 182 Results For Rhyme Production November of Year 1 375
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Table 183 Results For Final Phoneme Identification November of Year 1 375
Table 184 Results For Segmentation 1 November of Year 1 375
Table 185 Results For Blending November of Year 1 375
Table 186 Results For Initial Phoneme Deletion November of Year 1 376
Table 187 Results For Segmentation 2 November of Year 1 376
Table 188 Percentage Frequency of Parents’ Perceptions of Children’s 382 Personal Characteristics and Interests in November of Year 1
Table 189 Percentage Frequency of Parents’ Perception of Children’s 382 Enjoyment of School in November of Year 1
Table 190 Percentage Frequency of Parents’ Perceptions of Children’s 383 Academic and Literacy Achievements
Table 191 Percentage Frequency of Parents’ Perceptions of Who Reads to Year 384 1 Children at Home
Table 192 Percentage Frequency of Parents’ Perceptions of How Often Year 1 385 Children are Read to at Home
Table 193 Parents’ Perceptions of Periods of Time Spent Reading to Year 1 385 Children at Home
Table 194 Parents’ Perceptions of Estimates of the Number of Books at Home 386 For Year 1 Children
Table 195 Parents’ Perceptions of Texts Shared at Home With Year 1 Children 386
Table 196 Parents’ Perceptions of People Who Listen to Year 1 Children Read 387 at Home
Table 197 Parents’ Perceptions of How Often Listening to Year 1 Children’s 388 Reading Occurred at Home
Table 198 Parents’ Perceptions of Periods of Time Spent Listening to Year 1 388 Children Reading at Home
Table 199 Parents’ Perceptions of Year 1 Children’s Time spent Writing at 389 Home
Table 200 Teachers’ Perceptions of Class Conduct in November of Year 1 393
Table 201 Teachers’ Perceptions of Literacy Progress in November of Year 1 393 (A)
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Table 202 Teachers’ Perceptions of Literacy Progress in November of Year 1 394 (B) Table 203 Rotated Component Matrix For the Single-factor Solution Parents’ 399 Perceptions – Child Characteristics
Table 204 Rotated Component Matrix For the Single-factor Solution For 400 Parents’ Perceptions – Children’s Literacy Progress
Table 205 Rotated Component Matrix For Parents’ Perceptions of Home 401 Literacy Practices Derived From Parent Survey 2
Table 206 Rotated Component Matrix For Teachers’ Perceptions – Class 403 Conduct 2
Table 207 Rotated Component Matrix For Teachers’ Perceptions – Literacy 404 Progress
Table 208 Significant Correlations of Background Factors From November of 407 Year 1
Table 209 Rotated Component Matrix For Concepts About Print in November 412 of Year 1
Table 210 Significant Correlations For Concepts About Print in November of 413 Year 1
Table 211 Rotated Component Matrix For Sutherland Phonological Awareness 416 in November of Year 1
Table 212 Significant Correlations For Sutherland Phonological Awareness in 417 November of Year 1
Table 213 Component Matrix For Spelling and Dictation Factor in November 419 of Year 1
Table 214 Significant Correlations For Spelling and Dictation Factor in 419 November of Year 1
Table 215 Significant Correlations With Reading Rank in November of Year 1 423
Table 216 Significant Results For Variable Set A With Literacy Tasks 425 Completed in November of Year 1
Table 217 Means and Standard Errors For Variable Set A on Ohio Word Test 426 in November of Year 1
Table 218 Means and Standard Errors For Variable Set A on Reading Rank 427 Measures in November of Year 1
Table of Contents Table 219 Variable Set A (Based on CAP Preschool) With significant 429 Preschool, May/June and November Year 1 Literacy Assessment Measures Depicting the Highest and Lowest Cluster Mean Scores
Table 220 Profiles of the Best Performing Cluster and Least Well Performing 430 Clusters in Variable Set A
Table 221 Significant Results For Variable Set B With Literacy Tasks 432 Completed in November of Year 1
Table 222 Means and Standard Errors For Variable Set B on Spelling and 433 Dictation Measures in November of Year 1
Table 223 Means and Standard Errors For Variable Set B on Ohio Word Test 434 Measures in November of Year 1
Table 224 Means and Standard Errors For Variable Set B on Reading Rank 435 Measures in November of Year 1
Table 225 Variable Set B (based on Environmental Print and Letter 437 Knowledge) With Significant Literacy Factors and Scores Depicting the Highest and Lowest Mean Scores in Preschool, May/June and November of Year 1
Table 226 Profiles of the Best Performing Cluster and the Least Well 438 Performing Clusters in Variable Set B
Table 227 Means and Standard Errors For Variable Set C on Blending and 440 Rhyme Production Measures in November of Year 1
Table 228 Means and Standard Errors For Variable Set C on Phoneme 440 Deletion and Identification Measures in November of Year 1
Table 229 Means and Standard Errors For Variable Set C on Segmenting 441 Measures in November of Year 1
Table 230 Variable Set C (Based on Phonological Awareness) With Significant 443 Preschool Literacy Factors and Scores Depicting the Highest and Lowest Mean Scores in Preschool, May/June and November of Year 1
Table 231 Profiles of the Best Performing and Least Well Performing Clusters 444 in Variable Set C
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LIST OF FIGURES
Figure 1 Distribution of Students’ Ages While at Preschool 115
Figure 2 Distribution of Students’ Ages Across Three Age-Group Ranges 116
Figure 3 Distribution of Students’ Gender 116
Figure 4 Mothers’ Occupations When Their Children Were in Preschool 119
Figure 5 Mothers’ Education Level When Their Children Were in Preschool 120
Figure 6 Fathers’ Occupation When Their Children Were in Preschool 124
Figure 7 Fathers’ Education Level When Their Children Were in Preschool 125
Figure 8 Students’ Results For Reading Words in Preschool 215
Figure 9 Positive Correlation of Parents’ Perceptions – Child Characteristics 239 and Parents’ Perceptions – Home Writing
Figure 10 Negative Correlations of Teachers’ Perceptions – Student Conduct 241 and Parents’ Perceptions Children’s Characteristics
Figure 11 Scree Test For PCA of Environmental Print Task Measures 242
Figure 12 Positive Correlation of Parents’ Perception – Children’s 247 Characteristics Factor and Letter Knowledge Factor From Preschool
Figure 13 Negative Correlation Teachers’ Perception – Reading Progress 248 Factor and Letter Knowledge Factor in Preschool
Figure 14 Scree Test For PCA of Concepts About Print Test in Preschool 249
Figure 15 Scree Test For PCA of Print Knowledge Task 256
Figure 16 Scree Test For PCA of Sutherland Phonological Awareness Test 260
Figure 17 Positive Correlation of Father SES and Rhyme and Syllable Factor 262
Figure 18 Negative Correlation of Teachers’ Perceptions – Writing, and 263 Rhyme, Onset and Final Phoneme Factor
Figure 19 Positive Correlation of Parents’ Perceptions – Child Characteristics 335 and Letter Knowledge 2
Figure 20 Negative Correlation of Teachers’ Perceptions – Reading and Letter 336 Knowledge 2
Table of Contents Figure 21 Positive Correlation of CAP Factor 4 – Concept of a Word and 341 Parents’ Perception – Enjoy Preschool
Figure 22 Negative Correlation Teachers’ Perception – Reading and CAP 342 Factor 6 – Place to Start Reading
Figure 23 Highest Level of Text Read by the Students in Each Setting in 378 November of Year 1 as a Percentage of Each School Population
Figure 24 Positive Correlation of Parents’ Perception of Literacy Progress 408 With Parents’ Perceptions of Child Characteristics
Figure 25 Negative Correlation of Teachers’ Perceptions of Literacy Progress 409 With Parents’ Perception of Literacy Progress
Figure 26 Positive Correlation of Parents’ Perceptions of Literacy Progress 414 With CAP Factor 4 – Letter Concept
Figure 27 Negative Correlation of Teachers’ Perception – Literacy Progress 415 and CAP Factor 1 – Ordering Letters and Words
Figure 28 Positive Correlation of Parents’ Perception – Literacy Progress and 420 Spelling and Dictation Factor
Figure 29 Negative Correlation of Teachers’ Perception – Literacy Progress 421 and Spelling and Dictation Factor
Table of Contents ACKNOWLEDGEMENTS
I acknowledge the support received and express my thanks to:
Professor Peter Freebody for his guidance, encouragement, support and inspiration as Principal Supervisor of this project.
Associate Professor Brendan Bartlett for his support, encouragement and advice as second Principal Supervisor.
My husband, John, for maintaining constant encouragement.
My children, Elizabeth and David who affirmed my work with patience and understanding.
My parents, Pat and Olga Dunphy, for instilling in me the love for learning and the courage to pursue a dream and carry it through.
Principals, school administrators, parents and teachers from participating schools who so kindly granted me the privilege of being able to work with the children.
The children for their interactions, enthusiasm, inquisitiveness and co-operation throughout the duration of the study. I have learnt much and appreciate more fully the many and varied pathways young children travel as they learn to be literate.
Finally, I thank Griffith University for the support received during my candidature.
I certify that this thesis is the result of my own research, and that this work has not previously been submitted for a degree or diploma in any university.
To the best of my knowledge and belief, the thesis contains no material previously written by another person except where due reference is made in the thesis itself.
Janelle Patricia YOUNG
______Date
CHAPTER ONE
INTRODUCTION
In today’s schools, too many children struggle with learning to read. As
many teachers and parents will attest, reading failure has exacted a
tremendous long-term consequence for children’s developing self-
confidence and motivation to learn, as well as for their later school
performance. (Armbruster, Lehr, & Osborn, 2001, p. ii)
Current global, industrial, economic and technological changes impact on lifelong literacy practices as children and adults face an increasingly broad range of literacies within their everyday lives at home, in education and in work. These additional demands increase the need to pay greater attention to the development of language and literacy skills and knowledge from an early age.
The ability to use language is fundamental to all pursuits both in and out of school. Using language to communicate in a range of modes is essential for personal, recreational, educational and work-related pursuits. In order to participate fully as a citizen and fulfill the rights of citizenship, appropriate levels of language and literacy are needed. Economic prosperity requires people with high levels of literacy skills to ensure social, national and economic demands are met (Lo Bianco & Freebody, 2001). A socially just world requires citizens who have high levels of literacy skills that enable the critical analysis of an ever- increasing range of texts within society.
Chapter 1: Introduction 1
Learning to read has been the focus of numerous research studies and educators have grappled with finding effective methods, materials and instruments that enable the measurement of reading achievement. A focus has been placed on beginning literacy and patterns of early literacy development among young children have been studied. These studies aim to predict patterns of early literacy achievement in school and have been conducted during the transition from home to school and throughout the first year of formal schooling. A number of these studies have shown that those who fail to develop literacy skills within the first three years of schooling are more likely to experience serious difficulties in the long term (Clay, 1972; Juel & Leavell, 1988; Stanovich, 1986). Knowing more about patterns of literacy development and being able to predict those most likely to face early literacy difficulties are important issues in a world where literacy demands are increasing (Snow, Burns & Griffin, 1998).
Learning to be literate remains a priority for those who care for and educate young children. Becoming literate is highly complex, and yet it is often presented simplistically. Research in the area is vast and diverse. Chall (1967) saw the need for researchers to move forward with their studies and resist concerning themselves solely with isolated studies where accumulated knowledge and theories are continually tested. That need is still pertinent today.
A key finding emerges from the body of research on early literacy. If a child fails to learn to be literate in the early years of schooling, then the chances of gaining a high level of proficiency in reading and writing later on are greatly reduced
(Juel & Leavell, 1988). Recent longitudinal studies reiterate messages from past decades that children need experience with print in the home and in their own
Chapter 1: Introduction 2
community contexts prior to attending school (Blatchford, Burke, Farquar,
Plewis & Tizard, 1987; Dickinson & Tabors, 1991; Juel 1988; LeFevre &
Senechal, 1999). There needs to be an emphasis on recognition of print in the local community, teaching the alphabetic code and phonological awareness skills so word recognition skills are developed early (Badian, 1998; Hatcher & Hulme,
1999; Hecht, Burgess, Torgesan, Wagner & Rashotte, 2000; Stanovich, 1986,
1993, 2000).
1.1 THE RESEARCH QUESTIONS
One key question guides this study.
Key Question: How do young students develop literacy capabilities during the first year of schooling?
To develop an investigation guided by this key question, five contributing questions were utilised.
1. What knowledge of literacy and understanding of it do students bring to
school?
2. What aspects of literacy knowledge and understanding do students develop in
the prior-to-school period?
3. How do aspects of students’ literacy knowledge and understanding prior to
school relate to one another and students’ background?
4. How do child, home and school factors relate to literacy development in the
first year of school?
5. How do students’ literacy knowledge and understanding of it in the prior-to-
school period predict students’ literacy achievement during the first year of
school?
Chapter 1: Introduction 3
1.2 SIGNIFICANCE OF THE RESEARCH QUESTIONS
This study contributes to the development of theory, research methodology, teaching practice and policy formulation. Its longitudinal nature provided for the in-depth study of patterns of literacy development in the early years and enabled an examination of cross-time relations on a range of measures. However, an argument continues whether children should be ready for school, or schools should be ready to cope with the diverse skills, knowledge and dispositions that children bring to school (La Paro & Pianta, 2000).
If educators are to be informed in responding to the first of the contributing questions, it is vital that children’s knowledge and understanding about print is assessed as they enter Year 1. This can be done using basic tasks and observing children’s literacy behaviours closely. Research has shown that children develop literacy knowledge and understandings in the prior-to-school period (Blatchford,
1985; Clay, 1991; McNaughton, 1995, 2002; Strickland & Morrow, 1989a,
1989b; Teale & Sulzby, 1986b; Whitehurst & Lonigan, 2001). However, teachers do not always acknowledge different levels of literacy skills as children enter school (Burgess, Lundgren, Lloyd & Pianta, 2001; McCutchen, Abbott, Green &
Beretvas, 2002; McGill- Franzen, Lanford & Adams, 2002; Raban, Ure & Smith,
1999). This lack of acknowledgement means individual needs are not always being considered when planning for literacy in the early months of formal schooling.
Educators not only need to acknowledge that children develop literacy knowledge and understandings prior to school, but they also should be informed
Chapter 1: Introduction 4
about which aspects of literacy knowledge influence future literacy achievements. Researchers have found that preschool children may acquire: concepts about print; knowledge of environmental print; knowledge of letters; word decoding skills; phonological awareness and listening comprehension
(Grogan, 1995; Kirby & Parrila, 1999; Lonigan, Burgess & Anthony, 2000;
Scarborough, 2001; Smith, 1997; Storch & Whitehurst, 2002; Weinberger,
1996). Teachers then need to take steps to measure these skills as children move from home to school.
It is essential that teachers not only acknowledge and measure children’s early literacy understandings and skills but they recognise how these contribute to children’s overall development as readers and writers. Research (Freebody,
Ludwig & Gunn, 1995; Jordan, Reyes-Blanes, Peel, Peel & Lane, 1998) has shown that teachers hold beliefs that particular children will struggle with literacy and there is a tendency to blame disadvantaged or culturally different children. Classroom practices as well as children’s innate capabilities need to be acknowledged as contributing to literacy development (Freebody, Ludwig, &
Gunn, 1995). Each child needs to be observed carefully by a class teacher with consideration being granted for cultural differences and credit being given for existing knowledge, skills and understandings.
Examining home and school factors as children learn to be literate is also crucial.
Research (Britto, 2001; Dickinson & Tabors, 2001; McCarthey, 2000; Purcell-
Gates, 2000) has shown that children from supportive homes where literacy practices are valued often develop early understandings about print. Despite a
Chapter 1: Introduction 5
number of studies, we still do not have enough evidence to be able to predict accurately how a child’s literacy skills will develop. However, there is growing evidence that most reading difficulties are caused from limitations in the child’s personal experiences with print or less than adequate instruction, not some innate cognitive dysfunction within the child (Vellutino & Scanlon, 2001).
1.1.1 Theory
Theories ‘are not facts; they are constructs that enable us to work more effectively on the problem’ (Gordon, 1979, p. 370). Theories usually evolve from field research or reviews of research. Broad generalisations are drawn from existing knowledge and a theory is proposed. Educational theories often cause debate as community members defend their positions in relation to a theory.
In recent times, Chall (1999) summarised theoretical models of reading as either
‘one stage or two stage’ (p. 163). A one-stage model presumes a single process for extracting meaning from print. In such a model reading is seen as a natural process that can be likened to learning to speak. In contrast, the two-stage model involves the systematic study of the symbol system to assist the reader to gain meaning from texts. This model assumes reading must be taught, not just learned naturally. Studies, particularly those conducted longitudinally, enable the scientific study of phenomena as well as the evaluation of such theoretical approaches. In this study, a range of variables centred on child, home and school are investigated within the prior-to-school period in order to make predictions relating to literacy development after one year of school.
Chapter 1: Introduction 6
1.1.2 Methodology
This study reports correlational, longitudinal research designed to predict patterns of early literacy achievement after one year of school. Participants in the study include 114 young students, their parents and 11 Year 1 teachers. The study commenced at the end of the preschool year and continued for a period of twelve months. Data were gathered using measures of achievement with the students, surveys with parents and surveys and checklists with teachers. Cross- time comparisons of literacy achievement were possible as data were gathered three times from the students throughout the study.
Analyses of data include statistical descriptions of performance on the numerous measures and interrelations within the data. They enabled an examination of the patterns of literacy achievement and an investigation of the predictability of children’s literacy progress after one year of schooling. This study breaks new ground in the adoption of multiple forms of analyses to investigate more closely the child, home and school factors from the prior-to-school period that may impact on and predict later literacy development. It also investigates the relationships among parents’ perceptions, teachers’ perceptions and children’s literacy achievements prior to and throughout the first year of schooling.
1.1.3 Practice
Findings from research usually influence policy and practice. A number of findings relating to patterns of early literacy achievement have already begun to influence practice, but there is a need to ensure teachers are informed about
Chapter 1: Introduction 7
research findings more regularly and then are able to apply these to classroom practices.
There is a need to ensure students from diverse backgrounds are acknowledged and their learning needs are accommodated. Throughout the western world there are students from diverse backgrounds who differ from mainstream students in primary language and social class, who consistently perform below average on measures of literacy (Education Queensland, 2000a; International Reading
Association, 1999a; Masters & Forster, 1997). When national testing is used, literacy is seen as a set of skills not a cultural practice and some scholars react against this perspective (Gee, 2001; Luke & Freebody, 1997; Street, 1995).
However, there is a need to conduct more research on the literacy practices of non-mainstream communities and apply the knowledge gained to improve literacy practices in schools.
Teachers may have different academic expectations for students of different cultural backgrounds (Oakes & Gutton, 1995). Students from diverse backgrounds are placed in remedial classes in greater numbers and literacy expectations may be lower. Remedial teachers may emphasise, skill development and oral reading and place less emphasis on reading comprehension (Au &
Raphael, 2000). For equity purposes, changes need to be made and educators need to find more successful ways of assisting students with diverse backgrounds to be literate.
Chapter 1: Introduction 8
With the increasing use of the information communication technology, reporting of findings from research may begin to filter more successfully into schools. An emphasis on research-based literacy practices has gained wider acceptance
(Barone & Mandel Morrow, 2003; International Reading Association, 1999b;
United States Department of Education, 2002b). Position statements published by the International Reading Association provide some current guidelines for teachers. These can assist teachers as they provide findings from research about literacy learning and guidelines for teaching strategies. An overview and summary from a selected number of Position Statements relevant to this study are now provided.
A Position Statement, Excellent Reading Teachers (International Reading
Association, 2000a) includes information on qualities of knowledge and practice recommended for teachers of literacy. These include:
• Understanding reading and writing development;
• Believing all children can learn to read and write;
• Knowing a variety of ways to teach reading;
• Using flexible grouping strategies. (p.1)
A second Position Statement, Making a Difference Means Making it Different:
Honoring Children’s Rights to Excellent Reading Instruction (International
Reading Association, 2000b) includes a set of ten principles defined as the right of every child. Three of these principles that relate closely to this study are:
• Early reading instruction based on needs (p.3);
• Reading instruction that builds skill and desire (p.4) and
Chapter 1: Introduction 9
• Assessment that identifies strengths and needs (p.7).
Educators are encouraged to build family-school partnerships and the Position
Statement, Family-school Partnerships: Essential Elements of Literacy
Instruction in the United States (International Reading Association, 2002a), offers research evidence that family involvement in children’s education enhances literacy development. However, schools face the complex task of building relationships within their communities.
Three Position Statements relate specifically to reading instruction. The first,
Using Multiple Methods of Beginning Reading Instruction (International Reading
Association, 1999b), includes a call for flexibility in instruction as research has shown that no one method guarantees success for every child and nor has any one method been shown to be superior to others (p.1). The second Position
Statement, The Role of Phonics in Reading Instruction (1997), supports the teaching of phonics as “an important aspect of beginning reading instruction” (p.
2). Phonemic Awareness and the Teaching of Reading, (International Reading
Association, 1998), describes the role and importance of phonemic awareness to beginning reading and provides strategies for teachers to include within class programs.
All of these Position Statements support the need for the current study. First the importance of learning to read is highlighted in all six Position Statements.
Second, the family is seen as an important means of support for children as they learn to be literate and finding out more about the influences of families on
Chapter 1: Introduction 10
literacy development is crucial. Third, obtaining information about meeting needs of individual children is essential for selecting appropriate teaching strategies in the early years.
Studying patterns of early literacy development with a view to predicting early literacy achievement extends upon current research findings and may impact on practice. Understanding particular aspects of young children’s literacy knowledge and understanding in the prior-to-school period may alert Year 1 teachers to the nature and extent of children’s literacy knowledge as they enter school. This particular information may highlight the need to learn about children’s experiences with print and to build on these in the early weeks of school. Finally results from this study may influence the curriculum in the prior- to-school years as literacy-related strategies that enhance children’s chances of becoming successful learners of literacy become more accepted and are included in these educational settings.
1.1.4 Policy
Educational policy plays a significant role in teaching practices in schools. Policy usually defines ways that education budgets will be expended and funded initiatives must adhere to policy guidelines. In all western nations elected governments are responsible for education policy and setting goals for educational change. Policy is usually guided by research findings, but particular perspectives are usually privileged and these may not cater for all needs.
Chapter 1: Introduction 11
In Australia, the current Commonwealth literacy policy, Literacy for All: The
Challenge for Australian Schools was announced in 1998. This policy aims to provide better educational accountability through improved assessment and reporting practices. Improved communication with families is advocated in order to keep parents informed about their child’s education. The policy is driven by a focus on learning outcomes where equal opportunity and meeting the needs of individuals are emphasised (Department of Employment, Education and Youth
Affairs, 1998). Each Australian State or Territory enacts Commonwealth education policy.
In the United States, the Bush administration has taken a strong stand on educational policy and linked policy to education funding. The government has proclaimed that too many children have low levels of literacy. An increase in funding has been set aside to improve standards. A new law, No Child Left
Behind 2001, was passed in 2002 and this law represents new reforms in elementary and secondary education (United States Department of Education,
2002b).
In the United Kingdom, the National Literacy Strategy is the current policy. This policy is a response to reports of poor literacy standards by some children. The government has provided high levels of funding for schools actively supporting the policy. Ways of improving teaching practices have been investigated and resources are readily available for teachers. Schools and teachers are offered incentives to improve standards (Department for Education and Employment,
1997).
Chapter 1: Introduction 12
In New Zealand, the government is also responding to some low standards of literacy achievement throughout the country. Maori and Pacific Islander children are performing below the level of other students and a Literacy Taskforce is currently investigating initiatives to address the issue (New Zealand Ministry of
Education, 2000).
1.3 PREVIEW OF THE PROJECT
A correlational, longitudinal study of early literacy achievement is reported. The aim of the study is to predict later patterns of early literacy achievement from students’ knowledge and understandings prior to commencing school. One hundred and fourteen students with a mean age of 67 months commenced the study in November of the preschool year. Measures of literacy knowledge and understanding were gathered using one-to-one interviews with each child in three schools. Data also were gathered from parents and Year 1 teachers regarding their perceptions of home literacy practices, school behaviour and progress in learning to be literate.
Multiple forms of analyses enabled an in-depth examination of children’s personal characteristics and literacy knowledge with a view to examining these for predicting later literacy achievement. This study is significant in that the longitudinal design enabled cross-time measures to be gathered and compared.
Complex analyses were utilised to examine longitudinal data in new and novel ways by exploring relationships among a range of variables. Relationships among parents’ perceptions, teachers’ perceptions and children’s literacy
Chapter 1: Introduction 13
achievements prior to school and throughout the first year of schooling are also studied.
The study is timely as there is currently a common interest in raising literacy standards and ensuring there is increased accountability for schools particularly in United States, United Kingdom, New Zealand and Australia. Insights into literacy understandings children bring to school should provide findings that will affect classroom practice in both the prior-to-school period and the early years of schooling.
Chapter Two is a review of literature relevant to this study. Theoretical models and practices in the early years dating from the beginning of the twentieth century are reviewed first and this is followed by an examination of current literacy policy and practices in parts of the developed world. This examination contextualises the study and enables a comparison of Australia’s literacy policy and practices with those in the United States, United Kingdom and New Zealand.
Research on literacy development in the early years is then reviewed with a particular emphasis being placed on longitudinal predictive studies that commence data collection in the prior-to-school period or in the early months of
Year 1.
Participants, settings, instruments and procedures used within the study are described in Chapter Three. Methodological considerations in relation to the correlational longitudinal study are included. These methods were designed with
Chapter 1: Introduction 14
a view to predicting patterns of early literacy achievement after one year of schooling.
Statistical descriptors of student performance measures and data collected from parents and teachers during the preschool period are described in Chapter Four.
Multivariate effects relating to school, age and gender also are reported. Data from parents revealed family background information, home literacy practices and parents’ perceptions of the learning characteristics of their children. Teachers provided information on their perceptions of students’ literacy knowledge and understanding and the students’ classroom conduct during the first six to eight weeks of Year 1. These results addressed the questions:
1. What knowledge of literacy and understanding of it do students bring to
school?
2. What aspects of literacy knowledge and understanding do students develop in
the prior-to-school period? and
3. How do aspects of students’ literacy knowledge and understanding prior to
school relate to one another and students’ background?’
Principal Component Analyses (PCA) used to explore the underlying dimensions within the data are described in Chapter Five. These analyses were conducted with children’s preschool literacy measures of achievement, background data from parents’ perceptions and teachers’ perceptions of children as well as particular demographic features of families. The calculation of background and preschool literacy achievement factor scores enabled further analyses through correlation to examine the relationships among all three sets of factors. Cluster
Chapter 1: Introduction 15
analyses of preschool literacy factors were then conducted where students with similar performance profiles were grouped together. These analyses helped to determine various pathways of early literacy development and addressed the questions:
3. How do aspects of students’ literacy knowledge and understanding prior to
school relate to one another and to students’ background?
4. How do child, home and school factors relate to literacy development in the
first year of school? and
5. How do students’ literacy knowledge and understanding of it in the prior-to-
school period predict literacy achievement during the first year of school?
Data collected from students during the May/June period of Year 1 are reported in Chapter Six. Results of multivariate and univariate effects due to school, age and gender and descriptive results of the literacy assessment tasks are reported.
Data from students in May/June of Year 1 enabled an examination of the fourth contributing question ‘How do child, home and school factors relate to literacy development in the first year of school?’
Principal Component Analysis (PCA) was conducted on May/June data to investigate underlying factors. These analyses are reported in Chapter Seven and addressed the contributing questions ‘How do child, home and school factors relate to literacy development in the first year of school?’ and ‘How do students’ literacy knowledge and understanding in the prior-to-school period predict literacy achievement during the first year of school?’ Analyses were conducted with Letter Knowledge (Clay, 1979a, 1985, 1993a), Concepts About Print (Clay,
Chapter 1: Introduction 16
1979a, 1985, 1993a) and Sutherland Phonological Awareness (Neilson, 1999) measures as these were the only literacy tasks from the May/June period that could be subjected to factor analyses. Factors calculated from the May/June literacy achievement measures were analysed with Variable Sets A, B and C derived from cluster analyses in preschool to determine relationships.
Statistical descriptions of performance on literacy assessment measures administered in November of Year 1 are described in Chapter Eight. Multivariate effects relating to school, age and gender are reported in order to address the question ‘How do child, home and school factors relate to literacy development in the first year of school?’ Data from Parent Survey 2 and Teacher Checklist 2 provided further perceptions of home, child and school-related issues in
November of Year 1.
Data collected from students, parents and teachers in November of Year 1 are examined in Chapter Nine. Principal Component Analysis (PCA) was conducted to investigate underlying factors that existed within the data from students, parents and teachers. Data provided from the students’ literacy assessment measures in November of Year 1 provided data to examine relationships with earlier achievement measures and with previously derived background factors.
Parent Survey 2 and Teacher Checklist 2 provided a second set of background factors calculated from parents’ and teachers’ perceptions of students’ characteristics, behaviour and literacy progress. The calculation of these background factors enabled further analyses by correlation and examined relationships among the three sets of factors. Finally, Variable Sets, A, B and C
Chapter 1: Introduction 17
(derived from literacy measures in preschool) were analysed with factors from
Parent Survey 2, Teacher Checklist 2 and the November Literacy Assessment measures. Relationships within these sets of data were determined to ascertain predictive patterns of early literacy development. This chapter addresses the questions ‘ How do child, home and school factors relate to literacy development in the first year of school?’ and ‘How do students’ literacy knowledge and understanding of it in the prior-to-school predict literacy achievement during the first year of school?’
Findings from the study, with attention paid to implications for theory, research methodology, policy and practice, are included in Chapter Ten. Limitations are examined and directions for future research suggested.
Chapter 1: Introduction 18 CHAPTER TWO
LITERATURE REVIEW
2.1 INTRODUCTION
Each of the three corpuses of data collected for this study poses analytic and theoretical questions within educational research. Learning to read has attracted great attention. Jeanne Chall (1967) commented that “reading has been the most researched of the school subjects; for each study in arithmetic, there are probably three studies in reading” (p. 1). More recently, within the Report of the National
Reading Panel, the team reported “… that approximately 100,000 research studies on reading have been published since 1996, with perhaps 15,000 more appearing before that time” (National Institute of Child Health, 2000a, p. 1).
Early literacy research has an interdisciplinary nature and has been studied by cultural anthropologists (Heath, 1983; Schieffelin & Cochran-Smith, 1984), linguists (Cazden, 1981; Gee, 2001), early childhood educators (Hiebert &
Taylor, 2000; Schickedanz, 1986) and cognitive and developmental psychologists (Bryant, 1998; Clay, 1991; Snow, Burns, & Griffin, 1998). As such, any review of literature in the field of early literacy needs to be selective.
Research pertinent to the corpuses of data relating to early literacy development are addressed in this literature review and comprise several sections. First, the study is theoretically positioned through an historical examination of theories of language and literacy from the early 1900s to the present time. Classroom practices associated with these theories also are addressed. Current literacy policies and major research studies and reviews conducted during the last decade
Chapter 2: Literature Review 19 in Australia, the State of Queensland, United States, United Kingdom and New
Zealand are then examined. These research studies, reviews and policies situate the study reported in this thesis. Next, influences on children’s literacy knowledge and skills in the preschool years and in the first year of school are examined. Lastly, the relationship between literacy knowledge and understanding in the preschool period and the implications for later literacy achievement are addressed.
2.2 THEORETICAL MODELS AND PRACTICES IN THE
EARLY YEARS
Learning theories impact on theories of language and literacy and on classroom practice. Practical applications of theoretical models in classrooms have not always been readily accessible to teachers (Tierney, 1994) or often have not been trialled or applied until a number of years after a theory has been proposed.
According to some researchers, theories relating to the teaching of reading have emerged mainly as debates about whether reading instruction should centre “on letters, on words, or on the meaningfulness of text” (Adams, 1999, p. 167). Other issues such as context, the role of background knowledge, prior experiences with texts, the nature of meaning-making, role of predictions, peer influences and the role of teachers (Tierney, 1994) have been included to varying degrees in proposed theoretical models.
Significant theoretical developments have overlapped and co-occurred presenting problems in relation to describing theoretical models of reading. “… models overlap, but they are also distinct from one another – especially in terms of
Chapter 2: Literature Review 20 emphases, nuances with respect to processes, and the roles of and interrelationships among certain factors” (Tierney, 1994, p. 1169). Those who study theoretical models face an added level of complexity. Scholars who originally propose a model often modify their perspectives. They may be influenced by other scholars, or may formulate new ideas themselves. Educators of today face additional dilemmas as the range and types of texts being used become more diversified while at the same time new theoretical positions are evolving. Theoretical models that can be applied to print texts cannot be so easily accommodated for multimedia, multi-modal and multi-layered texts. Theoretical models challenge thinking as they help educators to look differently at the same issue and perhaps see things that have not been seen before. All of these complexities are linked to ways different readers interpret texts and make meaning as they partake in transactions involving a reader and text.
Chall (1999) described theoretical models of reading as either “one stage or two stage” (p. 163). A one-stage model presumes a single process of getting meaning from print. Learning to read using this model is seen as a natural process that can be likened to learning to speak. A two-stage model involves the study of letters and sounds first and then gaining meaning from texts. Support for this model assumes reading must be taught and learned. Theoretical models of learning to read have oscillated between these two types of models throughout the last century.
Within the next section of the literature review an historical examination of theories of language and literacy from the Maturational perspective in the early
Chapter 2: Literature Review 21 1900s to Critical Social theories of the present time are briefly outlined.
Associated classroom practices also are addressed.
2.2.1 MATURATIONAL PERSPECTIVE
Theories proposed for beginning reading during the early years of the twentieth century were characterised by Froebelian philosophy that underlined the kindergarten movement. This philosophy was based on maturationalist beliefs
“…young children needed time to mature and to develop knowledge of the self before beginning formal reading instruction” (Crawford, 1995, p. 72). It was perceived that damage could be done to children if reading instruction commenced too early, but no risks were presumed if instruction was left until the child matured (Gesell, 1925). The notion of ‘reading readiness’ emerged, and beliefs relating to delaying the teaching of reading until a child reached a certain level of cognitive maturity became popular (Morphett & Washburne, 1931). The definition of school readiness has been defined as “… the task of allowing the psychological forces underlying learning to unfold so that physiological and constitutional structures can eventually emerge” (Meisels, 1998, p. 8). Tests were developed to provide information about children’s readiness for school, a practice that continued well into the 1950s.
In 1965 Chall conducted a critical review of research (1910 – 1965) on beginning reading. Her landmark publication Learning to read: The great debate, published in 1967, made recommendations to educators concerning teaching methods for beginning reading. Chall drew conclusions about the teaching of reading during the period 1930 to the early 1960s and she formulated eight principles of
Chapter 2: Literature Review 22 classroom practice. These principles “based partly on the interpretation of research findings, partly on theory, partly on combined experience of classroom teachers and partly on faith and belief” (Chall, 1967, p. 15) soon became conventional wisdom in beginning reading instruction. A condensed summary of the eight principles is as follows:
1. Reading should involve word recognition, comprehension, appreciation of
what is read to address personal and social problems. These processes should
begin from the start of instruction.
2. Children should start with meaningful reading of whole words, sentences
and stories linked to personal experiences and interests. Silent reading
should be stressed from the beginning.
3. When approximately 50 words have been learnt by sight the child should
begin to learn the phonemes and graphemes. Picture and meaning cues
should also be used. Structural analysis should be used at the same time.
4. Phonics instruction should occur over the whole six years of the elementary
school.
5. Drill and practice of phonics in isolation should be avoided. It should be
integrated with meaningful reading.
6. Words in student readers should be repeated often to assist learning.
7. A slow easy start is needed in the first year. All children should go through a
preparatory or readiness period. Those who need it should have longer
readiness periods.
8. Children should be taught in small groups that are based on student
achievement. (Austin & Morrison, 1963; Barton & Wilder, 1964; Chall,
1967)
Chapter 2: Literature Review 23 2.2.2 DEVELOPMENTAL AND NATIVIST PERSPECTIVES
Following a period dominated by the maturationalist view, a developmentalist view of reading emerged where advocates proposed that nurturing a child with worthwhile experiences and instruction could assist with becoming ‘ready’ for school (Durkin, 1966). Project Head Start, a preschool program for disadvantaged young children, commenced during the 1960s and is still operating today. The Direct Instruction Model (DISTAR) (Engelmann, &
Osborn, 1976) was used in Head Start and gained popularity. This model was based on four assumptions: All children are capable of learning to read and write, basic skills are essential, all disadvantaged children lack skills, and experience and steps must be taken to help disadvantaged children develop (Becker, 1977).
The influences of the DISTAR model could be seen through the use of pre- reading experiences to develop children’s level of readiness, standardised readiness tests and basal instructional materials that were skill-based and sequenced. The developmentalist view gained popularity and soon became entrenched, influencing early childhood classrooms for more than three decades.
Popularity for these practices began to wane when Chomsky, a linguist, published Syntactic Structures (Chomsky, 1957) and Aspects of the Theory of
Syntax (Chomsky, 1965). He refuted previous thinking about language comprehension and acquisition that had prevailed for almost 50 years. Chomsky also proposed a nativist view that “humans come to the world ‘wired’ to acquire the language of the community into which they are born” (Pearson & Stephens,
1994, p. 25). This view caused psychologists to re-examine behaviourist views of reading comprehension and acquisition and a new perspective emerged.
Chapter 2: Literature Review 24 2.2.3 PSYCHOLINGUISTIC PERSPECTIVE
Following Chomsky’s publications a new field of psycholinguistic research evolved. The purpose of this research was to investigate Chomsky’s proposal of an innate human ability to comprehend and acquire language. Those studying language acquisition soon found that young children did not rely on imitation alone, but they were active constructors of language who began to generalise grammatical rules and apply them within their own personal spoken language
(Brown, 1970). Chomsky’s work had a major impact on reading educators over many years as researchers began to test out a possible innate ability for learning to read and write (Goodman & Goodman, 1979; Harste, Woodward, & Burke,
1984; Smith, 1973).
Two influential researchers, Goodman and Smith were amongst those who sought to address questions raised by Chomsky’s work. Goodman conducted research with 100 children in grades 1, 2 and 3. He compared children’s ability to read the same words when presented as a text and as a list. Results showed the children made fewer errors when reading the whole text thus prompting
Goodman to infer that readers use the context of a text to assist them as they read. He also concluded that children’s errors in reading should not be regarded as mistakes but as ‘miscues’ or pieces of valuable information that provide insights into reading behaviour (Goodman, 1965; Goodman & Burke, 1972). In a seminal paper in 1967, Reading: A psycholinguistic guessing game, Goodman proposed that readers use three cueing systems. Syntactic cues are gained from the word order and grammar of the text while semantic cues assist with meaning and enable readers to develop prediction skills. A third cueing system relates to
Chapter 2: Literature Review 25 the graphophonic cueing system where readers use their knowledge of sound- symbol relationships in order to recognise words in a text (Goodman, 1967).
Smith also held a psycholinguistic perspective. He published Understanding
Reading in 1971 and Psycholinguistics and Reading in 1973. Both publications contributed to the popularity of the psycholinguistic perspective. Smith proposed that “reading cannot be formally taught …that children learn to read by reading”
(Smith, 1971, p. 186). He also described a teacher as a “facilitator and guide” (p.
187) who needs to understand the reading process. Readers, Smith argued, could rely heavily on a range of cueing systems and yet use only a limited amount of visual information (Smith, 1979). It was Smith’s belief that readers who focused too heavily on visual information would do so to the detriment of comprehending text. Those who supported the psycholinguistic perspective argued that readers were active constructors of meaning and that a range of cues were used to enable readers to predict words and meaning during reading (Pearson & Stephens,
1994). Smith described “three radical insights” espoused by linguists and cognitive psychologists at the time. The insights were:
1. Only a small part of the information necessary for reading comprehension
comes from the printed page.
2. Comprehension must precede the identification of individual words.
3. Reading is not decoding to spoken language. (Smith, 1973, p. v)
The psycholinguistic perspective gained much support over time and a philosophy of learning and teaching called Whole Language evolved (Dechant,
1993). The psycholinguistic perspective influenced the field of reading and
Chapter 2: Literature Review 26 classroom practice in five notable ways. First, there was increased interest in reading for meaning and this was in contrast to skill-based practices where worksheets, games and phonics placed an emphasis on reading accuracy. Second, educators began to look critically at reading materials being used to teach reading. Many texts, early basal readers in particular, were found to lack real- world meaning. This was caused by the composition of texts in which the repetition of high frequency words was commonplace. Third, the reading process became better known. Fourth, teachers began to use children’s miscues as an important insight into reading behaviour. A specific tool, the Miscue Analysis, provided a means by which teachers could record information about children’s oral reading and comprehension of texts. The last major influence from the psycholinguistic perspective was that it caused educators to reflect more closely on the relationship between teaching and learning (Pearson & Stephens, 1994).
The psycholinguistic perspective and the Whole Language philosophy had a major effect on the teaching of reading during the 1970s to early 1990s and remnants of the philosophy can still be seen in classrooms today.
While the Whole Language philosophy was widely accepted throughout the western world, it was not free from controversy. Five beliefs underpinning the psycholinguistic perspective identified the model as being different from previous models of reading. Goodman espoused first that “written language has all the basic characteristics of oral language” (Goodman, 1986, p. 23) and second that children could learn to be literate in a natural way with limited instruction if the right conditions were provided. Third, there was a de-emphasis on decoding as part of the reading process and a denial that a set of sub-skills was a
Chapter 2: Literature Review 27 prerequisite for beginning readers. Fourth, the experiences and prior knowledge of a reader were valued and thought to play a major role in the reading process.
Fifth, the teaching of phonics in supporting children’s comprehension of texts was played down (Cambourne, 1976). Thus, while support for Whole Language was widespread, the philosophy began to lose support when some children taught during this period began to experience difficulties with reading and spelling.
Goodman and Goodman “translated their theory into some excellent recommendations and activities toward developing children’s appreciation of text and thoughtfulness during reading” (Adams, 1990, p. 99), but later research into visual fixations of readers dispute the notion that readers are selective in their focus while reading. In fact, readers seem to process individual letters as they read (Adams, 1990). Thus, recent research denied that children could learn to read and write successfully without some explicit instruction in phonological awareness.
2.2.4 CONNECTIONIST PERSPECTIVE
As support for psycholinguistic theory and Whole Language philosophy began to wane, a re-emergence of a part-to-whole model for teaching reading occurred.
Adams, in her publication, Beginning to Read (1990), proposed a new
Connectionist theory in response to Goodman and Smith. Adams conceded at the time of writing her text that the theory was new and in need of further research.
Some resistance occurred because it was perceived as similar to behaviourist theory, but a strong argument in support of the theory was presented in the text
(Adams, 1990).
Chapter 2: Literature Review 28
There is some return to the ‘readiness’ perception within Connectionist theory and this aligns the theory to traditionally-driven reading instruction. It is held within the theory that there are stages of development and children must pass through each stage in order to develop as a reader. Fast, automatic word recognition seems to be needed in order to read fluently and with understanding, and those who support Connectionist theory argue for explicit instruction in sound/symbol relationships of the alphabetic system. Supporters of Connectionist theory conceded, in line with Whole Language philosophy, the need for using meaningful texts with young readers. Some researchers claimed that an ‘eclectic approach’ was advocated with a combination of the best of traditional and holistic practices being included. Thus, a more ‘balanced’ literacy curriculum was recommended (Crawford, 1995).
2.2.5 EMERGENT PERSPECTIVE
Within the same decade that the psycholinguistic perspective was receiving attention, Clay, a developmental psychologist, completed her doctoral dissertation, Emergent Reading Behaviour (Clay, 1966) and established that children travel different pathways to literacy. Observing children’s behaviours became the key for Clay as she examined the reading behaviour of 100 children in the first year of school (Clay, 1979a, 1982, 1991). Young children between the ages of five and six years were studied in New Zealand and qualitative and quantitative data were gathered both in home and school contexts. Results from
Clay’s study caused her to question theoretical models and classroom practices relating to readiness for reading instruction. She had not found that children
Chapter 2: Literature Review 29 needed to master a set of readiness sub-skills prior to learning to read, and children demonstrated a range of understandings and skills associated with written language prior to entering school. Clay considered the current notion of
‘readiness’ to be misleading and findings from the study caused her to describe children’s reading growth as ‘emergent’.
In 1986, Teale and Sulzby published Emergent Literacy: Writing and Reading, acknowledging the relationship of children’s reading and writing development in the early years. The authors acknowledged Clay’s work and expanded upon it to include writing as well as reading. They challenged the notion of reading readiness and drew the following conclusions from previous research of early literacy development:
1. Literacy development begins long before children start formal instruction.
2. Literacy development is the appropriate way to describe what was called
reading readiness. The child develops as a writer/reader. The notion of
reading preceding writing, or vice versa is a misconception.
3. Literacy develops in real-life settings for real-life activities in order to get
things done.
4. Children are doing critical cognitive work in literacy development from
birth to six years.
5. Children learn written language through active engagement with their
world. They interact socially with adults in writing and reading situations;
they explore print on their own, and they profit from modeling of literacy
by significant adults, particularly their parents.
Chapter 2: Literature Review 30 6. Although children’s learning about literacy can be described in terms of
generalised stages, children pass through these stages in a variety of ways
at different ages. Any attempts to ‘scope and sequence’ instruction should
take this developmental variation into account. (Teale & Sulzby, 1986b,
p. xviii)
Defining emergent literacy remains a difficult task as the term covers a broad spectrum of epistemological and methodological stances and is used inconsistently. “Historically, then, the term emergent literacy can be seen as implying a broad theoretical stance about literacy learning (developmental and constructivist), an age group (birth to age 5-6 years), and a focus on informal learning in holistic activities at home, preschool or kindergarten” (Yaden, Rowe,
& MacGillivray, 2000, p. 426). This definition was contentious in aligning the theory with an existing psychological perspective with allegiances to both
Piaget’s and Vygotsky’s theories. These two psychological perspectives are compatible in some respects, but also demonstrate differences relating to cognitive development (Kuhn, 1997).
Emergent literacy theorists have drawn on Piagetian developmental theory and also on Vygotsky’s theory of language development as a social process. Piaget proposed that children construct knowledge as they interact within the environment. Children assimilate experiences from the environment then accommodate them within their current understandings (Phillips, 1981).
Vygotsky distinguishes between measured development and the child’s ongoing development as the “zone of proximal development … as the distance between
Chapter 2: Literature Review 31 the actual developmental level as determined by independent problem solving and the level of potential development as determined through problem solving under adult guidance or in collaboration with more capable peers” (Vygotsky,
1978, p.86). The child is perceived as an active participant in learning and immersion in print-rich environments is recommended. Lastly, those who support emergent literacy theory acknowledge that children develop awareness of print and explicit knowledge and understanding about written language prior to starting school (Labbo & Teale, 1997). Strong support for the theories of
Vygotsky continue with the Social Constructivist Theory.
2.2.6 SOCIAL CONSTRUCTIVIST THEORY
While a social constructivist theory is similar to emergent theory in some respects, there is divergence at significant points. Both perspectives recognise children as active learners and that learning to be literate begins before formal schooling. It is recognised that children learn best when immersed in an environment rich in print. Both theories reject any behaviourist notion of reading readiness. However the two perspectives differ in that emergent literacy draws on cognitive developmental psychology while the social constructivist perspective draws on sociolinguistics and cultural anthropology (Crawford, 1995).
Social constructivist theory is aligned to Vygotsky for whom language leads development. Social constructivists reject emergent literacy theory as they deny stages of literacy exist even though emergent literacy theorists adopt a broad view in relation to pathways of development (Labbo & Teale, 1997). Terms such as ‘literacy acquisition’ are rejected as social constructivists hold the belief that
Chapter 2: Literature Review 32 children do not acquire literacy, but make sense of a complex set of signs and symbols in conjunction with more capable adults to make meaning (Harste,
Woodward & Burke, 1984). Five key assumptions described by Crawford (1995) characterise the social constructivist perspective and these have been summarised from Harste, Woodward & Burke (1984) & Vygotsky (1978).
• Language and literacy are socially constructed;
• Language and literacy are culturally specific;
• There is no set of universal, invariant developmental stages;
• Literacy is based on the intent to make sense of social events;
• Young readers and writers engage in the same types of literacy processes,
though at a less sophisticated level, as those engaged in by older children
and adults. (Crawford, 1995, p. 80)
2.2.7 CRITICAL THEORY
Following the development of a social constructivist theory, a critical stance with respect to literacy emerged with researchers such as (Freire, 1970, 1973, 1983,
1985), (Gilbert, 1989, 1993) and (Lankshear, 1994). This theoretical perspective is now described.
Critical theory builds on the social constructivist perspective and extends beyond it. The two perspectives are similar in that there is agreement that learners are active participants, language interactions are not neutral and these occur in specific cultural and social contexts. The difference occurs within a critical perspective as it considers historical and sociopolitical agendas that can affect language interactions and texts. Levels of power within all contexts are
Chapter 2: Literature Review 33 acknowledged and recognised as not being equal, with the needs of the dominant culture being more readily accepted (Freire, 1970). From an educational perspective it is recognised that children come to school from different cultural backgrounds and they also bring different home-based Discourses with them.
According to Gee (2003), these Discourses are “ways of coordinating and integrating words, signs, acts, values, thoughts, beliefs, attitudes and social identities as well as gestures, glances, body positions, objects and settings” (p. 5).
Critical theories of literacy derive from “critical social theory and its interest in matters of class, gender and ethnicity” (Morgan, 1997, p. 1). A view is held that within the world there is an ongoing struggle to gain knowledge, power and material goods. Some within the world are more privileged and succeed with the struggle, while others are marginalised and continue to struggle. The notion underpinning critical literacy is that since assumptions are ideologically and historically constructed, they also can be reconstructed (Morgan, 1997).
Notions of critical literacy are emerging, and how it is defined in the literature varies. Those who advocate using critical literacy propose that critical literacy varies depending on the questions asked (Comber, 1993). Three guiding principles provide for a range of critical literacy practices and these include engaging children as researchers of language, assisting children to respect minority cultures and questioning and problematising everyday and school texts.
There does not appear to be a single “orthodoxy of critical literacy” (Lankshear,
1994, p. 4) but “text, literacy as social practice and discourse” (Green, 2001, p.8) appear to remain key constituents.
Chapter 2: Literature Review 34
Critical literacy includes “…an awareness of how, why and in whose interests particular texts might work” (Luke & Freebody, 1997, p. 218). When examining texts from a critical perspective, readers are encouraged to respond to texts from alternative perspectives, to examine the author’s point of view and how various groups or individuals may be marginalised or left out of the text (Education
Queensland, 2000b; Healy, 1998; Wignell, 1998). A common strategy that enhances critical literacy is to juxtapose texts and read them against each other in order to examine deeper meanings and alternative perspectives. Texts can be studied at the lexico-grammatical level in order to explore an author’s choice of words and clause construction to develop particular meanings in texts (Luke &
Freebody, 1997). Alternatively texts may be studied from a socio-political perspective where cultural values and practices are examined and questioned.
Teachers also need to examine how and why certain texts are selected, what practices are used and how these practices position students to think and act in particular ways. Critical literacy occurs only when children have the opportunity to engage in real literacy encounters and respond to and create texts that require real engagement. Practical examples of critical literacy include:
• Interrogating a range of texts in class;
• Questioning everyday texts at school;
• Exploring identity, using film as the medium. (Comber, 2002, p. 4-16)
Chapter 2: Literature Review 35 2.3 CURRENT LITERACY POLICIES AND RESEARCH
Global, industrial, technological and economic changes are constantly impacting on literacy practices around the world. These changes must be continually monitored to ensure literacy practices in schools are keeping pace and preparing young learners for an ever-changing world. Australian education policy is influenced by and can exert influence on policy in other English speaking countries. A brief look at current literacy policies, major research and reviews conducted in the developed world since 1990 allows for comparison with
Australian policy and literacy practices in schools. This comparison of literacy policy, research and practices in Australia, United States, United Kingdom and
New Zealand situates the study of Beginning Literacy described in this thesis within National and International contexts. Recent reports and policy within the
State of Queensland will also be examined to provide a description of literacy priorities within the home State and situate the study at a local level. A brief examination of policies, reports and research for each of the above countries is now presented, in chronological order.
2.3.1 CURRENT LITERACY PRACTICES IN PARTS OF THE
DEVELOPED WORLD
2.3.1.1 Australia
Public policy relating to language and literacy in Australia at the Commonwealth level commenced in 1987 with the National Policy on Languages (LoBianco,
1987). Under this policy, language and literacy initiatives received a co-ordinated approach. Funding and programs for Indigenous languages, Asian languages,
Chapter 2: Literature Review 36 English as a second language and literacy were ensured (Freebody & Gilbert,
1999).
Policy, a research focus and practices in schools have changed since the introduction of the National Policy on Languages. These changes are reflected in the interplay noted among readers, texts and cultural and economic contexts.
Prior to the late 1980s English literacy practices in schools had centered around the study of classical and contemporary literature. In 1994 A Statement on
English for Australian Schools (Curriculum Corporation, 1994) was published and urged educators to include a range of literature, everyday texts and mass media texts for study in schools (Freebody & Gilbert, 1999).
Calls for greater accountability in Australian schools have been noted in the popular press as complaints about levels of literacy achievements and subsequent consequences of literacy failure have seemingly increased. Some have argued that these complaints are somewhat unfounded, as “according to UNESCO surveys, New Zealand and Australia are almost completely literate, with estimated adult rates of about 99 percent” (Freebody, 1999, p. 442). A call for national data of children’s progress in literacy continues to be voiced. Key policy and research reports in Australia of the last decade are now examined.
Australia’s Language: The Australian Language and Literacy Policy 1991
In 1991 Australia’s Language: The Australian Language and Literacy Policy was published. This document revealed “about 1 million people in all, or up to
10% of the Australian population, do not possess effective English literacy skills, and this includes many who speak English as their first language” (Department
Chapter 2: Literature Review 37 of Employment, Education and Training, 1991, p. iii). Four National Goals were included in the policy and these related to developing and maintaining effective
English literacy, learning languages other than English, maintaining Aboriginal and Torres Strait Islander languages and expanding language services within
Australia.
The period of children’s beginning literacy was prioritised and profiling literacy development in Years 3, 6 and 9 was recommended. No specific teaching strategies or theoretical positions were advocated, but a high priority was placed on “nationally consistent guidelines” (Department of Employment Education and
Training, 1991, p. 6). These allowed for authentic assessment of children’s literacy skills to be undertaken. This policy also saw the commencement of an emphasis on literacy in the early years.
Shaping the Future 1994
Within the State of Queensland a major review of curriculum commenced in
1992. The final report, Shaping the Future, influenced curriculum in Queensland schools. Wiltshire, McMeniman and Tolhurst conducted the review. The report was published in three volumes and a total of 105 recommendations listed within
11 categories were made (Wiltshire, McMeniman, & Tolhurst, 1994). The
Queensland State Government prioritised nine recommendations and consulted widely to develop a strategic implementation plan that commenced in 1995.
Actioning the recommendations significantly increased the emphasis on literacy throughout all years of schooling and placed a particular emphasis on the early years. Recommendations specifically relating to early literacy included a call for
Chapter 2: Literature Review 38 detailed assessment of literacy in Year 2, with a more flexible approach being advocated in the first three years of schooling. The Year 2 Diagnostic Net was devised using the Western Australian First Steps Developmental Continua for
Reading and Writing as tools for monitoring children’s long-term development.
The process included monitoring children’s reading and writing development by using the continua and incorporating running records and analysing children’s written texts for those identified as experiencing reading and writing difficulties
(Department of Education, Queensland, 1995; Education Department of Western
Australia, 1994a; Education Department of Western Australia, 1994c). Statewide testing for literacy and numeracy was introduced to Years 4 and 6 and later changed to Years 3, 5 and 7. A second literacy initiative in the early years was the introduction of Reading Recovery (Clay, 1985) into Queensland State schools. Reading Recovery, devised by Clay, is an early intervention process for children who struggle with learning to read in the early years. The program involved withdrawing children from their classes for one-on-one literacy instruction conducted by trained teachers.
Mapping Literacy Achievement 1992- 1994
In 1992 an Australian report, The Literacy Challenge: Strategies for Early
Intervention for Literacy and Learning for Australian Children was published.
This report of the House of Representatives Standing Committee on Employment
Education and Training reported a lack of National data on the literacy achievements of Australian children. While most States had initiatives in place to monitor and measure children’s literacy progress, different methodologies for data collection across the States, made the collation of National data impossible
(House of Representatives Standing Committee on Employment, 1992). A close
Chapter 2: Literature Review 39 link between low levels of literacy and poverty for the most disadvantaged families in Australia was noted in a report, Australia’s Literacy Challenge: The importance of breaking the poverty cycle for Australia’s disadvantaged families
(Orr, 1994). Both of these reports influenced an initiative to gather National literacy data for Australian children. In May 1994 a White Paper on employment,
Working Nation, Policies and Programs, prompted the Commonwealth
Government to allocate $3 million to collect National data on the literacy achievements of Australian children (Commonwealth of Australia, 1994).
Mapping the literacy achievements of Australian children included sampling
Reading, Writing, Speaking, Listening and Viewing for children in Year 3 and
Year 5. The project was a complex task and involved setting up national membership of a Steering Committee, a Management Committee and five sub- committees (Masters & Forster, 1997). The methodology extended beyond implementing common tasks for measuring students’ achievements and included teacher judgement and ways of enhancing professional skills of participating teachers.
National Literacy and Numeracy Goal 1997
In Australia in March 1997, Commonwealth, State and Territory Ministers agreed to a national literacy and numeracy goal “That every child leaving primary school should be numerate, and be able to read, write and spell at an appropriate level”. There was also agreement to the sub-goal, “That every child commencing school from 1998 will achieve a minimum acceptable literacy and numeracy standard within four years” (Department of Employment, Education,
Chapter 2: Literature Review 40 Training and Youth Affairs, 1998, p. 5). The goal and sub-goal were inclusive of all children, but recognised that a small percentage of students have severe educational difficulties and may not achieve the stated goal.
Literacy for All: The Challenge for Australian Schools 1998
In 1998 the Department of Employment, Education, Training and Youth Affairs
(DEETYA) published Literacy for All: The Challenge for Australian Schools and this is the current literacy policy guiding funding, research and literacy practices in schools throughout Australia. Government and non-government authorities receive funding associated with the National Literacy and Numeracy Plan and this funding is tied to a demonstration of outcomes. Within the National Plan, literacy in the early years features prominently. Dimensions of the emphasis on the early years include improving equity and catering to diversity. Critical factors relating to the acquisition of literacy in the early years include:
• The central importance of literacy in the early years;
• Recognition that children who fail to learn basic skills in reading, writing,
speaking and listening by the end of Year 3 can be disadvantaged for life;
• Importance of home literacy practices which support literacy
development in the pre-school and early years, such as early exposure to
print, especially stories and a supportive family environment;
• Significance of parental involvement in the early years of schooling and
family literacy programmes;
• Need for teachers in the early years to have an extensive repertoire of
effective teaching and intervention strategies;
• Impact of attendance and participation;
Chapter 2: Literature Review 41 • Need for adequate school time to be devoted to literacy teaching.
(Department of Employment, Education, Training and Youth Affairs,
1998, p. 10)
The early identification of literacy difficulties and the provision of early intervention became the focus throughout Australia. All State and Territory
Education ministers agreed to participate in the formulation of National benchmarks or standards for Year 3, 5, 7, and 9 in order to report outcomes for literacy and numeracy at a National level (Department of Employment,
Education, Training and Youth Affairs, 1998). Thus, this study of how young children develop literacy capabilities in the first year of school is timely and in line with National literacy priorities. The research contributes to the field by examining child, home and school influences in the prior-to-school period with a view to predicting literacy achievement in school.
Literate Futures 2000
In 2000 in the State of Queensland, a Literacy review was commissioned to examine literacy programs, practices and resources and to establish a futures- oriented view of literacy for Queensland State schools. Luke, Freebody and Land conducted the review. The report, Literate Futures: Report of the Literacy
Review for Queensland State Schools, published four priority action areas including:
• Student diversity;
• Whole-school programs and community partnerships;
• Teaching of reading;
Chapter 2: Literature Review 42 • Future literacies. (Education Queensland, 2000a, p. 65)
School employing authorities in the State of Queensland are currently responding to the priorities outlined in Literate Futures. The teaching of reading with an emphasis on the early years has been prioritised.
Literacy is defined within this report as “the flexible and sustainable mastery of a repertoire of practices with the texts of traditional and new communications technologies via spoken language, print, and multimedia” (Education
Queensland, 2000a, p. 9). In order for teachers to adjust their classroom practices in line with this definition “repertoires of practice” (p. 11) are required.
Following the lead of several other Australian States the “four resources framework” (Freebody & Luke, 1990; Luke & Freebody, 1997) was recommended for adoption.
Four broad roles were recommended for readers within a repertoire of practices and these include:
• Code Breaker: The practices required to ‘crack’ the codes and systems
of written and spoken and visual images;
• Meaning Maker: The practices required to build and construct cultural
meanings from texts;
• Text User: The practices required to use texts effectively in everyday,
face-to-face situations;
• Text Analyst: The practices required to analyse, critique and second-
guess texts. (Education Queensland, 2000a, p. 11-12)
Chapter 2: Literature Review 43
2.3.1.2 United States
Within the United States, literacy practices in schools also have been influenced by major reviews and reports and these are now outlined.
Beginning to Read: Thinking and Learning about Print 1990
Literacy policies and practices in the United States over the last decade developed first in response to the publication of the report Beginning to Read:
Thinking and Learning about Print (Adams, 1990). Adams, author of the report, conducted the study in conjunction with the Reading Research and Education
Center, University of Illinois. The report required “a review of all aspects of phonics and early reading instruction” (Adams, 1990, p. v).
This seminal report had an effect on literacy practices at a time when many teachers were currently following a Whole Language approach. Adams concluded that the debate concerning ‘code emphasis’ or ‘meaning emphasis’ was irrelevant with arguments about which instructional activities are ‘key’ and which are ‘support’ activities was not adding to the important issue of helping children learn to be proficient readers who comprehend as they read. According to Adams reading is complex and, “all of its component knowledge and skills must work together within a single integrated and interdependent system”
(Adams, 1990, p. 423). Adams proclaimed that there is no one method for teaching reading, but that teachers must consider the learners, the context, the resources and the compatibility and interrelatedness of all of these elements when planning for the teaching of reading. Adams put word recognition at the heart of reading.
Chapter 2: Literature Review 44 Before you pick up this book, you should understand fully that the topic
at issue is that of reading words. Before you put this book down,
however, you should understand fully that the ability to read words,
quickly, accurately and effortlessly, is critical to skilful reading
comprehension – in the obvious ways and in a number of more subtle
ones. (Adams, 1990, p. 3)
Early explicit phonics instruction, while using meaningful texts, was advocated by Adams so children develop proficient word recognition skills and simultaneously learn to comprehend the meaning of texts. When examining research on pre-readers, Adams reported findings that knowing letter names best predicted a child’s reading achievement (Bond & Dykstra, 1967; Chall, 1967).
Many debates followed the reporting of this result, but a number of studies confirmed the finding (Meuhl & DiNello, 1976; Richek, 1977-1978; Stevenson,
Parker, Wilkinson, Hegion, & Fish, 1979). However, merely teaching children the names of letters did not have the same predictable effect on learning to read.
Adams noted, “By implication we are left with the conclusion that the likelihood that a child will succeed in the first grade depends, most of all, on how much she or he has already learned about reading before getting there” (Adams, 1990, p.
8). Finally Adams concluded that skilled readers displayed “speed, accuracy and effortlessness” when responding to print (Adams, 1990, p. 8). She also concluded that orthographic, phonological, semantic and syntactic cues were utilised in complex ways as readers responded to and comprehended the meaning of texts.
Chapter 2: Literature Review 45 Preventing Reading Difficulties in Young Children 1998
In the United States a second influential literacy report was published. The report, Preventing Reading Difficulties in Young Children, (1998) edited by
Snow, Burns and Griffin impacted upon literacy policy and instruction in the
United States. The report arose from concerns that a large number of American children could not read sufficiently well enough to cope with the literacy demands of the modern world. Three stumbling blocks were identified as preventing children from becoming skilled readers. First, being able to understand and use the alphabetic code, second, transferring the ability of comprehending oral language in speech to the comprehension of written texts and finally maintaining interest in and motivation for reading (Snow, Burns &
Griffin, 1998).
One of the key findings emanating from this report was that children who enter school with little prior knowledge, understanding and skills relating to written texts are at far greater risk of failure than those with rich literacy experiences in the prior-to-school period. Skills that are deemed most relevant include “general verbal abilities, the ability to attend to the sounds of language as distinct from its meaning, familiarity with the basic purposes and mechanisms of reading and letter knowledge” (Snow, Burns & Griffin, 1998, p. 5).
While the report was generally regarded as wide-ranging and even-handed in its summary of research, Pearson (1999) criticised the exclusion of descriptive and quasi-experimental research. The generalisability of results, particularly for linguistic and culturally different communities, was called into question.
Chapter 2: Literature Review 46 Pearson’s criticism was pertinent given that studies designed to investigate communities more closely were not included in the review.
National Reading Panel: Teaching Children to Read 2000
In 1997 United States, Congress asked the Director of the National Health and
Human Development (NICHD), in consultation with the Secretary of Education, to convene a National Panel to assess the effectiveness of different approaches used for the teaching of reading. The panel spent more than two years reviewing research and consulting throughout the United States and in the year 2000 the report, National Reading Panel: Teaching Children to Read, was published
(National Institute of Child Health, 2000a, 2000b).
Following public hearings with teachers, parents and students, the National
Reading Panel adopted five major topics to be studied.
1. Alphabetics
2. Fluency
3. Comprehension
• Vocabulary instruction
• Text comprehension instruction
• Teacher preparation and comprehension strategies instruction
4. Teacher Education and Reading Instruction
5. Computer Technology and Reading Instruction. (National Institute of
Child Health, 2000a, Adoption of Topics To Be Studied, ¶ 1)
Findings for each of the major issues are summarised below:
Chapter 2: Literature Review 47 Alphabetics
An integrated approach to the teaching of reading was recommended with due attention to be paid to phonemic awareness training and phonics instruction.
(National Institute of Child Health, 2000a)
Fluency
Fluent readers are able to read orally with speed, accuracy and proper expression and it is a critical skill for reading comprehension. (National Institute of Child
Health, 2000a)
Comprehension
Recommendations for comprehension were presented in three sub-sections within the report. These were vocabulary, text comprehension instruction and teacher preparation and comprehension strategies instruction. Both explicit and implicit instruction of vocabulary was recommended to enhance students’ reading comprehension. (National Institute of Child Health, 2000a)
Teacher Education and Reading Instruction
A total of 32 studies met the methodological requirements of the National
Reading Panel and consisted of 11 pre-service and 21 in-service teacher education studies. The panel raised many unanswered questions following the review of these studies including:
1. What is the optimal combination of pre-service and in-service education,
and what are the effects of preservice experience on in-service
performance?
Chapter 2: Literature Review 48 2. What are the best ways to assess the effectiveness of teacher education
and professional development?
3. How can teachers be optimally supported over the long term to ensure
sustained implementation of new methods and to ensure student
achievement?
Thus this section of the report did not conclude with many firm recommendations, but raised lots of questions that could be the focus for investigations in the future. (National Institute of Child Health, 2000b, Teacher
Education and Reading Instruction, Findings and Determinations, ¶ 3)
Computer Technology and Reading Instruction
As this was a new field of study, just 21 studies met the methodological requirements of the National Reading Panel. The research showed:
1. It is possible to use computer technology for reading instruction;
2. The use of hypertext may be an instructional advantage;
3. Linking speech to computer-presented text may be a promising use of
technology in reading instruction. (National Institute of Child Health, 2000b,
Findings and Determinations, ¶ 1 & 2)
The report, National Reading Panel: Teaching Children to Read, received widespread publicity and support particularly from political arenas. There have been critics however who have expressed concerns associated with the study itself and the reporting of findings. Garan (2001) published a critique of the
National Reading Panel subgroup report relating to Alphabetics. Briefly, Garan
Chapter 2: Literature Review 49 raised a number of issues relating to the conduct of the study as well as the accuracy, consistency and conclusions drawn in the report.
Shanahan and Ehri, both members of the National Reading Panel, published responses to the critique and defended the report findings. However, some acknowledgement was given to criticisms of the discrepancies found between the report and the published Summary.
No Child Left Behind
In 2002, No Child Left Behind Act became law in the United States. This new law represented new reforms for Elementary and Secondary education and has four underlying principles. The principles included stronger accountability for results, flexibility for states and communities, concentrating resources on proven education methods and creating more choice for parents (United States
Department of Education, 2002a, 2002b, 2002c, 2002d, 2002e).
Both Democrat and Republican parties approved the new reforms for education declaring that the effectiveness of schools be measured in terms of every child learning. Despite increased funding to improve educational outcomes for disadvantaged children in the United States the following statistics remain.
• Only 32 percent of fourth graders can read skillfully at grade level;
• Most of the 68 percent who can’t read are minority children and those
who live in poverty. (United States Department of Education, 2002e, ¶ 1)
Chapter 2: Literature Review 50 Local solutions to local problems were encouraged and test data identified strengths and weaknesses in the system. Parents were encouraged to become proactive in their child’s education and monitor progress being made by schools.
Schools that do not show improvement in student learning were described as
“failing schools” and parents can access district funds to transport their child to a
“better school” or demand “supplemental or after-school services” for their children (United States Department of Education, 2002c, ¶ 5).
Reading First, a $900 million grant system, promoted the use of scientifically- based reading research findings to provide high quality reading instruction for grades K-3. This grant scheme sought to improve the statistic of 85 percent of fourth-graders in high-poverty schools scoring below the ‘proficient’ reading level (United States Department of Education, 2002a). United States Secretary of
Education, Paige endorsed the National Reading Panel Report, Teaching
Children to Read, particularly the endorcement of explicit teaching of phonics.
(United States Department of Education, 2002d)
While many educators in the United States have not welcomed strong government involvement in the education of children, some observers noted that schools have brought this upon themselves by not acting sufficiently well enough to the 1994 federal legislation. Demands for annual testing may seem like
‘overkill’ but some observers noted that increased accountability should improve educational outcomes for all including those who are educationally most disadvantaged (Lewis, 2001).
Chapter 2: Literature Review 51 2.3.1.3 United Kingdom
In the United Kingdom an examination of literacy standards also prompted government action and the National Literacy Strategy was enacted in 1997.
National Literacy Strategy 1997
In 1996 ‘The Literacy Taskforce’ led by Barber was established by the Labor
Party. The terms of reference for the taskforce included developing a strategy to substantially raise literacy standards in primary schools. A report, A Reading
Revolution – How We Can Help Every Child to Read Well, was published in
February 1997. This report recognised that ‘standards of literacy have not changed significantly between the end of the second world war and the early
1990s and that there is wide variation in performance among primary schools’
(Department for Education and Employment, 1997). Results of National testing showed that in 1996 just 57% of 11 year olds reached the standard expected for their age. As a consequence of the report and the published literacy results of 11 year-old children, the National Literacy Strategy was launched in September
1997.
Within the National Literacy Strategy a Framework for Teaching defined teaching objectives for Reception to Year 6 to “enable pupils to become fully literate” (Department for Education and Skills, 1998). This framework included a
‘Literacy Hour’ and detailed guidelines for the implementation of this initiative were sent to schools in 1998. An emphasis was placed on the importance of high quality school leadership to manage and monitor the implementation of the
National Literacy Strategy in order to raise literacy standards. Children’s
Chapter 2: Literature Review 52 progress was described in Key Stages with national literacy tests occurring in years 2, 6 and 9.
Within the Teaching Framework, guidelines defined literacy, reading, writing and student expectations. For the teaching of reading, an emphasis was placed on ensuring word level strategies were made explicit by teachers so that students learnt to distinguish between different sounds in words. This emphasis was put in place in order to improve spelling and reading results within and beyond the early years. In relation to writing, an emphasis was placed on ensuring students learn to write different genres while writing for particular audiences and using the writing process that is modelled by their teachers (Department for Education and Skills, 1998).
The National Literacy Strategy is still current in the United Kingdom, and the
Office of Standards in Education (OFSTED) provides an annual report of progress. In November 2002 data were reported that projected outcomes had not been fully realised. While progress has been made it has not continued consistently since 1998. “Fewer than 4% of primary schools in England have made progress every year under the National Literacy Strategy” (Office of
Standards in Education, 2002). Standards in English have improved from 64% of
11 year olds achieving the required standards in 1998 to 75% in the year 2000.
“Analysis of the 300 representative schools that OFSTED are tracking show more than 285 schools have had a year in which standards have stalled or even fell”. The teaching of phonics in the early years has been criticised with “an
Chapter 2: Literature Review 53 estimated 200,000 seven year olds not reaching the expected standard in Key
Stage 1” (Office of Standards in Education, 2002).
In the United Kingdom the National Literacy Strategy is ongoing with the current
Labor Government trying to achieve a projected improvement in literacy standards at a National level. In relation to the Teaching Framework an emphasis has been placed on The Literacy Hour where all teachers are expected to devote a full hour each day to teaching and learning associated with the development of literacy skills. In the Early Years a strong emphasis has been placed on including the explicit teaching of ‘word level’ strategies particularly phonics to assist children to learn the relationship between phonemes and graphemes in English and improve spelling skills.
2.3.1.4 New Zealand
In New Zealand there also has been a call for National data relating to literacy standards, so accountability measures are more transparent (Reid, 1994).
Report of the Literacy Taskforce 1999
In 1998 the New Zealand government established a Literacy Taskforce to provide advice on a range of theoretical and academic issues. The brief for the taskforce was to assist the government in reaching the goal that “by 2005 every child turning nine will be able to read, write and do maths for success” (New
Zealand Ministry of Education, 2000, p.1). Successful reading and writing were defined as being identified across multiple text types and included comprehension, accuracy, fluency and self-motivation. Recommendations were provided for general school settings as well as Kura kaupapa Maori and Maori
Chapter 2: Literature Review 54 medium settings. The taskforce recommended using a range of teaching approaches including whole language and phonics. Families needed to be included in children’s education in order to address the large disparity of literacy achievement between various groups of children, especially those with Maori and Pacific Islander backgrounds.
Within the report of the Literacy Taskforce it was noted that reliable National literacy data were not available. New Zealand children participated in the
International Evaluation of Achievement (IEA) in 1970 and 1990 but “the picture is murky” (Nicholson, 2000, p. 16). In the mid 1990s the New Zealand
Government initiated the National Education Monitoring Project (NEMP) and light sampling was used to monitor children’s progress across a range of curriculum areas including reading. A call for more comprehensive data remains
(Nicholson, 2000).
Reading Recovery processes identify approximately 20% of children in New
Zealand who are making relatively limited progress after one year of schooling and these children receive individual focussed instruction. Although the
Taskforce recommended maintaining the use of Reading Recovery, it raised several issues about the implementation and monitoring of its educational outcomes. Only two independent research studies of Reading Recovery in New
Zealand have been conducted and the Taskforce called for further research particularly when the program is used with children who have Maori and Pacific
Islander backgrounds (New Zealand Ministry of Education, 1999).
Chapter 2: Literature Review 55 A research project, Picking up the Pace, showed improved literacy outcomes for children following a concentrated professional development program in literacy instruction for early childhood and new entrant teachers (New Zealand Ministry of Education, 2002). The project aimed to enhance literacy programs of early childhood and primary teachers and to improve the links between the two educational settings. The study showed that children who seemingly are at high risk for literacy difficulties achieved if given the right opportunities and instruction. The study showed that the “gap” in achievement should not be regarded as “inevitable or unbridgeable” (New Zealand Ministry of Education,
2002, p. 6).
2.3.2 LITERACY PRACTICES IN THE ENGLISH-SPEAKING WORLD:
SIMILARITIES AND DIFFERENCES
An examination of literacy policy, research and practices in four English- speaking nations has revealed similarities and differences in mandating literacy policy. There is a common call for National data on literacy outcomes to gauge
National standards. Australia and the United Kingdom have such processes in place and the United States also is moving towards such data gathering within the terms of the new law, No Child Left Behind (United States Department of
Education, 2002b). Recommendations have been made to the New Zealand government, but as yet plans for gathering comprehensive data are not in place
(New Zealand Ministry of Education, 1999).
Mandating literacy practices in the United Kingdom, through its National
Literacy Strategy (Department for Education and Employment, 1997), has put in
Chapter 2: Literature Review 56 place common practices in the early years. These practices include the ‘literacy hour’ and the teaching of phonics with children’s progress being monitored using key stages of development. The United States government is currently only willing to fund teaching initiatives that reflect scientifically-based reading research findings, so particular practices such as the teaching of phonics are being mandated. In New Zealand and Australia while recommendations for practice have been made, no obligations to include particular practices are in place. However, in Australia some funding is tied to achieving outcomes linked to Literacy for All: The Challenge for Australian Schools (Department of
Employment, Education, Training and Youth Affairs, 1998). Thus, while recommendations have been made in Australia and New Zealand, mandated practices are not currently in place.
In all four nations where policies have been examined there is a concern for the number of children who continue to fail to meet adequate standards of proficiency in reading and writing. These children, most commonly include some, but not all, who are socio-economically disadvantaged, have English as a second language, are from culturally diverse backgrounds, live in remote or isolated areas, have sensory, physical, emotional or intellectual impairments and are male (Alloway, Freebody, Gilbert, & Muspratt, 2002; Department for
Education and Employment, 1997; Education Queensland, 2000a; Freebody,
Ludwig, & Gunn, 1995; Lingard, Martino, Mills, & Bahr, 2002; United States
Department of Education, 2002b).
Chapter 2: Literature Review 57 This study is timely and fits in with the literacy agenda of many English- speaking nations as it seeks to extend current knowledge of how literacy capabilities of young children develop during the first year of schooling and seeks to learn more about predicting patterns of early literacy development. This knowledge contributes to educators’ understandings about prior-to-school literacy knowledge and provides valuable information relating to catering for children who enter school with a diverse range of literacy experiences.
2.4 RESEARCH ON LITERACY IN THE EARLY YEARS
Studying beginning literacy development in the early years has been the focus for numerous research studies. Most of these studies focused on young children during the first three years of schooling, but over the last three decades the focus has also included the period immediately prior to commencing school.
2.4.1 EMERGENT AND EARLY LITERACY DEVELOPMENT
The process of becoming literate in current times is not seen to commence when a child enters school. Researchers over the past three decades (Clay, 1966,
1979a, 1991; Hall, 1987; McNaughton, 1995; Teale & Sulzby, 1986a;
Whitehurst & Lonigan, 2001; Yaden, Rowe, & MacGillivray, 1999) have acknowledged that young children begin the process of becoming literate prior to commencing school. These children are usually not ‘taught’ during this period, but actively participate as “hypothesis-testers” or “constructors of language”
(Teale & Sulzby, 1986a, p. xv). Young children actively engage in making sense of complex patterns in oral and written language in order to gain meaning from texts. Clay, used the term, Emergent Literacy, in 1967 following the publication of her doctoral dissertation. Historically the term implies a “broad theoretical
Chapter 2: Literature Review 58 stance about literacy learning (developmental and constructivist), an age group
(birth to age 5-6) and a focus on informal learning in holistic activities at home, preschool or kindergarten” (Yaden et al., 1999, p. 2).
Clay was a “pioneer in examining children’s reading and writing in the light of language acquisition research” (Teale & Sulzby, 1986a, p. xv). Prior to this period ‘reading readiness’ was a popular term that was linked to maturational development. Clay’s longitudinal study of 100 five-year-old children during the first year of school prompted her to propose that waiting for a child to mature prior to introducing the child to texts was unfounded and that the young child was in fact disadvantaged if texts were withheld. When a child enters school “he has a private frame of reference which stems from his past experiences” (Clay,
1979a, p. 15) and if those experiences do not involve interactions with a range of texts, then the child is disadvantaged. Research and publications by Clay have impacted greatly on the study described in this dissertation and relevant work relating to early literacy is now examined.
2.4.1.1 The Influence of Clay
Clay, “one of the most remarkable educators and scholars of the twentieth century” (Anderson, 1999, p. vii) was born in 1926 in Wellington, New Zealand.
Her work as an educator, psychologist, researcher and scholar has contributed greatly to worldwide understanding of how young children become literate.
Many notable contributions can be listed, but her ongoing ability to stand back from her own research and examine it from a new perspective has added substantially to knowledge about pathways young children may take as they
Chapter 2: Literature Review 59 become literate. Also notable is Clay’s ability to maintain the perspective of a classroom teacher as she grappled with educational dilemmas relating to difficulties some children face as they strive to become literate.
Clay had worked as a teacher, psychologist and tertiary educator prior to completing her doctoral dissertation in 1966. It was the research associated with her dissertation that saw the beginning of a number of seminal publications, some of which are still popular today (Clay, 1972, 1985, 1991, 1993a, 1993b,
1998). Clay is well known for the early intervention program, Reading Recovery, a program “designed to reduce dramatically the number of children with reading and writing difficulties that persist throughout their schooling” (Clay, 1992, p.
22).
Clay’s first major research study was completed for her doctoral dissertation and involved studying the emergent reading behaviour of 100 young children during their first year of school. Data collected for the study included listening to each child read every week from a text he/she had been studying in class. As well as these data, a battery of 17 tests was administered and analysed three times during the project (Clay, 1982). The study described in this doctoral dissertation also examines the literacy development of more than 100 young children during a twelve-month period from the end of the preschool year to the end of Year one.
Data also were gathered three times from children during this year-long study.
Adjustments to performance measures were made in this study in order to cater for the children’s developing literacy skills. Within the current study, further data were gathered from parents and class teachers throughout the period of the study.
Chapter 2: Literature Review 60
Key findings that emanated from Clay’s first major research study included describing ways young readers integrate complex elements in order to become literate. “A good reader manipulates a network of language, spatial and visual perception cues and sorts these implicitly but efficiently, searching for dissonant relations and best-fit solutions” (Clay, 1967, p.30). A child gradually learns to co-ordinate contextual, syntactic and visual cues in order to commence reading.
Thus, the child learns to integrate personal life experiences, language competency and knowledge about visual symbols on the page in order to encode and comprehend the meaning in texts. During the early stages of development,
Clay argues, close observations by the class teacher are needed. Some children may place too much reliance on contextual and syntax cues and not enough on visual cues and this practice can have long-term consequences for young readers
(Clay, 1967). Clay found that some young readers may fail to utilise graphophonic cues adequately when reading and develop major difficulties with word recognition.
If just four elements of knowledge were gleaned from Clay’s work with young children they would include first, the way she forged an interactive relationship among research, theory and practice. Clay has not entered into debates about theories, research or teaching practices. She has “focused steadfastly on her evolving interests, the purposes of her research, and her belief in children’s ability to learn” (Jones & Smith-Burke, 1999, p. 282). Second, Clay advocated close observation and monitoring of child literacy behaviour during the early years. Information relating to methods of observation has been published and
Chapter 2: Literature Review 61 includes strategies for taking running records to monitor the accuracy of oral reading. The Concepts About Print test, devised by Clay, has been widely used to elicit children’s developing understandings about book-handling skills, print directionality, the alphabetic symbol system, written words and punctuation in the first year of schooling (Clay, 1993a).
Third, Clay advocated not laying blame on the child when literacy learning difficulties arise, but learning to “distinguish between experiential/instructional and cognitive deficits as primary causes of reading difficulties” (Vellutino &
Scanlon, 2001, p. 296). Lastly, educators should not wait for young children to gain “sudden insight” (Clay, 1979a, p. 13) and wait for time to rectify all literacy learning difficulties or slow starts. The following statement made by Clay provides a strong message for educators.
There is an unbounded optimism among teachers that children who are
late in starting will indeed catch up. Given time, something will happen!
A temporary backwardness will eventually be relieved by suitable
teaching and children may even grow out of it themselves! In particular,
there is a belief that the intelligent child who fails to learn to read will
catch up to his intelligent classmates once he has made a start. Do we
have any evidence of accelerated progress in late starters? There may be
isolated examples that support this hope, but correlations from a follow-
up study of 100 children two and three years after school entry lead me to
state rather dogmatically that where a child stood in relation to his age-
mates at the end of the first year at school was roughly where one could
expect to find him at 7.0 or 8.0. (Clay, 1979a, p. 13)
Chapter 2: Literature Review 62
Clay’s work has contributed to the design of the current study where a number of instruments for measuring children’s literacy achievements were utilised. Clay’s insights into literacy development in the early years have also been a source encouragement to pursue this knowledge further. Despite a vast body of research in this field, there are many unanswered questions. It is critical that educators pay close attention to providing literacy-related experiences in the prior-to-school period and educate parents about the need to communicate regularly and share texts with young children. Moreover, it is equally important that close teacher observation of literacy-related behaviours and regular monitoring of literacy development take place during the first year of schooling. Research suggests that this period is vital for literacy learning and the majority of children who fail to begin to develop early literacy skills during the first year of schooling face a long-term struggle (Clay, 1998; Scarborough, 2001).
2.4.1.2 Influences on Emergent and Early Literacy Development
The study of emergent and early literacy development has attracted much attention since the time of Clay’s longitudinal study. Researchers have focused attention on the range of influences on emergent and early literacy development
(Neuman & Dickinson, 2001). Cultural, socio-economic, home influences, children’s emerging skills and abilities as well as innate child attributes have all been studied. Innate child characteristics including physical, intellectual, sensory and socio-emotional and personal health-related factors all contribute to a child’s acquisition of literacy, but these are not examined within this dissertation.
Chapter 2: Literature Review 63 Much has been learnt particularly from longitudinal studies where learning environments and children’s developing skills and abilities have been examined using cross-time data. These studies have influenced thinking in relation to young children’s ‘readiness’ to become literate. While during past decades beliefs supported “waiting patiently on the sidelines until children bloom, untouched”, this is no longer the case as research has shown they are “more likely to wilt than bloom” (Watson, 1996, p. 166). So what evidence is there that young children begin the journey towards becoming literate before commencing school? What factors influence children’s skill development and what domains of knowledge can be acquired and under what conditions? As stated earlier in this chapter, more than 100,000 studies of reading have been published since 1996 alone, so studies reviewed in this chapter can represent only a selection from this body of research.
Longitudinal predictive studies of early literacy commencing in the prior-to- school period or at the beginning of Year 1, and continuing into the period of early schooling, provide a good place to begin an examination of influences on emergent and early literacy development. Searches of educational databases for journal publications, reports, handbooks of research and other texts revealed a total of 53 publications, representing 43 studies, of longitudinal studies of young children’s emergent and early literacy (see Appendix A). These studies dating from 1966 to 2002 include those with uni-dimensional or a multivariate focus.
Key themes found within the set of longitudinal studies with young children include studies that focus on:
• Early intervention;
Chapter 2: Literature Review 64 • Home environment;
• Young children’s developing literacy skills and abilities;
• Parent participation in children’s early literacy;
• Children’s oral language development;
• Young children’s motivation towards literacy;
• Children with special literacy learning needs;
• Instructional approaches to teaching literacy in the early years.
Aspects of some of these themes are included in the literature review, but a focused examination of each is not possible within the scope of this dissertation.
Influences on emergent and early literacy development are now examined.
Cultural, socio-economic and home influences on the acquisition of early literacy
Since the late 1980s ‘emergent literacy’ has gained popularity and the belief that literacy development begins long before children commence formal literacy instruction has gained wider acceptance (McNaughton, 1995; Strickland &
Morrow, 1989a; Teale & Sulzby, 1986b; Wells, 1986; Whitehurst & Lonigan,
2001). The ongoing support for emergent literacy has placed a greater emphasis on examining cultural, socio-economic and family factors that may influence children’s early literacy acquisition. Homes and family life as well as classrooms are contexts for literacy practices and the interactions and participants in each context “construct particular ways of acting, believing and valuing” (Cairney &
Ruge, 1997, p. 5). Both ethnographic, experimental and correlational studies have been reported with data being gathered in homes using observation of family interactions, parent interviews and written surveys as well as measures of
Chapter 2: Literature Review 65 young children’s developing language and literacy skills and knowledge.
Definitions of what constitutes home background or family literacy in absolute terms are unable to be clearly articulated because of the complex social, economic, cultural and personal factors that are involved in each household
(Purcell-Gates, 2000; Teale & Sulzby, 1986b). Most noteworthy is that “virtually unexplored by research is the issue of compatibility among the cultures of schools, homes, and family literacy programs” (Purcell-Gates, 2000, p. 866).
Families engage in everyday language and literacy-related practices (Burgess,
Hecht, & Lonigan, 2002; Evans, 1998) and provide models for young children as they “become expert members of the social and cultural groups to which the family belongs” (McNaughton, 1995, p. 17). Family practices include demonstrations of ways of using spoken and written language. Young children begin to learn about the purposes and practices for using language and this learning has an effect on literacy development in the future (Britto, 2001;
Dickinson & Tabors, 2001; McCarthey, 2000; Snow, Tabors, & Dickinson,
2001; Wells, 1985). Taylor (1983), who conducted an ethnographic study of white middle-class children who were successful readers and writers, described three conditions that assist young children to understand the role of print. These conditions include immersing children in print at home, exploring print during play and developing an understanding of how print is used for everyday purposes. Further statistical evidence relating to these conditions is needed. As an increasing number of children attend early childhood care and education settings prior to school there is a need to examine ways of embedding literacy practices into these environments as well (Dickinson & Sprague, 2001; Roskos &
Chapter 2: Literature Review 66 Neuman, 2001). Early literacy experiences cannot be thought as a single construct (LeFevre & Senechal, 1999) with activities such as shared storybook reading and explicit conversations about the alphabetic code contributing differently to children’s developing literacy (Evans, Shaw, & Bell, 2000).
Children from cultural backgrounds where English is not the first language, learn to be literate while facing different social and cultural dimensions within the home and school contexts (Dickinson & Tabors, 1991; Tett & Crowther, 1998).
Much has been learned from early literacy studies with children from other cultural backgrounds. Heath (1983) conducted ethnographic research in three communities and found that each community used language and literacy-related practices differently. Heath studied three communities in Piedmont, Carolina.
These included Roadville, a white working class community, Trackton, a black
African American working class community and Mainstream, middle-class townspeople of mixed African American and European American community.
Each community within the study used language in different ways and Heath drew implications relating to the children’s preparedness to enter school. Parents in Roadville provided books, toys and leisure activities for their children in the prior-to-school period, but did not develop close partnerships in learning with the school. Trackton parents believed it was the role of the school to educate children and they did not take an active role in preparing their children for school.
Mainstream parents on the other hand, took steps to help their children get ready for school and continued to support children’s learning at school (Heath, 1986).
Heath proposed that children from particular communities who may not have
Chapter 2: Literature Review 67 many opportunities to prepare for school, may find school language interactions a challenge. In later research, Heath found that middle-class mainstream families
“prepare their young children for the special ways of using language that the school rewards” (Heath, 1991, p. 19) and this often provides the groundwork for early literacy success.
Teale (1986), conducted an ethnographic enquiry into the relationship of home background and children’s literacy development with 24 children aged between 2 years and 6 months and 3 years and 6 months of age. The sample included 8
Anglo, 8 Black and 8 Mexican children with approximately equal numbers of females and males included. Data were collected by participant observers in the children’s homes where the focus related to the young child participating in regular home and literacy experiences. While the number of hours each child was observed varied across the sample a total of 1,400 hours was recorded (Teale,
1986). Results showed that all children participated in a range of literacy-related activities at home and Teale concluded “virtually all children in a literate society like ours have numerous experiences with written language before they ever get to school” (Teale, 1986, p. 192). These experiences take place within regular social activities of families within their own communities.
Disadvantaged families, or those living in poverty, often face challenges acquiring literacy. There are however differing circumstances and not all members of these families face difficulties learning to be literate. A study by
Taylor and Dorsey-Gaines (1988) with five low-income families whose children were successful at school, challenged the belief that the economically
Chapter 2: Literature Review 68 disadvantaged do not participate in literacy-related activities. Results showed these particular families used literacy in a range of situations in order to meet the demands of daily life. Similarly, Purcell-Gates (1996) conducted research in 20 low-income families and findings confirmed that these families exposed their children to a range of literacy materials and they showed concern for and interest in their children’s education. Britto (2001) in a study of 126 low-income African
American children and their families, reported that many dimensions of the home come together to provide “a complex tapestry of activities, experiences and opportunities” (p. 347) that promote literacy acquisition.
Studies have shown that children from low-income families and those whose first language is not English may be exposed to everyday literacy-related practices in the home. However, International, National and State data have established that these groups of children are at high risk of literacy failure (Children's Defense
Fund 1994; Education Queensland, 2000a; Gadsden, 1999; Masters & Forster,
1997; Purcell-Gates, 1994; Snow, Burns & Griffin, 1998). Bilingual children living in poverty face an even greater risk. These children need more than exposure to everyday texts in the home to ensure they experience success with literacy in the early years. Test results show many bilingual children living in poverty face educational learning difficulties stemming from poor literacy learning (Goldenberg, 2001; Tabors & Snow, 2001; Vernon-Feagans, Scheffner
Hammer, Miccio, & Manlove, 2001). Thus, while children may be exposed to print materials at home, researchers have found that children’s language development also plays a major role in preparing them for the school context
(Snow, Tabors & Dickinson, 2001).
Chapter 2: Literature Review 69
A longitudinal study by Wells in the United Kingdom investigated both the language and literacy development of young children in order to ascertain if
“differential educational attainment has specific linguistic antecedents” (Wells,
1985, p. 229). The study, conducted over ten years, commenced with a group of
128 children at 15 months of age. Language samples were collected at three- monthly intervals. The children had no known handicaps and all lived in English- speaking families. Thirty-two of the children were involved in the systematic investigation of the relationship between the uses of language in home and school. During the first phase of the study the children’s oral language development was charted to investigate the relationship between the acquisition of various linguistic systems and home learning environment.
The methodology employed to gather language interactions in the home involved the child wearing a radio microphone between the hours of 9am and 6pm. The equipment was programmed to record 24, ninety-second samples at approximately 20-minute intervals throughout the day. No observers were present while the samples were being collected, but later in the day the samples were re-played for parents who were asked to recall the location, activity and participants in each sample. While differences in the rate of language acquisition were noted, “by the time they entered school at five years of age all children studied had achieved a basic command of English and all communicated freely and effectively with people in their home environment” (Wells, 1985, p. 229).
Neither the differences between the children or between the parents during the
Chapter 2: Literature Review 70 prior-to-school period were related to children’s class of family background
(Wells, 1985).
Within the study conducted by Wells, a different set of results emerged when the children were tested during the first term of Year 1. Some children adapted more readily to school than others and this was shown through the children’s test results. Teachers’ perceptions of children’s ability showed a “highly significant relationship between the teachers’ rated ability and class of family background”
(Wells, 1985, p. 230). The early-school assessments were confirmed two years later when subsequent assessments were shown to have accurately predicted children’s achievements. Classroom observations revealed that some children found difficulty responding to the teacher in certain types of language interactions particularly when the children were asked to respond to decontextualised situations (e.g. responding to or describing a picture).
While these types of language interactions were not unfamiliar to the children in the home, the decontextualised nature of the activity at school was at times new for some children and was a source of challange. Similar findings occurred in the study, Everyday Literacy Practices in and out of Schools in Low Socio-economic
Urban Communities, where researchers described classroom language difficulties as ‘interactive trouble’ (Freebody, Ludwig & Gunn, 1995). Transcripts from literacy lessons showed children experiencing difficulty understanding the response being demanded by the teacher. Lesson transcripts also revealed how teachers’ talk, particularly that associated with shared book experience, was often hard to understand. Teachers tended to try to meet multiple purposes within any
Chapter 2: Literature Review 71 one lesson and talk associated with the lesson was mixed with talk relating to class behaviour management (Freebody, Ludwig & Gunn, 1995).
Wells (1985) also found that measures of literacy knowledge and understanding in the prior-to-school period correlated with items on a parent questionnaire.
These items included perceptions of the number of books at home owned by the child, the child’s interest in literacy and the child’s concentration. Measures of literacy used by Wells included Concepts About Print test Sand and letter identification tasks devised by Clay (1979b, 1985). Test results and variables on the parent questionnaire were significantly associated with the children’s class of family background (Wells, 1985). These results prompted Wells to re-evaluate the place and value given to literacy in the everyday activities of the family.
Various literacy interactions were observed in homes and these interactions were coded in four ways.
• Looking at books or other printed material;
• Listening to a story being read or told from a book;
• Drawing and colouring; and
• Writing (being executed by either the child or parent). (Wells, 1985, p.
345)
Of the four interactions, looking at books was the most common. Writing, was least common, with only two instances occurring. The writing interactions were subsequently not used in further analyses. Listening to a story, was observed at least once for 53% of the children and 78% of the children also engaged in drawing or colouring on at least one occasion (Wells, 1985). From analyses of
Chapter 2: Literature Review 72 listening to story interactions, Wells concluded that parents who enjoyed reading themselves were more likely to indicate they enjoyed reading to their children than those who did not. Those who did not enjoy reading indicated they found reading to their children an “unrewarding chore” (Wells, 1985, p. 245). Parents who enjoy reading themselves were more likely to perform reading aloud with skill and actively discuss aspects of the text than those parents who did not enjoy the task. Reading aloud was significantly correlated with mothers’ education level and the combined education level of both parents as well as children’s early success in reading (Wells, 1985, 1986).
Joint storybook reading at home has received ‘widespread agreement’ that the practice is “a highly beneficial parental practice that promotes the acquisition of literacy-related knowledge and consequently paves the way for successful achievement” (Scarborough & Dobrich, 1994, p. 284). However, the extent of the influence has been questioned and reviews of past studies (Bus, van
IJzendoorn, & Pellegrini, 1995; Scarborough et al, 1994) reveal that the results have been “unexpectedly modest” (Scarborough & Dobrich, 1994, p. 285). Data were gathered in relation to joint storybook reading through parental reports and direct observation and results across 20 correlational studies and 11 intervention studies are surprisingly similar with r = < .30. However, researchers acknowledge that data provided by parents may reflect the ‘socially acceptable’ response and not be a measure close to reality.
Dunning, Mason and Stewart (1994) responded to Scarborough and Dobrich by advocating for the continuation of parents reading to children as they argued the
Chapter 2: Literature Review 73 benefits were far-reaching and not easily measured (Dunning et al, 1994). Bus
(2001) contended that reading to young children was more than the mere act of opening a book and reciting the words, and that enjoyment of the experience rested very much with the way adults interact and respond to the text and create interest for the child. If the adult was not an interested, skilled reader then the experience may not be pleasurable or valuable for either the child or the parent and the joint reading may, as a consequence, occur less frequently.
Another aspect of joint storybook reading that researchers have targeted is measuring the complex talk that occurs during joint reading experiences
(DeTemple, 2001). These measures were included within the ongoing longitudinal study, ‘The Home-School Study of Language and Literacy
Development’ being conducted by Snow, Dickinson and Tabors. Findings revealed mothers show a consistent style when reading fiction and that style included the amount of talk each mother engaged in as the story was being read.
The amount of talk with fiction texts remained consistent with each mother throughout several book-sharing sessions. Teachers on the other hand, talked far more during shared book experiences (Dickinson, 1992). However, style differences were noted when non-fiction texts were shared at home, and great variability of style existed.
A distinction of language style that occurred during storybook interactions was that talk varied between immediate and non-immediate talk. Immediate talk occurred when a child and adult talk about the illustrations and text in a direct way (e.g. by pointing and labelling). In contrast, non-immediate talk referred to
Chapter 2: Literature Review 74 any discussion that does not involve the illustrations or the text and typically involved using more complex language and longer utterances (DeTemple &
Beals, 1991; DeTemple, 2001; Dickinson, 1992). Results showed that there was a strong positive association between mothers’ use of non-immediate language when reading to a three year old child and the child’s achievement on some components of SHELL (School Home Early Language and Literacy) tasks
(Snow, Tabors, Nicholson & Kurland, 1995) in kindergarten. The tasks that correlated with non-immediate talk included “story comprehension, emergent literacy and receptive vocabulary” (DeTemple, 2001, p. 41). A broader application of these findings includes ensuring non-immediate talk is included in early childhood settings along with early intervention rather than relying on later remediation (Strickland, 2001). When parents and caregivers provide positive environments and language and literacy practices are valued, then children’s emerging literacy scores are more likely to be higher (Hildebrand & Bader,
1992).
Home-School Connections
Within the current study the influence of family on children’s literacy development is measured using information from parent surveys and analysing this information in relation to children’s developing skills and understandings in the prior-to-school period and throughout the first year of school. Information gathered from families included family composition, education and occupation of parents, parents’ perceptions of children’s personal attributes and family literacy materials and practices.
Chapter 2: Literature Review 75 Once a child enters school, the role of the family in the child’s language and literacy development does not diminish. Strong parental involvement in schools has been shown to have a positive effect on educational learning outcomes for children (Cairney, 2000a; Epstein, Sanders, Simon, Clark Salinas, Rodriguez
Jansorn & Van Voorhis 2002; Feuerstein, 2000; Riley, 2002). In recent times, as shown in the previous section, educational policies in western nations are reflecting these findings and schools are being encouraged to develop and maintain collaborative partnerships with parents (Education Queensland, 2000a;
International Reading Association, 2002; National Institute of Child Health,
2000a). Learning to be literate is at the heart of education and some researchers advocate educating parents about ways to help their children at home as a focus for building relationships between the home and school (Cairney, 2000a).
Building such a relationship is not a simple matter as the complexities of role definition and responsibilities within partnership are many and varied.
Despite almost universal acceptance of the need for parents and school personnel to develop shared goals and work together, barriers exist and few schools have developed and maintained successful parent partnerships (Ashton & Cairney,
2001; Cullingford & Morrison, 1999; Pena, 2000). In recent times many schools have assumed a simplistic view of becoming literate and devised parent literacy programs where parents are taught a range of skills to use at home with their children (Cairney, 2000b). In Australia, a national mapping exercise of initiatives used in the middle years of schooling was conducted in 1995 and 261 major initiatives and 101 small-scale projects were identified (Cairney, Ruge,
Buchanan, & Lowe, 1995). Despite the large number of initiatives, little formal
Chapter 2: Literature Review 76 evaluation has been conducted. This poses dilemmas for educators as to the effectiveness of the initiatives from the school, parent or child perspective.
Recommendations from the mapping exercise included further investigations to address the “mismatches between literacy practices of home and school” and the
“link between literacy problems and membership of specific target groups”
(Cairney, Ruge, Buchanan, Lowe, & Munsie, 1995, p. 33).
Studies have recognised the value of parents interacting with their children in everyday situations and including a range of texts in these interactions (Edwards
& Warin, 1999; Greenhough & Hughes, 1998; Handel, 1992; Neuman, Caperelli,
& Kee, 1998; Stainthorp & Hughes, 2000; Stevenson, Lee, & Schweingruber,
1999). However, when schools devised programs for parents they often advocated parents become ‘teacher like’ in their interactions and this advice fails to “acknowledge and build on the social richness of home and community”
(Cairney, 2000a, p. 4). A reciprocal relationship exists where schools could assist children with literacy development if they understood better and included aspects of the child’s family language and literacy practices (Fagan, 1987; Orellana,
Monkman, & MacGillivray, 2002; Shapiro & Doiron, 1987).
Challenges faced by schools when forming partnerships are many and varied.
Defining roles and responsibilities within the partnership can be a challenge as school personnel seek to maintain control over territory, and parents seek to have a voice in school affairs (Todd & Higgins, 1998). Parents may not feel welcomed or valued in some school contexts and not all parents have the confidence to volunteer to participate. Parents who feel most vulnerable include working class
Chapter 2: Literature Review 77 parents, those with a non-mainstream cultural background, parents who are unemployed and those who lack educational qualifications (Lareau, 1987; Lareau
& Horvat, 1999; National PTA, 2000). Studies have shown that teachers working in schools with a high percentage of disadvantaged and non-mainstream families, associated children’s learning with their family background (Danielson, 1997).
The influence of family is considered paramount and on many occasions unsupportive of the goals of the school. All families possess “funds of knowledge” that are unique and include aspects of their everyday life and experiences (Moll, Amanti, Neff, & Gonzalez, 1992, p. 133). If a family is financially poor, teachers seem to associate this with low intelligence within the family, lack of interest in the children’s education and lack of responsibility. This differs from middle class school settings where teachers’ discourses indicated these families provided the physical, emotional and material support that children needed to be successful at school (Ashton & Cairney, 2001; Freebody, Ludwig,
Gunn, 1995).
Language and discourse within schools also contribute to creating and maintaining power structures within schools (Ashton & Cairney, 2001; Gee,
1996). Often communication in schools is a one-way interaction where the school initiates and takes control of the agenda. Research has shown that parents contribute greatly to their children’s learning at home and opportunities to share ideas with other parents and school personnel would be most beneficial (Lazar &
Weisberg, 1996; Nistler & Maiers, 1999). One initiative trialled within Australia,
Successful Learning: The Parent Factor, involved parents receiving training as literacy educators and then presenting a program for parents in their schools
Chapter 2: Literature Review 78 (Australian Parents Council, 1997). Intervention and support programs also offer families strategies that promote children’s literacy development. A qualitative study conducted with 15 families taught strategies for including conversation, reading books, browsing through books, borrowing books, dramatising and improvising, relating toys to a story, learning nursery rhymes and cooking
(Saracho, 1999). The study showed that these type of interventions are possible and can improve educational outcomes for young children.
While parents’ reading to children has been the focus of a number of studies in the prior-to-school years, listening to children read at home has also generated interest from researchers who studied the effect of this activity on children’s reading development (Anderson, 2000; Robinson, 1995; Weinberger, 1996). The practice, first designed by Morgan (1976) involved teaching parents to listen and respond appropriately as children read aloud (Morgan, 1976). The practice referred to as ‘paired reading’ became popular during the late 1970s and 1980s and a number of studies were conducted to evaluate its effect (Tizard, Schofield,
& Hewison, 1982; Topping & Knight, 1984; Young & Tyre, 1983). A review of research conducted in 1992 revealed results were positive with children’s reading levels improving and if the technique was conducted in a “context of well- organised service delivery” (Topping & Lindsay, 1992, p. 222).
Thus, family and home language and literacy practices have been shown in a range of ethnographic/qualitative studies to play major roles in children’s literacy development in the prior-to school period and during the early years of schooling. Research has shown that all families use language and literacy in specific ways as they go about their everyday lives and all children have had
Chapter 2: Literature Review 79 some exposure to print before they commence school. However, children from non-mainstream cultural backgrounds and economically disadvantaged families may not be well regarded by school personnel and their home language and literacy practices not appreciated as contributing to children’s learning.
While home-school partnerships in children’s learning are seen to be advantageous for improving learning outcomes with children, the formation and maintenance of these partnerships seem plagued by barriers and challenges.
Despite research having shown that family practices contributed to children’s learning success, the school maintained the position of ‘all knowing’ and communication with parents in most instances was a one-way communication from school to parents. In relation to supporting children’s literacy learning, schools have used parent programs where parents are taught strategies to use at home with their children, but the outcomes of these programs have not been measured adequately. A recent review of 41 studies evaluated K-12 parent involvement programs in order to assess claims that such programs influence student learning outcomes (Mattingly, Prislin, McKenzie, Rodriguez & Kayzar,
2002). The result of the review was that there was little empirical support for the view that parent programs are an effective means of improving student learning outcomes. Many studies had inherent design, methodological and analytical flaws.
2.4.1.3 Literacy development in the prior–to-school period
Predictive studies in which children’s literacy achievement in the early years of schooling has been measured in the prior-to-school period and then during the
Chapter 2: Literature Review 80 early years of schooling are now reviewed. Studies that focus on early literacy acquisition have been either multivariate or uni-dimensional. Two key themes are noted for uni-dimensional studies and include the development of phonological awareness and concepts about print. Selected longitudinal studies of a similar design to the one reported in this dissertation, will be examined in detail. Prior to examining the predictive studies beginning in the prior-to-school period, some key related issues are explored. These issues include attributing cause from predictive studies, the wider acceptance of measuring children’s developing skills in the prior-to–school period and the variation in design and range of samples found within these studies.
Results from correlational studies cannot be viewed as causes or explanations of levels of reading success or difficulties. When factors correlate with later reading achievement they are deemed associated conditions that may relate to possible reading problems. Exceptions to this trend however, have been reported in every sample (Scarborough, 2001). Correlations reported in studies from one year in the primary school to the next are typically in the (.6 to .8) range. These results are strong, but not perfect. Correlations of kindergarten predictors with later reading scores are typically not as strong and are within the (.4 to .6) range
(Snow, Burns & Griffin, 1998).
The validity of assessing children’s developing literacy skills in the prior-to- school period however, is not universally accepted by educators. The debate not only involves contrasting views of early literacy assessment, but some present the view that attempts to measure literacy skills in the prior-to-school period
Chapter 2: Literature Review 81 should be abandoned altogether (Johnston & Rogers, 2001; Salinger, 2001;
Valencia, 1997). Reasons given in support of abandoning the practice are that assessment routines are first interpretive, discursive practices that are influenced by values, beliefs and language (Gee, 1996). Second, ill-informed labelling may result in undesirable long-term consequences for some children (Pearson,
DeStefano, & Garcia, 1998; Shepard, 1994; Shepard & Smith, 1989; Valencia,
1997). Third, some propose greater use of non-intrusive teacher observation of children within productive literacy environments would be more suitable.
Contextually relevant assessment practices can then be invoked as they are used during the first year of formal schooling (Clay, 1991, 1993a, 1998). This emphasis assumes literacy is acquired from active participation in literacy-related activities and removes the deficit model where problems may be located in the child. Lack of appropriate literacy experiences and poor teaching, rather then intellectual deficits within the child, need to be emphasised and examined more closely (Vellutino & Scanlon, 2001).
Longitudinal predictive studies vary in design. Some include intervention procedures where literacy skills are measured at an early age and particular teaching strategies are trialled and outcomes measured. Other longitudinal studies conduct tests of children’s prior-to-school knowledge and understanding and continue to measure the developing literacy skills in the early years of schooling. The advantage of longitudinal studies is the cross-time measures that allow cross-validation of predictors. Other variations in the design of longitudinal studies include those where a single instrument is relied upon to measure outcomes, compared to those where multiple measures are utilised.
Chapter 2: Literature Review 82 Variations in analyses of data also distinguish predictive studies with some researchers designing correlational studies and others seeking ways to reduce and combine variables in valid and reliable ways. These studies may utilise Principal
Component Analysis (PCA), Multiple Analyses of Variance (MANOVA),
Cluster Analyses, or Multiple Regression or a combination of these methods.
The type of sample selected for each study differed. Scarborough (2001) proposed three different sample types usually are found in studies of young children’s developing literacy skills. These include preschool children deemed
‘at risk’ of developing literacy learning difficulties, offspring of parents who have reading disabilities or difficulties and unselected samples including birth or school cohorts. The study described in this dissertation includes multiple measures of children’s literacy skills and uses an unselected sample of 114 children. The children represent three school cohorts where families were invited to participate. Sample size as well as type can vary within predictive studies and these include studies with more than 1000 participants to fewer than 40. The attrition rate of participants within longitudinal studies can be a drawback.
Despite the debate, in the United States more than one third of the States require young children to be ‘screened’ for pre-academic skills. Children who fail may be deemed ‘not ready’ and may be placed in transition classes or asked to wait another year before entering kindergarten classes (La Paro & Pianta, 2000;
Meisels, 1998). A number of researchers advocate assessing children’s developing literacy skills in the prior-to-school period and during the first year of schooling as results provide valuable information. This information primarily
Chapter 2: Literature Review 83 addresses developmental patterns in the acquisition of reading-related skills and provides insights for theoretical questions and classroom practice (Al Otaiba,
2001; Juel, Griffith, & Gough, 1986; Raban, Ure & Smith, 1999; Scarborough,
2001).
Findings from studies where prior-to-school literacy skills are measured are now reported with a particular emphasis being accorded to longitudinal studies.
Selected studies of similar design to the one reported in this dissertation are addressed in more detail. On close examination of the longitudinal studies listed in Appendix A, it was found that:
• 8 studies are concerned primarily with influences of the home and family on
early literacy development;
• 28 studies describe multivariate measures where a range of performance
measures of children’s skills are conducted during the prior-to-school period
or at the beginning of the first year of schooling;
• 14 studies place an emphasis on measuring and predicting reading
acquisition from measures of phonological sensitivity and
• 3 studies have a different focus e.g. children’s motivation, programming for
literacy learning, intervention studies etc.
It should be noted that some overlap within the categories listed above occurs, for example, multivariate studies may have also included measures of home literacy environment or phonological sensitivity. It should also be noted that while 53 publications are listed in Appendix A, these represent a total of 43
Chapter 2: Literature Review 84 studies. Within the multivariate studies the main types of performance measures used with young children are broadly categorised as:
• Oral language measures
• General intelligence measures
• Environmental print;
• Concepts of print;
• Letter knowledge;
• Word decoding;
• Phonological awareness;
• Comprehension.
Three longitudinal predictive studies that align with the current study are examined first. Broader findings relating to longitudinal studies of language and linguistic development, phonological awareness and acquired knowledge of literacy are then examined.
Longitudinal studies
Research conducted by Burgess, Hecht and Lonigan (2002) aligns with the current study. This multivariate study examined home literacy environment in relation to children’s development of oral language, phonological sensitivity, and early literacy achievement. Results from a sample of 115 middle class preschool children in seven school locations within northern Florida were reported.
Performance measures of children’s developing literacy abilities were conducted twice during the study and these occurred first in prior-to-school settings (Time
1) and then one year later during the first year of schooling (Time 2). By the
Chapter 2: Literature Review 85 second measurement period, the sample had been reduced to 97. The sample was gender balanced with a male component of 52.6%. The mean age of the students at the time of the first performance measurement was 60.4 months with an age range of 48 to 70 months.
Performance measures used in Time 1 included two standardised tests of oral language, four tests of phonological sensitivity and two tests of letter knowledge.
An estimate of children’s receptive language abilities was made using the grammatical subtests of the Illinois Test of Psycholinguistic Abilities (Kirk,
McCarthy, & Kirk, 1968) and Test of Language Development Primary
(Newcomer & Hammill, 1997). Phonological sensitivity was determined using three types of measures rhyme oddity, blending and elision tasks. All tasks consisted of practice items and task trials. Letter knowledge measures included naming upper case letters and providing the sound for each uppercase letter
(Burgess, Hecht, Lonigan, 2002).
Performance measures for Time 2 included re-testing of the two standardised tests of oral language, re-testing and increasing the number of tasks for the four tests of phonological sensitivity, re-testing of letter knowledge and including two tests of word decoding ability. Word decoding measures included naming words from the Woodcock Reading Mastery Test-Revised (Woodcock, 1998) and naming words compiled from the 100 most frequently used words (Burgess,
Hecht & Lonigan, 2002). Home literacy environment measures were obtained via a parent questionnaire to gauge “family demographics, parental leisure reading habits and family storybook reading habits” (Burgess et al., 2002, p. 414).
Chapter 2: Literature Review 86
Overall results from the study indicated that home literacy environment was significantly related to oral language, phonological sensitivity and word decoding. The magnitude of these results was of a median order similar to those reported by Bus, van IJzendoorn & Pellegrini (1995), La Paro & Pianta (2000) and Scarborough & Dobrich (1994). Researchers of this study drew implications for the importance of the largely untapped potential of children’s home as a potential resource for enhancing children’s developing literacy achievements.
By way of contrast in relation to sample type was the study by Storch and
Whitehurst (2002). This study was conducted in one of eight selected Head Start centers in Suffolk County, New York with 626 low-income students. The students were eligible for Head Start, an early intervention program for economically disadvantaged children. The study examined code-related and oral language precursors to reading with young students from preschool to Year 4.
The sample was gender balanced with 52% being male. Ethnic mix within the sample included 39% African American, 34% Caucasian, 16% Latin American and 11% of other ethnic origins.
Children’s language and literacy skills were measured six times during the study.
The first was during the Head Start period followed by kindergarten and once each year from Years 1 to 4. Code-related performance measures consisting of a battery of 12 readiness subtests from the Developmental Checklist (CTB, 1990) were used during the Head Start period and in kindergarten. The subtests measured memory, print, auditory, writing and drawing concepts. Each subtest
Chapter 2: Literature Review 87 consisted of multiple questions. Oral language skills were measured each year using multiple measures including the Peabody Picture Vocabulary Test –
Revised (Dunn & Dunn, 1981) and the One Word Picture Vocabulary Test
(Gardner, 1990).
Reading measures were also used once students commenced formal reading instruction. A range of reading tests were used in Years 1 to 4 including subtests of the Woodcock Reading Mastery Tests (Woodcock, 1998) and Stanford
Achievement Test (Psychological Corporation, 1989). These tests measured both reading accuracy and comprehension.
Results of language skills, code-related skills and reading achievement were mapped using structural equation modeling. Oral language and code-related skills were shown to be statistically significant in the prior-to-school period, but not significantly related in Years 1 and 2. There was longitudinal continuity reported with oral language and code-related skill domains having similar levels of variance being accounted for in preschool and in Years 1 to 2. Oral language for example accounted for 90% of variance in preschool and 88% in Years 1 to 2.
Tasks that reflected reading accuracy and reading comprehension were directly related to code-related ability with 58% of the variance in Year 1 reading ability accounted for by code-related skills. Reading comprehension in Years 3 and 4 were significantly influenced by three sources: a child’s prior reading achievement (18% of variance), a child’s concurrent reading accuracy (16% of variance) and a child’s concurrent language skill (7% of the variance). This study
Chapter 2: Literature Review 88 had some similarities to the one reported in this dissertation as multiple measures were utilised, and some procedures used for analysis, for example, Principal
Component Analysis and Analysis of Variance were similar.
The third longitudinal multivariate study took place in Australia. This study,
‘One Hundred Children Go to School’ (Hill, Comber, Louden, Rivalland, &
Reid, 1998), was similar to the current study in that connections between literacy development in the prior-to-school period and the first six months of schooling were investigated. Multiple measures of children’s developing literacy understandings were collected including letter knowledge, environmental print, concepts of print, word decoding and phonological sensitivity. The sample included in this study was diverse and included children living in three states of
Australia.
Children from whole class groups in five different geographical locations were included. The sites were: “a remote Aboriginal community school, a school in a large rural town, a high socio-economic status city school, an inner-suburban school characterised by high proportions of children with home languages other then English, and a city school characterised by high proportions of families with a low income” (Hill, Comber, Louden, Rivalland & Reid, 1998, p. 116). Both quantitative and qualitative data were gathered with 20 case studies as well as whole class groups. The total sample size was 109 in the prior-to-school period and 101 in the first year of schooling.
Chapter 2: Literature Review 89 Performance measures used in preschool & Year 1 included environment print identification, Concepts About Print Test (Clay, 1993a), writing observation
(Clay, 1993a), letter identification (Clay, 1993a), phonemic segmentation (Yopp,
1995), and reading behaviours on text gradients (Fountas & Pinnell, 1996).
Additional measures for the second round of assessments included retelling tasks from School Entry Assessment (New Zealand Ministry of Education, 1997),
Ready to Read (Clay, 1993a) and mapping spelling and writing on developmental continua (Education Department of Western Australia, 1994b &
1994c). A total of 58 assessment items were used in the prior-to-school period and 75 in Year 1.
As well as frequency measures of results, data were analysed using heirarchical cluster analysis in order to seek out and examine similar cases and classify them according to those similarities. Five cluster groupings were formed enabling a more refined interpretation of results. The clustering process however was carried out with the children’s results only after six months in Year 1, and not with the results in the prior-to-school period. Thus, there could be no examination of the different compositions of the cluster groups over time and the ability to investigate predicting children’s achievement after six months of schooling was not possible (Hill, Comber, Louden, Rivalland & Reid, 1998).
Findings reported from the study included a broad conclusion that differences of performance have been produced “through the interaction of many factors” (Hill,
Comber, Louden, Rivalland & Reid, 1998, p. 151). Possible factors suggested by the researchers that may have an effect on the children’s developing literacy
Chapter 2: Literature Review 90 achievement included family circumstances, literacy experience, culture, individual child differences and school experiences including teaching practices and strategies used in school. Children’s literacy development was not found to be consistently sequential across the sample. This suggests that educators need to be mindful of these results when using developmental continua, such as the
Western Australian First Steps materials (Education Department of Western
Australia 1994a; 1994b; 1994c). Many pathways seem possible and an expectation that children will develop in linear fashion as outlined on the continua may be flawed.
Differences in student characteristics seem to have contributed to the final cluster of homogenous groups formed from literacy achievements children had made after six months of schooling. Student characteristics considered by researchers included age, gender, social class, home language and cultural background. A number of ‘accepted beliefs’ relating to the acquisition of literacy have not been demonstrated within the results of this study. A developmental view of growth within early childhood has endorsed the view that age is an important consideration for children’s learning. Hill, Comber, Louden, Rivalland and Reid,
(1998) found that age may be considered an important difference when students in the highest performing cluster were examined as they were on average three and a half months older than children in all remaining cluster groups. However, this hypothesis was not sustained when all clusters were examined. No significant difference for age was found within this study. Gender was also considered as a likely factor to explain different levels of performance, but again
Chapter 2: Literature Review 91 no significant difference was found within the performance clusters (Hill,
Comber, Louden, Rivalland & Reid, 1998).
Finally, data were examined to ascertain if social class, home language or cultural background contributed to differences in literacy achievement after six months of schooling. Social class differences could have contributed to the highest performing and average performing clusters, but the influence of social class was much less clear when the composition of the remaining three cluster groups was examined. Differences in home language frequently were associated with lower literacy acquisition performance, but in this study results did not directly support that notion. Many of the children whose home language was other than English were included in Cluster 3, and results, although inconsistent, were near average levels.
Cultural differences between home and school may also have contributed to differences in literacy performance. A number of Aboriginal children in the study were placed in the lowest performing cluster. But, absenteeism, lateness and transience were major factors that needed to be considered. Thus, in this study, student characteristics of age, gender, social class, home language and cultural background could not be attributed clearly to levels of performance after six months of schooling (Hill, Comber, Louden, Rivalland & Reid, 1998). This study received further funding and continued until students finished Year 4 (Hill,
Comber, Louden, Rivalland & Reid, 2002). Similarities of Hill, Comber,
Louden, Rivalland & Reid (1998) study with the current study being reported include similar sample size and performance measures of students’ literacy
Chapter 2: Literature Review 92 acquisition. Differences are period of time for the study, sample type, the inclusion of qualitative data, methods used for analysis and interpretation of data.
Language and linguistic development
It was reported earlier in Chapter Two that longitudinal studies by Wells (1985) and Snow (1983) found that children’s experience with decontextualised language at home influenced literacy learning outcomes in school. In addition,
Snow, Burns and Griffin (1998) reported that preschool children who have early language impairments are likely to encounter reading problems. Despite these findings, few longitudinal studies have traced oral language development from birth. One study by Shapiro, Palmer, Antell, Bilker, Ross and Capute (1990) reported a composite measure of infant language achievements predicted reading disability with a 73% success rate. Within this study oral language competency in the prior-to-school period was shown to affect later measures of early reading.
Other studies that included oral language measures in the prior-to-school period used socioeconomic factors and oral language to predict school outcomes in
Years 1 to 3. These two early language measures were found to be highly correlated. They also correlated moderately with reading scores in Years 1 to 3
(Walker, Greenwood, & Carta, 1994). A study by Bryant, Bradley, Maclean, &
Crossland, 1989) tested young children on a number of phonological awareness measures and IQ. Findings were that reading performance was predicted by expressive language, receptive vocabulary and nursery rhyme recitation (Bryant,
1990; Bryant et al, 1989). Scarborough (1991) considered a number of language and reading measures as well as IQ as predictors of children’s reading achievements in Year two. Half of the sample had parents or siblings with
Chapter 2: Literature Review 93 reading problems. Findings reported that receptive language and IQ correlated moderately with later reading. Results were mixed in that some children with a family history of reading difficulties became successful readers. Children who became poor readers were much weaker than other groups on phonological and syntactic language measures.
Phonological awareness
“Much evidence is now available to suggest that awareness of the phonological constituents of words – or as it is sometimes called, metalinguistic awareness – is most germane to the acquisition of literacy” (Liberman & Shankweiler, 1985, p.10). Phonological awareness or phonological sensitivity is the “ability to attend explicitly to the phonological structure of spoken words, rather than just to their meanings and syntactic roles” (Snow, Burns & Griffin, 1998, p. 111). A recent meta-analytic review of research (Ehri, Nunes, Willows, & Schuster, 2001) advocated the need to provide instruction in phonological awareness for young developing readers. Phonemes are described by Bowey (2000) as being
“perceived automatically below the level of consciousness’ and as ‘abstract categories that cannot be precisely isolated in the acoustic wavelength” (p. 6).
Two key aspects of research are gaining prominence and these are phonological awareness and the teaching of phonics. Some researchers claim scientific studies of reading have shown “converging evidence” relating to the importance of phonological sensitivity and the teaching of reading (Stanovich, 2000, p. xiii).
Over the last few decades several comprehensive reviews of teaching young children to read have been conducted. Chall’s seminal text Learning to Read in
Chapter 2: Literature Review 94 1967 was the first publication in more recent times to advocate the teaching of alphabetic basics to young children. Two further reviews of research, Adams
(1990) and Snow, Burns and Griffin (1998) reiterated two key recommendations.
First all three reports urged from the start children be fully and actively
engaged in the kinds of thoughtful and supported reading and writing
activities through which reading comprehension must grow. Second, all
three of these reports firmly concluded that providing beginning readers
with explicit well-organised instruction in the alphabetic basics, including
phonics was essential. (Adams, 2001, p.66)
A more recent review of research also advocated including phonological awareness instruction and the teaching of phonics as integral components of the teaching of reading (National Institute of Child Health, 2000a).
In English, printed symbols represent the sounds of the language. Young children need to begin to understand that spoken language can be represented as words, syllables and phonemes (Snow, Burns & Griffin, 1998). Given the importance of being skilled at phoneme-letter mapping in the English alphabetic writing system it would be expected that phonological awareness would be an excellent predictor of reading skills. “This metalinguistic skill involves treating language as the object of thought, rather than merely using language for communication”
(Snow et al., 1998, p. 111). A number of studies have shown that children in the prior-to-school period or in the early years of schooling who demonstrated strong phonological awareness skills are more likely to be successful readers than poor readers (Ehri, Nunes, Willows and Schuster, 2001; Scarborough, 1989). Many
Chapter 2: Literature Review 95 children however with weak phonological skills also become adequate readers
(Bradley & Bryant, 1985; Catts, 1991).
For some children an awareness of the phonological structure of speech developed in the prior-to-school period and some demonstrated this awareness when they ‘play with words’ particularly rhyme and alliteration (Snow, Burns &
Griffin, 1998). However, most will not develop these insights without explicit instruction (Blachman, 2000). Skills within phonological sensitivity are usually developed in a particular order with children first demonstrating rhyme sensitivity, then phoneme counting and segmenting and lastly the most challenging of the skills phoneme deletion and phoneme reversal (Adams, 1990;
Torgesen & Mathes, 1998).
A number of research studies have demonstrated that when phonological awareness is measured in young children in the prior-to-school period, it remains a strong predictor of early reading achievement (Bryant, Bradley, Maclean &
Crossland, 1989; Scarborough, 1990; Snow, Burns & Griffin, 1998). Ehri,
Nunes, Willows & Schuster (2001) conducted a meta-analysis of 52 studies for the National Reading Panel subgroup on Alphabetics. Two key questions guided the review:
1. Is phonemic awareness effective in helping children learn to read?
2. Under what circumstances and with which children is it most effective?
(p. 1)
Studies were examined for scientifically valid findings and aimed to find classroom applications relating to the research. Three types of samples were
Chapter 2: Literature Review 96 found within the studies and these included: disabled readers, children in classes prior to Year 2 who were deemed at-risk for reading failure and unselected samples. Instructional programs trialled within the studies included those with a single focus where just one phonological skill was taught, a double focus where two skills were taught and global focus where a range of skills were taught.
The effect sizes reported in each study were examined and correlations conducted to ascertain the overall effect size across the studies. A summary of findings from the review were:
• A large overall effect size (.86) on learning to read was found;
• The instruction was of benefit to normally-developing readers as well as
children at-risk;
• Socio-economic status was not significantly related to findings and in some
studies was not reported;
• Small group instruction was found to be more effective than one-to-one
tutoring or whole class teaching;
• Optimal amount of time needed for the instruction was between five and nine
hours;
• Programs with a double focus showed the highest effect level;
• Classroom teachers were found to be effective tutors of phonological
awareness programs;
• The optimal time for the instruction appears to be in the pre-school period;
• The effect size on spelling development for disabled readers was low
compared to reading;
Chapter 2: Literature Review 97 • Phonological awareness is only one component required for learning to read.
(Ehri, Nunes, Willows & Schuster, 2001)
Longitudinal studies using multivariate measures
Longitudinal predictive studies using multivariate measures are now examined.
These studies addressed children’s acquired knowledge of literacy in the prior-to- school period as a means of predicting later literacy achievements. Some studies incorporated a broad range of measures, including phonological understandings.
Studies published in the years 1980 to 1989 are examined first and then those dating from 1990 to 2002.
Two Australian studies provided important findings during the 1980s. Butler,
Marsh, Sheppard & Sheppard (1982) administered the Sheppard School
Screening Test to 320 children in kindergarten to determine its value as a predictive measure of reading ability in Years 1, 2 and 3. Results showed the
Screening Test was a valuable instrument for predicting reading in Years 1 and 2 and to a lesser extent in Year 3. Ten measures were used including standardised reading and word recognition tests and the Slossen Intelligence test (Butler,
Marsh, Sheppard, & Sheppard, 1982).
The second study conducted by Share, Jorm, Maclean and Matthews (1984) examined individual differences in early reading acquisition. Multiple measures of early reading skills were used with a sample of 543 children. Results showed that “individual attributes have a far greater impact on differences in educational
Chapter 2: Literature Review 98 achievement than in-school factors such as schools and teachers” (Share et al.,
1984, p. 1323).
In the United States, Berninger (1986) conducted a longitudinal study with 48 kindergarten children. The sample consisted of children from stable families with low to middle income and included children from a range of cultural backgrounds. Linguistic and visual measures were administered in kindergarten and at the end of Year 1 to investigate if any of the measures predicted reading difficulties after one year of instruction. Results showed a combination of linguistic and visual skills related to low achievement on word decoding/encoding at the end of Year 1 (Berninger, 1986).
Juel, Griffith and Gough (1986) also from the United States, conducted a study with 129 middle class children of mixed ethnic origins during Year 1 and Year 2.
Results indicated that phonemic awareness training is warranted as a routine precursor to reading instruction and that young children “will not acquire spelling-sound correspondence knowledge until a prerequisite amount of phonemic awareness has been attained” (Juel et al., 1986, p. 254). A second study of 54 children by Juel (1988) is quoted often in the literature. Juel reported how poor decoding prevents poor readers from improving their reading skills and that motivated proficient readers read more words because they read more often.
According to Juel “Children who became poor readers entered first grade with little phonemic awareness. By the end of fourth grade, the poor readers had still not achieved the level of decoding skill that the good readers had achieved at the beginning of second grade” (1988, p. 437). This result aligned with research completed by Clay (1966), Lundberg, Frost, & Petersen, (1988) and Stanovich,
Chapter 2: Literature Review 99 (1986). The frequently quoted result from Juel’s study is that “the probability that a child would remain a poor reader at the end of fourth grade if the child was a poor reader at the end of first grade is .88” (Juel, 1988, p. 437). This result reflected the oft-quoted message in the seminal paper by Stanovich (1986). This paper described how children who read a lot developed their skills and ‘the rich get richer’. This is in contrast to poorer readers who read less and seemingly ‘get poorer’.
A multivariate study (Blatchford, Burke, Farquar, Plewis & Tizard, 1987) conducted in 33 inner-London schools studied the literacy development of 343 children. The study took place from the end of preschool (children’s average age
- 4years 9 months) until Year 2 (average age - 7 years 6 months). The sample included children from a range of cultural backgrounds and “the majority of schools were in working-class areas, often relatively disadvantaged” (Blatchford,
Burke, Farquar, Plewis & Tizard, 1987, p. 18). At the end of the preschool year, five literacy-related tests and a writing task were administered. A summary of results is presented.
• Word matching: mean score of less than 50% for visual word matching
task;
• Concepts about print: (5 items from Concepts About Print Test (Clay,
1985) - < 50% knew one reads the print not the pictures; <30% knew
directionality of print; very few could identify words & letters;
• Letter identification: results showed a bimodal result. >50% knew names
or sounds of approximately 5 letters and 12% could identify 20 letters;
Chapter 2: Literature Review 100 • Word reading: Only 9 children in the study could read words on word
cards;
• Oral vocabulary: scores a little below the national average;
• Handwriting: Only 25% could write their name correctly from memory
and 17% could copy a phrase “on the ground” (Blatchford, Burke,
Farquar, Plewis & Tizard, 1987, p. 19)
A reading test was administered when the children were approximately 7 years old. Results showed that for the remaining 245 children the strongest correlation occurred for letter identification scores in preschool (p = .61) and this was followed by name writing and copying of the phrase (p = .49).
As a close examination of all multivariate longitudinal studies for the period
1980 –1989, is not possible, results from the remaining longitudinal studies are summarised in Table 1.
Table 1
Summary of Results for Remaining Longitudinal Multivariate Studies (1980- 1989)
Authors Findings Vellutino & Scanlon (1987) Phonologic coding deficits constitute a major source of reading difficulty in beginning readers.
Kontos (1988) Print awareness is not the only prerequisite to reading achievement, but is intertwined with other knowledge and skills.
Tunmer, Herriman & Nesdale In the early stages of reading development, (1988) metalinguistic awareness assists children to understand that print maps onto speech.
Bryant, Bradley Maclean & A strong relationship was found between early Crossland (1989) knowledge of Nursery Rhymes and success in reading and spelling in the prior-to-school period.
Chapter 2: Literature Review 101 Multivariate longitudinal studies dating from 1990 to 2002 are now examined.
Findings from three multivariate longitudinal studies (Burgess, Hecht &
Lonigan, 2002; Hill, Comber, Louden, Rivalland & Reid, 1998 and Storch &
Whitehurst, 2002 ) were described in detail earlier in this chapter and will not be included in this section. Studies included here are those where the overall purpose, design, sample and/or instruments resemble the current predictive study.
Three Australian studies Bowey, (1995), Meiers and Forster, (1999) and Raban,
Ure and Smith (1999) are examined first.
Bowey (1995) conducted a study in Australia with 238 five-year-old children from different socio-economic backgrounds. The purpose of the study was to examine the effect of phonological sensitivity in the prior-to-school period on word level reading achievement after one year of schooling. Tests administered during preschool period included general intelligence, receptive vocabulary and grammar, verbal working memory, phonological sensitivity, letter knowledge and novice reading ability (Bowey, 1995). Results showed that “marked group differences were observed on most measures” (Bowey, 1995 p. 476). It was found that “school entrants’ phonological sensitivity predicted subsequent reading achievement, even with IQ and vocabulary abilities statistically controlled” (Bowey, 1995 p. 485). A strong recommendation resulting from this study was that “preschool and kindergarten programs should include activities that foster children’s understanding that words can share sound patterns”
(Bowey, 1995, p. 485). A second recommendation was that activities in prior-to- school centres should include looking at words in order to detect similar visual and auditory patterns.
Chapter 2: Literature Review 102
The second Australian study is currently being conducted by Meiers and Forster,
(1999). This seven-year longitudinal study (1999-2005) involves 1000 children in 100 schools throughout Australia. Goals for the study include:
• Identify and describe typical development of skills in reading, writing,
speaking, listening and viewing;
• Identify and describe typical development of skills in number, measurement,
space, chance and data;
• Identify and describe background variables that affect literacy and numeracy
throughout primary years of schooling;
• Link data of students’ achievements in literacy with the National School
English Literacy Survey;
• Explore the relationships between literacy and numeracy development;
• Investigate teaching approaches in literacy and numeracy in a special
targeted sample. (Meiers & Forster, 1999 p. 3)
While results are not yet available, this study includes an examination of the literacy skills that young children acquired prior to entering school. Year 1 teachers conducted a one-to-one interaction with each child in the first few weeks of school. Measures in this early period were: environmental print, phonemic awareness, book orientation, listening comprehension and retelling and concepts about print. Similar types of measures are also included in the preschool period of the current study.
Chapter 2: Literature Review 103 The third Australian study, conducted by Raban, Ure and Smith (1999) took place in 40 preschools in the State of Victoria. During the first stage of the project information was sought from preschool teachers relating to their knowledge about young children’s emergent literacy development. While seeking volunteers for the project the researchers noted that a number of early childhood professionals refused to partake in the study. It was during telephone conversations where the project was described that a number of these professionals stressed that “literacy was not an issue for them or their centre and so they did not wish to be involved” (Raban, Ure & Smith, 1999, p. 4). Results from stage one revealed that early childhood teachers had experienced little access to current thinking relating to emergent literacy, either in initial training programs or through subsequent professional development opportunities and as such expressed “overwhelming uncertainty about the role of literacy in their programs” (Raban et al, p. 4).
Stage two provided professional development for early childhood professionals and supported them in reviewing and changing practice. Stage three followed the children from these classes (N = 347) from preschool to the end of their first year of school in order to gauge literacy achievements. Children’s achievements at the end of Year 1 were compared with a group of children (N = 613) whose teachers had not partaken in the project. One measure of oral language (Clay, Gill, Glynn,
McNaughton & Salmon, 1983), six measures of reading and writing, (Clay,
1993a) and the Burt Word Reading Test (New Zealand Council for Educational
Research, 1981) were used to measure literacy achievements. The six measures of reading and writing included letter identification, Concepts About Print test,
Chapter 2: Literature Review 104 dictation task, word test, Robinson’s Test of Writing Vocabulary and running records with different levels of text. All six of these measures were used within the current study in the prior-to-school period, in May/June of Year 1 and in
November of Year 1.
Results of the study conducted by Raban, Ure and Smith (1999) showed children who attended the preschools where teachers had experienced professional development within the research project achieved significantly higher results on all measures. The study, conducted by Raban, Ure and Smith, was different from the current study in that it included an intervention process for early childhood professionals. Measures of literacy achievement after one year of schooling were similar. The importance of early childhood professionals including literacy- related activities in their programs was demonstrated in this study.
An American longitudinal correlational study (Wagner, Torgesen, Rashotte,
Hecht, Barker, Burgess, Donahue & Garon, 1997) investigated phonological processing abilities and word-level reading with a sample of 216 children. The study was conducted from kindergarten to Year 4 where annual assessments of a) phonological processing skills (analysis and synthesis) and phonological memory and serial naming, b) word-level reading and c) verbal aptitude were carried out.
Results showed that individual differences in phonological awareness, naming and vocabulary influenced subsequent individual differences in word-level reading (Wagner et al, 1997). The extent of the effect is not limited to the beginning reading period, but extended to fourth grade. These results add to the growing body of evidence that phonological processing can be viewed as stable
Chapter 2: Literature Review 105 and can be likened to children’s innate cognitive abilities. Researchers advocate early screening of phonological processing abilities in order to identify those children most at risk of reading failure (Wagner et al, 1997).
A second multivariate longitudinal study extending from preschool to Year three confirmed results shown in Wagner, Torgesen, Rashotte, Hecht, Barker, Burgess,
Donahue & Garon, 1997). This study (Smith, 1997) commenced with a sample of 64 children in six preschools and emergent literacy knowledge was measured using four informal measures of literacy and four measures of explicit literacy- related awareness. A parent survey seeking information relating to home literacy practices was also administered at the same time. Regular contact with the children was not maintained, but five years later 57 of the children were contacted and further measures were administered. Results showed that “virtually all preschoolers who entered preschool with advanced knowledge about print or rich literacy experiences did become good readers five years later” (Smith, 1997, p. 262). While not all preschoolers whose literacy measures were in the lowest quartile in preschool became poor readers, seventy five percent of them showed unsatisfactory performance in Year 3. Familiarity with letters is reported as an important aspect of preschool knowledge as it appears to provide a “literacy connection” (p. 262) for young children and assists them to make progress with beginning literacy. As a close examination of all multivariate longitudinal studies for this period (1990 – 2002) is not possible, results from the remaining studies are summarised in Table 2.
Chapter 2: Literature Review 106 Table 2
Summary of Results for Remaining Multivariate Longitudinal Studies (1990 - 2002)
Authors Findings Spector (1992) Segmentation not rhyming shown as the best predictor of Year 1 reading achievement.
Muter, Hulme, Snowling Segmentation not rhyming found to be strongly correlated with & Taylor (1997) end of Year 1 reading and spelling.
Badian (1994) Preschool measures of serial naming and orthographic processing made a strong contribution to predicting reading achievement two years later.
Torgesen, Wagner & Results confirmed phonological deficits cause early reading Rashotte (1994) failure. Training in phonological awareness is recommended to help prevent reading difficulties.
Bowey (1996) [same study Findings do not support phonological memory as being more as Bowey, 1995] strongly associated with receptive vocabulary than phonological sensitivity.
Weinberger (1996) Findings showed that significant factors associated with successful reading in the early years included: 1. having a favourite book at three years of age 2. children’s letter knowledge 3. parents reading to children at school entry 4. having access to home computers 5. parents understanding literacy teaching
Cunningham & Stanovich First grade reading measures strongly predicted Year 11 (1997) outcomes. Researchers propose a fast initial start at reading acquisition may help to develop a lifetime of reading.
Snider (1997) Lack of homogeneity among low-performing students in relation to phonemic awareness calls for caution. These results should indicate extra support is needed.
Badian (1998) Pre-kindergarten screening measures should include awareness of rhyme, onset & rime or knowledge of phonemes, but not syllable recognition, as this task was not found to be effective in identifying children predisposed to reading difficulties.
Burgess (1999) The findings suggested that growth in phonological sensitivity can be explained and predicted in children prior to school entry and the beginning of formal reading instruction.
Chapter 2: Literature Review 107 Authors Findings Taylor, Pearson, Clark & School and classroom factors found to relate to primary-grade Walpole (1999) reading achievement included: 1. strong links to parents; 2. systematic assessment of pupil progress; 3. strong building of communication; 4. collaborative model for reading instruction, including early reading interventions; 5. time spent in small group instruction; 6. time spent in independent reading; 7. high pupil engagement; and 8. strong home communication.
Hecht, Burgess, Torgesen, Findings were that the reasons for social class differences in Wagner & Rashotte (2000) growth of reading skills depended on the time interval that was considered.
Lonigan, Burgess & The relationship among oral language, print knowledge and Anthony (2000) phonological knowledge was studied during preschool and the early years of schooling. Structural equation modeling revealed significant developmental continuity of these skills, particularly for letter knowledge and phonological sensitivity from late preschool to early school, both of which were the only unique predictors of decoding.
Multivariate longitudinal studies have contributed to current knowledge and understanding about emergent literacy and early literacy development in significant ways. Cross-time measures of skills have allowed for progressive assessments and enabled prediction of later literacy achievement to be made from measures gathered during the prior-to-school period. Findings from longitudinal predictive studies include:
• That the home influences oral language, phonological sensitivity and word
decoding;
• Children develop literacy in different ways;
• Students’ characteristics of age, gender, social class home language and
cultural background could not be attributed to levels of performance after six
months of school;
Chapter 2: Literature Review 108 • Children’s decontextualised language use at home influences school literacy
outcomes;
• Reading performance is predicted by expressive language, receptive
vocabulary and nursery rhyme recitation;
• Phonological and syntactic language measures predict literacy learning
difficulties;
• Children with prior-to-school phonological knowledge are more likely to be
successful rather than poor readers;
• Some children with weak phonological knowledge in preschool become
successful readers;
• Phonological awareness in preschool is a strong predictor of later reading
achievement;
• Results of screening tests in preschool help to predict later reading
achievements;
• Children’s personal attributes are more important than school-related
attributes in predicting educational achievement;
• Children who are poor readers after one year of schooling are at high risk of
remaining poor readers by Year 4;
• Professional development in literacy for early childhood teachers can
influence literacy learning outcomes for young children;
• Researchers advocate early screening of children to measure literacy
understandings in the prior-to-school period;
• Virtually all preschool children who entered school with advanced
knowledge about print and rich literacy experiences were good readers five
years later;
Chapter 2: Literature Review 109 • Not all children who have low literacy understandings at preschool become
poor readers. Results show 75% of them demonstrated unsatisfactory
performance in Year 3;
• Letter knowledge and being read to at home are significant factors associated
with successful literacy learning;
• First grade reading measures have been shown to predict achievement levels
in Year 11;
2.5 RESEARCH QUESTIONS RESTATED
The central concern of the current study is to examine patterns of early literacy with a view to defining ways of predicting patterns of early literacy achievement in school. This issue is explored by examining the following key question that guides the overall enquiry.
Key Question:How do young students develop literacy capabilities over the first year of school?
Five contributing questions were used to explore different facets of the study.
1. What knowledge of literacy and understanding of it do students bring to
school?
2. What aspects of literacy knowledge and understanding do students develop in
the prior-to-school period?
3. How do aspects of students’ literacy knowledge and understanding prior to
school relate to one another and students’ background?
4. How do child, home and school factors relate to literacy development in the
first year of school?
Chapter 2: Literature Review 110 5. How do students’ literacy knowledge and understanding of it in the prior-to-
school period predict literacy achievement during the first year of school?
Section 2.2 included an historical examination of theories of language and literacy from the early 1900s to the present day. Teaching practices associated with each theory were also described. Theories ranged from the Maturational perspective in the 1920s to 1930s where it was proposed that children needed time to mature and develop knowledge of self prior to learning to read to Critical
Theory that is current today. Critical Theory considers historical and sociopolitical agendas that affect language interactions and texts (Luke &
Freebody, 1997).
Current literacy policies were examined in Section 2.3. It was shown how a common research agenda is emerging in the English-speaking world with a greater emphasis being placed on standards and accountability. In the United
States and United Kingdom in particular, educational funding is being directed towards those schools that can demonstrate improved standards.
Literacy research in early childhood was examined in Section 2.4. The number of studies is vast and findings are converging. Many researchers agree that young children in the prior-to-school period demonstrate a range of developing literacy skills and abilities. Longitudinal predictive studies highlight that a child’s phonological awareness prior to school predicts later literacy achievement.
Chapter 2: Literature Review 111 The current study is described in the following chapters. The study breaks new ground in the adoption of multiple forms of analyses used to investigate more closely the ways child, home and school factors impact on and predict later literacy development. It also investigates the relationships among parents’ perceptions, teachers’ perceptions and children’s literacy achievements prior to and throughout the first year of schooling.
Participants, sites, data collection and analytic procedures used in the current study are described in Chapter 3. Methodological considerations for the longitudinal study also are described.
Chapter 2: Literature Review 112 CHAPTER THREE
METHOD
A description is provided in this chapter of participants, settings, instruments and procedures used within a longitudinal study that took place over a twelve-month period. The study, conducted with 114 students in three school settings, occurred during the period from the end of the preschool year to the end of the students’ first year of primary school.
The study involved an examination of child, home and school influences on young students' literacy development with a view to predicting patterns of early literacy achievement after one year of schooling. Students' knowledge and understanding of written language were assessed at the end of the preschool year and then twice during the first year of primary school. Data also were collected from parents and teachers.
3.1 SUBJECTS
Participants were 114 preschool students, the students' parents and 11 Year 1 teachers.
3.1.1 STUDENTS
Subjects were drawn from three Preschools (A, B & C) in the metropolitan area of an Australian capital city. Each was part of a primary school complex, where students may attend the one school setting from Preschool through to Year 7. This
Chapter 3: Method 113 arrangement enabled students’ literacy progress to be mapped from the end of
Preschool and throughout Year 1.
Students from two Catholic Preschools and one State Preschool participated in the study. Following approval from relevant education authorities and school principals, contact was made with the parents of all preschool students who had enrolled their children in Year 1 within the school complex. A letter seeking permission was sent home early in November of the preschool year. The letters were printed on school letterhead paper and signed by the principal and the researcher (see Appendix B).
Written permission was provided by 114 parents, 43 parents from Preschool A, 33 from Preschool B and 38 from Preschool C. One student from Preschool C was unable to complete the study because he did not continue his education in Year 1 within that particular school complex.
When the study commenced in November of the preschool year, the ages of the students ranged from 59 months to 76 months with a mean age of 67 months shown in Figure 1. There was no significant mean age difference for gender, with a mean age for boys of 67 months and 66 months for girls.
Chapter 3: Method 114 12
10
8
6 Percent
4
2
0 Mi 59.0060.0061.0062.0063.0064.0065.0066.0067.0068.0069.0070.0071.0072.0073.0075.00 ssing
Students' ages in months
Figure 1. Distributions of students’ ages while at preschool
To assist with analyses of data, students were categorised in three age groups. These were, the youngest age group (59-64 months), the middle age group (65-70 months) and the oldest age group (71-76 months). The majority of students (56%) were aged
65-70 months, while a little more than a quarter of the students (26.3%) were in the youngest age range (59-64 months) and 17% were in the oldest age range (71-76 months). The distribution varied across the three Preschools. In Preschool A approximately 40% of the sample were in the middle age range, in Preschool B, approximately 73%, and 60% in Preschool C as shown in Figure 2.
Chapter 3: Method 115 80
60
40 Percent
Preschools 20 Preschool A
Preschool B
0 Preschool C 59-64 months 65-70 months 71-76 months
Students' age
Figure 2. Distribution of students' ages across three age-group ranges
The gender make-up within the sample was relatively even across each of the
Preschools. Figure 3 presents this distribution. The total percentage of boys in the study was 48.2%. The gender distribution within each Preschool also was relatively evenly distributed in each setting.
60
50
40 t 30 Percen
20 Preschools
Preschool A 10 Preschool B
0 Preschool C male female
Students' gender
Figure 3. Distribution of students’ gender
Chapter 3: Method 116 Parents provided information about the cultural background and languages spoken by their children. The results, shown in Table 3, reveal 5.7% of the students in the study speak a second language and all of these students attended Preschool C. Only one student had an Aboriginal background and that student also attended Preschool
C. The range of languages spoken is presented in Table 3.
Table 3.
Languages Spoken by Preschool Students
Languages Frequency Percent Valid Cumulative Percent Percent Polish 1 .9 .9 .9 Yugoslav 2 1.8 1.9 2.8 Sinhalese 1 .9 .9 3.8 Greek 1 .9 .9 4.7 Persian 1 .9 .9 5.7 English 100 87.7 94.3 100.0
Sub-total 106 93.0 100.0 Missing 9.00 8 7.0 Total 114 100.0
3.1.2 PARENTS
Personal information relating to the family and parents was collected in Parent
Survey 1 (see Appendix C) distributed in November of the preschool year. Ninety- three percent of parents returned the first survey. The majority of families (94%) were two-parent families, with 6% of mothers indicating they lived in single-parent households. The first survey was completed mostly by the mother of the household, with just 5% being completed by the father.
Chapter 3: Method 117 The age range for female parents was 21 to 50 years with a mean age of 35 years, while the age range for male parents was 26 to 55 years with a mean age of 37 years.
Data were gathered relating to the occupation and highest level of education for both male and female adults in the families. Occupations were classified into six categories using the Australian Standard Classification of Occupations (ASCO)
(Australian Bureau of Statistics, 1990). Occupations and education levels of mothers in the study are presented first, followed by those for fathers.
3.1.2.1 Mothers
The six categories adapted from ASCO were Category 1: professional, manager or administrator; Category 2: tradesperson, para-professional or self-employed;
Category 3: salesperson, clerk; Category 4: labourer, plant & machinery operator;
Category 5: student, deceased or unemployed; Category 6: home duties. Mothers’ occupations are shown in Figure 4 and the distribution by school is presented in
Table 4.
Chapter 3: Method 118 50
40
30
Percent 20
10
0 Mis hom student/ labour sales/cle t prof rade sing e / e duti e se ssi une r/ r lf on/ e pl k -employed s mpl ant opera ma na oye ger d
Mothers' Occupation
Figure 4. Mothers’ occupations when their children were in preschool
Table 4
Mothers’ Occupations for Each Preschool
ASCO Category Frequency/% Frequency/% Frequency/% Frequency/% Total Preschool A Preschool B Preschool C Home duties 44 (38.6) 17 (39.5) 14 (42.4) 13 (34.2)
Student/ unemployed 2 (1.8) 0 (0.0) 0 (0.0) 2 (5.3)
Labourer, plant 10 (8.8) 1 (2.3) 3 (9.1) 6 (15.8) operator
Salespersons, clerks 12 (10.5) 3 (7.0) 3 (9.1) 6 (15.8)
Trade, self employed 18 (15.8) 11 (25.6) 3 (9.1) 4 (10.5)
Professional, manager, 19 (16.7) 7 (16.3) 7 (21.2) 5 (13.2)
Sub-total 105 (92.1) 39 (90.7) 30 (90.9) 36 (94.7)
Missing 9 (7.9) 4 (9.3) 3 (9.1) 2 (5.3) Total 114 (100.0) 43 (100.00) 33 (100.0) 38 (100.0)
Chapter 3: Method 119 ‘Home duties’ was the most common occupation for mothers in this study (38.6%).
A smaller percentage worked in paraprofessional (15.8%) and professional managerial or administrative roles (16.7%). More that 34% of mothers in each
Preschool listed home duties as their occupation. The highest percentage within this category (42.5%) was shown for Preschool B. In relation to professional or managerial roles in the workforce, Preschool B had the highest percentage of mothers working in this category (21.2%), while Preschool C had the lowest percentage (13.2%).
Information relating to the highest level of education for mothers also was gathered and the data are presented in Figure 5 using four categories: Year 10 & Year 11;
Year 12; Technical and Further Education (TAFE) and University. Data for mothers’ education level distributed by Preschool are shown in Table 5.
40
30
20 Percent
10
0 Year 10/11 Year 12 TAFE University missing
Mothers' Education Level
Figure 5. Mothers’ education level when their children were in preschool
Chapter 3: Method 120 Table 5
Highest Education Level for Mothers
Level Frequency/% Frequency/% Frequency/% Frequency/% Total Preschool A Preschool B Preschool C
Year 10/11 35 (30.7) 14 (32.6) 8 (24.2) 13 (34.2)
Year 12 24 (21.1) 8 (18.6) 8 (24.2) 8 (21.1)
TAFE 21 (18.4) 5 (11.6) 7 (21.2) 9 (23.7)
University 24 (21.1) 11 (25.6) 6 (18.2) 7(18.4)
Missing 10 (8.7) 5 (11.6) 4 (12.2) 1 (2.6)
Total 114 (100.0) 43 (100.0) 33 (100.0) 38 (100.0)
When examining the total sample of mothers the greatest number are found in the category Year 10/11 qualifications (30.7%). Twenty-one percent of mothers held university qualifications. Education and occupation profiles for mothers in each setting are distinctively different.
Preschool A had the highest percentage of mothers with a university qualification
(25.6%) and Preschool C the highest percentage with Year 10/11 (34.2%).
Preschools B and C had a very similar percentage of mothers with university qualifications (18.2% and 18.4%) and also a similar percentage of mothers with either Year 12 or TAFE qualifications (Year 12 + TAFE combined 45.4% and
44.8% respectively). Profiles of mothers for each setting are now examined.
3.1.2.2 Mothers in Preschool A
Mothers in Preschool A have the greatest percentage with university qualifications
(25.6%), but a lower percentage (16.3%) indicated they worked in professional
Chapter 3: Method 121 occupations. The largest group of mothers in any qualification category is shown for
Year 10/11 qualifications (32.6%), but a very low percentage (2.3%) of mothers in
Preschool A indicated they worked in the lesser skilled occupational categories. If the two highest levels for qualifications are combined (university + TAFE), 37.2% of mothers in Preschool A indicated these categories.
3.1.2.3 Mothers in Preschool B
Mothers in Preschool B presented a different profile. The highest percentage
(42.4%) in any one setting listed home duties as their occupation. A relatively large percentage (21.2%) compared to the whole sample (16.7%) indicated they worked in professional and/or managerial occupations despite 18.2% having listed the highest qualification held as being a university qualification. A similar percentage of mothers indicated Year 10/11 qualifications (24.2%), Year 12 (24.2%) and TAFE
(21.2%). Two of these categories (Year 12 and TAFE) were higher than for the whole sample. If university and TAFE qualifications are combined this accounts for
39.4% of mothers in Preschool B.
3.1.2.4 Mothers in Preschool C
The percentage of university-qualified mothers in Preschool C is 18.4%. This result is very similar to the result for Preschool B (18.2%), but lower than the percentage for the whole sample (21.1%). Mothers in this setting also recorded the highest percentage with Year 10/11 qualifications (34.2%). This percentage is higher than
Chapter 3: Method 122 that recorded for the whole sample (30.7%). Mothers in this setting indicated the lowest percentage working in professional/managerial occupations (13.2%). When university and TAFE qualifications are combined this group has the highest percentage (42.1%) in these two levels of qualifications.
In relation to mothers' occupational and educational level some distinctions exist particularly in relation to professional and managerial occupations and highest levels of qualification. In broad terms, Preschool A appears to have the most highly qualified mothers if university qualifications are examined, but if the two highest levels (university + TAFE) are examined then mothers in Preschool C are the most qualified. Additionally, mothers in Preschool B have the highest percentage (21.2%) working in professional occupations. Profiles of mothers are complex and not easily delineated or compared. The task is made more difficult when more than 30% of mothers in each setting are currently not in the paid workforce but are occupied with home duties.
3.1.2.5 Fathers
The occupational and educational profile of fathers is now examined. These data are presented in Figures 6 and 7 and Tables 6 and 7.
Chapter 3: Method 123 50
40
30
Percent 20
10
0 m home dut st l sale tr profes i udent abou ade/ ssi s/ ng rer cl sel si /unempl / er f on/ ie pl k -em s ant m opera pl anager o oyed yed
Fathers' Occupation
Figure 6. Fathers’ occupation when their children were in preschool
Table 6 Fathers’ Occupations for Each Preschool Occupations Frequency/% Frequency/% Frequency/% Frequency/% Total Preschool A Preschool B Preschool C
Home duties 1 (0.9) 0 (0.0) 0 (0.0) 1 (2.6)
Deceased, unemployed, 2 (1.8) 1 (2.6) 0 (0.0) 1 (2.6) student
Labourers, plant & 9 (7.9) 5 (11.6) 0 (0.0) 4 (10.5) machinery operators
Salespersons, clerks 7 (6.1) 1 (2.3) 0 (0.0) 6 (15.8)
Tradespersons, self- 27 (23.7) 5 (11.6) 13 (39.4) 9 (23.7) employed, para- professional
Professional, managers 53 (46.5) 26 (60.5) 16 (48.5) 11 (28.9) & administrators
Sub-total 99 (86.8) 38 (88.4) 29 (87.9) 32 (84.2)
Missing 15 (13.2) 5 (11.6) 4 (12.1) 6 (15.8)
Total 114 (100.0) 43 (100.0) 33 (100.0) 38 (100.0)
Chapter 3: Method 124
The occupational profile for fathers in the study was substantially different from that of mothers. Only one father (0.9%) listed home duties as an occupation compared to
38.6% of mothers. The majority (46.5%) worked in professional, managerial roles with the second largest group (23.7%) indicating a trade or a paraprofessional occupation.
Information presented in Table 6 indicates considerable difference in the occupational profile for fathers in each Preschool. The greatest percentage of fathers in professional or managerial roles (60.05%) was shown for Preschool A. Preschool
B has 48.5% and Preschool C has 28.9%. Preschool A also has the greatest percentage of labourers, plant or machinery operators (11.6%) while Preschool B has none. Data on the highest educational level achieved by the fathers are presented in Figure 7 and Table 7
30
20 Percent
10
0 Other Year 10/11 Year 12 TAFE University Missing
Fathers' Education Level
Figure 7. Fathers’ education level when their children were in preschool
Chapter 3: Method 125 Table 7
Highest Education Level for Fathers
Qualifications Frequency/% Frequency/% Frequency/% Frequency/% Total Preschool A Preschool B Preschool C Other 1 (0.9) 0 (0.0) 0 (0.0) 1 (2.6)
Year 10/11 25 (21.9) 11 (25.6) 5 (15.2) 9 (23.7)
Year 12 20 (17.5) 9 (20.9) 7 (21.2) 4 (10.5)
TAFE 22 (19.3) 6 (14.0) 8 (24.2) 8 (21.1)
University 32 (28.1) 13 (30.2) 9 (27.3) 10 (26.3)
Missing 14 (12.3) 4 (9.3) 4 (12.1) 6 (15.8)
Total 114 (100.0) 43 (100.0) 33 (100.0) 38 (100.0)
The largest single group (28.1%) across the sample within any one category was university-trained. Slightly smaller percentages received their highest level of education in Year 10/11 (21.9%) or in TAFE (19.3%).
A similar percentage of fathers in each Preschool indicated they had university qualifications (Preschool A, 30.2%; Preschool B, 27.3%; Preschool C, 26.3%).
When examining those with Year 10/11 qualifications, it can be seen that Preschools
A and C have a similar percentage (25.6% and 23.7%), while in Preschool B data showed 15.2%.
The highest educational qualification and occupation of fathers in the study presents a different profile from that of mothers. Overall fathers have higher qualifications from university (28.1%) and TAFE (19.3%) showing a total of 47.4%. Mothers, on the other hand, indicated university qualifications for 21.1% of the sample and
Chapter 3: Method 126 TAFE qualifications for 18.4%, a total of 39.5%. The main occupational difference occurred with 38.6% of mothers listing home duties as their occupation and this contrasts with .9% of fathers.
The percentage of fathers working in professional and/or managerial occupations was 46.5% and this was the highest percentage category for fathers. Para- professional and trade occupations accounted for 23.7%, the second largest percentage category of occupation. A small percentage of fathers listed salesperson/clerk (6.1%) and labourer, plant and machinery operator (7.9%) as their occupation.
When comparing occupations of mothers and fathers, it can be seen that more fathers work in professional and para-professional occupations than mothers, and that more mothers work in the semi-skilled categories of occupation.
3.1.2.6 Fathers in Preschool A
Fathers in Preschool A have the highest percentage of university qualifications
(30.2%), compared to Preschool B (27.3%) and Preschool C (26.3%). If the two highest levels of educational qualifications (university and TAFE) are combined, the fathers in Preschool A (44.2%) are the least qualified of all three groups with
Preschool B having 51.5% and Preschool C having 47.4%. Quite a large percentage of fathers in Preschool A recorded Year 12 (20.9%) and Year 10/11 (25.6%) as their highest level of education, but these fathers were not working in occupations necessarily commensurate with their educational qualifications. The largest
Chapter 3: Method 127 percentage group of fathers in any setting was listed for Year 10/11 qualifications in
Preschool A with 25.6%.
When comparing the three preschool settings, the biggest difference occurred for professional/managerial occupations in Preschool A with 60.5% listing this category. This contrasts with 48.5% in Preschool B and 28.9% in Preschool C. In relation to para-professional/trade occupations and labourer/plant and machinery operator occupation, 11.6% work in both of these categories and just 2.3% in the salesman/clerk category. Thus, while fathers in Preschool A do not appear to be more educationally qualified, they are more commonly found working in professional occupations than fathers in either Preschool B or C. In general terms, they appear to be working in occupations usually associated with higher educational qualifications than they possess.
3.1.2.7 Fathers in Preschool B
Fathers in Preschool B present a different educational/occupation profile. Almost half of these fathers (48.5%) work in professional and/or managerial roles and a sizeable percentage, 39.4% work in paraprofessional/trade professions. These two categories account for 87.9% of fathers in this setting. No other category of occupation was recorded by fathers from this Preschool. Information relating to the remaining 12.1% was unavailable due to one-parent family situations.
Chapter 3: Method 128 Fathers in Preschool B were the most highly qualified when university and TAFE categories are combined (51.5%), but fewer had university qualifications than fathers in Preschool A.
3.1.2.8 Fathers in Preschool C
In Preschool C the highest percentage group of fathers (28.9%) work in professional/managerial occupations. This compares to 60.5% for Preschool A and
48.5% for Preschool B. While fathers in Preschool C are not the least qualified group, they appear to be working in occupations more closely related to their qualifications. Year 10/11 was listed as the highest level of educational qualification for 23.7%, and this compares with 21.9% for the whole sample.
In summary, the majority of fathers from Preschool A (60.5%) work in professional occupations, the highest percentage for any context in the study, despite not having the highest level of qualifications. There is an apparent discrepancy in the data when comparing the relationship between the educational qualifications and occupations.
Fathers in Preschool B work only in professional or para-professional/trade occupations and when combining the two highest levels of educational qualifications, they are the most qualified. When comparing occupations across the whole sample, fathers in Preschool C account for the highest percentage working in semi-skilled occupations (sales/labourer/plant/machinery operator), although they are the second most qualified when comparing educational qualifications (university and TAFE combined).
Chapter 3: Method 129 3.1.3 YEAR 1 TEACHERS
When students progressed to Year 1 at the beginning of the school year they were distributed across 11 classes. There were four classes at School A and School C and three at School B. Teachers working in each of these classes participated in the study.
Ages of the Year 1 teachers ranged from 24 years to 62 years and their teaching experience ranged from three to 32 years. Their specific experience in the early years (Years 1 to 3) was one to 25 years with a mean of 12 years. Teachers’ qualifications varied. Two teachers had a Teaching Certificate (two years of training), six had a Diploma (three years of training) and three had a Bachelor degree (four years of training).
3.2 SETTINGS
Schools were selected to represent variation of locality, school size and population- type. Information obtained from school administrators was used to describe each school setting and its population.
Preschool/School A is located in a shire situated to the North of the Capital city in an area that is experiencing rapid growth in new residential housing. This school is a co-educational Catholic school catering for students from Preschool to Year 7.
School population at the commencement of the study was 532. Parents whose children attend this school are seen to be middle class in terms of socio-economic status where 95% of families pay school fees. Parents are supportive of the school as
Chapter 3: Method 130 evidenced by their high attendance at school functions, celebrations, liturgies,
Masses, sporting events and providing assistance in the classroom.
Preschool/School B is located in a shire to the far South of the Capital city. The school is a co-educational Catholic school catering for students from Preschool to
Year 7. The school population at the commencement of the study was 655 students and included a small proportion of non-Australian born children for whom English is a second language. No students in the sample from this setting were from a non-
English speaking background. Students attending this school were from various social and economic backgrounds with a large proportion of families living as single-parent families.
Preschool/School C also is located to the South of the Capital city and is within the main City Council area. The school is a co-educational State school catering for students from Preschool to Year 7. At the commencement of this study the school population was 890 students. Parents whose children attend this school come from a wide range of nationalities and many were born overseas. Parents were employed in a range of occupations with the majority working in semi-professional, semi-skilled or unskilled occupations. Parents are reported to be very supportive of the school and show a sustained interest in their children’s education.
Chapter 3: Method 131 3.3 CONTENT AND ADMINISTRATION OF ASSESSMENT
INSTRUMENTS
Several tasks were constructed to assess students’ literacy three times throughout the study. Literacy Assessment Tasks (LAT 1) were used in November of the preschool year, May/June of Year 1 (LAT 2) and November of Year 1 (LAT 3). A number of
Clay’s strategies described in the Observation Survey of Early Literacy
Achievement (Clay, 1993a) were used along with other tasks to gauge phonological awareness, environmental print knowledge, writing ability and print awareness.
Administration of LAT was on a one-to-one basis throughout the study. Each session took approximately 45 minutes and for most students this occurred in the one session unless interrupted by morning tea or a lunch break.
3.3.1 LITERACY ASSESSMENT TASKS: THE PRESCHOOL PERIOD
The first assessment of students’ literacy knowledge and understanding took place in
November of the preschool year. Students completed 9 tasks (see Appendix D) and these were presented in a non-threatening, relaxed manner. Each of the tasks is now described.
3.3.1.1 Environmental Print Awareness
Thirteen food products were used with the students to ascertain if they could recognise a product and its name in three different ways. Where the level of contextualisation was high, the whole product was presented for recognition. Where there was a low level of contextualisation, only the name of the product on a card
Chapter 3: Method 132 was presented. There was no replication of colour, font or print size usually found on the product name for the most decontextualised tasks.
The products used were milk, jam, honey, jelly crystals, juice, milk additive (milo), sandwich spread (peanut butter), breakfast cereal (rice bubbles), snack foods
(twisties, freddo and milky way), savoury biscuits (jatz) and tinned food (spaghetti).
Four tasks were used in order to gauge students' ability to recognise the product and its name. Task 1 involved presenting the whole product to each student. If the student recognised the product, he/she was asked to point to its name as Task 2.
Products used in Tasks 1 and 2 were then removed from sight prior to commencing
Task 3. Cut-out labels for each product were placed on a table for Task 3. And students were asked to select labels they recognised and to name the product. When this task was completed all cut-out labels were removed from sight prior to commencing Task 4. Product names, printed in a plain black font on word cards (see
Appendix E) were used for Task 4. Students were asked to identify the product name on these cards.
3.3.1.2 Story Comprehension
Students had two stories read to them from small picture books. The stories were My
Grandma (1994) by S. Keane and Oscar Got the Blame (1997) by T. Ross (see
Appendix F). These stories were selected using five criteria.
The first criterion was that the text needed to be a true narrative, one where the story included a setting, complication and resolution. Many texts produced for young
Chapter 3: Method 133 students can be classed as caption books where a single sentence merely describes an illustration and no real story develops. These types of texts were not chosen because students' listening comprehension was the critical feature of the task.
The second criterion was that each text needed to be relatively brief. The selected texts took approximately two minutes to read and this allowed time for the student to look briefly at the illustrations on each page. Due consideration was given to the age of the preschool students who were to complete a number of literacy-related tasks.
The chosen texts were of similar length with My Grandma 145 words long and
Oscar Got the Blame being 159 words long.
The third criterion was that the story needed to be realistic, suitable for students of preschool age and not too conceptually demanding. This criterion also was met with these texts as the plot of the first story related to a Grandma who was ‘a little bit different’ and the second text was about a boy who ‘got into mischief’. The fourth criterion was that the story should contain humour. The final criterion was the text needed to be brightly presented. The selected texts met all five criteria.
The task required students to listen to the stories being read by an adult and then to verify statements proposed by the adult. The statements probed students' understanding of literal and inferential comprehension. Four statements for each comprehension category and two nonsense statements were posed for each story (see
Chapter 3: Method 134 Appendix G). The stories were not presented to the students immediately following each other, but were presented as the second and eighth component of LAT 1.
3.3.1.3 Student Writing Own Name and Recognising Letter Names
Each student was asked to write his or her name on a piece of paper. Each also was required to identify as many names of these letters as possible.
3.3.1.4 Robinson’s Test of Writing Vocabulary
Robinson's Test of Writing Vocabulary described in Clay (1985, pp35-36) was used.
The task required a student to write as many words as possible in a 10-minute period. Each student was asked to write other words apart from their own name.
When students indicated they could not write any other words, they were not forced or expected to complete this task.
3.3.1.5 Letter Knowledge and Identification:
Students were asked to identify all of the upper and lower case letters in three ways following the procedure outlined by Clay (1985). Students named the letter, then provided the sound made by the letter and gave a word that starts with the letter.
3.3.1.6 Concepts About Print Test: Version Sand
Each student completed Clay’s Concepts About Print Test (1979a; 1985; 1993a), version Sand (Clay, 1979b) (see Appendix H). A description of the test procedures and the 24 test items are outlined below. The test is conducted with an adult sharing the text, Sand, individually with a student. The text is a children's story produced mainly in black and white and contains a number of errors that students are asked to
Chapter 3: Method 135 identify. Errors include one illustration that is upside down, one page where print is upside down, one page where lines of print are in reverse order and two pages where letters within eight words are in mixed order. Throughout the test students are asked to point to various parts of the text to help identify whether they have observed the staged errors. Details of test items for the storybook Sand include:
Test: Orientation of a book (Cover).
Item 1: The student is given the storybook vertically with the spine pointing towards them and asked to show the tester the front of the book. The tester says “Show me the front of this book.”
Test: Concept that print, not picture, carries the message (Pages 2/3).
Item 2: The tester says, “I’ll read this story. You help me. Show me where to start reading. Where do I begin to read?”
Test: Directional rules (Pages 4/5)
Item 3: The tester says, “Show me where to start.”
Item 4: The tester says, “Which way do I go?”
Item 5: The tester says, “Where do I go after that?”
Test: Word by word pointing (Pages 4/5)
Item 6: The tester says, “Point to it while I read it.”
Test: Concept of first and last (Page 6)
Item 7: The tester says, “Show me the first part of the story. Show me the last part.”
Test: Inversion of picture (Page 7)
Item 8: The tester says, “Show me the bottom of the picture.”
Chapter 3: Method 136 Test: Response to inverted print (Pages 8/9)
Item 9: The tester says, “Where do I begin?’ Which way do I go?’ ‘Where do I go after that?”
Test: Line sequence (Page 10/11)
Item 10: The tester reads the bottom line first and says, “What’s wrong with this?”
Test: A left-hand page is read before a right-hand page (Page 12)
Item 11: The tester says, “Where do I start reading?”
Test: Word sequence (Page 12)
Item 12: The tester says while pointing to page number 12, “What’s wrong on this page?”
Test: Letter order (Page 13)
Item 13: The tester says while pointing to page number 13, “What’s wrong on this page?”
Test: Re-ordering letters within a word (Page 14)
Item 14: The tester says, “What’s wrong with the writing on this page?”
Test: Meaning of a question mark (Page 15)
Item 15: The tester says while pointing to the question mark, “What’s this for?”
Test: Punctuation (Pages 16/17)
Item 16: The tester says while pointing to the full stop, “What’s this for?”
Item 17: The tester says while pointing to the comma, “What’s this for?”
Item 18: The tester says while pointing to quotation marks, “What’s are these for?”
Chapter 3: Method 137 Test: Capital and lower case correspondence (Pages 16/17)
Item 19: The tester says while pointing to ‘T’, “Find a little letter like this.”
The tester says while pointing to ‘M’ then ‘H’, “Find a little letter like this.”
Test: Reversible words (Pages 18/19)
Item 20: The tester says, “Show me - was. Show me - no.”
Test: Letter concepts (Page 20)
Item 21: The tester gives the student two pieces of card (13cm x 5cm) and says, “I want you to push the cards across the story like this until all you can see is
(deliberately with stress) just one letter.” The tester then says, “ Now show me two letters.”
Item 22: The tester says, “Show me just one word. Now show me two words.”
Test: First and last letter concepts (Page 20)
Item 23: The tester says, “Show me the first letter of a word. Show me the last letter of a word.”
Test: Capital letter concepts (Page 20)
Item 24: The tester says, “Show me a capital letter.” (Clay 1985, pp. 27-31)
3.3.1.7 Canberra Word Test
Clough, McIntyre and Cowey (1990) devised the Canberra Word Test. High frequency words commonly found in children's reading materials used in primary schools in Canberra, Australia, were selected as items for the test. The sampling of children’s reading materials included Storybox (Rigby), Sunshine Books (Rigby),
Eureka Treasure Chest (Longman Cheshire) and Bookshelf (Martin Educational).
Forty-six of the most frequently occurring words were chosen for the test. The test
Chapter 3: Method 138 has three versions A, B and C, each consisting of 15 words. According to the authors, the test ‘does not discriminate between better readers, but it may be used together with careful observations, such as running records of text reading, to assess children's early progress’ (Clough, McIntyre, & Cowey 1990, pp. 2). Field trialling of the test was conducted in schools in Canberra with 300 children aged between six and seven years. Normalised stanine scores were developed from the trial and these are published with the Canberra Word Test.
List B was used in this study. Words were placed on a card, printed in a column using a large font. During the test the words were covered with a piece of paper and revealed one at a time. Students were asked to read as many of the fifteen words as possible. The words in List B are: dog, a, we, can, went, Mum, are, of, will, up, was, that, she, not, here (see Appendix I).
3.3.1.8 Print Knowledge Task
The nursery rhyme, Humpty Dumpty (see Appendix J), was printed using a large font on two charts. One was left as a whole text and the other was cut into four strips. Students were asked to complete 17 print awareness and word knowledge tasks relating to the rhyme using the chart or the strips of print. The tasks completed by students included:
1. Pointing to the first line of print;
2. Pointing to a word;
3. Pointing to a letter;
4. Pointing to a name in the rhyme;
Chapter 3: Method 139 5. Finding the word wall;
6. Finding a rhyming word for wall;
7. Finding a word that begins the same way as had;
8. Matching the print strips to the whole chart;
9. Recognising that a strip of text is out of order;
10. Fixing the strip that is out of order;
11. Recognising a strip that is upside down;
12. Fixing the strip that is upside down;
13. Reading the rhyme while pointing to each word;
14. Pointing to the word Humpty;
15. Pointing to the word sat;
16. Pointing to the word fall;
17. Pointing to the word great;
3.3.1.9 Sutherland Phonological Awareness Test
Sutherland Phonological Awareness Test (SPAT) (Neilson, 1995, 1999) (see
Appendix K) is an individually administered test that consists of 11 auditory subtests and two subtests that involve non-word reading and non-word spelling. Subtests are arranged in approximate order of difficulty and each subtest begins with a demonstration and practice items. Four test items of approximately equivalent difficulty are used for each subtest. Subtests 1-5 were used with the students during
LAT 1. The five subtests consisted of syllable counting; rhyme detection; rhyme production; onset identification and final phoneme identification. Details of the tasks are:
Chapter 3: Method 140
Subtest 1: Syllable Counting
Demonstration and practice: {kangaroo; alligator}
Test Items 1-4: {picnic; television; elephant; supermarket}
Subtest 2: Rhyme Detection
Demonstration and practice: {cat, bell, bat} {pig, dig, cup}
Test Items: 1. {map, tap, kite} 2. {sun, shirt, gun} 3. {fox, box, zip} 4. {wall, fish, ball}
Subtest 3: Rhyme Production
Demonstration and practice: {can, fan, man} {cat, fat, ……}
Test Items 1-4: {night, fight, …}{toe, show, ...}{bed, red, ...}{four, sore, ...}
Subtest 4: Onset Identification
Demonstration and practice: {ball = /b/} {sun = /s/}
Test Items 1-4: {fat = /?/} {moon = /?/} {torch = /?/} {girl = /?/}
Subtest 5: Final Phoneme Production
Demonstration and practice: {game = /m/} {boot = /t/}
Test Items 1-4: {bus = /?/} {cap = /?/} {roof = /?/} {duck = /?/ }
3.3.2 LITERACY ASSESSMENT TASKS: MAY/JUNE YEAR 1
Students completed the second set of Literacy Assessment Tasks (see Appendix L) during the May/June period of Year 1. Eight component tasks were used to gauge students' literacy knowledge and understanding and to ascertain their growth in literacy development. Some of the tasks were repeated measures and these are clearly indicated in the list that follows.
Chapter 3: Method 141 3.3.2.1 Student Writes Own Name (Retest)
Each student wrote her/his own name. They were asked to write given name and surname if possible.
3.3.2.2 Robinson’s Test of Writing Vocabulary (Retest)
This task was a retest where each student was asked to write as many words as possible in a period of 10 minutes.
3.3.2.3 Letter Knowledge and Identification (Partial Retest)
Students were asked to identify lower case letters in three ways as described by Clay
(1985).
3.3.2.4 Concepts About Print Test Sand (Retest)
Students completed Clay’s Concepts About Print Test, version Sand (Clay, 1979b) and responded to the 24 items of the test.
3.3.2.5 Canberra Word Test (Retest)
Students were asked to read as many of the fifteen words as possible using the same procedure described previously for LAT 1.
3.3.2.6 Story Comprehension
The story, My Brother John, Church (1990) (see transcript in Appendix M), was read to the students. Literal, inferential and nonsense statements were then posed for verification by the students who responded that the statement was either true or not true. Ten statements were used (see Appendix N).
Chapter 3: Method 142 3.3.2.7 Print Knowledge Task (Retest)
This task used the rhyme Humpty Dumpty and was described previously for LAT 1.
3.3.2.8 Sutherland Phonological Awareness Tasks (Retest)
Subtests 1-5 were used again and included syllable counting; rhyme detection; rhyme production; onset identification and final phoneme identification.
3.3.3 LITERACY ASSESSMENT TASKS: NOVEMBER YEAR 1
Four components of LAT (see Appendix O) were completed with the students in
November of Year 1. As the students had received one year of literacy instruction, the components had to be carefully chosen to suit their levels of literacy development and to avoid a ceiling effect. Some of the previously used LAT components were usable. Other components were upgraded.
3.3.3.1 Ohio Word Test
Ohio Word Test List A, consisting of 20 words, was used with the same method used for the Canberra word test being utilised. Words were presented on a card and gradually uncovered as the students read each one (see Appendix P). The method of construction for this test was described by Pinnell, Lyons, Young and Deford,
(1987). Three versions, A, B and C of the Ohio Word Test are available and each list contains twenty high frequency words taken from the Dolch Word List (Dolch,
1948). Students were asked to read as many of the twenty words from List A as possible. List A words were: and, the, pretty, has, down, where, after, let, here, them, there, over, little, did, what, them, one, like, could, yes.
Chapter 3: Method 143 3.3.3.2 Dictation and Spelling Test
Two sentences were dictated and students wrote these down. Form D and Form E were used. The sentences for Form D were ‘The bus is coming. It will stop here to let me get on’ and the sentences for Form E were ‘The boy is riding his bike. He can go very fast on it’ (Clay, 1985 pp. 38-40). Two scores were allocated, the first for every correct sound correspondence that students wrote, and second for correct spelling of words within the sentences.
3.3.3.3 Concepts About Print Test: Version Stones
Students completed Clay’s Concepts About Print Test, version Stones (Clay, 1979c) and responded to the 24 items of the test. These items were similar to those described for the version, Sand administered in the preschool period (Clay, 1979b).
All test items were the same except for minor changes in Items 9, 19 and 21 where the vocabulary in the story is different.
3.3.3.4 Sutherland Phonological Awareness Tasks (Partial Retest)
Six subtests from the Sutherland Phonological Awareness Test (Neilson, 1995,
1999) were undertaken. Two of these subtests, three and five were repeated measures. The subtests used were Subtest 3: rhyme production; Subtest 5: final phoneme identification; Subtest 6: segmentation 1; Subtest 7: blending; Subtest 8: initial phoneme deletion; Subtest 9: segmentation 2. A demonstration and practice task and four questions were completed for each subtest. Items included in each subtest were as follows:
Chapter 3: Method 144 Subtest 3: Rhyme Production (Retest)
Demonstration and practice: {can, fan, man} {cat, fat, ……}
Test Items 1-4: {night, fight, …}{toe, show, ...}{bed, red, ...}{four, sore, ...}
Subtest 5: Final Phoneme Identification (Retest)
Demonstration and practice: {game = /m/} {boot = /t/}
Test Items 1-4: {bus = /?/} {cap = /?/} {roof = /?/} {duck = /?/ }
Subtest 6: Segmentation 1
Demonstration and practice: {up = /u/ /p/ } {pin = /p/ /i/ /n/}
Test Items 1-4: {am; go; seat; mug}
Subtest 7: Blending
Demonstration and practice: { /i/ + /ce/ = ice} {/m/ + /oo/ + /n/ = moon}
Test Items 1-4: {/s/ + /ee/ = ...}{/d/ + /ay/ = …}{/r/ + /oa/ +/d/ = ...}{/g/ + /a/ +/te/ = …}
Subtest 8: Initial Phoneme Deletion
Demonstration and practice: {boat; minus /b/ = oat} {meat; minus /m/ = eat}
Test Items 1-4: {tame; minus /t/ = ame} {shout; minus /sh/ = out}
{bark; minus /b/ = ark} {mat; minus /m/ = at}
Subtest 9: Segmentation 2
Demonstration and practice: {sleep =/s/ /l/ /ee/ /p/} {snake = /s/ /n/ /a/ ke/}
Test Items 1-4: {trip = /t/ /r/ /i/ /p/} {spoon = /s/ /p/ /oo/ /n/} {beast = /b/ /ea/ /s/ /t/}
{bond =/b/ /o/ /n/ /d/}.
Chapter 3: Method 145 3.3.3.5 Miscue Analysis
Five texts were selected for Year 1 students to read. Reading Recovery levels of texts (Department of Education, Victoria. 1997) at Levels 1, 6, 12, 16, and 24 were used (see transcripts Appendix Q). The chosen texts were:
Level 1: A Toybox (Butler, 1989a) and The Farm (Butler, 1989b);
Level 6: Having a Picnic by (Garland, 1995);
Level 12: If You Like Strawberries, Don't Read This Book by (Noonan, 1993);
Level 16: First Flight by (McPhail, 1987);
Level 24: Grandpa's Cardigan by (Watson, 1993).
Each student commenced reading Having a Picnic by Garland (1995), a Reading
Recovery Level 6 text. A Level 6 text was chosen after examining the current practices relating to the Year 2 Diagnostic Net, an initiative of the Education
Department of Queensland where a miscue analysis is used for diagnostic purposes in May of Year 2 (Department of Education Queensland, 1995). It was found that a
Level 16 text is used in May of Year 2 and thus to use a Level 6 text in November of
Year 1 was considered to be a reading task at an appropriate level of challenge for the majority of students.
Trials in a pilot study with students of the same age (Young, 1996) showed that an
83% accuracy rate was a suitable level of reading accuracy to determine if a student could be asked to attempt to read a more advanced text. The 83% cut-off level was applied in this study. Students progressed through the remaining selected levels of
Chapter 3: Method 146 text if 83% accuracy was achieved. If the student was unable to read the Level 6 text then the simpler Level 1 texts The Farm and A Toybox were read. Students were asked to retell after reading each book and comprehension questions also were asked
(see Appendix R).
3.3.4 SURVEYS
3.3.4.1 Parent Surveys 1 and 2
Parent Survey 1 (see Appendix C) was sent to parents in November of the preschool year. Parents provided information relating to family size and their preschool child’s relative position in the family. Parents also provided information concerning parents’ occupations, highest level of parents’ education, cultural background of family members and home literacy practices.
Parent Survey 2, (see Appendix S) was sent to parents in November of Year 1 and information relating to home literacy practices, parents’ perceptions of their child’s personal characteristics and literacy progress were gathered.
3.3.4.2 Teacher Survey
A teacher survey (see Appendix T) was sent to Year 1 teachers in March of Year 1.
It sought information relating to each teacher’s experience, qualifications and perceptions of literacy experiences of students as they commenced school.
Information about commonly-used teaching strategies and literacy resources also was collected.
Chapter 3: Method 147 3.5 CHECKLISTS
3.3.5.1 Teacher Checklists 1 and 2
Teacher Checklist 1, (see Appendix U) was sent to Year 1 teachers in March. This checklist sought information about students’ school adjustment, current work habits and literacy progress. A second checklist, Teacher Checklist 2, (see Appendix V) was completed in November of Year 1. Teachers provided information relating to students’ current school and work habits as well as their literacy progress.
3.4 METHODOLOGICAL CONSIDERATIONS
A correlational, longitudinal study was designed in order to predict patterns of early literacy achievement after one year of schooling. This study used descriptive statistics complemented by relevant correlations to enable an investigation of potential relationships. Predictive associations rather than causality, is determined by this type of study. Further studies using large representative samples may later be conducted to investigate the relationships between variables in greater depth and perhaps determine causality (Black, 1999; Burns, 2000). Analyses within this study moved beyond simple correlations in that Principal Component Analyses on student, parent and teacher data also were utilised prior to determining relationships. Cluster
Analyses were then used to group preschool students with similar literacy profiles together. These cluster groups were then used to examine if literacy progress made by students from Preschool to the end of Year 1 remained constant and if literacy variables from Preschool were able to predict literacy achievement at the end of
Year 1.
Chapter 3: Method 148
In summary, this study of twelve months duration took place with 114 young students, their parents and 11 Year 1 teachers from the end of the preschool year to the end of Year 1. Data were gathered using measures of achievement with the students, surveys with parents and surveys and checklists with teachers. Cross-time comparisons of literacy achievement were possible as data were gathered from the students three times during the study. Comparisons were made possible first by the test/retest design that occurred from the end of Preschool to May/June of Year 1.
This was followed by an examination of students’ literacy results from the prior-to- school period with their literacy achievement in both May/June and November of
Year 1. Different literacy measures were used at the end of Year 1 to account for students’ developing literacy skills. Cross-time comparisons also were conducted with data from parent surveys, teacher surveys and teacher checklists. Here information relating to child characteristics, home literacy practices and school literacy behaviours and achievements were compared.
Four considerations legitimise the use of a correlational design, at times making such studies preferable. First, because of practical and ethical considerations, some relationships can only be examined using studies with a correlational design.
Second, correlational studies are useful when testing hypotheses that may lead to new findings or relationships. Third, correlational studies are best conducted in a range of naturally-occurring contexts rather than in a laboratory. Finally, because of
Chapter 3: Method 149 external validity there are opportunities for trialling predictor studies (Heiman,
2001).
Analyses of data for this study were conducted using SPSS Release 10 (SPSS Inc,
2001). Initially, descriptive statistics were calculated including frequency and frequency distributions, mean and standard deviation. These results were compared and displayed using charts or frequency tables. In order to examine the relationships between variables, correlation analyses were conducted. Pearson’s correlation was used in this study to measure the strength of the relationship between two variables
(Griffiths, Stirling & Weldon, 1998). Relationships are reported using Pearson’s correlation coefficient r.
Factor analyses also were conducted. This technique “is a data reduction technique used to reduce a large number of variables to a smaller set of underlying factors that summarise the essential information contained in the variables” (Coakes & Steed,
1999, p. 155). Factors generated from the data included demographic factors, background factors derived from perceptions of parents and teachers and achievement factors derived from the students’ test scores. These factors were then subjected to analysis of variance (ANOVA) or multivariate analysis of variance
(MANOVA) to determine relationships among dependent and independent variables. Degrees of significance are also reported.
Chapter 3: Method 150 Cluster analyses were then conducted. The technique ‘uses similarities or proximities between people as the basis for producing clusters’ (Drew & Bishop,
1998, p. 243). Cluster analysis was carried out using literacy achievement measures gathered from the students in Preschool. Clusters of students with similar profiles were determined. Three different sets of achievement scores (factor scores) were used to determine the clusters in order to examine ways of predicting literacy achievement after one year of formal schooling. Three cluster trials were conducted and Variable Sets A, B and C were devised. Trial one involved using the six-factor result devised from Concepts About Print Test version Sand (Clay, 1979b). Trial two utilised a combination of two environmental print factors and the single letter knowledge factor. Trial three utilised two phonological awareness factors devised from Sutherland Phonological Awareness tests. All three variable sets were subjected to further analyses in order to determine relatedness and capabilities for predicting patterns of literacy achievement after one year of schooling. These analyses included Pearson’s chi-square test for relatedness.
3.5 REPORTING RESULTS
This study involved an investigation of how literacy capabilities develop over the first year of schooling for 114 young students with a view to predicting later patterns of literacy achievement. A large corpus of data collected from students, their parents and teachers and the reporting of results from data analyses needed careful consideration and logical sequencing. It is with these factors in mind that the following plan for reporting of results has been adopted.
Chapter 3: Method 151 Data are reported in an historical time sequence commencing with the preschool
period then moving to early Year 1, May/June of Year 1 and lastly November of
Year 1. The second important consideration is how to present these data logically so that the range of analyses conducted will enhance the story emerging from the data.
It is with this consideration in mind that the data is presented using two broad headings:
• Describing and Correlating Data and
• Reducing Dimensions: Seeing Relationships in Data.
Each of these headings will be used three times so that results from all data collected over the twelve-month period may be reported. A schema will be used at the beginning of each chapter and relevant sections of chapters to guide the reader through the results of this study. Rows within the schema will be shaded to identify the relevant section of the results being reported. The schema is presented here.
CHAPTER CONTENT DESCRIPTION Chapter 4: Describing and Correlating Preschool/Early Year 1 Data 4.1 Parent Survey 1 (November of Preschool) 4.2 Literacy Assessment 1 (November of Preschool) 4.3 Teacher Checklist 1 (March of Year 1) 4.4 Teacher Survey (March of Year 1) Chapter 5: Reducing dimensions: Relationships in the Preschool/Early Year 1 Data 5.1 Factor Analysis of Parent Survey 1;Teacher Checklist 1; Literacy Assessment 1 5.2 Cluster Analysis based on Literacy Assessment 1 – Preschool period Chapter 6: Describing and Correlating Year 1 (May) Data 6.1 Literacy Assessment 2 (May of Year 1) Chapter 7: Reducing dimensions: Relationships in the Year 1 (May) Data 7.1 Factor Analyses: Literacy Assessment 2 7.2 Cluster Analysis of Literacy Assessment 2 Chapter 8: Describing and Correlating Year 1 (November ) Data 8.1 Literacy Assessment 3 (November of Year 1) 8.2 Parent Survey 2 8.3 Teacher Checklist 2 Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 9.1 Factor Analysis: Parent Survey 2; Teacher Checklist 2; Literacy Assessment 3 9.2 Cluster Analysis of Literacy Assessment 3
Chapter 3: Method 152 CHAPTER FOUR
DESCRIBING AND CORRELATING PRESCHOOL DATA
Data collected from parents, students and Year 1 teachers during the preschool and early Year 1 period are reported in this chapter. The terms ‘child or children’ will be used when referring to young participants in this study when their home or parents are being discussed. The terms ‘student or students’ will be used when referring to them in the preschool or school context. Data in the preschool period were gathered using:
• Parent Survey 1 (see Appendix C) in November of the preschool year;
• Literacy Assessment Tasks (see Appendix D) with students in November of the
preschool year;
• Teacher Checklist 1 (see Appendix U) by Year 1 teachers in March of Year 1
and
• Teacher Survey (see Appendix T) by Year 1 teachers in March of the school
year.
Two research questions are addressed through these results.
1. What knowledge and understanding about literacy do students bring to school?
3. How do aspects of prior-to-school literacy knowledge and understanding relate to
one another and students’ background?
Data gathered from parents relate to family background information, home literacy practices and parents’ perceptions of the learning characteristics of their children.
Chapter 4: Describing and Correlating Preschool Data 153 Data gathered from Year 1 teachers relate specifically to teachers’ perceptions of the students’ literacy knowledge and understanding and classroom conduct observed during the first six to eight weeks of Year 1. Descriptive statistics are reported first, then multivariate analysis of effects relating to school, age or gender.
As described earlier a schema is used to guide the reader through the chapters where all results for the longitudinal study are reported. The shaded row indicates the current section.
CHAPTER CONTENT DESCRIPTION Chapter 4: Describing and Correlating Preschool/Early Year 1 Data 4.1 Parent Survey 1 (November of Preschool) 4.2 Literacy Assessment 1 (November of Preschool). 4.3 Teacher Checklist (March of Year 1) 4.4 Teacher Survey (March of Year 1). Chapter 5: Reducing dimensions: Relationships in the Preschool/Early Year 1 Data 5.1 Factor Analysis of Parent Survey 1;Teacher Checklist 1; Literacy Assessment 1. 5.2 Cluster Analysis based on Literacy Assessment 1 – Preschool period. Chapter 6: Describing and Correlating Year 1 (May) Data 6.1 Literacy Assessment 2 (May of Year 1) Chapter 7: Reducing dimensions: Relationships in the Year 1 (May) Data 7.1 Factor Analyses: Literacy Assessment 2 7.2 Cluster Analysis of Literacy Assessment 2 Chapter 8: Describing and Correlating Year 1 (November ) Data 8.1 Literacy Assessment 3 (November of Year 1) 8.2 Parent Survey 2 8.3 Teacher Checklist 2 Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 9.1 Factor Analysis: Parent Survey 2; Teacher Checklist 2; Literacy Assessment 3 9.2 Cluster Analysis of Literacy Assessment 3
4.1 PARENT SURVEY 1
In November of the preschool year, Parent Survey 1 (see Appendix C) was sent home to parents of participating students. A ninety-three percent return rate was achieved. Demographic information relating to families was gathered and reported in Chapter 3. Parents’ perceptions of their children’s personal characteristics, interests and home literacy practices are reported in this chapter.
Chapter 4: Describing and Correlating Preschool Data 154 4.1.1 PARENTS’ PERCEPTIONS: CHILDREN’S PERSONAL CHARACTERISTICS AND INTERESTS
Parents’ perceptions of their children’s personal characteristics and interests were gathered using Parent Survey 1. Perceptions relate to enjoyment of preschool, ability to concentrate, memory, interest in books and interest in writing. Results showed that 83% of students were seen to always enjoy preschool while 7% were described as sometimes enjoying the experience. An analysis of variance found no significant differences on enjoyment that were due to preschool, age or gender.
Results for ratings given by parents for children’s ability to concentrate, memory performances, interest in books and writing for the total sample are shown in Table 8 with results expressed as valid percentages.
Table 8
Percentage Frequencies of Children’s Personal Characteristics and Interests From Parent Survey 1
Sample Rating from Concentration Memory Interest in Interest in the survey Books Writing Total Excellent 15.2 48.1 46.2 22.5 Very Good 50.5 36.8 32.1 47.2 Good 22.9 12.3 17.0 14.2 Satisfactory 10.5 0.9 4.7 6.6 Poor 1.0 1.9 0.0 6.6
Multivariate analyses were conducted to examine significant effects due to preschool, age or gender. No significant effect was shown for preschool (p = .28).
Age was analysed using three age ranges for the students and included 59-64 months for the youngest group, 65-70 months for the middle age group and 71-76 months
Chapter 4: Describing and Correlating Preschool Data 155 for the oldest group. Age attained statistical significance in relation to personal characteristics and interests [Wilks’s Lambda = .81, MVF (8,198) = 2.63; p <.001; eta-squared = .09]. Examining the univariate effects, it was found that significant age differences related to personal characteristics and interests across the three age ranges. Mean scores are shown in Table 9 indicating that on all four variables parents rated age group inversely with performance.
Table 9
Comparison of Means From Parental Ratings of Children’s Concentration, Memory and Interest in Reading and Writing by Age Group
Children’s age Score Ability to Memory Interest in Interest in concentrate books writing 59-64 months N 26 27 27 27 Mean 3.92 4.44 4.48 4.14 SD .62 .64 .70 .90
65-70 months N 60.0 60.0 60.0 60.0 Mean 3.73 4.38 4.20 3.86 SD .86 .71 .85 .99
71-76 months N 19.0 19.0 19.0 19.0 Mean 3.21 3.73 3.78 3.00 SD 1.13 1.28 1.08 1.33
Total N 105.0 106.0 106.0 106.0 Mean 3.68 4.28 4.19 3.78 SD .89 .85 .88 1.10 Note that scores allocated to these ratings when entering data are: excellent = 5, very good = 4, good = 3, satisfactory = 2 and poor = 1.
Analysis of variance showed a significant effect on all four variables related to age group. These are: ability to concentrate, (p = .02); memory, (p = <.01); interest in books, (p = .03); interest in writing, (p = <.01).
Chapter 4: Describing and Correlating Preschool Data 156 Turning to the post-hoc contrasts among the three age groups on these measures, it was found that the youngest age group (59-64 months) and the oldest age group (71-
76 months) differed significantly on the univariate effect for all four variables.
Results for youngest versus oldest group were: p = .03 for concentration; .02 for memory; .03 for interest in books and <.01 for interest in writing (Scheffe). The middle age group (65 – 70 months) differed significantly from the oldest age group
(71-76 months) for memory and interest in writing [middle versus oldest: p = .01 for memory and <.01 for interest in writing (Scheffe)].
Mean scores also were compared for the children’s personal characteristics and interests in relation to gender and are shown in Table 10.
Table 10
Comparison of Mean Scores From Parental Ratings of Children’s Concentration, Memory, Interest in Books and Interest in Writing by Gender
Children’s Score Concentration Memory Interest in books Interest in writing gender Male N 50.0 51.0 51.0 51.0 Mean 3.66 4.31 4.07 3.45 SD .96 .83 .99 1.15
Female N 55.0 55.0 55.0 55.0 Mean 3.70 4.25 4.30 4.09 SD .83 .88 .76 .96
Total N 105.0 106.0 106.0 106.0 Mean 3.68 4.28 4.19 3.78 SD .89 .85 .88 1.10
A mean score comparison revealed that parents rated female children more highly than male children for concentration, interest in books and interest in writing, while male children were rated more highly for memory. Analysis of variance of the four
Chapter 4: Describing and Correlating Preschool Data 157 variables indicated a significant difference for girls for only one of these variables, interest in writing [F (1,104) = 9.61, p<.01].
4.1.2 PARENTS’ PERCEPTIONS OF HOME LITERACY PRACTICES
4.1.2.1 Reading to preschool children
Parents were asked if they read to their preschool child. Ninety-eight percent responded positively. One child in Preschool B and one in Preschool C reportedly were not read to at all. Data also were collected relating to who read to the preschool child at home. Categories for collating this information were: mother, father, sister, brother and other. Several members of the family read to the preschool students.
Mother was most commonly nominated with father next. Results are shown in Table
11.
Table 11
Percentages of Those Who Read at Home to Preschool Children as Reported by Parents
Family Total Preschool A Preschool B Preschool C members Mother 89.6 94.9 83.3 89.2 Father 51.9 61.5 36.7 54.1 Sister 24.5 28.2 16.7 27.0 Brother 13.2 12.8 13.3 13.5 Other 11.3 12.8 3.3 16.2
Multivariate analyses carried out to examine effects due to preschool or age on who reads to the preschool child showed no significant differences. Parents also were asked how often they read to their preschool children at home and for what period of time. Results are presented in Tables 12 and 13.
Chapter 4: Describing and Correlating Preschool Data 158 Table 12
Percentages of Parents Reporting Time Frequency for Reading to Preschool Children
Time frequency Total Preschool A Preschool B Preschool C Occasionally 1.9 2.6 0.0 2.8 1-2 times /week 12.5 7.7 17.2 13.9 3-4 times /week 23.1 30.8 6.9 27.8 5-6 times/week 25.0 17.9 31.0 27.8 Daily 37.5 41.0 44.8 27.8
Table 13
Percentages of Parents Reporting Periods of Daily Time Spent Reading to Preschool Children
Daily time Total Preschool A Preschool B Preschool C < 5 minutes 1.9 2.6 0.0 2.8 6-10 minutes 33.0 47.4 27.6 22.2 11-15 minutes 32.0 36.8 37.9 22.2 16-20 minutes 25.2 7.9 24.1 44.4 21-25 minutes 5.8 5.3 3.4 8.3 >25 minutes 1.9 0.0 6.9 0.0
No significant differences related to preschool, age or gender were shown in the variation of reading times at home. A significant univariate effect related to time spent on reading at home [F(2, 100) = 4.90, p<.01]. Multiple comparisons of mean scores revealed a significant preschool difference occurred for the time taken for reading sessions between Preschools C and A and trending for Preschools B and A with parents at Preschool C indicating they read for longer periods [Preschool C versus Preschool A (Scheffe’s: p = .01)]. While occupation and education levels of parents in the three preschools presented a range within each setting (reported in
Chapter 3), mothers from Preschool C tended to be least qualified and fathers in
Preschool C constituted the largest group working in semi-skilled occupations.
Chapter 4: Describing and Correlating Preschool Data 159
4.1.2.2 Texts read to preschool children
All parents indicated that their children enjoyed being read to at home. Five types of texts picture storybooks, comics, children’s magazines, puzzle books and factual texts were shared at home. Most parents indicated they shared more than one type of text with their children. Results, expressed as a valid percentage, are shown in Table
14.
Table 14
Percentage Estimates From Parents of Texts Shared at Home with Preschool Children
Types of texts Total Preschool A Preschool B Preschool C Picture storybooks 99.0 100.0 100.0 97.3 Factual texts 29.5 33.3 31.0 24.3 Puzzle books 19.0 15.4 24.1 18.9 Children’s magazines 8.6 12.8 3.4 8.1 Comics 1.9 0.0 3.4 2.7
Picture storybooks were most frequently shared. Factual texts were used by approximately 30% of families, with children’s puzzle books, magazines and comics being used less frequently. Results show that the majority of families shared picture storybooks with preschool children and the range of texts shared with them appears to be somewhat contained. Multivariate analyses showed no significant effect for preschool, age or gender in relation to the types of texts read.
4.1.2.3 Books at home and use of local libraries
Parents estimated the number of books they had at home that were suitable for their preschool children. Results are shown in Table 15.
Chapter 4: Describing and Correlating Preschool Data 160 Table 15
Percentage Estimates From Parents of the Number of Books at Home Suitable for Preschool Children
Number of Total Preschool A Preschool B Preschool C books at home About 10 4.8 7.7 0.0 5.4 10-30 25.7 12.8 34.5 32.4 30-50 29.5 30.8 27.6 29.7 >50 40.0 48.7 37.9 32.4
Analysis of variance for number of books indicated no significant effect for preschool, age or gender. Results showed approximately 30% of parents own between 30 and 50 texts suitable for their preschool children with 40% indicating they own more than 50 such suitable texts.
Seventy-six percent of parents reported using local libraries. Frequency of use of these libraries is shown in Table 16
Table 16
Percentage Estimates From Parents for Use of Local Libraries
Use of local libraries Total Preschool A Preschool B Preschool C Occasionally 26.3 25.8 34.6 17.4 Once/month 47.5 48.4 42.3 52.2 Every fortnight 25.0 25.8 19.2 30.4 Other 1.3 0.0 3.8 0.0
Analysis of variance revealed no significant effect due to preschool, age or gender for frequency of library use. Regular use of the local library, either fortnightly or once a month, was indicated by 72% of respondents.
Chapter 4: Describing and Correlating Preschool Data 161 4.1.2.4 Preschool children’s writing at home
Information relating to preschool children’s writing habits at home was collected from responses on Parent Survey 1. In the survey details about children’s interest in writing, developing skills for writing their own names, attempts to write at home, and how often these practices occurred were sought. Results revealed that 90% of children showed interest in writing and that 99% could write their own names by the end of the preschool year. Other than writing their own name, 90% also engaged in other writing. These data frequencies are shown in Table 17.
Table 17
Percentage Estimates From Parents of Preschool Children’s Frequency of Writing at Home Other Than Writing Own Name
Time estimates Total Preschool A Preschool B Preschool C Occasionally 8.5 10.3 3.3 10.8 Twice/month 1.9 2.6 0.0 2.7 Once/week 18.9 15.4 30.0 13.5 >Once/week 70.8 71.8 66.7 73.0 Values attached to the responses are as follows: >once/week = 5; once/week = 4; once a fortnight = 3; occasionally = 2; other = 1.
Analysis of variance revealed no significant effect for preschool or age. Mean score comparison for girls and boys showed that parents perceived girls wrote more frequently than boys. These data are presented in Table 18.
Table 18 Comparison of Perceptions of Frequency of Writing at Home by Gender
Students’ Gender Mean N SD Male 4.21 51 1.04 Female 4.80 55 .62 Total 4.51 106 .89
Chapter 4: Describing and Correlating Preschool Data 162 Analysis of variance showed a significant gender difference. Girls were considered by their parents to write more often than boys [F (1, 104) = 12.45, p<.01].
4.1.3 SUMMARY
The following summary was derived from results on Parent Survey 1. A majority of parents perceived that their children:
• enjoyed preschool;
• had good concentration;
• displayed good memory skills;
• were interested in books; and
• were interested in writing.
No significant preschool effect was found for the various child characteristics or interests reported.
Some significant effects were found for age and gender in relation to parents’ perceptions of children’s targeted characteristics and interests. A significant effect was shown for children in the youngest age group (59-64 months) who reportedly had better concentration, memory skills and greater interest in books and writing than the older age group (71-76 months). Children in the middle age group (65-70 months) were perceived as having significantly better memory and a greater interest in writing than those in the older age group (71-76 months). Girls also were seen to have greater concentration, interest in books and interest in writing while boys were deemed to have better memories.
Chapter 4: Describing and Correlating Preschool Data 163 In relation to literacy practices at home, all but two families, indicated they read to their preschool children. Mother is the person who reads most often, with fathers also reading to children in approximately half of the families. In some families, either a brother or sister also read to the preschool child. Girls are perceived by their parents as being more interested than boys in writing during the preschool period.
The data suggest that the practice of reading to a preschool child occurs frequently with a high percentage of parents reading between three and seven times a week.
More than half of the parents surveyed indicated they read to their child for a period between 11 and 25 minutes. Most read picture storybooks with approximately one third indicating they read non-fiction texts. Approximately 75% of parents indicated they used local libraries and use was most typically visiting a library every month.
For children in this study, writing at home appeared to be a common practice with
99% of parents indicating their children could write their own name by the end of the preschool year and in 71% of cases children were writing at home more than once a week. Results indicated that girls wrote significantly more frequently than boys during the preschool year.
In order to pursue the relationship between such perceptions and students’ literacy capabilities, the next section reports results from Literacy Assessment Tasks (LAT
1) completed by students in November of the preschool year.
Chapter 4: Describing and Correlating Preschool Data 164 CHAPTER CONTENT DESCRIPTION Chapter 4: Describing and Correlating Preschool/Early Year 1 Data 4.1 Parent Survey 1 (November of Preschool) 4.2 Literacy Assessment 1 (November of Preschool) 4.3 Teacher Checklist 1 (March of Year 1) 4.4 Teacher Survey (March of Year 1) Chapter 5: Reducing dimensions: Relationships in the Preschool/Early Year 1 Data 5.1 Factor Analysis of Parent Survey 1;Teacher Checklist 1; Literacy Assessment 1 5.2 Cluster Analysis based on Literacy Assessment 1 – Preschool period Chapter 6: Describing and Correlating Year 1 (May) Data 6.1 Literacy Assessment 2 (May of Year 1) Chapter 7: Reducing dimensions: Relationships in the Year 1 (May) Data 7.1 Factor Analyses: Literacy Assessment 2 7.2 Cluster Analysis of Literacy Assessment 2 Chapter 8: Describing and Correlating Year 1 (November) Data 8.1 Literacy Assessment 3 (November of Year 1) 8.2 Parent Survey 2 8.3 Teacher Checklist 2 Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 9.1 Factor Analysis: Parent Survey 2; Teacher Checklist 2; Literacy Assessment 3 9.2 Cluster Analysis of Literacy Assessment 3
4.2 LITERACY ASSESSMENT TASKS: PRESCHOOL PERIOD
A battery of Literacy Assessment Tasks was administered on three occasions throughout the study. The first administration of approximately forty-five minutes duration occurred in November of the students’ preschool year. Subsequent testing occurred in May/June and November of Year 1. The first battery of tasks consisted of one-to-one assessments as follows:
1. Environmental print awareness;
2. Story Comprehension using the texts, My Grandma and Oscar Got the Blame;
3. Student writing his/her own name and naming each letter;
4. Robinson’s Test of Writing Vocabulary (Clay, 1985);
5. Letter Knowledge and Identification (Clay, 1985);
6. Concepts About Print Test, version Sand (Clay, 1979b);
Chapter 4: Describing and Correlating Preschool Data 165 7. Canberra Word Test (Clough, McIntyre & Cowey, 1990);
8. Print Knowledge Task using the rhyme, Humpty Dumpty;
9. Sutherland Phonological Awareness Test (Neilson, 1999);
10. Asking students about their reading practices at home.
Within this section descriptive statistics are reported relating to the Literacy
Assessment Tasks in Preschool. Multivariate and univariate analyses relating to the tasks also are reported, and each is examined to indicate preschool, age and gender effects. Preschool effects are of interest in order to examine the impact of different family factors. These factors include differences relating to the education and occupation of parents.
4.2.1 ENVIRONMENTAL PRINT AWARENESS
Preschool students completed four tasks relating to knowledge of selected food products and their labels. The tasks were progressively decontextualised so that by the fourth task all products and packaging were removed and the product name only was printed on a card. As all contextual clues of colour, font and packaging were removed for the final task it provided an indication of those children who were using print awareness strategies to identify words.
4.2.1.1 Task 1: Recognising Food Products
Thirteen selected food items were shown to the students. These items were Rice
Bubbles, jam, Twisties, Milky Way, milk, Milo, Jatz biscuits, spaghetti, honey,
Freddo chocolate, peanut butter, juice and jelly. The task was to identify any of these food items. It is acknowledged that if a child’s family normally did not purchase the
Chapter 4: Describing and Correlating Preschool Data 166 presented item, or the child had not seen the item advertised, then the likelihood of the child recognising the product would be reduced. Means and standard deviations for recognition of the items are presented in Table 19.
Table 19
Recognition of Selected Food Products (Task 1)
Score Total Preschool A Preschool B Preschool C Mean 9.05 9.04 9.36 8.78 SD 2.44 2.61 1.99 2.63
Results showed that the students recognised many of the 13 selected food items.
Two students did not recognise any of the products, while three, one from each preschool, recognised all 13 products.
4.2.1.2 Task 2: Recognition of Product Name
As a second task the students were asked to locate the product name on the product.
Table 20 shows these results.
Table 20
Recognition of Product Names on the Selected Products (Task 2)
Score Total Preschool A Preschool B Preschool C Mean 7.35 7.67 7.45 6.92 SD 3.18 3.18 2.67 3.60
Scores for this task were a little lower than on recognition of the product itself.
However, the task is more demanding and is more likely to require some awareness of print. Four students were not able to recognise the label on any product. Five students recognised labels for all 13 products.
Chapter 4: Describing and Correlating Preschool Data 167 4.2.1.3 Task 3: Recognition of the Cut-Out Labels
The label (product name) for each item was detached from the product and placed on a table. Some contextual assistance (i.e. the major part of surrounding packaging) had been removed for this task. Students selected and identified any labels they knew. Results are shown in Table 21.
Table 21
Recognition of Cut-out Labels for the Selected Products (Task 3)
Score Total Preschool A Preschool B Preschool C Mean 5.09 6.44 3.93 4.57 SD 3.55 3.80 2.69 3.50
Nine students were unable to recognise any of the cut-out labels. Five students recognised all 13 labels.
4.2.1.4 Task 4: Recognition of Words on Cards
The final task for environmental print involved using cards on which the product name had been printed. All contextual support was removed from sight, so students needed to identify the word using print awareness skills in order to score positively on this task. Results are shown in Table 22.
Table 22
Recognition of Selected Product Names on Cards (Task 4)
Score Total Preschool A Preschool B Preschool C Mean 2.17 3.32 0.96 1.92 SD 3.56 4.19 2.50 3.24
Chapter 4: Describing and Correlating Preschool Data 168 Sixty-six students (57.9%) did not recognise any of the product names. Three students (2.6%) correctly read all 13 names. Comparison across Tables 19-22 indicates a decreasing mean score as tasks became increasingly decontextualised.
Task 4 resembled actual reading more closely when compared to Task 1.
4.2.1.5. Analysing Environmental Print
Each of the four tasks had 13 items so a cumulative score provides another check of students’ responses. A comparison of cumulative mean scores is presented in Table 23. Table 23
Comparison of Cumulative Scores for Recognition of Environmental Print Tasks
Score Total Preschool A Preschool B Preschool C Mean 23.68 26.48 21.72 22.21 SD 10.53 11.54 8.06 10.80
Results showed students from Preschool A achieved the highest mean score (26.5).
Multivariate analysis of variance investigated differences due to preschool, age or gender. The multivariate effect for preschool attained statistical significance
[Wilks’s Lambda = .84, MVF(8,216) = 2.38; p=.02; eta-squared =.08]. For the variables taken together, there is a strong, significant effect for preschool. A univariate effect was found for preschools on Task 3, the recognition of cut-out labels, [UVF(2,111) = 5.66, p<.01; eta-squared =.09] and Task 4, recognition of words on cards, [UVF(2,111) = 4.48, p =.01, eta-squared= .08].
Chapter 4: Describing and Correlating Preschool Data 169 Post-hoc contrasts of the three preschools indicated that, Preschools A and B differed significantly on Task 3 [Scheffe’s: p = <.01] and Preschool A and B differed significantly on Task 4 [Scheffe’s: p = .01]. These results suggest that students from Preschool A had an advantage on the relatively decontextualised recognition tasks. This better relative performance may be associated with greater experience with decontextualised written language, with greater awareness of labelling that occurs on food products, both, or some other unknown factor.
Multivariate analysis also was conducted for age and awareness of environmental print scores, but no significant effects were found (p = .68). Similarly, no significant effect occurred for gender (p = .92). Thus, neither age nor gender made an observable difference in relation to environmental print skills and knowledge in preschool and this was demonstrated on all four tasks.
4.2.1.6 Summary
Results for the Environmental Print Literacy Assessment Tasks in the preschool period showed that students demonstrated that they know much about written language prior to commencing school, and that they are learning about it in everyday situations associated with food products. Students scored more highly when the print tasks were contextualised (Tasks 1 and 2). Results on Tasks 3 and 4 showed a significant effect for preschool. No significant differences were attained due to age or gender on any of the environmental print tasks. Older students did not perform significantly better than younger ones and neither girls nor boys performed significantly better.
Chapter 4: Describing and Correlating Preschool Data 170 4.2.2 STORY COMPREHENSION
Preschool students had two stories read to them from small picture books. The stories were My Grandma (Keane, 1994) and Oscar Got the Blame (Ross, 1997) and are included as Appendix F. Ten statements were posed following the reading of each story to which students responded ‘true’ or ‘not true’. Four tested literal comprehension, four tested inferential comprehension and two were nonsense questions (see Appendix G).
4.2.2.1 Comprehension score for My Grandma
Results are shown in Table 24 for the story, My Grandma.
Table 24
Comprehension Scores for the Story My Grandma
Score Total Preschool A Preschool B Preschool C Mean 7.49 7.67 7.39 7.36 SD 1.76 1.56 1.51 2.16
Results reflected students’ ability to listen to a story and respond to statements posed by adults. Within the total sample, 57% scored eight, nine, or ten from a possible score of ten. One student scored zero on the task and eight students scored ten
(100%) for the task.
4.2.2.2 Comprehension score for Oscar Got the Blame
The mean score for comprehension of Oscar Got the Blame was 7.81. Results are shown in Table 25.
Chapter 4: Describing and Correlating Preschool Data 171 Table 25
Comprehension Scores for the Story Oscar Got the Blame
Score Total Preschool A Preschool B Preschool C Mean 7.81 8.10 7.87 7.39 SD 1.92 1.47 1.90 2.33
Results for the second story showed that 64.9% of students scored eight, nine, or ten for the comprehension questions. One student scored one, while 20 students scored ten (100%) for this task.
4.2.2.3 Literal comprehension across the two stories
Results for literal comprehension were scores ranging from two to eight on the eight literal comprehension statements. Four students scored two and 23 students responded correctly to all eight statements. These results are presented in Table 26.
Table 26
Literal Comprehension Scores for the Two Stories in Preschool
Score Total Preschool A Preschool B Preschool C Mean 6.10 6.04 6.18 6.10 SD 1.56 1.43 1.62 1.68
Further results for literal comprehension showed that 71.1% of students scored six, seven or eight and only 6.1% within the total sample scored fewer than four. Further analyses were conducted to investigate if results differed significantly because of preschool, age or gender. No difference was shown for preschool (p = .93) or gender
(p = .79). A significant difference was noted for age [(p = .04) Scheffe]. This result occurred for the youngest (55-64 months) students with a mean score of 5.5 compared to the middle age group (65-70 months) with a mean score of 6.3.
Chapter 4: Describing and Correlating Preschool Data 172
4.2.2.4. Inferential comprehension across the two stories
Eight inferential comprehension statements were used across the two stories and students’ scores ranged from one to eight with one child scoring one and 11 scoring eight. Results of these performances are presented in Table 27
Table 27 Inferential Comprehension Scores for the Two Stories in Preschool
Score Total Preschool A Preschool B Preschool C Mean 5.76 5.72 5.90 5.68 SD 1.57 1.86 1.35 1.77
For inferential comprehension 64.9% of the students scored six, seven, or eight. This is a smaller percentage than that obtained in response to literal comprehension items.
Approximately 90% of students correctly answered four or more of the inferential questions. Further analyses were conducted to ascertain if mean scores for inferential comprehension differed significantly for preschool, age or gender. No significant effect was shown for preschool (p = .81), age (p = .41) or gender (p= .40).
4.2.2.5 Summary
Results from the two comprehension tasks confirmed that preschool students were capable of listening to and comprehending stories. The overall mean scores of 7.49 for My Grandma and 7.81 for Oscar Got the Blame confirmed their listening comprehension ability. Multivariate analyses showed one significant effect for literal comprehension due to age and no significant difference due to preschool or gender.
Results for inferential comprehension showed no significant difference due to preschool, age or gender.
Chapter 4: Describing and Correlating Preschool Data 173 4.2.3 WRITING NAMES AND NAMING LETTERS
Students were given a blank piece of paper and asked to write their names. One was unable to attempt the task and another did not complete the task. Name writing was analysed to examine if the students wrote given name only or both given name and surname. Results are shown in Table 28.
Table 28
Number and Valid Percentages of Students Who Could Write Their Name in Preschool
Parts of the name written Total Preschool Preschool Preschool A B C Given name + family 19 (16.7) 13 (30.2) 5 (15.2) 1 (2.6) name Given name 93 (81.6) 30 (69.8) 28 (84.8) 35 (92.1) Total 114 (100.0) 43 (100.0) 33 (100.0) 38 (100.0)
Details of the cases used by students and letter order are shown in Table 29.
Table 29
Frequency and Valid Percentages of Cases Used by Students and Order of Letters When Writing Their Own Names
Case and order Total Preschool Preschool Preschool A B C All lower case 9 (7.9) 7 (16.3) 1 (3.0) 1 (2.6) All upper case 18 (15.8) 4 (9.3) 3 (9.1) 11 (28.9) Mixed case 40 (35.1) 23 (53.5) 7 (21.2) 10 (26.3) Conventional order 46 (40.4) 9 (20.9) 22 (66.7) 15 (39.5) Missing 1 (0.9) 0 (00.0) 0 (00.0) 1 (2.6)
Total 114 (100.0) 43 (100.0) 33 (100.0) 38 (100.0)
Some students used all lower case letters (7.9%), some used all upper case letters
(15.8%). Some mixed case within the name (35.1%) e.g. jAne. The conventional
Chapter 4: Describing and Correlating Preschool Data 174 order for writing a name beginning with an upper case letter and then using lower case letters (e.g. Jane) was used by 40.4% of the sample.
A majority of students (66.7%) in Preschool B wrote their names conventionally, performing better than those at other sites. A majority of students in Preschool A
(53.5%) used mixed upper and lower case letters when writing their name. In
Preschool C, the percentage of students who wrote their name in conventional style
(39.5%) almost matched the percentage for the total sample (40.4%).
The spelling students used when writing their names was analysed and results are shown in Table 30. A majority (82.5%) was able to spell their names correctly. An additional 15.8% spelt some of their name correctly.
Table 30
Students’ Accuracy When Spelling Their Names in November of Preschool
Result Total Preschool Preschool Preschool A B C None 1 (0.9) 0 (00.0) 0 (00.0) 1 (2.6) correct
Some 18 (15.8) 6 (13.9) 5 (15.1) 7 (18.4) correct
All 94 (82.5) 37 (86.0) 28 (84.8) 29 (76.3) correct
Missing 1 (0.9) 0 (00.0) 0 (00.0) 1 (2.6)
Total 114 (100.0) 43 (100.0) 33 (100.0) 38 (100.0)
A majority of preschool students in all settings spelt their names correctly (A = 86%;
B = 84.8%; C = 76.3%) and only one student was not able to write any correct letters for his name.
Chapter 4: Describing and Correlating Preschool Data 175
One further activity was associated with the name-writing task. Each child was asked to name the letters in his/her name. A majority (71.1%) knew all of the letter names. Two (1.8%), did not know the names of any one letter. Results are shown in
Table 31.
Table 31
Students’ Knowledge of Letters in Their Own Names
Result Total Preschool Preschool Preschool A B C Knows none 2 (1.8) 1 (2.3) 0 (00.0) 1 (2.6) Knows some 31 (27.2) 8 (18.6) 3 (27.3) 14 (36.9) Knows all 81 (71.1) 34 (79.1) 24 (72.7) 23 (60.5) Total 114 (100.0) 43 (100.0) 33 (100.0) 38 (100.0)
Results showed the majority of students in each setting knew the names of all the letters in their own name (A = 79.1%; B = 72.7%; C = 60.5%) and that only one from Preschool A and one from Preschool C did not know any one letter.
4.2.3.1. Summary
Preschool students in this study showed they were able to write their own name.
Results showed one student was unable to complete the task and one student did not complete the task. The majority of students (82%) wrote their given name only, with
17% demonstrating they could write given name and surname. Forty percent of students wrote their name in the conventional manner using first a capital letter then lower case for the following letters. Approximately one third used mixed lower and upper case when writing their name while 16% used upper case only. Fewer than
10% chose to use lower case letters only when writing their name. Eighty-two
Chapter 4: Describing and Correlating Preschool Data 176 percent wrote their name with total accuracy. When asked to name letters that made up their name, 71% were able to do so successfully. These results illustrate that immediately prior to commencing school the majority of students in this study were able to write their names accurately.
4.2.4 ROBINSON'S TEST OF WRITING VOCABULARY
Robinson's Test of Writing Vocabulary (Clay, 1985, pp.35-36) requires students to write as many words as they can in a ten-minute period. No pressure is placed on respondents. In the application of this test with subjects of this study those who stated they were unable to write words other than their names were not expected to proceed further. Words were scored as correct only if they were spelt correctly.
Table 32 shows the results.
Table 32
Students’ Scores on Robinson’s Test of Writing Vocabulary
Score Total Score Preschool A Preschool B Preschool C Mean 1.36 1.44 2.18 0.57 SD 2.98 1.99 4.86 1.00
Approximately 65% of students attempted to write words, while 35% declined to do so. Of those who attempted to write words, 13.1% did not write any correctly-spelt words. Almost half (48.2%) wrote correctly at least one word other than their name.
Thirty-nine percent wrote between one and three words and 9.7% wrote between four and 28 words. A girl from Preschool B wrote 28 words in ten minutes and produced a unique result within this sample. She wrote one word with six letters; one word with five letters; two words with four letters; 22 words with three letters;
Chapter 4: Describing and Correlating Preschool Data 177 and two words with two letters. This result was 19 words more than the next highest score of nine words completed by a child from Preschool A.
When results for Robinson's Test of Writing Vocabulary were compared across preschools it was found that students from Preschool C wrote fewest words and represented the highest percentage (68.4%) of children who wrote no words.
Students in Preschools A and B produced similar results. Students in Preschool B wrote between one and five words and in Preschool A they wrote between one and nine words.
The size of the words written by the students showed some variation with three- letter words being the most common words written by the students. Results are shown in Table 33.
Table 33
Number of Words of Different Sizes Written by Preschool Students
Students Students Students Students Students Students who wrote who wrote who wrote who wrote who wrote who wrote 1 letter 2 letter 3 letter 4 letter 5 letter words > 5 words words words words words letters Student 2 9 36 14 18 13 subtotal
Thirty-six students wrote one or more three-letter words, the most common size word written by the preschool children. A further comparison of results was made by examining multivariate effects for preschool, age and gender. There was no statistical significance for preschool (p = .32) or age (p = .27). However the multivariate effect for gender attained statistical significance [Wilks’ Lambda = .89,
Chapter 4: Describing and Correlating Preschool Data 178 MVF (6, 107) = 2.17; p = .05; eta-squared = .10]. Analysis of variance (Tables 34 and 35) showed variation in the production of words longer than five letters differed significantly for gender with girls (mean score .22) writing significantly more longer words than the boys (mean = .05).
Table 34
Comparison of Mean Scores for Robinson’s Test of Writing Vocabulary by Gender
Gender Score No. of No. of No. of No. of No. of No. of 1 letter 2 letter 3 letter 4 letter 5 letter >5 letter words words words words words words Male Mean .00 .10 .38 .18 .12 .05 SD .00 .36 .70 .51 .43 .22 Female Mean .03 .08 1.05 .20 .25 .22 SD .18 .33 2.96 .66 .51 .52 Total Mean .02 .01 .72 .19 .19 .14 SD .13 .35 2.20 .59 .47 .41
Table 35
Univariate Analysis for Robinson’s Test of Writing Vocabulary by Gender for Words Longer than Five Letters
N. of words written with Sum of df Mean F Sig. more than 5 letters Squares Square Between Groups .78 1 .78 4.61 .03 Within Groups 18.97 112 .16 Total 19.75 113
4.2.4.1 Summary
Results showed that preschool students displayed developing skills in writing words.
They scored only when they had written correctly spelt words and approximations of spelling were not marked as correct within this study. Mean score for the total cohort was 1.36. Preschool students were given the choice of writing other words apart from their name and 65% attempted to do so. Of these, 13% did not write any
Chapter 4: Describing and Correlating Preschool Data 179 correctly spelt words. Effectively, this means that almost half (48.2%) of the students could successfully write other words. While most students did not write many words, one female student wrote 28 words. The size of the most commonly written words by preschool students was three-letter words.
Multivariate analyses of performances on Robinson’s Test of Writing Vocabulary showed no significant effect for preschool or age, but a significant effect was attained for gender. Girls wrote significantly greater number of words that had more than five letters. This finding is consistent with parents’ reporting on Parent Survey
1 where they perceived girls write more than boys at home.
4.2.5 LETTER KNOWLEDGE AND IDENTIFICATION
Students were asked to identify all upper and lower case letters in three ways following the procedure outlined by Clay (1985). First, students were asked to name the letter. Then they were asked to provide the common sound made by the letter and finally they were asked to give a word that started with the letter.
Fifty-four letters were presented to the students with the 26 letters of the alphabet presented in upper and lower case, then two other letters, lower case ‘a’, and lower case ‘g’ also being presented in the font as indicated. These two letters are commonly found in children’s published texts in this font, so they also are included in the test. Descriptive statistics for students’ performances are shown in Table 36 for Preschools A, B and C.
Chapter 4: Describing and Correlating Preschool Data 180 Table 36
Preschool Students’ Knowledge of Letter Names, Sounds and Words Beginning with Each Letter
Task Preschools Mean SD N Letter names A 28.7 18.6 43 B 28.3 16.6 33 C 22.4 17.6 38 Total 26.5 17.8 114
Letter sounds A 10.6 15.5 43 B 8.7 13.2 33 C 4.1 10.0 38 Total 7.9 13.4 114
Words beginning with the specified letters A 13.5 15.1 43 B 15.2 14.2 33 C 10.5 11.8 38 Total 13.0 13.8 114
Preschool students in each context performed differently when naming letters, with mean scores for the total sample = 26.5 (Preschool A = 28.7; Preschool B = 28.3 and
Preschool C = 22.4). The range of scores was broad: from zero to 54. and 15 students (13.2%) scored between zero and five.
The second task, in which students gave the sound for each letter, showed an overall mean score of 7.9 (10.6 for Preschool A; 8.7 for Preschool B and 4.1 for Preschool
C). The range of scores for this task was zero to 54. Fifty students (43.9%) scored zero and one student scored 54 (100%).
Results for the third task in which students were asked to provide a word starting with a particular letter, showed a mean score of 13.0 for the whole sample. The mean scores for each preschool were Preschool A = 13.5; Preschool B = 15.2 and
Chapter 4: Describing and Correlating Preschool Data 181 Preschool C = 10.5. Scores for this task ranged from zero to 52. Approximately 40% of students scored between zero and five.
Multivariate analyses of variance were conducted to examine effects of preschool, age and gender on letter knowledge and identification. No significant effect was shown for preschool. Results for the three tasks were: Task 1 (p = .22); Task 2 (p =
.09); Task 3 (p = .34). No significant effect was shown for age and results for the three tasks were: Task 1 (p = .84); Task 2 (p = .86); Task 3 (p = .35). Similarly, no significant difference was shown for gender with results as follows: Task 1(p = .34);
Task 2 (p = .90) and Task 3 (p = .81).
4.2.5.1 Summary
Young students not yet in compulsory schooling with its formal teaching of reading, tended to know letters and their sounds. Assumptions that students in preschool know little, or nothing, about the alphabetic code are not supported by these findings. The results described so far can be tabulated broadly into three categories of established knowledge.
1. Students’ areas of well-established knowledge
• recognition of food products;
• recognition of labels on food products;
• comprehension of stories;
• writing names and naming the letters;
• knowing letter names;
Chapter 4: Describing and Correlating Preschool Data 182
2. Students’ partially-established knowledge
• recognition of labels separated from products;
• writing words apart from own name;
• knowing words starting with particular letters;
3. Minimal current knowledge
• recognising product names printed on cards;
• knowing letter sounds;
4.2.6 CONCEPTS ABOUT PRINT TEST (CAP)
Each student completed Clay’s Concepts About Print Test, version Sand (Clay,
1979b). A description of the administration and scoring guidelines (Clay 1985, pp.
27-31) is in Appendix H. An adult shared the text Sand individually with each child.
The text is a picture storybook produced mainly in black and white. It contains errors that students are asked to identify during the test. Throughout the test respondents are asked to point to various parts and indicate the errors. Results for
Concepts About Print Test are shown in Table 37.
Chapter 4: Describing and Correlating Preschool Data 183 Table 37
Performances for Concepts About Print Test in Preschool
Score Total Preschool A Preschool B Preschool C Mean 11.05 10.95 11.78 10.52 SD 4.38 4.59 3.76 4.66
Multivariate analysis of variance was conducted to examine preschool, age and gender effects. Results for preschool (p = .65) and age (p = .26) did not attain statistical significance. However, results showed a statistically significant effect for gender [F(1,112) = 5.09, p =.03] with girls achieving a higher overall mean score than the boys (girls = 11.93; boys = 10.10). Results from the CAP test showed that the girls scored significantly higher on Items 2, 4, 7, 9, 11, and 13. These items from the test related to:
• Knowing print contains a message (Item 2);
• Knowing to read from left to right (Item 4);
• Indentifying the first part of the story and the last part (Item 7);
• Responding to inverted print and knowing left to right direction (Item 9);
• Knowing the left page is read before the right page (Item 11);
• Identifying letters that are out of order (Item 13).
Except for Item 2, all of these items relate to print directionality.
Results showed that preschool students are developing their knowledge and understanding about print. On the CAP test, four test items were answered correctly by more than 80% of the total sample. These were:
Chapter 4: Describing and Correlating Preschool Data 184 • Item 1: ‘Show me the front of this book.’
• Item 3: ‘Show me where to start (i.e. reading).’
• Item 4: ‘Which way do I go?’
• Item 21: ‘Now show me two letters.’
These results demonstrated that a majority of preschool students in the sample have well-developed knowledge of how to handle books, and that they were aware of the directionality of print. They also demonstrated an understanding of the concept of a letter.
The most challenging tasks for preschool students were scored correctly by fewer than 20% in the sample. These tasks were:
• Item 14:‘What’s wrong with the writing on this page”. (re-ordering letters within
a word)
• Item 15: ‘What’s this for?’ (Pointing to a question mark).
• Item 17: ‘What’s this for?’ (Pointing to a comma).
• Item 18: ‘What’s this for?’ (Pointing to quotation marks).
• Item 20: ‘ Show me [was].’
• Item 24: Show me a capital letter.’
Results for these items revealed that the students were not familiar with the function of all punctuation marks and did not as yet have well developed word recognition skills. They also appeared to be unfamiliar with the term ‘capital letter.’ Perhaps these findings reflect the purposes adults have when they share texts with young students. Main purposes are more likely to be gaining enjoyment from the story and
Chapter 4: Describing and Correlating Preschool Data 185 illustrations and understanding an author’s meaning. Most parents and early childhood teachers would not set their main objective as familiarising preschool students with punctuation or metalinguistic terms such as the ‘capital letter’.
4.2.6.1. Summary
Results for Concepts About Print Test in Preschool revealed students’ developing knowledge and understanding of the alphabetic principle. They indicated their experience with text sharing by knowing the front of a book, where to start reading and showing an understanding of print directionality. Other skills are not so well- developed and these include understanding the function of punctuation marks such as the question mark, the comma and quotation marks. Preschool students also were not familiar with identifying words, or knowing letter patterns in common words or understanding what is meant by a capital letter. Results showed no significant effect on performance from the CAP test for preschool or age. However, a gender effect was shown with the girls achieving a higher mean score.
4.2.7 CANBERRA WORD TEST
The Canberra Word Test (Clough, McIntyre and Cowey, 1990) was used to ascertain students’ ability to recognise words in isolation. List B, consisting of 15 words commonly found in children's early readers was used (see Appendix I). Students were asked to look at each word in turn, slide down a piece of paper that was covering the words and read each word in turn. All attempted this task, although not
Chapter 4: Describing and Correlating Preschool Data 186 all were able to read words. Scores for the Canberra Word Test are shown in Table
38.
Table 38
Scores for the Canberra Word Test in Preschool
Score Total Preschool A Preschool B Preschool C Mean 1.27 1.58 1.33 0.86 SD 2.81 3.11 3.01 2.21
Results revealed the difficulties students experienced when reading words in isolation prior to commencing school. The majority (60.5%) did not read any words.
However, results can be examined for those students who were able to read one or more words. Results showed that 45 students from the total sample did so. The majority of this sub-group (24 students) could read one word from the list. Of the remaining 21 students, 12 read two, three or four words; three students read five, six or seven words; and six students read between 10 and 14 words.
The number and percentage of students who could read words from each setting are as follows: 20 students (46.5%) from Preschool A; 13 students (39%) from
Preschool B; 12 students (31.5%) from Preschool C. Analysis of variance was conducted to examine the significance of preschool, age or gender. Results showed statistical significance was not indicated [preschool (p = .52), age (p = .75) or gender
(p = .35)].
Chapter 4: Describing and Correlating Preschool Data 187 4.2.7.1 Summary
Results for the Canberra Word Test revealed that 39.5% of preschool students could read at least one word from the list prior to commencing primary school. Nine (8%) could read five or more words. These results further illustrate students’ prior knowledge and understanding about words as they enter Year 1. The assumption that preschool students commence Year 1 with little or no knowledge about print is not supported by these results.
4.2.8 PRINT KNOWLEDGE TASK USING THE RHYME HUMPTY DUMPTY
Resources for this task were two copies of a printed chart of the nursery rhyme,
Humpty Dumpty. One was cut into strips of print. Preschool students were asked to complete 17 print awareness and word awareness tasks. Results are presented in
Table 39.
Table 39
Performances in Preschool for Print Knowledge
Score Total Preschool A Preschool B Preschool C Mean 9.40 9.65 9.51 9.02 SD 3.52 3.32 3.65 3.67
Analyses of variance showed no significant effect due to preschool (p = .34), age (p
= .82) or gender (p = .78).
Chapter 4: Describing and Correlating Preschool Data 188 4.2.8.1 Summary
Results for Print Knowledge using the nursery rhyme, Humpty Dumpty, were comparable in all settings, for all ages and for both boys and girls. The individual item results from this task revealed some concepts about print that were well- established, some that were partially-established and some that illustrated little current knowledge. These findings are shown below:
Well- established knowledge (75% or more of the students answered correctly)
• Point to the first line of print (Item 1);
• Point to a word (Item 2);
• Point to a letter (Item 3);
• Recognise a strip of text that is upside down (Item 11);
• Fix the strip of text that is upside down (Item 12);
• Point to the word, Humpty (Item 14);
Partially established knowledge (50% - 74% of students answered correctly)
• Find a word that starts the same way as, had (Item 7);
• Match text strips to the whole text (Item 8);
• Recognise a strip of text that was out of order (Item 9);
• Fix a strip that was out of order (Item 10);
Little current knowledge (fewer than 50% of students answered correctly)
• Identify a name in the rhyme (Item 4);
Chapter 4: Describing and Correlating Preschool Data 189 • Find the word, wall (Item 5);
• Find a rhyming word for wall (Item 6);
• Read the rhyme while pointing to the words (Item 13);
• Point to the word, sat (Item 15);
• Point to the word, fall (Item 16);
• Point to the word, great (Item 17).
In summary, preschool students showed a range of knowledge relating to identifying letters by shape. Some knowledge also was shown where sound-symbol relationship knowledge was required. The tasks students found most difficult related to one-to- one correspondence when saying the rhyme while pointing to the words in the text.
4.2.9 SUTHERLAND PHONOLOGICAL AWARENESS TEST
Sutherland Phonological Awareness Test consists of 11 subtests. The first five were administered in November of the preschool year (see Appendix K). These were:
• Subtest 1: Syllable counting;
• Subtest 2: Rhyme detection;
• Subtest 3: Rhyme production;
• Subtest 4: Onset identification;
• Subtest 5: Final phoneme production.
Results for each of the subtests in all settings are presented in Tables 40-44.
Table 40
Scores in Preschool for Syllable Counting
Score Total Preschool A Preschool B Preschool C Mean 3.11 3.48 3.06 2.73 SD 1.06 0.76 0.99 1.26
Chapter 4: Describing and Correlating Preschool Data 190
Table 41
Scores in Preschool for Rhyme Detection
Score Total Preschool A Preschool B Preschool C Mean 3.46 3.46 3.78 3.18 SD 0.84 0.66 0.48 1.13
Table 42
Scores in Preschool for Rhyme Production
Score Total Preschool A Preschool B Preschool C Mean 2.05 2.06 2.63 1.52 SD 1.67 1.63 1.63 1.60
Table 43
Scores in Preschool for Onset Identification
Score Total Preschool A Preschool B Preschool C Mean 1.45 1.11 2.33 1.07 SD 1.59 1.48 1.51 1.51
Table 44
Scores in Preschool for Final Phoneme Production
Score Total Preschool A Preschool B Preschool C Mean 0.82 0.93 0.90 0.63 SD 1.29 1.38 1.25 1.21
Results showed some variation across mean scores for the five subtests. Students in
Preschool C scored the lowest for each of the five subtests. Those in Preschool A scored the highest mean score for subtest one, Syllable Counting and subtest five,
Final Phoneme Production. Students in Preschool B scored the highest mean scores for the three remaining subtests, Rhyme Detection, Rhyme Production and Onset
Chapter 4: Describing and Correlating Preschool Data 191 Identification. Multivariate analysis of variance revealed a significant preschool effect [Wilks Lambda = .71, MFV (10, 21) = 3.88; p < .01; eta-squared = .15].
Post hoc analysis (Scheffe) revealed significant effects occurred for the first four subtests. Multiple comparisons within these analyses revealed the following significant differences:
• Subtest 1, Syllable Counting Preschool A > Preschool C (p < .01);
• Subtest 2, Rhyme Detection Preschool B > Preschool C (p = .01);
• Subtest 3, Rhyme Production Preschool B > Preschool C (p = .01);
• Subtest 4, Onset Identification Preschool B > Preschool A (p < .01) and
Preschool B > Preschool C (p < .01).
No significant age effect was shown for any of the Sutherland Phonological
Awareness Tasks: Syllable Counting (p = .11); Rhyme Detection (p = .17); Rhyme
Production (p = .55); Onset Identification (p = .53) or Final Phoneme Identification
(p = .82). Similarly, no significant gender effect was shown on any of the tasks:
Syllable Counting (p = .63); Rhyme Detection (p = .21); Rhyme Production (p =
.44); Onset Identification (p = .34) or Final Phoneme Identification (p = .62).
4.2.9.1 Summary
Comparison of mean scores for the total sample showed that Rhyme Detection had the highest mean score suggesting this was the easiest task for preschool students.
This task involved the adult facilitator saying a word (e.g. ‘cat’) followed by two
Chapter 4: Describing and Correlating Preschool Data 192 more words (e.g. ‘bell’ & ‘bat’). Preschool students were asked to select the rhyming word for ‘cat’ from the set of two words.
The second highest mean score was attained on Syllable Counting performances and this involved students tapping out the number of syllables in words (e.g. ‘kangaroo’ has three syllables). The next highest mean score obtained was for Rhyme
Production where the preschool students listened to two rhyming words and then had to provide another rhyming word.
The tasks, Onset Identification and Final Phoneme Production, elicited relatively low mean scores. For onset identification students were asked to listen to a word given by the adult facilitator and to identify its beginning sound (e.g. ‘ball’ starts with /b/). Final phoneme production involved the students listening to a word given by the adult facilitator and then identifying the final sound in the word (e.g. ‘boot’ ends with /t/). Both tasks involved the students isolating sounds in words and at this stage of development, most students found this to be challenging. Students were given practice activities prior to all subtests.
Results of the phonological awareness tasks showed no significant difference due to age or gender, but four of the subtests resulted in significant preschool differences.
Of these four, three showed a significantly better performance by Preschool B. A possible explanation could be an emphasis within the preschool program for phonological awareness tasks, but this was not confirmed within this study.
Chapter 4: Describing and Correlating Preschool Data 193 4.2.10 STUDENTS’ PERCEPTIONS OF READING PRACTICES AT HOME
During the one-to-one interview, preschool students were asked three questions about reading at home. These were:
1. Does someone at home read to you?
2. Who reads to you?
3. What is your favourite story?
Results were that 110 (96.5%) of preschool students indicated they were read to at home. Four (3.5%) responded negatively to the question. Positive responses from the students for question one produced the following results from each preschool context: Preschool A, 41 (95.3%); Preschool B 33 (100%); and in Preschool C 36
(94.7%). These results align somewhat with the responses from parents on Parent
Survey 1. On the survey two parents, one from Preschool B and one from Preschool
C, indicated they did not read to their children, while two students from Preschool A and two from Preschool C indicated they were not read to at home.
For question two, results were analysed to identify who read to students at home.
Mum, Dad, Sister, Brother and Grandma were the most common responses given by preschool students and many listed more than one person who read to them at home.
Results are shown in Table 45.
Chapter 4: Describing and Correlating Preschool Data 194 Table 45
Family Members Identified by Preschool Students for Reading to Them at Home
Family Total Preschool A Preschool B Preschool C members Yes No Yes No Yes No Yes No Mum 90 24 32 11 28 5 30 8 Dad 69 45 27 16 22 11 20 18 Sister 24 90 11 32 6 27 7 31 Brother 14 107 4 39 5 28 5 33 Grandmother 7 107 5 38 0 33 2 33 Other 5 109 2 41 0 33 3 35
In relation to question three, 97 (85.1%) students named a favourite book while 17
(14.9%) were not able to do so.
4.2.10.1 Summary
Students reported being read to at home by family members. Although no indication was given of how often, or for what period the reading occurred, students should be familiar with the reading process and the language of books. Data relating to how often reading took place, and for what period of time, were gathered on Parent
Survey 1 and these data were reported earlier in this chapter.
The next section reports results from Teacher Checklist 1 (see Appendix U) completed with Year 1 teachers four months following the collection of data reported in the preceding section.
Chapter 4: Describing and Correlating Preschool Data 195 4.3 TEACHER CHECKLIST 1
The shaded row on the following schema indicates the current results section.
CHAPTER CONTENT DESCRIPTION Chapter 4: Describing and Correlating Preschool/Early Year 1 Data 4.1 Parent Survey 1 (November of Preschool) 4.2 Literacy Assessment 1 (November of Preschool) 4.3 Teacher Checklist 1 (March of Year 1) 4.4 Teacher Survey (March of Year 1) Chapter 5: Reducing dimensions: Relationships in the Preschool/Early Year 1 Data 5.1 Factor Analysis of Parent Survey 1;Teacher Checklist 1; Literacy Assessment 1 5.2 Cluster Analysis based on Literacy Assessment 1 – Preschool period Chapter 6: Describing and Correlating Year 1 (May) Data 6.1 Literacy Assessment 2 (May of Year 1) Chapter 7: Reducing dimensions: Relationships in the Year 1 (May) Data 7.1 Factor Analyses: Literacy Assessment 2 7.2 Cluster Analysis of Literacy Assessment 2 Chapter 8: Describing and Correlating Year 1 (November ) Data 8.1 Literacy Assessment 3 (November of Year 1) 8.2 Parent Survey 2 8.3 Teacher Checklist 2 Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 9.1 Factor Analysis: Parent Survey 2; Teacher Checklist 2; Literacy Assessment 3 9.2 Cluster Analysis of Literacy Assessment 3
Students in this study commenced Year 1 at the end of January and they were placed
in 11 Year 1 classes (4 at School A; 3 at School B; and 4 at School C).
Approximately six weeks after the students commenced school in Year 1, teachers were asked to complete Teacher Checklist 1 (see Appendix U). This checklist sought information about each child’s adjustment to school, work habits and progress in reading and writing.
Two different rating scales for the responses were included on the checklist. The first scale, used for adjustment to school and work habits, consisted of: excellent; very good; good; satisfactory and variable. The second scale used for reading, writing and handwriting progress consisted of a six-point rating scale: excellent;
Chapter 4: Describing and Correlating Preschool Data 196 very good; good; satisfactory; somewhat slow; little development to date. Results for these data are reported in two sets.
4.3.1 ADJUSTMENT TO SCHOOL AND WORK HABITS
All of the 11 Year 1 teachers completed Teacher Checklist 1 in March. Results showed a range of teacher perceptions about students’ adjustment to school and work habits. Results expressed as percentage are shown in Table 46.
Table 46
Percentage Distributions of Year 1 Teachers’ Perceptions of Students’ Adjustment to School and Work Habits
Variable Excellent Very good Good Satisfactory Variable Adjustment to school Separates from parents 36.3 27.4 16.8 8.8 10.6 Settled into Year 1 31.3 32.1 18.8 16.1 1.8 Work habits Concentration 16.8 27.4 26.5 15.0 14.2 Application to tasks 17.7 24.8 30.1 16.8 10.6 Personal organization 15.9 26.5 23.0 23.0 11.5 Follows instructions 17.7 29.2 18.6 23.0 11.5
A scale used for recording data concerning adjustment to school and work habits is as follows; excellent = 5; very good = 4; good = 3; satisfactory = 2; variable = 1.
This scaling enabled a comparison of mean scores. These data are shown in Table
47.
Table 47
A Comparison of Mean Scores for Adjustment to School and Work Habits
Score Child Settled Ability to On task Personal Follows separates into Yr1 concentrate organisation instructions Mean 3.69 3.75 3.17 3.22 3.12 3.18 SD 1.32 1.11 1.28 1.23 1.26 1.29
Chapter 4: Describing and Correlating Preschool Data 197 Multivariate analysis of variance showed no significant effect for adjustment to school and work habits (p = .08). A similar non-significant effect was obtained for age (p = .21). A significant difference was shown for gender [Wilks’s Lambda = .88,
MVF(6, 105) = 2.19; p = .04; eta squared = .11]. Differences occurred for application to tasks and personal organisation with female students scoring significantly higher than male students. A comparison of mean scores is shown in
Tables 48 and 49.
Table 48 A Comparison of Means for Year 1 Teachers’ Perceptions of Application to Tasks and Personal Organisation by Gender
Subjects Score Application to tasks Personal organisation Male Mean 2.96 2.83 SD 1.25 1.27
Female Mean 3.45 3.38 SD 1.16 1.20
Total Mean 3.22 3.12 SD 1.23 1.26
Table 49
Tests of Between-Subject Effects for Application to Tasks and Personal Organisation with Gender
Source Dep. Variable Type III df Mean Square F Sig. Eta Sum of Squared Squares Corrected Application to tasks 7.55 1 7.55 5.18 .02 .04 Model Personal organisation 9.42 1 9.42 6.18 .01 .05
4.3.1.1 Summary
Teachers’ perceptions of students’ adjustment to school and work habits revealed no significant effect for school or age. A significant effect for gender was shown with
Chapter 4: Describing and Correlating Preschool Data 198 girls being rated more highly than boys for their application to tasks and personal organisation.
4.3.2 LITERACY PROGRESS AND HANDWRITING
The second set of items from Teacher Checklist 1 related to students’ reading, writing and handwriting progress. For reading the categories were interest in reading, progress in reading, letter recognition, sight word knowledge and understanding sound symbol relationships. For writing, items on the checklist included interest in writing, ability shown for writing different texts and handwriting. Ratings were sought using the following scale excellent, very good, good, satisfactory, somewhat slow and little progress to date. Results for the total sample expressed as a percentage are shown in Table 50.
Table 50
Percentage Descriptions of Year 1 Teachers’ Perceptions of Students’ Interest and Progress in Reading, Writing and Handwriting
Variable Excellent Very Good Satisfactory Somewhat Little good slow progress to date Interest in 25.7 25.7 27.4 17.7 3.5 0.0 reading Progress in 10.6 25.7 33.6 17.7 7.1 5.3 reading Letter 15.0 31.0 27.4 15.0 8.8 2.7 recognition Sight words 8.8 30.1 31.9 15.9 8.8 4.4 Sound symbol 10.6 29.2 29.2 15.0 9.7 6.2 Interest in 8.0 17.7 35.4 12.4 6.2 20.4 writing Text writing 7.1 14.2 19.5 31.9 6.2 21.2 Handwriting 5.3 16.8 38.1 25.7 9.7 4.4
A comparison of mean scores for reading, writing and handwriting progress is shown in Tables 51 and 52.
Chapter 4: Describing and Correlating Preschool Data 199 Table 51
Comparing Mean Scores for Progress in Reading by School
School Score Interest Progress Letter Sight Words Sound Symbol in Reading in Reading Recognition Development A Mean 4.23 3.39 3.93 3.62 3.48 SD 1.34 1.44 1.54 1.46 1.65
B Mean 4.45 4.24 4.24 4.15 4.18 SD 1.00 1.06 1.11 1.09 1.15
C Mean 4.91 4.45 4.48 4.32 4.35 SD .95 .96 .98 1.02 .91
Total Mean 4.52 3.99 4.20 4.00 3.97 SD 1.15 1.27 1.27 1.25 1.35
Table 52
Comparing Mean Scores for Writing and Handwriting Progress by School
School Score Interest in Writing Text Writing Handwriting A Mean 3.81 3.34 3.51 SD 1.41 1.44 1.36
B Mean 4.06 3.81 3.75 SD 1.08 1.07 1.03
C Mean 2.56 2.48 3.83 SD 1.70 1.66 .98
Total Mean 3.47 3.20 3.69 SD 1.56 1.51 1.15
Multivariate analysis revealed a significant school effect [Wilks Lambda = .48,
MVF (16, 206) = 5.54; p < .01; eta-squared = .30]. Further analyses showed that this effect was shown for six of the eight literacy items. These are presented in Table 53.
Chapter 4: Describing and Correlating Preschool Data 200 Table 53
Multiple Comparisons for Literacy Progress Showing School Effect
Dependent Variable School 1 School 2 Mean Difference Sig. Interest in reading C A .68 .02 Progress in reading B A .84 .01 C A 1.06 .00 Sight words C A .69 .04 Sound symbol develop C A .86 .01 Interest in writing A C 1.24 .00 B C 1.49 .00 Text writing A C .86 .03 B C 1.33 .00
Teachers at School C perceived their Year 1 students to be doing significantly better than teachers at Preschool A on all four reading items. In one instance, namely, progress in reading, teachers at Preschool B also gave their students higher ratings.
Teachers from Preschool A, despite having the greatest number of students from professional families, did not rate their students’ progress as highly as the teachers from either of the two other schools in the study. This may indicate that students come to School A with less well-developed reading skills or the expectations of the teachers at Preschool A are different.
A possible hypothesis is that the students from Preschool A arrive at preschool showing some knowledge and understanding of reading and although they may progress in the first few weeks of Year 1, their teachers do not regard their progress as depicting a major change. When this occurred, teachers from Preschool A tended to rate students’ progress more conservatively than the teachers in Preschool B and
Preschool C where the progress may be more easily observed.
Chapter 4: Describing and Correlating Preschool Data 201 In relation to writing, four significant differences occurred. These were:
• Interest in writing: School A > School C (p < .01); School B > School C (p <
.01);
• Text writing: School A > School C (p = .03); School B > School C (p < .01).
Teachers at School A and School B rated their students more highly than the teachers at School C for both variables. This may indicate that the students at School
C come to preschool with far less well-developed writing skills than the students from the other two preschools, or that the teachers from Preschool C possibly have higher expectations of their students as beginning writers.
No significant effect occurred for writing progress with age (p = .07) or gender (p =
.06). However, a significant effect occurred for handwriting development [F(1,111)
= 4.82, p = .03]. Female students showed a higher mean score (3.91) compared to the mean score for male students (3.44).
4.3.2.1 Summary
Data from Teacher Checklist 1 provided Year 1 teachers’ perceptions of students’ adjustment to school, work habits, reading, writing and handwriting progress in the early weeks of Year 1. Significant differences due to school, age or gender have been highlighted. A summary of teachers’ perceptions is now presented.
Adjustment to school:
• Separates from parents: - 80.5% rated good, very good or excellent;
• Settled into Year 1: – 82.2% rated good, very good or excellent;
Chapter 4: Describing and Correlating Preschool Data 202 Personal student characteristics:
• Concentration – 70.7% rated good, very good or excellent;
• Application to tasks: – 72.6% rated good, very good or excellent;
• Personal organisation: – 65.4% rated good, very good or excellent;
• Follows instructions: – 65.5% rated good, very good or excellent.
Reading, writing and handwriting progress:
• Interest in reading – 78.8% rated good, very good or excellent;
• Letter recognition – 73.4% rated good, very good or excellent;
• Sight word knowledge: – 70.8% rated as good, very good or excellent;
• Progress in reading: – 69.9% rated good, very good or excellent;
• Sound symbol relationships: – 69% rated as good, very good or excellent;
• Interest in writing: – 61.1% rated as good, very good or excellent;
• Handwriting – 60.2% rated as good, very good or excellent;
• Text writing – 40.8% rated as good, very good or excellent;
Teachers perceived the majority of students in the study to be making good progress or better in all aspects of reading and all aspects of writing except for ‘writing texts’.
This result is understandable at such an early time in Year 1 when many young students are just beginning to understand the purposes for writing and many students are role-playing the writing of texts.
Chapter 4: Describing and Correlating Preschool Data 203 The overall picture from Year 1 teachers’ perspective is positive. The majority of students are seen to have adjusted well to school, and demonstrated a degree of good work habits. Students also were perceived as having good knowledge and skills in reading and writing.
The next section reports results from a Teacher Survey (see Appendix T) completed by Year 1 teachers in March of Year 1. The first part of the survey sought personal information from teachers relating to age, qualifications and teaching experience.
These data were reported in Chapter 3. The second part of the survey sought information from teachers relating to their perceptions of Year 1 students’ literacy knowledge and print awareness as they enter school and these results are reported in the next section. Further information relating to teaching activities used for literacy in Year 1 also is reported. All 11 Year 1 teachers completed the survey. Four teachers worked in School A, three teachers in School B and four teachers in School
C.
Chapter 4: Describing and Correlating Preschool Data 204
The shaded row on the schema indicates the current section in reporting results from
the Early Year 1 period.
CHAPTER CONTENT DESCRIPTION Chapter 4: Describing and Correlating Preschool Data/Early Year 1 4.1 Parent Survey 1 (November of Preschool) 4.2 Literacy Assessment 1 (November of Preschool). 4.3 Teacher Checklist (March of Year 1) 4.4 Teacher Survey (March of Year 1). Chapter 5: Reducing dimensions: Relationships in the Preschool/Early Year 1 Data 5.1 Factor Analysis of Parent Survey 1;Teacher Checklist 1; Literacy Assessment 1. 5.2 Cluster Analysis based on Literacy Assessment 1 – Preschool period. Chapter 6: Describing and Correlating Year 1 (May) Data 6.1 Literacy Assessment 2 (May of Year 1) Chapter 7: Reducing dimensions: Relationships in the Year 1 (May) Data 7.1 Factor Analyses: Literacy Assessment 2 7.2 Cluster Analysis of Literacy Assessment 2 Chapter 8: Describing and Correlating Year 1 (November ) Data 8.1 Literacy Assessment 3 (November of Year 1) 8.2 Parent Survey 2 8.3 Teacher Checklist 2 Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 9.1 Factor Analysis: Parent Survey 2; Teacher Checklist 2; Literacy Assessment 3 9.2 Cluster Analysis of Literacy Assessment 3
4.4 TEACHER SURVEY
4.4.1 TEACHERS’ PERCEPTIONS OF STUDENTS’ SKILLS WHEN ENTERING YEAR 1
Teachers were asked to give their perceptions of students’ literacy knowledge and
print awareness as they entered Year 1. Results of these perceptions are reported first
then these results are compared to those achieved by students on LAT 1 tasks
completed in preschool. This comparison enables Year 1 teachers’ perceptions of literacy knowledge and understanding that students bring to school to be compared with the literacy achievement of their students that was measured in Preschool.
Chapter 4: Describing and Correlating Preschool Data 205
4.4.1.1 Environmental Print
Teachers were asked to estimate the percentage of students in their Year 1 class who displayed knowledge of environmental print as they entered school. Results are shown in Table 54.
Table 54
Teachers’ Estimates of Students’ Knowledge of Environmental Print at the Beginning of Year 1
Percentage Total sample Preschool A Preschool B Preschool C (N=11) (N = 4) (N = 3) (N = 4) <10% 0 0 0 0 11-30% 0 0 0 0 31-50% 4 2 1 1 51-70% 1 0 1 0 71-90% 1 0 1 1 90-100% 4 2 0 2 Unsure 0 0 0 0 Total 11 4 3 4
Teachers’ perceptions varied across and within the three school settings. Four teachers (two from Preschool A and two from Preschool C) perceived that nearly all students (90%-100%) possessed knowledge of environmental print. Two teachers
(one from Preschool B and one from Preschool C) perceived fewer than half of the students showed knowledge of environmental print when they entered Year 1.
To compare these perceptions with students’ results in preschool, students’ scores for recognition of labels on products are examined. This task, consisting of 13 items provided data on students’ ability to recognise labels on food products. Task 2 was chosen from the four environmental print tasks because it replicates most closely the
Chapter 4: Describing and Correlating Preschool Data 206 notion of reading print from the environment. Task 1 involved recognising the product not the print and Tasks 3 and 4 were increasingly decontextualised to ascertain if students were paying attention to the print and engaging in early word recognition. Table 55 shows results for recognising labels in preschool.
Table 55
Students’ Scores in Preschool on Selected Items for the Recognition of Labels on Products
Score Total Preschool A Preschool B Preschool C Mean 7.35 7.67 7.45 6.92 SD 3.18 3.18 2.67 3.60
These results, along with knowing how many students in each setting could not recognise any product names, provide comparative data for teachers’ perceptions.
Two students from the whole sample scored zero for the recognition of labels on products. One attended Preschool A, the other attended Preschool C.
When comparing students’ results with teachers’ perceptions, it can be seen that only four of 11 teachers (36.3%) perceived correctly that nearly all students (90-
100%) had knowledge of environmental print. The remaining teachers’ perceptions were lower than the students’ results revealed. Thus, one third of the teachers had an accurate perception of the students’ ability with environmental print while two thirds had perceptions that were lower than students’ measured scores in Preschool.
Chapter 4: Describing and Correlating Preschool Data 207 4.4.1.2 Students indicate they have stories read to them
Teachers were asked to estimate the percentage of students they perceived had stories read to them prior to commencing school. Results are shown in Table 56.
Table 56
Teachers’ Estimates of the Proportion of Students Who Had Been Read to Prior to Beginning School
Range Total sample School A School B School C (N = 11) (N = 4) (N = 3) (N = 4) <10% 0 0 0 0 11-30% 0 0 0 0 31-50% 0 0 0 0 51-70% 1 1 0 0 71-90% 5 0 3 2 90-100% 5 3 0 2 unsure 0 0 0 0 Total 11 4 3 4
Five teachers (45.4%) estimated that nearly all of their students showed signs of having been read to prior to commencing school. A further five teachers considered that 71%-90% of their students appeared to have been read to, while one teacher thought that 51%-70% had been read to.
Data relating to students being read to at home was gathered from the students during LAT 1 and from their parents on Parent Survey 1. Most students (96.5%) reported they were read to at home, with four students (two from Preschool A and two from Preschool C) responding negatively to this question. Similarly, most parents (98.1%) reported that they read to their children prior to commencing school.
Two parents reported they had not read to their child, one from Preschool B and one from Preschool C. Thus, data from students and parents match closely. In contrast
Chapter 4: Describing and Correlating Preschool Data 208 most teachers (54.6%) underestimated the percentage of students who were read to at home.
4.4.1.3 Book-handling skills
Teachers were asked to indicate the percentage of students from their classes who displayed book-handling skills when they commenced school and results are presented in Table 57.
Table 57
Teachers’ Percentage Estimates of Students Displaying Book-Handling Skills at the Beginning of Year 1
Range Total sample Preschool A Preschool B Preschool C (N = 11) (N = 4) (N = 3) ( N = 4) <10% 0 0 0 0 11-30% 0 0 0 0 31-50% 2 0 1 1 51-70% 1 1 0 0 71-90% 4 2 1 1 90-100% 4 1 1 2 unsure 0 0 0 0 Total 11 4 3 4
Four teachers (36.3%) indicated that nearly all students demonstrated book-handling skills. A further four teachers considered 71%-90% of students had these skills and the remaining three nominated either 31%-50% or 51%-70% of students as having these skills.
Students’ book-handling skills were measured within the Concepts About Print Test
(CAP). Items 1 to 5 of the CAP test provided data on book-handling along with some awareness of print knowledge. Items 1 to 5 are:
Chapter 4: Describing and Correlating Preschool Data 209 • Item 1: Point to the front of the book;
• Item 2: Indicate print not the illustrations carry the message;
• Item 3: Indicate where to start reading;
• Item 4: Show that reading proceeds in a left to right direction;
• Item 5: Understand left to right directionality for each line of print (return
sweep).
Percentage results for students’ performances in Preschool on CAP Items 1-5 are shown in Table 58.
Table 58
Students’ Book-Handling in Preschool
CAP Item Total % Preschool A % Preschool B% Preschool C% Item 1 98.2 97.7 100.0 97.4 Item 2 69.3 72.1 69.7 65.8 Item 3 89.5 88.4 90.9 89.5 Item 4 86.0 86.0 84.8 86.8 Item 5 78.0 79.1 78.8 76.3
Results showed that the mean percentage scores were similar across all settings.
More than 98% of students were able to point correctly to the front of the book (Item
1). More than 69% of students indicated their understanding that print, not the illustrations, carried the message in print (Item 2) and more than 89% knew where to start reading (Item 3). Many students showed an understanding of directionality with more than 86% knowing that reading proceeds in a left to right direction (Item 4).
Furthermore, 78% understood the return sweep relating to directionality (Item 5).
Chapter 4: Describing and Correlating Preschool Data 210 Eight (72.7%) of the 11 teachers perceived students’ book-handling skills accurately by estimating (71% -100%). Three of the teachers (27.3%) underestimated these skills.
4.4.1.4 Students writing their own name
Teachers were asked to estimate the percentage of students in their classes who could write their given name with at least 90% accuracy at the beginning of the school year. Results are shown in Table 59.
Table 59
Teachers’ Estimates of Students Who Had Written Their Given Name with 90% Accuracy When Commencing School
Range Total sample School A School B School C (N = 11) (N = 4) (N = 3) (N = 4) <10% 0 0 0 0 11-30% 0 0 0 0 31-50% 1 0 0 1 51-70% 2 1 0 1 71-90% 5 2 2 1 90-100% 3 1 1 1 unsure 0 0 0 0 Total 11 4 3 4
Teachers’ results again differed across the sample and within school settings. Three teachers (27.2%) indicated that nearly all students (91%-100%) could have written their given name with 90% accuracy when they commenced school. Five others
(45.4%) estimated that 71%-90% of their students could have completed this task.
The remaining three indicated that between 31% and 70% of their class could satisfactorily have written their given names with 90% accuracy.
Chapter 4: Describing and Correlating Preschool Data 211 Students were asked to write their name as part of LAT 1 completed in November of the Preschool year. Results showed that 112 (98%) of students were able to write their name with 100% accuracy. Some students (81.6%) wrote given name only and some (16.7%) wrote given name and surname. These data are shown in Table 60.
Table 60
Percentage of Students Who Wrote Their Name Correctly in Preschool (LAT 1)
Name writing Total Preschool A Preschool B % Preschool C % % % Given name only 81.6 69.8 84.8 92.1 Given name and 16.7 30.2 15.2 2.6 surname
Only three teachers (27.2%) estimated correctly by indicating that nearly all (91%-
100%) students could satisfactorily complete this task. On LAT 1 students in preschool were required to write their name with 100% accuracy compared with the teachers’ estimations based on 90% accuracy.
Teachers also were asked to estimate the number of students in their class who could write both given name and surname with 90% accuracy. Results are shown in Table
61.
Chapter 4: Describing and Correlating Preschool Data 212 Table 61
Teachers’ Estimates of Students Who Could Write Given Name and Surname with 90% Accuracy When Commencing Year 1
Range Total sample School A School B School C (N = 11) (N = 4) (N = 3) (N = 4) <10% 3 1 0 2 11-30% 2 0 2 0 31-50% 2 1 1 0 51-70% 2 2 0 0 71-90% 0 0 0 0 90-100% 0 0 0 0 Unsure 2 0 0 2 Total 11 4 3 4
Students on LAT 1 revealed that when writing given name and surname, students’ performed differently at each school (see Tables 28-30). Approximately 17% overall had written both given name and surname while results in each setting were:
Preschool A (30.2%), Preschool B (15.2%) and Preschool C (2.6%). Because these results vary considerably from the mean percentage score for the whole sample, teachers’ perceptions will be compared to results for their own school, not the result for the whole sample.
Results showed that one of four teachers at School A estimated within the percentage range (31%-50%) closest to the students’ actual results of 30.2%. For the remaining teachers from School A, one underestimated and two overestimated students’ ability on this task.
Two of three teachers from Preschool B correctly estimated the percentage of students who completed this task successfully as 11%-30%. The other teacher
Chapter 4: Describing and Correlating Preschool Data 213 overestimated the number of students. For School C two of the four teachers estimated correctly by indicating <10%. The other two teachers indicated they were unable to estimate a percentage for this task. Thus across the three sites, five teachers (45.4%) correctly estimated their students’ ability to write their full name.
4.4.1.5 Students who can read on entering preschool
Teachers were asked to estimate the percentage of students in their classes who could read when they commenced school. All indicated fewer than 10% of students in their classes could do so. While a definition of ‘could read’ was not provided for the teachers, results collected from the students on LAT 1 in November of the preschool year are notable. Within these tasks students were not asked to read texts, but they were asked to read a total of 38 words. Thirteen were in Task 4 (reading words from word cards) during environmental print tasks. Three words were within the CAP test, a further seven were in the Print Awareness and Word Knowledge
Task and 15 were in the Canberra Word Test.
Only five students (4.4%) within the total sample scored zero for reading words.
One student from Preschool B scored 37 out of 38. Results for reading words in
Preschool are shown in Figure 8
Chapter 4: Describing and Correlating Preschool Data 214 30
20 Percent
10 Preschools
Preschool A
Preschool B
0 Preschool C .0 2. 4. 6 8. 10 1 14. 1 22. 33 3 0 00 00 .0 00 2. 7. 7. 0 .0 00 00 00 00 .0 00 0 0
Total number of words read in preschool
Figure 8. Students’ results for reading words in preschool
While no opportunities for reading texts were provided to preschool students, many of them demonstrated they could read words. One student, who scored 97.3% for reading words could read texts. She read the story ‘Oscar Got the Blame’ (see
Appendix F) to the adult facilitator rather than have the story read to her. When comparing students’ results for reading words with the teachers’ perceptions, then
Year 1 teachers appear to have once again underestimated their students’ ability.
4.4.1.6 Students who can write words
Teachers were asked to estimate the percentage of students who at the beginning of
Year 1 could write words apart from their names. Results are presented in Table 62.
Chapter 4: Describing and Correlating Preschool Data 215 Table 62
Teachers’ Estimates of Students Who at the Beginning of Year 1 Could Write Words Other Than Their Names
Range Total sample Preschool A Preschool B Preschool C <10% 8 2 3 3 11-30% 2 2 0 0 31-50% 1 0 0 1 51-70% 0 0 0 0 71-90% 0 0 0 0 90-100% 0 0 0 0 unsure 0 0 0 0 Total 11 4 3 4
The majority of the teachers perceived that fewer than ten percent of students could have written words apart from their names. Two indicated between 11% and 30% of students would have done so and one teacher perceived between 31% and 50%.
Robinson’s Test of Writing Vocabulary was one task within the LAT 1 in Preschool.
Students were asked to write as many words as they could in a ten-minute period.
Students’ results for this test are shown in Table 63.
Table 63
Preschool Students’ Scores for Robinson’s Test of Writing Vocabulary by Preschool
Score Total Preschool A Preschool B Preschool C % % % % .00 51.8 46.5 39.4 68.4 1.00 17.5 20.9 18.2 13.2 2.00 12.3 7.0 18.2 13.2 3.00 8.8 11.6 12.1 2.6 4.00 4.4 7.0 3.0 2.6 5.00 2.6 2.3 6.1 0.0 6.00 0.9 2.3 0.0 0.0 9.00 0.9 2.3 0.0 0.0 28.00 0.9 0.0 3.0 0.0 100.0 100.0 100.0 100.0
Chapter 4: Describing and Correlating Preschool Data 216 Fifty-five of the 114 students in this study could write other words apart from their name and spell them accurately prior to commencing primary school. These results were shown in LAT 1 for Robinson’s Test of Writing Vocabulary. When compared to Year 1 teachers’ perceptions these results once again showed teachers underestimated students’ ability. Only one teacher from Preschool C perceived students’ abilities accurately and this is shown in Table 64.
Table 64
Comparison of Teachers’ Estimates of Students’ Ability To Write Other Words on Entering School Compared to Students’ Achievement on Robinson’s Test of Writing Vocabulary in Preschool
Setting Teachers’ percentage estimates Percentage of students who wrote other words in preschool Preschool A 2 teachers < 0% 53% 2 teachers 11%-30%
Preschool B 3 teachers <10% 60%
Preschool C 3 teachers < 10% 31.5% 1 teacher 31% -50%
4.4.1.7 Naming Letters of the Alphabet
A final set of items in the Teachers’ Survey related to teachers estimating the percentage of students from their class who could name letters of the alphabet when they entered school. Categories for the responses included none; few; some; most; all and not known. Teachers’ estimates for the ‘none category’ are shown in Table
65.
Chapter 4: Describing and Correlating Preschool Data 217 Table 65
Frequency of Teachers’ Estimates of Students Who Knew No Letter Names at the Beginning of Year 1
Percentage Total sample Preschool A Preschool B Preschool C estimate .00 4 3 0 1 10.00 2 0 1 1 15.00 1 1 0 0 40.00 1 0 1 0 65.00 1 0 1 0 Missing 2 0 0 2 Total 11 4 3 4
When comparing teachers’ percentage estimates, it can be seen that four teachers
(three from Preschool A and one from Preschool C) indicated that no students would score zero for letter naming when they entered Year 1. Two teachers estimated 10% and one estimated 15% of students would not know the names of any letters.
Within LAT 1 in the preschool period students were asked to name all of the lower case letters and all upper case letters and an additional letter (a) and letter (g). Thus a possible total score for naming letters in LAT 1 was 54. One student from the sample scored zero on the letter naming task and that student came from Preschool
A. Thus the estimates of four teachers who had indicated no students would commence preschool knowing no letter names were fairly accurate. Two teachers indicated 10% and one estimated 15% of the students would not know letter names when they entered preschool and while these results underestimate the students’ ability, they are within a reasonable range.
Chapter 4: Describing and Correlating Preschool Data 218 Two teachers estimated well above the actual result. One teacher estimated 40% and another estimated 65% of students would not be able to name any letters of the alphabet. These teachers underestimated students’ ability on this task. Two teachers did not make an estimate on this survey question.
Teachers also provided an estimate of the percentage of students knowing the names of ‘all’ the letters of the alphabet. Their estimates are provided in Table 66.
Table 66
Teachers’ Estimates of Students Who Know the Names of All Letters of the Alphabet on Entering Year 1
Percentage Total sample Preschool A Preschool B Preschool C estimate .00 2 1 1 0 8.00 1 1 0 0 10.00 4 2 2 0 16.00 1 0 0 1 75.00 1 0 0 1 Missing 2 0 0 2 Total 11 4 3 4
Again teachers’ estimates varied considerably. Students’ actual scores are shown in
Table 67.
Table 67
Students’ Scores for Letter Naming in Preschool
Total Preschool A Preschool B Preschool C Number of students 114 43 33 38 Mean 26.50 28.74 28.30 22.42 SD 17.85 18.68 16.61 17.67 Minimum .00 .00 3.00 1.00 Maximum 54.00 54.00 54.00 54.00
These results indicated students show considerable knowledge of both upper and lower case letter names with Preschool A and B showing a very similar mean scores
Chapter 4: Describing and Correlating Preschool Data 219 (A = 28.74 and B = 28.30). Seven students in the sample named all 54 letters correctly. Of these five students (11.6%) were from Preschool A, one (3.0%) was from Preschool B and one (2.6%) was from Preschool C.
When comparing the Year 1 teachers’ estimates with students’ results, it is seen that in Preschool A all four teachers underestimated the students’ ability on this task.
Their estimates are all reasonable, within the range of 0%-10% when 11.6% of the students at this preschool knew all of the letter names.
For Preschool B where one student (3.0%) knew the names of all the letters, one teacher underestimated by indicating 0% and two teachers overestimated by indicating 10%. However, these estimates also are reasonable. In Preschool C where one student knew all of the letter names, both teachers overestimated the result. One teacher estimated 16% and another estimated 75% of the students could name all the letters of the alphabet. The estimate of 75% was well over a reasonable estimate of students’ ability on this task. Two teachers from Preschool C did not provide estimates.
4.4.2 DISCUSSION
A summary of the comparisons between the teachers’ estimated percentage results and students’ measured results in preschool is shown in Table 68. The table shows the accuracy of estimates made by the Year 1 teachers.
Chapter 4: Describing and Correlating Preschool Data 220 Table 68
Teachers’ Estimates of Students’ Literacy Abilities as They Enter Year 1
Tasks Accurate Overestimates Underestimates estimates Environmental Print 4 0 7 Stories read to students 5 0 6 Book-handling 8 0 3 Writing given name 3 0 8 Writing given name and surname 5 3 1 Can read (depending on definition) 0 0 11 Writing words 1 0 10 Knowing no letter names 4 0 5 Knowing all letter names 0 4 5 Total 30 7 56
From this summary it can be seen that the Year 1 teachers largely underestimated students’ skills and abilities on a number of early literacy tasks. Teachers were most accurate in estimating students’ abilities when observing behaviours such as, book- handling skills and estimating if the students had been read to prior to commencing school. They were least accurate when estimating knowledge about students’ writing ability or knowledge of letter names. These results clearly indicate a need for Year 1 teachers to expand their general classroom observation of students’ behaviours to include more focussed observations of individuals and measurements of students’ literacy skills and abilities as they enter Year 1.
There is a risk that teachers may underestimate students’ knowledge, skills and understanding about the alphabetic code and conventions of written language. There are consequences of these underestimates. More able students may become bored with learning activities and less able students may go unnoticed (Clay, 1998;
McNaughton, 2002; Watson & Badenhop, 1992). Researchers have found in
Chapter 4: Describing and Correlating Preschool Data 221 previous studies that students who fail to make progress with reading and writing in the early years of schooling suffer long term consequences of this deficit throughout their education (Juel, 1988; Snow, Burns & Griffin, 1998; Stanovich, 1986).
4.4.3 TEACHING ACTIVITIES USED BY YEAR 1 TEACHERS
Teacher Survey (Items 9-18) sought information from the Year 1 teachers about teaching activities used when teaching students to be literate. Information was sought on the following: shared book experience; word recognition; phonological awareness; handwriting; modelling the writing of texts; students writing their own texts; using children’s literature; using reading schemes; using materials brought in by the students; using teacher-made resources. Response options were: more than once daily; daily; 3-4 times per week; 1-2 times per week; once per week; rarely or never. Results are presented in Tables 69–78. Missing responses have not been included in the tables.
Table 69
Percentage Frequency of Using Shared Book Experience
Frequency Total Preschool A Preschool B Preschool C > Once daily 30.8 25.0 - 75.0 Daily 46.2 75.0 66.7 25.0 3-4 times/week 23.1 - 33.3 -
Table 70
Percentage Frequency for Teaching Word Recognition
Frequency Total Preschool A Preschool B Preschool C > Once daily 30.8 50.0 - 50.0 Daily 61.5 50.0 66.7 50.0 3-4 times/wk 7.7 - 33.3 -
Chapter 4: Describing and Correlating Preschool Data 222 Table 71
Percentage Frequency for Teaching Phonological Awareness
Frequency Total Preschool A Preschool B Preschool C > Once daily 30.8 50.0 - 50.0 Daily 69.2 50.0 100.0 50.0
Table 72
Percentage Frequency for the Teaching of Handwriting
Frequency Total Preschool A Preschool B Preschool C > Once daily 18.30 - 50.0 Daily 72.7 75.0 100.0 50.0 3-4 times/wk 9.0 25.0 - -
Table 73
Percentage Frequency for Modelling the Writing of Texts
Frequency Total Preschool A Preschool B Preschool C Daily 81.5 100.0 66.7 75 3-4 times/wk 9.0 33.3 -
Table 74
Percentage Frequency for Students Writing Their Own Texts
Frequency Total Preschool A Preschool B Preschool C > Once daily 7.7 25.0 - 25.0 Daily 53.8 50.0 100.0 - 3-4 times/wk 15.4 25.0 - 25.0 Rarely/never 23.1 - - 50.0
Table 75
Percentage Frequency for Using Children’s Literature
Frequency Total Preschool A Preschool B Preschool C > Once daily 23.1 25.0 - 50.0 Daily 53.8 50.0 66.7 25.0 3-4 times/wk 7.7 25.0 - - 1-2 times/wk 15.4 - 33.3 25.0
Chapter 4: Describing and Correlating Preschool Data 223 Table 76
Percentage Frequency for Using Reading Scheme Materials
Frequency Total Preschool A Preschool B Preschool C > Once daily 7.7 25.0 - - Daily 84.6 50.0 100.0 100.0 3-4 times/wk 7.7 25.0 - -
Table 77
Percentage Frequency for Using Materials Brought by Students
Frequency Total Preschool A Preschool B Preschool C > Once daily 7.7 25.0 - - Daily 53.8 50.0 - - 3-4 times/wk 15.4 - 33.3 50.0 1-2 times/wk 23.1 25.0 - 25.0 Once/week - - 66.7 - Rarely/never - - - 25.0
Table 78
Percentage Frequency for the Use of Teacher-Made Materials
Frequency Total Preschool A Preschool B Preschool C > Once daily 7.7 25.0 - - Daily 53.8 50.0 33.3 75.0 3-4 times/wk 15.4 - 33.3 - 1-2 times/wk 23.1 25.0 33.3 25.0
Results showed most of the teaching activities are used several times every week.
The greatest variation occurred for using materials brought to school by students and for teacher-made resources. Multivariate analysis of variance for teaching activities and school showed no significant difference (p = .66). On this basis there is no prima facie reason to suspect radically-different pedagogies affecting students’ literacy progress during the first year at school.
Chapter 4: Describing and Correlating Preschool Data 224 4.4.4 DISCUSSION
Teachers in all three schools used a similar set of teaching activities for literacy. The most common were used daily or more than once daily. These were using reading scheme materials, teaching phonological awareness, using children’s literature and teaching word recognition skills.
4.4.5 SUMMARY
Two questions guiding the current study were addressed in Chapter 4. They were:
1. ‘What knowledge and understanding about literacy do students’ bring to school?
2. ‘How do aspects of prior-to-school literacy knowledge and understanding relate
to one another and students’ background?’
In relation to Thesis Question 1, results from this chapter revealed that preschool students show degrees of knowledge about literacy. These are summarised below.
Well-established knowledge of literacy was shown by preschool students:
• Recognising food products;
• Recognising labels on food products;
• Comprehending stories;
• Writing own name and naming the letters;
• Recognising letter shapes and configuration;
• Knowing letter names;
• Detecting rhymes in simple words;
• Counting syllables;
• Handling books;
• Knowing directionality of print;
Chapter 4: Describing and Correlating Preschool Data 225 Partially-established knowledge was evident as preschool students demonstrated:
• Recognising labels separated from products;
• Writing words apart from their own names;
• Knowing words starting with particular letters;
• Producing rhyming words;
• Demonstrating knowledge of words that commence with particular sounds.
Little current knowledge in relation to:
Recognising product names printed on cards; • Knowing letter sounds;
Identifying onsets; • Producing final phonemes;
• Knowing the function of punctuation marks;
• Knowing letter patterns in common words;
• Knowing the term ‘capital letter’;
• Reading words from lists or texts.
Results from this chapter also addressed Thesis Question 2, ‘How do aspects of prior-to-school literacy knowledge and understanding relate to one another and students’ background?’ Data contributing to these results were gathered from parents, teachers and students. Findings are summarised below.
Chapter 4: Describing and Correlating Preschool Data 226 Parents’ perceived that:
• Their children have good concentration, memory, interest in books and interest
in writing;
• Younger and middle age children have greater concentration, memory, interest in
books and interest in writing than older children;
• Girls have greater concentration, interest in books and interest in writing than
boys;
• Boys have better memory than girls.
Home literacy practices:
• The majority of families read to their preschool children regularly and encourage
them to take an interest in writing;
• Parents’ perceived that girls showed a significantly higher interest in writing
than boys;
• The majority of families visited the local library regularly.
Results of literacy assessments in the preschool
• Preschool students demonstrated knowledge and understanding of the alphabetic
code and writing conventions;
• None of the results in preschool showed a significant age effect;
• Few gender differences were evident – one gender difference was shown when
writing longer words with girls showing greater skills;
Chapter 4: Describing and Correlating Preschool Data 227 • Only two significant preschool differences were reported and these occurred for
decontextualised environmental print tasks and phonological awareness tasks of
syllable counting, rhyme detection, rhyme production and onset identification.
Teachers’ perceptions
• Teachers perceived students adjusted well to school and that they displayed good
work habits;
• Girls were rated more highly for application to tasks and personal organisation;
• Literacy progress and handwriting were rated highly with significant school
effects being shown for particular aspects of reading and writing;
• Girls were perceived as having better handwriting than boys;
• Teachers generally underestimated students’ literacy skills and abilities in the
early weeks of Year 1.
In Chapter 5 Factor analyses conducted to reduce dimensions on Parent Survey 1,
Teacher Checklist 1 and Literacy Assessment Tasks from Preschool are reported.
These analyses allowed an examination of underlying dimensions in parents’ and teachers’ perceptions and literacy assessment data from the preschool period. Cluster analyses based on selected Literacy Assessment Task results also are reported. These analyses allow for examination of the predictive nature of literacy performance tasks completed by students in preschool with subsequent literacy achievements completed in May/June and November of their first year of schooling.
Chapter 4: Describing and Correlating Preschool Data 228 CHAPTER FIVE
REDUCING DIMENSIONS: RELATIONSHIPS IN THE PRESCHOOL DATA
This chapter addresses the following questions ‘How do aspects of prior-to-school literacy knowledge and understanding relate to one another and students’ background?’ and ‘How do analyses of prior-to-school literacy knowledge and understanding allow for prediction of students’ later literacy development during the first year of formal instruction in school?
Principal Component Analyses (PCA) and Cluster Analyses of preschool data are reported in this chapter. These analyses allowed an investigation into underlying dimensions within background data and preschool literacy measures. Additionally, they provided a means by which students with similar profiles were grouped so that cross-time comparisons of literacy achievement could be made. Relationships within these data were then explored and described and are presented here.
The following schema indicates the relationship of this chapter to the overall reporting of results.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 229
CHAPTER CONTENT DESCRIPTION Chapter 4: Describing and Correlating Preschool Data 4.1 Parent Survey 1 (November of Preschool) 4.2 Teacher Checklist 1 (March of Year 1) 4.3 Literacy Assessment 1 (November of Preschool). 4.4 Teacher Survey (March of Year 1). Chapter 5: Reducing dimensions: Relationships in the Preschool Data 5.1 Factor Analysis of Parent Survey 1;Teacher Checklist 1; Literacy Assessment 1. 5.2 Cluster Analysis based on Literacy Assessment 1 – Preschool period. Chapter 6: Describing and Correlating Year 1 (May) Data 6.1 Literacy Assessment 2 (May of Year 1) Chapter 7: Reducing dimensions: Relationships in the Year 1 (May) Data 7.1 Factor Analyses: Literacy Assessment 2 7.2 Cluster Analysis of Literacy Assessment 2 Chapter 8: Describing and Correlating Year 1 (November ) Data 8.1 Literacy Assessment 3 (November of Year 1) 8.2 Parent Survey 2 8.3 Teacher Checklist 2 Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 9.1 Factor Analysis: Parent Survey 2; Teacher Checklist 2; Literacy Assessment 3 9.2 Cluster Analysis of Literacy Assessment 3
5.1 FACTOR ANALYSES
In order to examine the factor structure of the data sets, items were grouped into comparably-administered groups of variables, such as demographic family factors, and Concepts About Print Test (CAP). In this section a report is provided of how these groups of variables were submitted to Principal Component Analysis (PCA).
Since orthogonal factors are sought in this exercise, varimax rotation was considered appropriate. It permits factor axes to move to highest-load positions, thus enabling the development of new factors for interpretation, while retaining factorial orthogonality, and clarity of interpretation. When displaying PCA in tables the variable weightings that contribute to the formation of the new factor are shown in bold and where the variable weightings are trending, they are shown in italics.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 230
5.1.1 BACKGROUND FACTORS
Data derived from demographic information, parents’ perceptions and teachers’ perceptions were analysed in order to devise background factor scores. These data were gathered on Parent Survey 1 (see Appendix C). Similarly, data relating to the teachers' perceptions of the students’ learning characteristics and literacy progress were collected on from Year 1 teachers on Teacher Checklist 1 in March of Year 1
(see Appendix U). Principal Component Analysis using Varimax rotation was used on these data in order to examine underlying factors that enabled a more detailed examination of the data gathered from the students’ Literacy Assessment Task
(LAT) measures in Preschool.
5.1.1.1 Background Factor: Demography
Principal Component Analysis is reported here using mothers' and fathers’ occupation and educational qualifications. Initial analysis of these four variables showed two factors with eigenvalues greater than 1.0. These factors accounted for
65% of the variance and the rotated component matrix is shown in Table 79.
Table 79
Rotated Component Matrix for Two-factor Solution on Parents’ Education Levels and Occupations
Parents’ Education/Occupation Mother SES Father SES Mothers’ education level .81 .08 Mothers’ occupation .76 -.01 Fathers’ occupation -.15 . 81 Fathers’ education level .23 .76
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 231
Factor 1 weighted heavily on mothers’ educational qualifications and occupation with light loadings on fathers’ educational qualifications. Factor 2 weighted on fathers’ occupation and fathers’ educational qualifications. These factors are broadly described as ‘mother SES factor’ and ‘father SES factor’ and showed little inter- correlation.
5.1.1.2 Background Factor: Parents’ Perceptions of Child Characteristics
Supplementary analyses of data concerning students’ literacy progress scores related to parents' perceptions of their children's characteristics. These data were collected on Parent Survey 1. PCA was conducted using data from questions 17, 18, 19, 20 and 21 (see Appendix C). They related to the students’ enjoyment of Preschool, interest in books and writing, concentration and memory. A two-factor solution is shown in Table 80 with these factors both having an eigenvalue greater than 1.0 and accounting together for 69% of the variance.
Table 80
Rotated Component Matrix for a Two-factor Solution for Parents' Perceptions of Their Children’s Concentration, Memory, Interest in Writing and Books and Enjoyment of Preschool
Survey Item Factor 1 Factor 2 Parents’ perceptions – Parents’ perceptions – child characteristics enjoy preschool Rate your child's concentration .83 .02 Rate your child's memory .80 -.09 Rate your child's interest in writing .76 .26 Rate your child's interest in books .57 .54 Child enjoy preschool? -.05 .90
The resultant solution showed heavy loadings for Factor 1 (named ‘parents’ perceptions – child characteristics’) based on parents' perceptions of children's Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 232 concentration, memory, interest in books and interest in writing. Factor 2 (named ‘ parents’ perceptions – enjoy preschool) showed heavy loadings on parents' perception of how much children enjoy Preschool and children’s interest in books, and captured to a lesser degree, children's interest in writing. This constitutes a background factor for concentration, memory and interest in writing and another for enjoying Preschool. Note that ‘interest in books’ loaded across both – that is partial loading associated with concentration, memory and interest in writing and partial loading associated with enjoyment of Preschool. Clearly, this item relates to both factors.
5.1.1.3 Background Factor: Parents’ Perceptions of Home Literacy Practices
Parents were asked about home literacy practices on questions 20-34 on Parent
Survey 1. A number of these items (20, 21, 22, 26, 27, 29, 30, 32) did not show a variation of response and therefore were not used in the Principal Component
Analysis. Items within the final analysis included questions relating to:
• Members of the family reading to children (question 23);
• Amount of time spent reading to children (question 24);
• How often joint reading took place at home (question 25);
• The number of preschool texts in the home (question 28) and
• Children's interest and active participation with writing at home
(questions 31, 33 and 34).
The resultant three-factor solution accounted for 52.3% of the variance and is shown in Table 81.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 233
Table 81
Rotated Component Matrix for Parents’ Perceptions of Home Literacy Practices
Survey Items Factor 1 Factor 2 Factor 3 Parents’ Parents’ Parents’ perceptions - perceptions - perceptions – home writing home reading who reads
Writing at home Does your child try write anything .81 .05 -.09 else at home? Child interested in writing .80 -.17 .00 How often does your child write at .78 .08 .02 home?
Reading at home Estimate number of books for .00 .79 -.07 Preschool student How often is the child read to? .01 .78 -.02 Time for reading sessions .09 .42 .30
People who read to the preschool child at home Does mother read to preschool student? -.07 .39 -.10 Does father read to preschool student? .00 .23 .76 Does sister read to preschool student? .00 -.17 .71 Does brother read to preschool student? -.08 -.15 .58
The solution showed Factor 1 (named ‘parents’ perceptions – home writing’) heavily loaded on children writing other things apart from their name at home; children's interest in writing and how often children write at home. Factor 2 (named parents’ perceptions – home reading) loaded heavily on the number of books at home suitable for preschool children, how often children were read to and to a lesser extent on the time taken for reading sessions. Factor 3 (named parents’ perceptions – who reads’) weighted heavily on fathers’ and siblings’ reading to preschool children and to a lesser extent on mothers’ reading to children. That is, we find a clear and distinct factor relating to writing, another relating to availability of books and
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 234 frequency of reading, and another relating to family members other than mother reading to the student.
5.1.1.4 Background Factor: Teachers’ Perceptions of Child Characteristics
In March the Year 1 teachers completed Teacher Checklist 1(see Appendix U). This checklist sought information from teachers relating to each child's learning characteristics and progress in literacy. Principal Component Analysis was conducted to examine underlying factors. The result was a two-factor solution.
Rotated component matrix accounts for 90% of the variance is shown in Table 82.
Table 82
Rotated Component Matrix for Year 1 Teachers’ Perceptions of Students’ Characteristics
Checklist Item Factor 1 Factor 2 Teachers’ perceptions – Teachers’ perceptions – class conduct independence Application to tasks .93 .19 Personal organisation .93 .17 Follows instructions .92 .22 Ability to concentrate .91 .25 Child separates from parents .08 .95 Settled into Yr1 .40 .84
Factor 1 (named teachers’ perceptions – class conduct) weighted heavily on class teachers’ perception of the children's application to tasks, personal organisation, ability to follow instructions and ability to concentrate. Factor 2 (named teachers’ perceptions – independence’) weighed heavily on variables relating to class teachers’ perceptions of how well children separated from their parents and settled into Year 1. Thus we find one factor relating to specific ways children conducted
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 235 themselves in class and one relating to a children's independence. Note that ‘settled into Year 1’ had some cross-loading. Data collected from Year 1 teachers on this checklist related to students’ behaviour during the first six weeks of Year 1.
5.1.1.5 Background Factor: Teachers’ Perceptions of Literacy Progress
Information about teachers’ perceptions of the students’ early literacy progress was collected in March using Teacher Checklist 1. Principal Component Analysis examined underlying factors and the result was a two-factor solution accounting for
87% of the variance. Rotated component matrix is shown in Table 83.
Table 83
Rotated Component Matrix for Teachers' Perceptions of Literacy Progress in March Year 1
Checklist Item Factor 1 Factor 2 Teachers’ perceptions – Teachers’ perceptions – reading writing Progress in reading .92 .19 Sound symbol development .91 .26 Letter recognition .90 .21 Sight word knowledge .89 .20 Interest in reading .81 .14 Interest in writing .18 .96 Text writing ability .25 .94
Factor 1 (named teachers’ perceptions – reading’) loaded heavily on the four variables relating to reading progress and Factor 2 (named ‘teachers’ perceptions – writing’) loaded heavily on the variables relating to writing progress. Thus, two clearly defined factors emerged, one relating to reading and one for writing.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 236
5.1.2 CORRELATIONS OF BACKGROUND FACTORS
Pearson’s correlation of the eleven calculated background factors was carried out to ascertain relationships among them. Results showed seven significant positive correlations and eight significant negative correlations. For ease of presentation these correlations are presented in two tables, one for positive correlations and one for negative correlations. Five of the significant positive correlations related to parents’ perception factors and two to teachers’ perceptions. Results for significant positive correlations are shown in Table 84.
Table 84
Significant Positive Correlations of Background Factors
Background Factors Mother Father Parents’ Teachers’ Teachers’ SES SES perceptions perceptions perceptions - factor factor home writing - conduct independence Parents’ perceptions -.07 .30** 1.00 in table 85 in table 85 -home writing Parents’ perceptions .03 .22* .47** in table 85 in table 85 - child characteristics Parents’ perceptions .21* -.01 .30** -.02 in table 85 – enjoy preschool Teachers’ perception .04 in table in table 85 .68** .29** - reading 85 ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed)
All eight significant negative correlations related to teachers’ perceptions. These results are shown in Table 85.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 237
Table 85
Significant Negative Correlations of Background Factors
Background Mother Father Parents’ Parents’ Parents’ factors SES SES perceptions – perceptions - perceptions - factor factor home writing child enjoy preschool characteristics Teachers’ .147 -.24* -.25** -.32** -.02 perceptions – conduct Teachers’ -.20* -.09 -.06 -.16 -.21* perceptions – independence Teachers’ .05 -.34** -.25* -.30** -.08 perceptions – reading ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed)
These correlation results were unpredicted in that the majority of the significant positive correlations (five out of seven) related to parents’ perceptions and all eight significant negative correlations related to teachers’ perceptions. For the positive correlations three of the positive correlations related to demographic factors. One related to ‘mother SES factor’ and two related to ‘father SES factor’. Thus, results indicated that if a child’s father worked in a professional occupation and was well educated then parents were more likely to report that children had an interest in writing at home and displayed good concentration and memory.
Similarly if the children’s mother had a high-status occupation and was well educated then parents were more likely to perceive that their children enjoyed
Preschool. Two significant positive correlations occurred for parents’ perceptions of their children’s interest in writing at home and these correlated with parents’ perceptions of their children’s concentration, memory and enjoyment of Preschool. Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 238
Figure 9 shows the positive correlation of parents’ perceptions – home writing with parents’ perceptions – child characteristics (.47** correlation).
2
1
0
-1
-2
-3 Parents' perception of child characteristics
-4 -4 -3 -2 -1 0 1
Parents' perception of writing at home
Figure 9. Positive correlation of parents’ perceptions – child characteristics and parents’ perceptions – home writing
The final two significant positive correlations showed a relationship between teachers’ perceptions of students’ reading progress with specific classroom conduct and displays of independent behaviour. This effectively means that the teachers positively correlated early reading progress with those students who showed application to tasks, followed directions, displayed good personal organisation and were able to concentrate. Teachers also related early reading progress with those students who separated easily from parents, settled easily into Year 1 and showed independence.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 239
Three of the significant negative correlations related to demographic factors. Two negative correlations related to the ‘father SES factor’ and these were teachers’ perceptions of conduct in class and progress in reading. These results indicated first that the students whose fathers work in professional occupations and were well- educated had not been rated highly by their teachers for application to classroom tasks, personal organisation, and ability to follow instructions. Second, these students also had not been rated highly by their teacher in March of Year 1 as showing good progress in reading.
The final significant negative correlation occurred for demography ‘mother SES factor’ with teachers’ perceptions of independence in March of Year 1. Those students whose mothers worked in professional occupations and had higher levels of education were not rated highly by their teachers for showing independent skills in
March of Year 1. Figure 10 illustrates a negative correlation and shows teachers’ perception of students’ conduct and parents’ perceptions of children’s characteristics
(-.32**).
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 240
2
1
0
-1
-2
-3 Parents' perceptions of children's characteristics -4 -2 -1 0 1 2 3
Teachers' perceptions of children's conduct
Figure 10. Negative correlation of teachers’ perception of students’ conduct and parents’ perception of children’s characteristics
The eleven background factors including demography, parents’ perceptions of child characteristics, parents’ perceptions of home literacy practices and teachers’ perceptions of child conduct and literacy progress provide a framework for examining the results from the Literacy Assessment Tasks in Preschool.
5.1.3 PERFORMANCE FACTORS
Factors derived from Literacy Assessment Tasks (performance factors) conducted with students in Preschool provided a way to examine the results from each literacy subtest more closely. Principal Component Analysis (PCA) was conducted to examine the underlying factor structure of the tasks.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 241
5.1.3.1 Performance Factor: Environmental Print Awareness
Students completed four tasks relating to identifying food products and reading the product name on 13 common food items. The four tasks became increasingly more difficult as contextual features of the products were removed gradually. The tasks involved identifying a common food product, finding the label on the product, identifying a cut-out label, and, reading the product name printed on a card. PCA was used to test for any underlying factors.
The initial analysis of the four tasks showed one factor with an eigenvalue greater than 1.0. In the light of the scree test (Figure 11) and in the interests of interpretation, a two-factor solution is preferred as some levelling out of the scree plot is observed.
3.0
2.5
2.0
1.5 Eigenvalue
1.0
.5
0.0 1 2 3 4
Component Number
Figure 11. Scree test for PCA of environmental print task measures
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 242
A two-factor solution accounting for 89.2% of the variance is shown in Table 86.
This solution shows a heavy weighting for Factor 1 (named ‘contextual’) on the highly contextualised tasks such as recognising the product and recognising the name on the product. Factor 2 (named ‘decontextual’) is heavily weighted on those tasks with low contextualisation where the students were asked to recognise the cut- out label and read the product name from a word card.
Table 86
Rotated Component Matrix for Four Environmental Print Tasks
Environmental Print Tasks Factor 1 Factor 2 Contextual Decontextual Task 1: Total recognition of products .95 .11 Task 2: Total recognition of labels on products .82 .44 Task 4: Total recognition of words on cards .11 .94 Task 3: Total recognition of cut-out labels .41 .82
The first factor loads heavily on tasks 1 and 2 showing a high level of contextualisation. Factor 2 loads heavily on tasks 3 and 4 where there is a low level of contextualisation. Factor 2 cross loads on task 2 and Factor 1 cross loads on task
3. This crossloading is an indication that two distinct factors one with a high level of contextualisation and one with a low level of contextualisation have not been calculated, but some traces of each still exist in both factors.
5.1.3.2 Background and Environmental Print Factors
Pearson's correlation with the calculated background factors, school, age and gender and the factor scores for environmental print awareness was carried out to ascertain if significant relationships exist. Sixteen variables were used in the correlation.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 243
Three of these variables are children's age, gender and school, eleven are calculated background factors reported earlier and the final two factors were the environmental print factors. Results revealed three significant, positive correlations and six significant, negative correlations. Results of the correlations are shown in Table 87.
Table 87
Correlations for Environmental Print Tasks
Background Factors Environmental print Environmental print (contextual) factor (decontextual) factor Father SES .20* .20* Parents’ perceptions – child characteristics .09 .26** Teachers’ perceptions – class conduct -.30** -.24* Teachers’ perceptions – independence .00 -.19* Teachers’ perceptions – reading -.27* -.29* Teachers’ perceptions – writing -.21* -.02 Parents’ perceptions - who reads .03 .06 ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed)
Three positive correlations occurred for environmental print scores, one for the contextual factor and two for the decontextual factor. The father SES factor correlated positively with the contextual factor and also with decontextual factor for environmental print. The decontextual factor also correlated positively with parents' perception of their children's concentration and memory.
Six factors correlated significantly and negatively with environmental factors. All negative correlations were associated with teachers’ perceptions of students’ conduct or their progress in reading and writing. These negative correlations raise questions about the criteria Year 1 teachers utilised as they perceived students’ literacy progress after six weeks in school. These negative correlations occurred with results
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 244 students had achieved for environmental print tasks in November of the preschool year.
5.1.3.3 Performance Factor: Letter Knowledge
Students were asked to identify all capital and lower case letters following the procedures outlined in Clay (1985, pp. 23-24). Tasks included naming the letter, giving the sound for each letter and providing a word that starts with each letter.
With such a large amount of data a PCA examined underlying factors.
Principal Component Analysis with varimax rotation was conducted and a single- factor solution that was unable to be rotated was the result. The 1-factor solution accounted for 88.4% of the variance is shown in Table 88.
Table 88
Component Matrix for Letter Knowledge in Preschool
Letter Knowledge Tasks Factor 1:Letter Knowledge 1 Total letter identification .97 Total words for specified letters .94 Total knowledge of letter sounds .90
5.1.3.4 Background and Letter Knowledge Factors
Pearson's correlation of background factor scores (demography, parents’ perceptions and teachers’ perceptions) age, gender, school and letter knowledge was carried out to ascertain relationships with children’s knowledge of letters. Results showing two
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 245 significant, positive correlations and three significant, negative correlations are presented in Table 89.
Table 89
Correlations for Letter Knowledge Factor in Preschool
Letter Father Parents’ Teachers’ Teachers’ Teachers’ Knowledge SES perceptions – perceptions - perceptions perceptions Factor factor child class conduct - reading – writing characteristics Letter .26** .31** -.37** -.46** -.36** knowledge and identification ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed)
The first significant, positive correlation occurred with the father SES factor. The second occurred with parents’ perceptions of child characteristics showing that their views of the child’s concentration, memory and interest in books correlated positively with the child’s letter knowledge score. A scatterplot of the positive correlation between parents’ perceptions – child characteristics and letter knowledge factor from Preschool is shown in Figure 12.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 246
4
3 eschool
2 m pr o r f
ctor 1 a
ledge f 0 know
-1 Letter
-2 -4 -3 -2 -1 0 1 2
Parents' perceptions of children's characteristics
Figure 12. Positive correlation of parents’ perception of children’s characteristics factor and letter knowledge factor from preschool
Significant, negative correlations occurred for teachers’ perceptions. These findings are notable in that they demonstrate teachers’ perceptions produced an effect opposite to the one that may be expected. Those students who showed skills relating to letter names and sounds in November of the preschool year, were not those perceived by the teachers in March of Year 1 as possessing learning characteristics usually associated with positive learning outcomes or those perceived to be progressing well with writing and reading. A sample scatterplot to illustrate the negative correlation is shown in Figure 13 and it clearly shows the highest performing students on the letter knowledge and identification tasks in Preschool were rated low by their Year 1 teachers in March of Year 1.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 247
3
ess 2 ogr
1 eading pr r 0
ceptions of -1 s' per
-2 eacher T
-3 -2 -1 0 1 2 3 4
Letter Knowledge factor from preschool
Figure 13. Negative correlation of teachers’ perception reading progress factor and letter knowledge factor in preschool
5.1.3.5 Performance Factor: Concepts About Print Test (CAP)
Students completed the Concept About Print Test (CAP) (Clay, 1985) for the first time in November of the preschool year. Students’ knowledge of print awareness, directionality, letter and word concepts and book-handling skills are measured using the 24 items in this test. Principal Component Analysis was conducted to examine underlying factors. The initial analysis of CAP showed an 8-factor solution with eigenvalues greater than 1.0, but in the light of the scree test, (Figure 14), a 6-factor solution is preferred with the scree showing some levelling out at six factors. This solution accounted for 57.9% of the variance.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 248
7
6
5
4
3 Eigenvalue
2
1
0 1 3 5 7 9 11 13 15 17 19 21 23
Component Number
Figure 14. Scree test for PCA of Concepts About Print test in preschool
A complex six-factor solution shown in the rotated matrix for CAP is presented in
Table 90.
Table 90
Rotated Component Matrix for Concepts About Print Test in Preschool
CAP Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6 item print directionality awareness of punctuation starting left and right awareness conventions points cap13 .85 .15 -.14 -.11 -.05 .13 cap12 .83 .11 -.03 -.10 -.08 .12 cap20 .81 .03 -.01 .03 .07 .03 cap10 .80 .05 .13 -.06 -.05 .03 cap14 .76 .09 -.15 -.07 .06 .06 cap19 .56 .12 .03 -.12 .33 .08 cap6 .55 .24 .27 .12 .20 -.05 cap9 .50 -.22 .29 .11 .23 .29 cap15 .36 .03 .31 -.17 .24 -.21 cap22 .32 .32 -.21 -.32 .24 .28 cap5 .10 .84 -.01 -.01 .20 .05 cap4 .14 .82 .03 -.03 .13 .06 cap3 .16 .64 .23 .17 -.29 .22 cap2 .12 .06 .73 .16 .03 -.09 cap7 -.15 .30 .62 -.11 .36 .08 cap16 -.07 -.08 .56 -.15 -.17 .33
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 249
CAP Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6 item print directionality awareness of punctuation starting left and right awareness conventions points cap17 -.04 .04 .13 .72 -.11 -.09 cap18 -.05 .08 -.07 .72 .23 .10 cap8 .24 .40 .17 -.54 .08 .02 cap24 .03 -.03 .12 -.01 .71 -.04 cap23 .31 .12 .08 .12 .48 .30 cap1 .01 .13 -.08 .01 .39 .14 cap21 .16 .14 -.13 -.06 .05 .75 cap11 .09 .09 .26 .02 .19 .61
This result clearly indicates the complex makeup of the CAP test and reporting results as a score out of 24 shows little appreciation of this complexity. Two items, item 15 (identifying the use of the question mark) and item 22 (identifying one word and two words) displayed high levels of communality with these items loading equally across a number of factors. Factor 1 (named ‘print awareness’) showed heavy weighting on eight CAP items. These were:
• Item 13, (recognising a change in letter order);
• Item 12, (recognising a change in word order);
• Item 20, (recognising reversed words);
• Item 10, (recognising line sequence alteration);
• Item 14, (recognising a change in letter order);
• Item 19, (locating pairs of upper and lower case letters);
• Item 6, (one-to-one correspondence for word pointing);
• Item 9, (knowing where to begin reading).
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 250
Factor 2 (named ‘directionality’) is heavily weighted on three test items. These were:
• Item 5, (understanding the return sweep when reading);
• Item 4, (knowing left to right direction for reading);
• Item 3, (knowing where to start reading).
Factor 3 (named ‘awareness of conventions’) weighted heavily on three test items.
These were:
• Item 2, (knowing print contains a message);
• Item 7, (understanding the concept of first and last);
• Item 16 (knowing the meaning of a full stop).
Factor 4 (named ‘punctuation’) weighted on:
• Item 17, (knowing the meaning of a comma);
• Item 18 (knowing the meaning of quotation marks); and
• Negatively on item 8 (pointing to the bottom of the inverted picture).
Factor 5 (named ‘starting points’) weighted on item 24, - recognising a capital letter and to a lesser degree on item 23 – identifying the first and last letters in a word.
Factor 6 (named ‘left and right’) weighted on item 21 - locating one letter and two letters and item 11 - knowing the left page is read before the right page.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 251
Four items from the CAP test in Preschool did not load heavily on any one factor, but have small loads distributed across a number of factors and these do not contribute significantly to the formation of the six factors. These items were:
• Item 1: Identifying the front of the book;
• Item 8: Pointing out the bottom of a picture;
• Item 15: Naming the use of the question mark;
• Item 22: Pointing to one word and two words.
5.1.3.6 Background and Concepts About Print Test Factors
Pearson’s correlations were carried out with the 11 background factor scores, school, age and gender and the six factors derived from the CAP test to ascertain their relationships. Three significant, positive correlations and six significant, negative correlations resulted and are shown in Table 91.
Table 91
Correlations of Background Factors with Preschool CAP Factors
Background Print Directionality Awareness Punctuation Starting Left and Factors awareness of points right conventions Gender 12 .10 .23* .07 -.07 .09 Father SES .16 -.04 .27** .02 .15 .06 factor Parents’ .10 .17 .24* .03 .14 .16 perceptions – child characteristics Teachers’ -.18 .01 -.20* -.01 -.09 -.34** perceptions – class conduct Teacher’ -.27* .08 -.22* -.03 -.19* -.29** perceptions – reading ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed)
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 252
Three significant positive correlations occurred for CAP Factor 3, awareness of conventions, and these related to gender, fathers’ SES, and parents’ perceptions of child characteristics. In relation to gender, girls performed significantly better than boys on CAP items 2, 7 and 16 and these are all components of CAP Factor 3, awareness of conventions.
All negative correlations were found with teachers’ perceptions of either students’ conduct in class, or their reading progress in March of Year 1. These correlations occurred for four of the six CAP factors. Teachers’ perceptions of conduct in class correlated negatively with CAP Factor 3, awareness of conventions, and CAP Factor
6, left and right. Teachers’ perceptions of reading factor correlated negatively with
CAP Factor 1, print awareness, CAP Factor 3, awareness of conventions, CAP
Factor 5, starting points and CAP Factor 6, left and right. Thus, teachers’ perceptions of students’ progress in reading in March of Year 1 again produced an unexpected negative correlation with students’ performance on parts of the CAP test completed in November of the preschool year. No significant correlations occurred for two CAP factors, understanding directionality or understanding punctuation.
In summary, significant positive correlations were shown for awareness of conventions factor with father SES factor’, gender and parents’ perceptions of child characteristics. This result indicates a positive relationship between parents’
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 253 perceptions of child memory, concentration, interest in books and writing and the students’ results on awareness of conventions factor.
Significant negative correlations all related to teachers’ perceptions of either child conduct in class or reading progress. Conduct in class included the child’s personal organisation, application to tasks, ability to concentrate and follow instructions.
Thus, teachers’ perceptions of children’s personal characteristics related negatively and significantly to the children’s achievement on two of the six CAP factors – awareness of conventions and understanding left and right convention when reading.
A possible explanation of these negative correlations is that teachers may be using different criteria when judging reading and writing progress in March of Year 1. It would appear from the results that if students display good personal organisation, apply themselves at school, follow instructions and show ability to concentrate, then teachers are more likely to judge literacy progress from these criteria and not from measures or observations of literacy skill development.
Teachers’ perceptions of student’s reading progress also correlated significantly and negatively with achievement on four of the CAP factors – print awareness, awareness of conventions, knowing starting points and knowing about left and right progression. These negative correlations could possibly be explained by an examination the concept of ‘reading progress’. It is known that young students enter school with different levels of knowledge and understanding about how written language works and it is possible that teachers judged students’ ability differently.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 254
Those who enter school knowing very little about written language may be judged as making the most progress because it is more easily observed than the progress being made by those who enter Year 1 with greater skills. Those with greater skills on entry to school may appear to be making slower day-by-day progress and this may be more difficult for teachers to observe and acknowledge. It is not possible to
‘clinch’ the explanations for the unexpected findings from these analyses, but it is clear that variable shifting and perhaps inaccurate interpretation by teachers of early literacy learning processes are in operation.
5.1.3.7 Performance Factor: Print Knowledge Task
Resources used for these tasks consisted of two charts on which the nursery rhyme
Humpty Dumpty was printed. One chart was cut into strips of print and the second chart remained intact. Students completed 17 print awareness and word awareness component tasks. Principal Component Analysis was conducted and initial results showed six factors with eigenvalues greater than 1.0. In the light of the scree test
Figure 15 and in the interests of interpretation, a three-factor solution seems preferable.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 255
5
4
3
Eigenvalue 2
1
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
Component Number
Figure 15. Scree test for PCA of print knowledge task
This solution accounted for 49% of the variance and the rotated component matrix is shown in Table 92.
Table 92
Rotated Component Matrix for Print Knowledge Task in Preschool
Print Awareness Item Factor 1 Factor 2 Factor 3 Read words Sequencing text Start reading Question 5 .78 .01 .17 Question 17 .74 .22 -.17 Question 16 .74 .23 -.07 Question 6 .73 .06 -.03 Question 15 .69 .11 .03 Question 4 .60 .02 -.08 Question 13 .56 .08 .37 Question 14 .46 -.11 .19 Question 10 .02 .85 .13 Question 9 .01 .81 .16 Question 12 .04 .77 .32 Question 11 .04 .75 .33 Question 7 .31 .39 -.30 Question 8 .06 .37 -.19 Question 2 .10 .34 -.10 Question 1 .01 .02 .83 Question 3 .06 .17 .40 Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 256
Factor 1, named ‘read words’, loads heavily on seven component tasks. These tasks include:
• Question 5 (find the word ‘wall’);
• Question 17 (point to the word ‘great’);
• Question 16 ( point to the word ‘fall’);
• Question 6 (find a rhyming word for ‘wall’);
• Question 15 (point to the word ‘sat’);
• Question 4 (point to a name in the rhyme);
• Question 13 (read the rhyme while pointing to the words).
Factor 2, named ‘sequencing text’, loads heavily on four component tasks. These tasks are:
• Question 10 (fix a strip placed out of order);
• Question 9 (recognise the strip placed out of order);
• Question 12 (fix a strip placed upside down);
• Question 11 (recognise the strip placed upside down).
Factor 3 named ‘start reading’, weighs heavily on question 1 (point to the first line of print).
Thus, the three underlying factors that underpin the Print Knowledge Task using the nursery rhyme Humpty Dumpty relate to reading words, sequencing text and knowing where to start reading. These tasks are somewhat similar to the type of
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 257 tasks completed in the Concepts About Print Test except that they were completed using a storybook.
5.1.3.8 Background and Print Knowledge Task Factors
Pearson’s correlation of background factors, school, age, gender and factor scores from the Print Knowledge Task was carried out to gauge relationships. Results revealed two significant, positive correlations and five significant negative correlations. These results are shown in Table 93.
Table 93
Correlations of Preschool Print Knowledge Task Factors and Background Factors
Print Father Parents’ Teachers’ Teachers’ Teachers’ Knowledge SES perceptions – perceptions – perceptions – perceptions Factors factor child class conduct reading –writing characteristics Reading .26** .25* -.20* -.32** -.30** words
Sequencing .11 .09 -.19* -.24** -.11 text
Start reading -.10 -.00 -.03 -.00 .04 ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed)
Two significant positive correlations occurred for ‘reading words factor’ in Print
Knowledge Task and these correlated with the father SES factor and the parents’ perceptions of child characteristics. Significant negative correlations occurred for teachers’ perceptions of class conduct, reading progress and writing progress. Once again results showed that scores on literacy measures in Preschool correlate significantly and negatively with teachers’ perceptions of students’ class conduct
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 258 and literacy progress. Significant positive correlations occurred for father SES factor and parents’ perceptions of child characteristics.
5.1.3.9 Performance Factor: Sutherland Phonological Awareness Test
Five subtests of the Sutherland Phonological Awareness Test (see Appendix K) were completed in Preschool. These were syllable counting, rhyme detection, rhyme production, onset identification and final phoneme production. Each subtest consisted of four items. Students were given practice for each item before commencing the test to ensure they understood the procedure.
PCA was conducted on children’s performances on Sutherland Phonological
Awareness Subtests to examine any underlying factors. The initial analysis resulted in a one-factor solution with an eigenvalue greater than 1.0. In the light of the scree test shown in Figure 16 and in the interests of interpretation, a two-factor solution seemed preferable and this solution accounted for 68% of the variance.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 259
7
6
5
4
3 Eigenvalue
2
1
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
Component Number
Figure 16. Scree test for PCA of Sutherland Phonological Awareness Subtests
The two-factor solution in Table 94 showed heavy weighting for Factor 1 named
‘rhyme, onset, final phoneme’, on onset identification, final phoneme identification and rhyme production questions. Factor 2 named ‘ rhyme and syllables’, weighed heavily on syllable counting, rhyme detection and rhyme production. It should be noted that both factors contain almost equal weighting of rhyme production.
Table 94
Rotated Component Matrix for Sutherland Phonological Awareness Test in Preschool
Sutherland Phonological Awareness Tasks Factor 1 Factor 2 rhyme, onset, rhyme & syllables final phoneme Total for onset identification .86 .19 Total for final phoneme identification .85 .07 Total for rhyme production .58 .52 Total syllable counting .02 .81 Total for rhyme detection .26 .73
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 260
5.1.3.10 Background and Sutherland Phonological Awareness Test Factors
Pearson’s correlation of the calculated background factors, school, age, gender, parents’ perception and teachers’ perception factors with the two factors for
Sutherland Phonological Awareness subtests was carried out to examine significant relationships. Results shown in Table 95 displayed five, significant positive correlations and four, significant negative correlations.
Table 95
Correlations for Preschool Sutherland Phonological Awareness Tasks with Background Factors
Background Factors Factor 1: Rhyme, onset, Factor 2: Rhyme, & final phoneme syllables Age -.00 .22* Father SES factor .19 .32** Mother SES factor .22* .00 Parents’ perceptions - home reading .21* -.12 Parents’ perceptions – enjoy .24* -.12 preschool Teachers’ perceptions – class -.21* -.21* conduct Teachers’ perceptions – reading -.32** -.08 Teachers’ perceptions - writing -.35** -.17 ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed)
Results showed five positive significant correlations. Three were shown for the first phonological awareness factor ‘rhyme, onset, final phoneme’. These occurred with mother SES factor and the two parents’ perception factors. Two further positive significant correlations occurred for phonological awareness Factor 2 ‘rhyme and syllables’. These occurred with age and the father SES factor. A scatterplot shown in
Figure 17 depicts a positive correlation for father SES with ‘rhyme and syllable factor’.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 261
2
1
0 er SES
Fath -1
-2
-3 -5 -4 -3 -2 -1 0 1 2
Rhyme and syllable factor
Figure 17. Positive correlation of father SES and rhyme and syllable factor
Three significant, negative correlations occurred with the first phonological awareness factor ‘rhyme, onset, final phoneme’. All were with teachers’ perception factors, one for child conduct in class and two relating to literacy progress, one for reading and one for writing. A further negative correlation also occurred for Factor 2
‘rhyme and syllables’ and this is seen with the teachers’ perception of class conduct.
Figure 18 shows a negative correlation for teachers’ perceptions - writing and rhyme onset and final phoneme factor.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 262
3
2
1
0
Teachers' perception - writing -1
-2 -2 -1 0 1 2 3
Rhyme onset and final phoneme factor
Figure 18. Negative correlation of teachers’ perception – writing and rhyme onset and final phoneme factor
5.1.4 DISCUSSION
The thesis question, ‘How do aspects of literacy knowledge and understanding prior to school relate to one another and students’ background’ is addressed in part following the reporting of factor analyses. A consistent pattern of correlations occurred in the data. Positive correlations were seen with parents’ perceptions and negative correlations with teachers’ perceptions. These results indicated parents perceive their children’s concentration and memory accurately in relation to beginning literacy learning. Teachers, on the other hand, appeared to be using other criteria when making judgements about literacy progress in the first few weeks of
Year 1, and their perceptions also correlate negatively with many of the literacy performance factors devised from preschool literacy measures.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 263
It appears as if teachers aligned students’ literacy progress with positive work application abilities in class. The abilities included positive application to tasks, demonstration of personal organisation, following instructions and showing effective concentration. These criteria have been shown to produce small, but significant negative correlations with students’ results on literacy tasks conducted in November of the preschool year. Thus, it appears that Year 1 teachers in March of Year 1 are not judging students’ reading and writing progress in absolute terms, certainly not in line with the literacy results achieved by the students four months earlier, in
November of the preschool year.
An examination of the significant positive and negative correlations that occurred between background factors and performance factors revealed that most of the positive correlations (10 out of 15) occurred with parents’ perceptions of child characteristics and the father SES factor. Most negative correlations (19 out of 24) occurred with teachers’ perceptions of class conduct or progress in reading.
It is also worth noting that no significant correlations occurred with school and only one positive significant correlation occurred with age, gender and the ‘mother SES’ factor. These results confirmed no school effect shown in the literacy results from the preschool period. Only one instance of age effect was shown with Factor 2
‘rhyme and syllables’ devised from phonological awareness results and one instance of a gender effect was shown with ‘awareness of conventions’ from the CAP test.
Similarly, one instance of an effect relating to the ‘mother SES’ factor occurred with
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 264 phonological awareness Factor 1 ‘rhyme, onset final phoneme’. It appears from these results as if there is little or no relationship between students’ literacy results in preschool with school, age, gender or the demography relating to mothers’ education and occupation. These results are slight or even ‘patchy’ compared to the kinds of positive associations found with parents’ perceptions and the negative associations found with teachers’ perceptions. This ‘patchiness’ can be seen also as specifying the particular relationships at work.
This following section reports Cluster Analyses based on Literacy Assessment tasks conducted in November of the preschool year. The following schema highlights the reporting of these results.
CHAPTER CONTENT DESCRIPTION Chapter 4: Describing and Correlating Preschool/Early Year 1 Data 4.1 Parent Survey 1 (November of Preschool) 4.2 Teacher Checklist 1 (March of Year 1) 4.3 Literacy Assessment 1 (November of Preschool). 4.4 Teacher Survey (March of Year 1). Chapter 5: Reducing dimensions: Relationships in the Preschool/Early Year 1 Data 5.1 Factor Analysis of Parent Survey 1;Teacher Checklist 1; Literacy Assessment 1. 5.2 Cluster Analysis based on Literacy Assessment 1 – Preschool period. Chapter 6: Describing and Correlating Year 1 (May) Data 6.1 Literacy Assessment 2 (May of Year 1) Chapter 7: Reducing dimensions: Relationships in the Year 1 (May) Data 7.1 Factor Analyses: Literacy Assessment 2 7.2 Cluster Analysis of Literacy Assessment 2 Chapter 8: Describing and Correlating Year 1 (November ) Data 8.1 Literacy Assessment 3 (November of Year 1) 8.2 Parent Survey 2 8.3 Teacher Checklist 2 Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 9.1 Factor Analysis: Parent Survey 2; Teacher Checklist 2; Literacy Assessment 3 9.2 Cluster Analysis of Literacy Assessment 3
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 265
5.2 CLUSTER ANALYSES
Cluster analyses, conducted on some preschool literacy factor scores, provided a means by which students with similar profiles could be grouped. This allows comparable multivariate profiles of performance to become visible, and their proportional presence in the sample can be ascertained. This method has theoretical significance in determining various pathways of early literacy development. Once students are placed in clusters, their subsequent literacy results in May/June and
November of Year 1 can be examined in the light of these cluster groups. First, it can be ascertained if the students remain consistently in the student clusters they are placed in according to the preschool literacy results, or if their results throughout
Year 1 suggest the initial clustering no longer applies. That is, the procedure offers a test of the proposition that the relevant capabilities have become reconfigured through a period of instruction and development.
Second, cluster analysis enables a closer examination of the cluster of preschool students who initially displayed varying levels of knowledge and understanding about literacy and to see if, after 12 months instruction in Year 1, they remain in the comparable groupings. By clustering students according to selected preschool literacy tasks this also allows the examination of the predictive nature of the literacy tasks used in the preschool period.
In order to investigate the predictive nature of the literacy tasks of the preschool period, Cluster Analyses were conducted. Factor scores (described earlier in Chapter Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 266
5) were used in the analyses. Following an explanation of the way each cluster grouping was devised and the characteristics of each cluster, results of chi-square analyses, multivariate and univariate analyses are reported.
Results of the Literacy Assessment Tasks from the preschool period were first examined closely to determine the levels of variance captured in each of the tests.
Factor scores devised from the Concepts About Print Test, Environmental Print
Awareness Tasks, Letter Knowledge and Identification and Sutherland Phonological
Awareness Tasks appear to capture a large amount of the variance from the preschool literacy tasks. These were used to develop three Variable Sets, A, B and
C. The three Variable Sets are as follows:
• Variable Set A (using CAP as the predictor set);
• Variable Set B (using Environmental Print and Letter Knowledge as the
predictor set);
• Variable Set C (using Sutherland Phonological Awareness as the predictor set).
The method adopted to cluster the students is based on Hall and Khanna (1977).
Factor scores devised from various preschool literacy tasks were submitted to
ISODATA routine to determine those student clusters that are most prevalent in the sample. The students are split into an increasing number of groups, and the increment in variance gained at each split is recorded. A scree test is then used to aid a decision about the optimal partitioning of the sample.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 267
5.2.1 VARIABLE SET A
Variable Set A utilises all six factors devised from the Concepts about Print Test administered in November of the preschool year. These factors are:
• Print awareness;
• Directionality;
• Awareness of conventions;
• Punctuation;
• Starting points;
• Left and right.
The ISODATA routine split students into seven groups accounting for 60.4% of the variance. Standardised cluster mean vectors for student groups within Variable Set A are shown in Table 96. Scores above and below the mean (> +.5 or -.5) are marked in italics and scores well above and well below the mean (> +1.00 or –1.00) are marked in bold.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 268
Table 96
Standardised Cluster Mean Vectors for Student Groups within Variable Set A
CAP Factors Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 Cluster 6 Cluster 7 N = 27 N = 3 N =15 N = 24 N = 20 N = 8 N = 17 Print -.72 -.32 -.35 1.71 -.36 -.05 -.43 awareness
Directionality .31 .65 - 2.13 .11 .64 -.03 .36
Awareness of .66 -.12 -.28 .00 -1.35 .88 .28 conventions
Punctuation -.35 4.64 -.15 -.08 -.12 .62 -.14
Starting -.27 1.17 .10 -.04 -.41 -1.22 1.24 points
Left and right .76 .66 -.11 .26 -.19 -2.04 -.42
An examination of the cluster mean vector scores enabled a description of each student cluster to be made. The convention used for describing each cluster includes:
• ‘around the mean’ for scores between -0.5 and +0.5;
• ‘above the mean’ for scores between 0.5 and 1.00;
• ‘well above the mean’ for scores above 1.00;
• ‘below the mean’ for scores between –0.5 and –1.00;
• ‘well below the mean’ for scores below –1.00.
A description of student clusters is as follows. Note that variables not mentioned are those for which the cluster mean was around the overall mean (i.e. within the mean range -.5 to +.5):
• Cluster 1 (27 students):
below the mean for print awareness;
above the mean for awareness of conventions and for left to right concept. Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 269
• Cluster 2 (3 students):
above the mean for directionality and left and right;
well above the mean for punctuation and starting points.
• Cluster 3 (15 students):
well below the mean for directionality.
• Cluster 4 (24 students):
well above the mean for print awareness.
• Cluster 5 (20 students):
well below the mean for awareness of conventions;
above the mean for directionality.
• Cluster 6 (8 students):
well below the mean for starting points and left and right progression;
above the mean for awareness of conventions and punctuation.
• Cluster 7 (17 students):
well above the mean for starting points.
Thus, an examination of the student clusters resulting from Variable Set A showed a range of performance patterns that had been determined by students’ results on the
Concept About Print test in November of the preschool year.
5.2.2 VARIABLE SET B
Variable Set B utilised three factors, two devised from environmental print and one from letter knowledge tasks. Details of the factors are:
• Contextual environmental print factor;
• Decontextualised environment print factor; Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 270
• Letter knowledge factor.
The ISODATA routine split students into six groups accounting for 77% of the variance. Standardised cluster mean vectors for student groups within Variable Set B are shown in Table 97. Scores above and below the mean marked in italics and scores well above and well below the mean are marked in bold.
Table 97
Standardised Cluster Mean Vectors for Student Groups within Variable Set B
Environmental Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 Cluster 6 print and letter N = 41 N = 37 N = 8 N = 9 N = 15 N = 4 knowledge factors Contextual .73 -.76 -.24 .65 .38 - 2.95 environmental print factor
Decontextual -.38 -.56 1.51 2.29 -.04 1.11 environmental print factor
Letter knowledge -.32 -.55 -.33 2.16 1.36 -.88 factor
A closer examination of the cluster mean vector scores enabled a description of each student cluster to be made. A description of the groups is as follows: Note that variables not mentioned are those for which the cluster mean was around the overall mean (i.e. within the mean range -.5 to +.5):
• Cluster 1 (41 students):
above the mean for environmental print and contextualised tasks.
• Cluster 2 (37 students):
below the mean for contextual tasks; decontextualised tasks and letter
knowledge.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 271
• Cluster 3 (8 students):
well above the mean for decontextualised tasks.
• Cluster 4 (9 students):
above the mean for contextual tasks;
well above the mean for decontextualised tasks and letter knowledge.
• Cluster 5 (15 students):
well above the mean for letter knowledge.
• Cluster 6 (4 students):
well below the mean for contextualised tasks;
below the mean for letter knowledge and understanding;
well above the mean for decontextualised tasks.
Once again a range of performance patterns was found in these student clusters devised from results obtained on environmental print tasks and letter knowledge tasks in November of the preschool year.
5.2.3 VARIABLE SET C
Variable Set C was calculated using two factors that underpin performances on the
Sutherland Phonological Awareness Subtests conducted in November of the preschool year. Factor 1 captured results from onset identification, final phoneme identification and rhyme production subtasks. Factor 2 captured results from syllable counting, rhyme detection and rhyme production. It should be noted that rhyme production loaded almost equally on both of these factors.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 272
The ISODATA routine split the students into five groups accounting for 80.9% of the variance. Standardised cluster mean vectors for student groups within Variable
Set C are shown in Table 98. Scores above and below the mean marked in italics and scores well above and well below the mean are marked in bold.
Table 98
Standardised Cluster Mean Vectors for Student Groups within Variable Set C
Sutherland Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 Phonological N = 20 N = 27 N = 41 N = 21 N = 5 Awareness factors Rhyme, onset, final 1.75 .34 -.85 -.34 -.37 phoneme
Rhyme & syllable -.08 .67 .45 -.97 -2.97
A closer examination of the cluster mean vector scores enabled a description of each student cluster to be made. Note that variables not mentioned are those for which the cluster mean was around the overall mean (i.e. within the range -.5 to +.5): A description of the groups follows:
• Cluster 1 (20 students):
well above the mean for onset identification, final phoneme identification
and rhyme production.
• Cluster 2 (27 students):
above the mean for syllable counting, rhyme detection and rhyme
production.
• Cluster 3 (41 students):
below the mean for onset identification, final phoneme identification and
rhyme production. Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 273
• Cluster 4 (21 students):
below the mean for syllable counting, rhyme detection and rhyme
production.
• Cluster 5 (4 students):
well below the mean for syllable counting, rhyme detection and rhyme
production.
Student clusters derived from Variable Cluster C showed a range of performance patterns devised from results of phonological awareness tasks in November of the preschool year.
5.2.4 RELATIONSHIPS AMONG VARIABLE SETS
Each Variable Set, A, B and C is examined first to ascertain relationships among the sets. Second, each is examined with background variables/factors of school, age, gender, demography, parents’ perceptions and teachers’ perceptions. Finally, each is examined with factors and scores derived from Literacy Assessment measures gathered in Preschool.
Some case selection was carried out where the number of students in particular student clusters was very small. Student Cluster 2 (3 students) from Variable Set A,
Student Cluster 6 (4 students) from Variable Set B and Student Cluster 5 (5 students) from Variable Set C were removed from these analyses. Pearson’s chi-square analysis was used to determine relationships among the three Variable Sets and also with background variables of school, age and gender. Multivariate analysis was used
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 274 to determine relationships of the Variable Sets with factors derived for SES, parents’ perceptions, teachers’ perceptions and preschool literacy achievement measures.
5.2.5 RELATIONSHIPS WITH VARIABLE SET A
Variable Set A (CAP) is examined first. Results showed no significant relationship with Variable Set B, school, age, or gender. But, a significant relationship was shown with Variable Set C. These results are in Table 99.
Table 99
Pearson’s Chi-square Analyses for Variable Set A and Background Variables
Variable Chi-square value p Variable Set B 21.44 .37 Variable Set C 37.13 <.01 School 7.27 .69 Age 10.15 .42 Gender 9.30 .09
These results showed that Variable Set A membership is not related to Variable Set
B membership. This provided a valuable way of examining the predictive nature of the students’ results in Preschool. Results also showed no significant relationship with school, age or gender thus showing students are distributed heterogeneously across Variable Sets A and B.
A significant relationship was shown between clusters from Variable Sets A and C
(shown in Table 100) indicating there was a relationship between the distribution of students in these sets. These results indicated an overlap of skills was present.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 275
Table 100
Chi-square for Cluster A (Derived from CAP 1) with Cluster C (Derived from Sutherland Phonological Awareness 1)
Cluster A Cluster C Total 1.00 2.00 3.00 4.00 Cluster A 1.00 Count 3 7 9 8 27 Expected Count 4.6 6.9 10.2 5.3 27.0 Std. Residual -.7 .0 -.4 1.1
3.00 Count 0 2 8 4 14 Expected Count 2.4 3.6 5.3 2.8 14.0 Std. Residual -1.5 -.8 1.2 .7
4.00 Count 11 9 4 0 24 Expected Count 4.1 6.1 9.1 4.8 24.0 Std. Residual 3.4 1.2 -1.7 -2.2
5.00 Count 0 3 11 3 17 Expected Count 2.9 4.3 6.4 3.4 17.0 Std. Residual -1.7 -.6 1.8 -.2
6.00 Count 1 1 3 2 7 Expected Count 1.2 1.8 2.6 1.4 7.0 Std. Residual -.2 -.6 .2 .5
7.00 Count 3 5 5 4 17 Expected Count 2.9 4.3 6.4 3.4 17.0 Std. Residual .1 .3 -.6 .3
Total Count 18 27 40 21 106 Expected Count 18.0 27.0 40.0 21.0 106.0
On closer examination of the chi-square it was found that the standardised residual for Cluster 4 (Variable Set A) with Cluster 1 (Variable Set C) is shown to be 3.4.
This occurred with a count of 11 students and this result is well above the expected count of four students, resulting in a significant departure from the expected result.
Descriptions of these two student clusters are as follows:
Cluster 4 (Variable Set A) – (24 students) well above the mean for print
awareness;
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 276
Cluster 1 (Variable Set C) – (20 students) well above the mean for onset
identification, final phoneme identification, and rhyme production.
A second chi-square result between Cluster 4 (Variable Set A) and Cluster 4
(Variable Set C) showed the standardised residual to be –2.2. This occurred with an expected count of 4.8, but an actual count of zero. Descriptions of these two student clusters are as follows:
Cluster 4 (Variable Set A) - (24 students) well above the mean for print
awareness;
Cluster 4 (variable Set C) – (21 students) below the mean for syllable counting,
rhyme detection and rhyme production.
A third chi-square result was trending towards significance. This occurred for
Cluster 5 (Variable Set A) with Cluster 3 (Variable Set C). A standardised residual of 1.8 occurred with a count of 11 students when there is an expected count of 6.4.
Descriptions for these two clusters are as follows:
Cluster 5 (Variable Set A) – (20 students) well below the mean for awareness of
conventions and above the mean for directionality;
Cluster 3 (Variable Set C) - (41 students) below the mean for onset
identification, final phoneme identification and rhyme production.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 277
Multivariate analysis of variance was carried out to examine relationships of
Variable Set A with background factors of SES, parents’ perceptions and teachers’ perceptions. All associations were non-significant, as presented in Table 101.
Table 101.
MANOVA From Variable Set A With Demography, Parents’ Perception and Teachers’ Perception Factors
Background Factors Wilk’s p Lambda SES – mother and father factors .90 .56
Parents’ perceptions of child characteristics – concentration, .89 .50 memory, interest in writing & interest in books; enjoyment of preschool & interest in books.
Parents’ perceptions – writing at home, interest in and frequency .82 .35 of writing at home.
Teachers’ perceptions – child conduct in class including .87 .25 application to tasks, personal organisation, following instructions and concentration; showing independence by separating from parents & settling into Year 1.
Teachers’ perceptions – reading progress and writing progress. .85 .11
These results showed that Variable Set A membership is independent of socio- economic status and parents’ perceptions of child characteristics and home literacy practices. Second, no relationship was found with teachers’ perceptions of child conduct in class, with reading or writing progress.
Further analyses of variance were carried out with Variable Set A to examine relationships with factors derived from the literacy tasks completed in November of the preschool year. Results showed one non-significant result for letter knowledge factor (p = .13) and eight significant effects. These significant effects are shown in
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 278
Table 102. It should be noted that in this table an asterisk (*) indicates factors where a significant effect occurred.
Table 102
Significant Results for Variable Set A With Preschool Literacy Task Measures
Factors/variables Wilk’s Lambda p & F-values Environmental print (contextualised*; decontextualised) WL = .72 < .01
Phonological awareness (onset identification, final WL = .63 < .01 phoneme identification, rhyme production*; syllable counting, rhyme rhyme detection, rhyme production)
Print Knowledge Task (reading words*; sequencing text*; WL = 2.36 < .01 where to start reading*)
Robinson word writing task score F = 3.04 < .01
Canberra word test score F = 2.64 .02
Reading words score in all literacy tasks F = 4.37 < .01
Literal comprehension score F = 2.70 .02
Inferential comprehension score F = 3.50 < .01
These results showed that Variable Set A membership relates significantly to eight of the nine preschool literacy task measures. These results validated the range of tests used in Preschool and showed that the six underlying CAP factors used to devise Variable Set A are present in the majority of other literacy tasks used in the preschool period.
Means and standard errors for each of the factors or scores where significance occurred with Variable Set A are now shown so that each of the seven student
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 279 clusters may be examined more closely. The first factor was the contextualised factor derived from environmental print scores. Results are shown in Table 103.
Table 103
Means and Standard Errors for Variable Set A on Contextualised Reading of Environmental Print Measures
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 2 is not in the analysis as the number of students (3) is too small) Student cluster and description N Mean St. Error 1. – print awareness; + awareness of conventions; + left- 27 .03 .14 right 3. – directionality 15 -.16 .19 4. ++ print awareness; 24 .77 .15 5. – awareness of conventions; + directionality; 20 .09 .18 6. – starting points; -- left-right; + awareness of 8 -.56 .27 conventions; + punctuation 7. ++ starting points 17 .15 .17
The table above indicates that Student Cluster 4 for Variable Set A solution, showed average performance on all CAP factors except for print awareness, on which they performed well above average. Student Cluster 4 performed best on the contextualised reading associated with environmental tasks. In contrast it can be seen that Student Cluster 6 showed results well below the mean for left and right concepts, below the mean for starting points, and above the mean for awareness of conventions and punctuation. It also was the lowest performing Student Cluster on contextualised reading.
Knowing membership of the clustering based on CAP does not permit significant prediction of decontextualised reading on these measures. Clearly, those students who have developed a stronger than average print awareness have also developed contextualised sight reading vocabulary that is above average for this group of
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 280 students. Similarly, those students with above average knowledge of print conventions and punctuation, but less developed knowledge concerning starting points and left to right reading, show below average performance on the contextualised reading vocabulary. Means and standard errors for the phonological awareness Factor 1 ‘rhyme, onset and final phoneme’, are now reported and shown in Table 104.
Table 104
Means and Standard Errors for Variable Set A on the Factor Score for Rhyme, Onset and Final Phoneme
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 2 is not in the analysis as the number of students (3) is too small) Cluster and description N Mean St. Error 1. – print awareness; + awareness of conventions; + left-right 27 -.10 .16 3. – directionality 15 -.51 .23 4. ++ print awareness; 24 1.00 .18 5. – awareness of conventions; + directionality; 20 -.68 .22 6. – starting points; -- left-right; + awareness of conventions; + 8 -.23 .32 punctuation 7. ++ starting points 17 .04 .20
These results showed once again that Student Cluster 4 achieved the highest mean score and that Cluster 5 with a mean score of -.68 scored lowest.
The third set of factors from literacy scores in Preschool that related significantly to
Variable Set A were all three factors derived from the Print Knowledge Task. The first factor related to reading words within the Humpty Dumpty rhyme task. The second related to sequencing tasks and the third factor associated with tasks where students indicated they knew where to start reading. The mean scores and standard errors for Variable Set A on each of these factors are shown in Table 105.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 281
Table 105
Means and Standard Errors for Variable Set A on Significant Print Knowledge Task Factors
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 2 is not in the analysis as the number of students (3) is too small) Print Knowledge Cluster and description N Mean St. Factor Error 1. Reading words 1. – print awareness; + awareness of 27 .13 .19 conventions; + left-right 3. – directionality 15 -.27 .26 4. ++ print awareness; 24 .41 .20 5. – awareness of conventions; + 20 -.44 .25 directionality; 6. – starting points; -- left-right; + 8 .05 .37 awareness of conventions; + punctuation 7. ++ starting points 17 .06 .23
2. Sequencing 1. – print awareness; + awareness of 27 -.31 .18 text conventions; + left-right 3. – directionality 15 -.40 .25 4. ++ print awareness; 24 .56 .20 5. – awareness of conventions; + 20 .04 .24 directionality; 6. – starting points; -- left-right; + 8 -.76 .35 awareness of conventions; + punctuation 7. ++ starting points 17 .21 .23
3. Start reading 1. – print awareness; + awareness of 27 -.24 .18 conventions; + left-right 3. – directionality 15 .39 .25 4. ++ print awareness; 24 .32 .20 5. – awareness of conventions; + 20 -.30 .25 directionality; 6. – starting points; -- left-right; + 8 .12 .36 awareness of conventions; + punctuation 7. ++ starting points 17 .12 .23
On Factor 1, ‘read words’, Student Cluster 4 showed the best results with a mean score of .41 with Student Cluster 5 achieved the lowest mean score of -.44. For the
Second Factor, ‘sequencing text’, Student Cluster 4 again scored best with a mean score of .56 and Student Cluster 6 scored the lowest with a mean score of -.76. For
Factor 3, ‘start reading’, Student Cluster 3 scored marginally better than Student
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 282
Cluster 4 with a mean score of .39 and Student Cluster 5 scored the lowest with a mean score of -.30.
Further significant effects on preschool literacy tests occurred for Robinson’s Test of
Writing Vocabulary, Canberra Word Test and a combined total score for reading words across all the literacy tasks. A comparison of mean scores for these tasks is shown in Table 106.
Table 106
Means and Standard Errors for Variable Set A on Robinson’s Test of Writing Vocabulary, Canberra Word Test and Reading Words on All Literacy Tasks
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 2 is not in the analysis as the number of students (3) is too small) Score Cluster and description N Mean St. Error Robinson’s 1. – print awareness; + awareness of conventions; + left- 27 .89 .24 Test of right Writing Vocabulary 3. – directionality 15 .64 .34 4. ++ print awareness; 24 3.52 1.18 5. – awareness of conventions; + directionality; 20 1.33 .50 6. – starting points; -- left-right; + awareness of 8 .00 .00 conventions; + punctuation 7. ++ starting points 17 1.00 .31
Canberra 1. – print awareness; + awareness of conventions; + left- 27 .85 .25 Word Test right 3. – directionality 15 .21 .15 4. ++ print awareness; 24 3.13 .99 5. – awareness of conventions; + directionality; 20 1.13 .86 6. – starting points; -- left-right; + awareness of 8 .71 .42 conventions; + punctuation 7. ++ starting points 17 1.05 .41
Total words 1. – print awareness; + awareness of conventions; + left- 27 4.89 1.37 read right 3. – directionality 15 3.00 1.90 4. ++ print awareness; 24 12.48 1.49 5. – awareness of conventions; + directionality; 20 6.06 1.84 6. – starting points; -- left-right; + awareness of 8 3.85 2.70 conventions; + punctuation 7. ++ starting points 17 6.76 1.72
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 283
Results showed that Student Cluster 4 achieved the best result for all three scores.
Students in Cluster 4 produced a mean score of 3.52 for correctly spelt words that were written in the preschool period while Student Cluster 6 produced the lowest mean score of 0.
For recognising common words from children’s early reading books in the Canberra
Word Recognition test, Student Cluster 4 scored the best with a mean score of 3.13 while Student Cluster 3 scored the lowest with a mean score of 0.21. From all of the tasks completed in the preschool period a total score was calculated where the students were required to read words. Once again Student Cluster 4 students were the most successful group with a mean score of 12.48 and Student Cluster 3 were the least successful with a mean score of 4.00.
Further significant effects with Variable Set A occurred for literal comprehension score compiled from the literal comprehension questions associated with two stories that were read aloud to the students in Preschool. A similar significant effect occurred for the inferential comprehension score compiled from the inferential comprehension questions of the same two stories. Mean score and standard error comparisons for comprehension are in Table 107.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 284
Table 107
Means and Standard Errors for Variable Set A on Literal and Inferential Comprehension Measures
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 2 is not in the analysis as the number of students (3) is too small) Score Cluster and description N Mean St. Error Literal 1. – print awareness; + awareness of 27 5.74 .28 comprehension conventions; + left-right 3. – directionality 15 6.00 .39 4. ++ print awareness; 24 6.95 .31 5. – awareness of conventions; + directionality; 20 6.60 .38 6. – starting points; -- left-right; + awareness of 8 5.28 .56 conventions; + punctuation 7. ++ starting points 17 5.88 .36
Inferential 1. – print awareness; + awareness of 27 5.26 .27 comprehension conventions; + left-right 3. – directionality 15 5.36 .37 4. ++ print awareness; 24 6.56 .29 5. – awareness of conventions; + directionality; 20 6.20 .36 6. – starting points; -- left-right; + awareness of 8 4.86 .52 conventions; + punctuation 7. ++ starting points 17 6.00 .33
For both literal and inferential comprehension scores Student Cluster 4 showed the
highest mean scores of 6.95 and 6.56 respectively. Student Cluster 6 showed the
lowest mean score for literal and inferential comprehension with mean scores of
5.28 and 4.86. It should be noted that the differences in mean scores for both literal and inferential comprehension scores are not large with the range of mean scores for literal comprehension being 5.28 to 6.95 and the range of mean scores for inferential comprehension being 4.86 to 6.56. It is seen once again that Student Cluster 4 performed best on comprehension measures and Student Cluster 6 was the lowest performing cluster.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 285
5.2.6 DISCUSSION OF VARIABLE SET A ASSOCIATIONS
It has been shown that Variable Set A related significantly to Variable Set C and to several factors derived from the literacy task measures completed in preschool.
Clusters of students who achieved the highest and lowest overall mean scores for these factors and scores have been highlighted and these are now presented together in Table 108. This table provides an overview of all significant results for Variable
Set A that was derived from students’ performance on Concepts About Print Test in the preschool period.
Table 108
Variable Set A (based on CAP) with Significant Preschool Literacy Factors and Scores Depicting the Highest and Lowest Cluster Mean Scores
Preschool Literacy Factors Highest mean Lowest mean result result Environmental print (contextual) Cluster 4 (.77) Cluster 6 (-.56) Phonological awareness (rhyme, onset, final Cluster 4 (1.00) Cluster 5 (-.68) phoneme) Print Knowledge Task (read words) Cluster 4 (.41) Cluster 5 (-.44) Print Knowledge Task (sequencing text) Cluster 4 (.56) Cluster 6 (-.76) Print Knowledge Task (start reading) Cluster 3 (.39) Cluster 5 (-.30) Robinson test of writing vocabulary Cluster 4 (3.52) Cluster 6 (.00) Canberra word recognition test Cluster 4 (3.13) Cluster 3 (.21) Reading words in all tests Cluster 4 (12.48) Cluster 3 (3.00) Literal comprehension Cluster 4 (6.95) Cluster 6 (5.28) Inferential comprehension Cluster 4 (6.65) Cluster 6 ( 4.85)
Student Cluster 4 achieved the highest mean score for nine out of ten factors and scores with Student Cluster 3 performing marginally better for the third factor of
Print Knowledge Task (where to start reading). Thus, Student Cluster 4 was consistently the highest achieving cluster group. Without these complex analyses
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 286 consisting of factor analyses then cluster analyses these relationships could not be shown. A number of researchers (Hill, Comber, Louden, Rivalland, & Reid, 1998;
Lonigan, Burgess & Anthony, 2000; Raban & Ure, 1999) have used the total score from the CAP test in the analyses, but this analysis alone fails to identify the underlying factor structure of the test. Without cluster analysis it is not possible to group together those students with similar skills. To exemplify this point, the total score achieved by the students in Cluster 4 of Variable Set A was examined. It was found that scores ranged from 13 to 22 with a mean score of 17. It seems unlikely that this group of students would be examined together if the total score achieved on the CAP test was used when analysing students’ results.
Three student clusters were shown to be achieving the lowest mean scores. These were Student Clusters 3, 5 and 6. Student Cluster 6 achieved the lowest mean score on five of the ten reported means, with Student Cluster 5 achieving the lowest scores for three of the ten reported means. Student Cluster 3 achieved the lowest mean scores for two of the ten mean scores. These results indicated Student Cluster 6 achieved the lowest mean scores 60% of the time and is therefore performing the lowest on literacy tasks in the preschool period. If the total score for the CAP test of these students is examined, it is found that scores range from 3 to 13 with a mean score of 7.5. Once again using factor analysis and cluster analysis demonstrated a new and different way of examining the underlying factor structure of the CAP test and the relationships that exist for students with similar literacy skills.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 287
5.2.7 RELATIONSHIPS WITH VARIABLE SET B
Variable Set B (environmental print and letter knowledge) is now examined.
Pearson’s chi-square showed a significant effect occurred with Variable Set C
(phonological awareness). All other chi-square analyses showed a non-significant effect. Results are shown in Table 109.
Table 109
Pearson’s Chi-square Analyses for Variable Set B and Background Variables.
Variable Chi-square value p Variable Set A 21.44 .37 Variable Set C 28.11 <.01 School 9.67 .28 Age 11.35 .18 Gender 0.57 .96
These results indicate that Variable Sets B and C are not independent and that some associations in membership occurred. Variable Set B showed no significant school, age or gender effect and once again as with Variable Set A, heterogeneous clusters were shown. A closer examination of the chi-square results is shown in Table 110.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 288
Table 110
Pearson’s Chi-square For Cluster B (Derived From Environmental Print and Letter Knowledge) With Cluster C (Derived from Sutherland Phonological Awareness 1)
Cluster B Cluster C Total 1.00 2.00 3.00 4.00 Cluster B 1.00 Count 9 11 14 6 40 Expected Count 7.5 10.2 14.7 7.5 40.0 Std. Residual .5 .3 -.2 -.6
2.00 Count 1 9 14 10 34 Expected Count 6.4 8.7 12.5 6.4 34.0 Std. Residual -2.1 .1 .4 1.4
3.00 Count 0 0 5 3 8 Expected Count 1.5 2.0 2.9 1.5 8.0 Std. Residual -1.2 -1.4 1.2 1.2
4.00 Count 4 3 1 1 9 Expected Count 1.7 2.3 3.3 1.7 9.0 Std. Residual 1.8 .5 -1.3 -.5
5.00 Count 6 4 5 0 15 Expected Count 2.8 3.8 5.5 2.8 15.0 Std. Residual 1.9 .1 -.2 -1.7
Total Count 20 27 39 20 106 Expected Count 20.0 27.0 39.0 20.0 106.0
These results showed that the standardised residual for Cluster 2 (Variable Set B) and Cluster 1 (Variable Set C) is – 2.1 and this result was a significant departure from the expected result. This occurs with a count of one student where there is an expected count of 6.4 students. Descriptions of these two clusters are as follows:
Cluster 2 (Variable Set B) – (37 students) below the mean for contextual tasks,
decontextualised tasks and letter knowledge.
Cluster 1 (Variable Set C) – (20 students) well above the mean for onset
identification, final phoneme identification and rhyme production.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 289
Cluster 5 (Variable Set B) and Cluster 1 (Variable Set C) were trending with a standardised residual of 1.9 where a count of 6 students is shown when the expected result is 2.8. This result again showed a significant departure from the expected result. Descriptions of these two student clusters are as follows:
Cluster 5 (Variable Set B) – (15 students) well above the mean for letter
knowledge;
Cluster 1 (Variable Set C) – (20 students) well above the mean for onset
identification, final phoneme identification and rhyme production.
A third result is also trending towards significance with Cluster 4 (Variable Set B) and Cluster 1 (Variable Set C) with a standardised residual of 1.8 where a count of 4 is shown with an expected result of 1.7. Descriptions of these two student clusters are as follows:
Cluster 4 (Variable Set B) - (9 students) above the mean for contextual tasks;
well above the mean for decontextualised tasks and letter knowledge;
Cluster 1 (Variable Set C) – (20 students) well above the mean for onset
identification, final phoneme identification and rhyme production.
Multivariate analysis of variance was carried out to examine relationships of
Variable Set B with other background factors of SES, parents’ perceptions and teachers’ perceptions. All results of parents’ perceptions with Variable Set B were non-significant and all results of teachers’ perceptions showed a significant effect.
These are shown in Table 111.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 290
Table 111
MANOVA of Variable Set B with Five Background Factors
Background Factors Wilk’s Lambda p Demography .92 .50 Parents’ perceptions child characteristics .85 .06 Parents’ perceptions home literacy practices .90 .63 Teachers’ perceptions class conduct and independence .82 <.01 Teachers’ perceptions reading and writing progress .67 <.01
Significant results with teachers’ perceptions indicated a positive relationship existed between Variable Set B results and the way teachers perceived students’ work habits, conduct in class and reading and writing progress. Socio-economic background and parents’ perceptions on the other hand do not appear to relate to cluster membership.
Further analyses of variance were carried out with Variable Set B to examine relationships with factors derived from the students’ literacy task measures in
Preschool. Results showed two non-significant results and six significant effects.
Both non-significant effects occurred for comprehension, (p = .08) for literal comprehension and (p = .17) for inferential comprehension. The significant effects for Variable Set B are shown in Table 112. It should be noted that an asterisk (*) indicates the factors where a significant effect occurred.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 291
Table 112
Significant Results for Variable Set B with Preschool Literacy Task Measures
Factors/Scores Wilk’s Lambda & p F-values Concepts About Print Test -print awareness*; WL = .51 < .01 awareness of conventions*; starting points*)
Phonological awareness – rhyme, onset & final WL = .74 < .01 phoneme*; rhyme & syllables
Print Knowledge Task - read words*, WL = .50 < .01 sequencing text*, starting points
Robinson’s Test of Writing Vocabulary F = 7.71 < .01
Canberra Word Test F = 27.60 < .01
Reading words in all literacy tasks F = 62.14 < .01
These results indicated cluster groups within Variable Set B are a good indication of skill development across a range of different types of tasks in the preschool period.
These cluster groups provided a valuable way of testing the predictive nature of the preschool literacy tasks. Means and standard error scores for the factors or scores where significance occurred with Variable Set B are now examined so the results of each of the six clusters may be examined more closely.
Teachers’ perceptions of class conduct and independence are examined first then teachers’ perceptions of reading and writing progress. This will be followed by a close examination of means and standard scores where significant effects were shown with preschool literacy tasks. Teachers’ perceptions are shown in Table 113.
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Table 113
Means and Standard Errors for Variable Set B on Teachers’ Perceptions – Class Conduct and Independence.
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 6 is not in the analysis as the number of students (4) is too small) Cluster and description – Class conduct N Mean St. Error 1. + contextualised environmental print tasks. 41 .03 .14 2. – contextualised environmental print tasks; 37 .29 .15 - decontextualised environmental print tasks; - letter knowledge 3. ++ decontextualised environmental print tasks. 8 -.40 .33 4. ++ decontextualised environmental print tasks; ++ letter 9 -.96 .31 knowledge; + contextualised environmental print tasks. 5. ++ letter knowledge. 15 -.28 .24
Cluster and description – Independence 1. + contextualised environmental print tasks. 41 .03 .15 2. – contextualised environmental print tasks; 37 .01 .16 - decontextualised environmental print tasks; - letter knowledge 3. ++ decontextualised environmental print tasks. 8 -.31 .34 4. ++ decontextualised environmental print tasks; ++ letter 9 -.49 .32 knowledge; + contextualised environmental print tasks. 5. ++ letter knowledge. 15 .39 .25
Results showed that Student Cluster 2 received the highest mean score from the teachers in relation to class conduct and Student Cluster 4 received the lowest mean score. This result shows a negative correlation occurred between students’ demonstrated skills in November of the preschool year with the teachers’ perceptions of their class conduct (ability to concentrate, application to tasks, personal organisation and ability to follow instructions).
When considering teachers’ perceptions of independence (ability to separate from parents and settle into Year 1) Cluster Group 5 received the highest mean score with
Cluster 4 receiving the lowest mean score. Further examination of these results
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 293 demonstrated once again that teachers have rated Cluster 4, (the most able cluster derived from Variable Set B), with the lowest mean score for independence.
Teachers’ perceptions of reading and writing progress also related significantly to
Variable Set B and means and standard errors are shown in Table 114.
Table 114
Means and Standard Errors for Variable Set B on Teachers’ Perceptions of Reading and Writing Progress.
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 6 is not in the analysis as the number of students (4) is too small) Factor Cluster and description N Mean St. Error 1. Teachers’ perceptions 1. + contextualised environmental print 41 .26 .14 - reading tasks. 2. - contextualised environmental print 37 .30 .16 tasks; - decontextualised environmental print tasks; - letter knowledge 3. ++ decontextualised environmental print 8 -.42 .31 tasks. 4. ++ decontextualised environmental print 9 -1.09 .30 tasks; ++ letter knowledge; + contextualised environmental print tasks. 5. ++ letter knowledge. 15 -.63 .23
2. Teachers’ perceptions 1. + contextualised environmental print 41 .03 .15 - writing tasks. 2. - contextualised environmental print 37 .15 .17 tasks; - decontextualised environmental print tasks; - letter knowledge 3. ++ decontextualised environmental print 8 .80 .34 tasks. 4. ++ decontextualised environmental print 9 -.80 .32 tasks; ++ letter knowledge; + contextualised environmental print tasks. 5. ++ letter knowledge. 15 -.40 .25
For reading progress, Student Cluster 2 received the highest mean rating from teachers with a score of .30. Student Cluster 4 received the lowest rating with a score
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 294 of –1.09. Again these results are curious and showed teachers ranking the lowest performing students most highly for reading progress and the highest performing students were rated the lowest.
For writing progress Student Cluster 3 achieved the highest mean score of .80 and
Student Cluster 4 the lowest with a mean score result of -.80. Once again the same pattern of results occurred. Cluster 4, the most able students in relation to writing ability in preschool, were rated lowest by their teachers for writing progress. These results are difficult to interpret, but it may be that the Year 1 teachers were not fully aware of students’ literacy skills after six weeks at school, or that they were identifying those students with less developed skills as having made the most noticeable improvement.
Mean scores and standard errors are now shown for Variable Set B with preschool literacy factors and scores where a significant effect was shown. The first comparison shows factor scores relating to Concepts About Print Test and these results are shown in Table 115.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 295
Table 115
Means and Standard Errors for Variable Set B on Significant Factors From Concepts About Print Test in Preschool
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 6 is not in the analysis as the number of students (4) is too small) Factor Cluster and description N Mean St. Error 1. Print awareness 1. + contextualised environmental print tasks. 41 .19 .16 2. – contextualised environmental print tasks; 37 -.36 .17 - decontextualised environmental print tasks; - letter knowledge 3. ++ decontextualised environmental print tasks. 8 -.29 .35 4. ++ decontextualised environmental print tasks; 9 .73 .33 ++ letter knowledge; + contextualised environmental print tasks. 5. ++ letter knowledge. 15 .26 .26
2.Awareness of 1. + contextualised environmental print tasks. 41 -.39 .15 conventions 2. – contextualised environmental print tasks; 37 .25 .16 - decontextualised environmental print tasks; - letter knowledge 3. ++ decontextualised environmental print tasks. 8 .20 .32 4. ++ decontextualised environmental print tasks; 9 .51 .31 ++ letter knowledge; + contextualised environmental print tasks. 5. ++ letter knowledge. 15 .61 .24
3. Starting points 1. + contextualised environmental print tasks. 41 -.23 .14 2. – contextualised environmental print tasks; 37 -.30 .16 - decontextualised environmental print tasks; - letter knowledge 3. ++ decontextualised environmental print tasks. 8 .37 .32 4. ++ decontextualised environmental print tasks; 9 .70 .30 ++ letter knowledge; + contextualised environmental print tasks. 5. ++ letter knowledge. 15 .71 .23
Results showed Student Cluster 4 achieved the highest mean score (.73) for print awareness and Student Cluster 5 the highest mean score for awareness of conventions. Clusters 4 and 5 achieved almost identical high mean scores for starting points. Thus a consistency of results is shown with Variable Set B, but an indication also of multiple pathways for students’ literacy learning in the early years.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 296
Student Cluster 2 achieved the lowest mean score for print awareness and starting points while Cluster 1 achieved the lowest mean score for awareness of conventions.
Again consistency of results was shown. A significant effect was shown with
Variable Set B and two factors derived from Phonological Awareness tasks in
Preschool. Means and standard errors for these two factors are presented in Table
116.
Table 116
Means and Standard Errors For Variable Set B With Significant Phonological Awareness Factors
Factor Cluster and description N Mean St. Error Rhyme, onset and 1. + contextualised environmental print tasks. 41 .10 .14 final phoneme 2. – contextualised environmental print tasks; 37 -.32 .15 - decontextualised environmental print tasks; - letter knowledge 3. ++ decontextualised environmental print tasks. 8 -.75 .32 4. ++ decontextualised environmental print tasks; 9 .96 .30 ++ letter knowledge; + contextualised environmental print tasks. 5. ++ letter knowledge. 15 .51 .23
Rhyme and 1. + contextualised environmental print tasks. 41 .09 .14 syllables 2. – contextualised environmental print tasks; 37 -.22 .15 - decontextualised environmental print tasks; - letter knowledge 3. ++ decontextualised environmental print tasks. 8 -.07 .32 4. ++ decontextualised environmental print tasks; 9 .42 .30 ++ letter knowledge; + contextualised environmental print tasks. 5. ++ letter knowledge. 15 .39 .23
Results showed Cluster 4 had the highest means score for both factors. The lowest mean scores occurred for Cluster 3 with rhyme, onset and final phoneme factor and with Cluster 2 for rhyme and syllables factor.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 297
The next significant effect with Variable Set B occurred with two factors derived from the Print Knowledge Task. The mean scores and standard error are reported in
Table 117.
Table 117
Mean Scores and Standard Errors for Variable Set B with Print Knowledge Task Factors
Factor Cluster and description N Mean St. Error Read words 1. + contextualised environmental print tasks. 41 -.32 .12 2. – contextualised environmental print tasks; 37 -.23 .14 - decontextualised environmental print tasks; - letter knowledge 3. ++ decontextualised environmental print tasks. 8 -.31 .28 4. ++ decontextualised environmental print tasks; 9 1.49 .26 ++ letter knowledge; + contextualised environmental print tasks. 5. ++ letter knowledge. 15 .88 .20
Sequencing text 1. + contextualised environmental print tasks. 41 .07 .15 2. – contextualised environmental print tasks; 37 -.53 .16 - decontextualised environmental print tasks; - letter knowledge 3. ++ decontextualised environmental print tasks. 8 .31 .33 4. ++ decontextualised environmental print tasks; 9 .37 .31 ++ letter knowledge; + contextualised environmental print tasks. 5. ++ letter knowledge. 15 .40 .24
The highest means scores with Variable Set B and Print Knowledge task occurred for Cluster 4 ‘read words’ and Cluster 5 ‘sequencing text’. Lowest mean scores occurred for Cluster 1 (read words) and Cluster 2 (sequencing text). Mean score results for Robinson’s Test of Writing Vocabulary, Canberra Word Test and a total score for reading words in all preschool literacy tasks will now be examined as these also showed a significant effect with Variable Set B. These results are shown in
Tables 118 – 120.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 298
Table 118
Mean Scores and Standard Errors for Variable Set B With Robinson’s Test of Writing Vocabulary
Factor Cluster and description N Mean St. Error Robinson’s Test of 1. + contextualised environmental print tasks. 41 .82 .20 Writing Vocabulary 2. – contextualised environmental print tasks; 37 .56 .16 - decontextualised environmental print tasks; - letter knowledge 3. ++ decontextualised environmental print tasks. 8 .75 .25 4. ++ decontextualised environmental print tasks; 9 5.88 2.83 ++ letter knowledge; + contextualised environmental print tasks. 5. ++ letter knowledge. 15 2.60 .58
Table 119
Mean Scores and Standard Errors for Variable Set B With Canberra Word Test
Factor Cluster and description N Mean St. Error Canberra Word 1. + contextualised environmental print tasks. 41 .46 .16 Test 2. – contextualised environmental print tasks; 37 .27 .08 - decontextualised environmental print tasks; - letter knowledge 3. ++ decontextualised environmental print tasks. 8 .75 .36 4. ++ decontextualised environmental print tasks; ++ 9 7.55 1.92 letter knowledge; + contextualised environmental print tasks. 5. ++ letter knowledge. 15 2.73 .70
Table 120
Mean Scores and Standard Errors for Variable Set B with Reading Words in all Literacy Task Measures
Factor Cluster and description N Mean St. Error Reading words in 1. + contextualised environmental print tasks. 41 4.17 .49 all literacy tasks 2. – contextualised environmental print tasks; 37 2.37 .30 - decontextualised environmental print tasks; - letter knowledge 3. ++ decontextualised environmental print tasks. 8 10.25 1.22 4. ++ decontextualised environmental print tasks; 9 25.66 3.33 ++ letter knowledge; + contextualised environmental print tasks. 5. ++ letter knowledge. 15 9.73 1.40
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 299
Results showed Cluster 4 had the highest mean score in all three literacy tasks in
Preschool and Cluster 2 achieved the lowest mean score in all three tasks. These results confirmed the relationship between reading and writing and showed those students who demonstrated skills in reading decontextualised environmental print words and had a high level of knowledge of the alphabet in Preschool could also write words and read words in a range of literacy tasks. By comparison, those students who found difficulty with environmental print tasks and demonstrated a lower level of knowledge of the alphabet also experienced difficulty writing words and reading words. A short discussion of all associations with Variable Set B is now presented.
5.2.8 DISCUSSION OF VARIABLE SET B ASSOCIATIONS
It has been shown that Variable Set B related significantly to Variable Set C and to teachers’ perceptions of student conduct in class, reading progress and writing progress. Teachers’ perceptions were however negatively correlated. As well,
Variable Set B related significantly to nine factors/scores from literacy tasks completed in the preschool period. Clusters of students who achieved the highest and lowest overall mean scores for literacy factors and scores have been highlighted in the previous section of this chapter and these are now presented together in Table
121.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 300
Table 121
Variable Set B (Based on Environmental Print and Letter Knowledge) with Significant Teachers’ Perceptions and Literacy Factors/Scores Depicting the Highest and Lowest Mean Scores
Factor Highest result / Lowest result / Mean score Mean score Teachers’ perceptions – class conduct Cluster 2 (.29) Cluster 4 (-.96) Teachers’ perceptions – independence Cluster 5 (.39) Cluster 4 (-.49) CAP - print awareness Cluster 4 (.73) Cluster 2 (-.36) CAP - awareness of conventions Cluster 5 (.61) Cluster 1 (-.40) CAP - starting points Cluster 5 (.71) Cluster 2 (-.30) Sutherland Phonological Awareness – rhyme, Cluster 4 (.96) Cluster 3 (-.75) onset, final phoneme Print Knowledge Task – read words Cluster 4 (1.49) Cluster 1 (-.32) Print Knowledge Task – sequencing text Cluster 5 ( .40) Cluster 2 (-.53) Robinson’s Test of Writing Vocabulary Cluster 4 (5.89) Cluster 2 ( .59) Canberra Word Test Cluster 4 (7.55) Cluster 2 ( .31) Reading words in all literacy tasks Cluster 4 (25.67) Cluster 2 (2.47)
As reported earlier in this chapter, teachers’ perceptions of Cluster 4 are curious in that students who achieved highly in the preschool period have been rated low by
Year 1 teachers. Also Cluster 2, students who achieved low results in Preschool have been rated highly by Year 1 teachers after six weeks of school. No clear explanation of these results is possible.
In contrast Student Cluster 4 achieved the highest mean score for six of the nine literacy results with Student Cluster 5 achieving the highest mean for three out of the nine results. Thus Student Cluster 4 achieved the highest performance overall. Three student clusters, namely Cluster 1, Cluster 2 and Cluster 3, achieved the lowest mean scores. Student Cluster 2 achieved the lowest mean score for six of the nine results and thus achieved the lowest overall result. Thus, for cluster analysis based on environmental print and letter knowledge there is consistency of results with Cluster
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 301
4 achieving the highest and Cluster 2 achieving the lowest on literacy tasks conducted in Preschool. This consistency of results indicates the viability of using
Cluster Analysis to examine students’ progress.
5.2.9 RELATIONSHIPS WITH VARIABLE SET C
Variable Set C (based on Sutherland Phonological Awareness factors) is now examined. Pearson’s chi-square showed that a significant effect occurred with gender, Variable Set A and Variable Set B (as described earlier). These results are shown in Table 122.
Table 122
Pearson’s Chi-square Analyses for Variable Set C and Background Variables
Variable Chi-square value p Variable Set A 37.13 <.01 Variable Set B 28.11 <.01 School 9.67 .28 Age 5.88 .43 Gender 8.33 .04
Upon close examination of the significant gender effect it is found that the standardised residuals for all four clusters do not show a significant departure from the expected result. Thus, while the overall chi-square result for Variable Set C and gender showed significance, the contributions to the total chi-square are distributed in small deviations rather than indicating a clear pattern of association.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 302
Multivariate analysis was carried out to examine relationships of Variable Set C with other background factors of SES, parents’ perceptions and teachers’ perceptions.
These results are shown in Table 123.
Table 123
MANOVA of Variable Set C With SES, Parents’ Perception and Teachers’ Perception Factors
Factors Wilk’s Lambda p Mother and Father SES factors .90 .15 Parents’ perceptions – child cognitive characteristics and .89 .11 enjoy preschool Parents’ perceptions – home writing .85 .11 Teachers’ perceptions – conduct and independence .90 .11 Teachers’ perceptions – reading and writing progress .74 <.01
Only one of the background factors, teachers’ perceptions of reading and writing progress, showed a significant relationship to Variable Set C. Upon closer examination of the two factors that contribute to teachers’ perceptions of reading and writing progress, it was shown that, for both reading and writing progress p = <.01.
Further analyses of variance was carried out with Variable Set C to examine relationships with factors and scores from literacy results in the preschool period.
Results showed significant results occurred for eight of the nine results. These results indicated that clustering students on phonological awareness results provided a means for prediction on almost all literacy task measures from the preschool period. These results are shown in Table 124. It should be noted that an asterisk (*) indicates the factors where a significant effect occurred.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 303
Table 124
Significant Results for Variable Set C With Literacy Tasks Completed in Preschool
Factors/Scores Wilk’s p Lambda F – value Environmental print (contextual*; decontextual) WL = .84 .01
Letter knowledge & understanding F = 10.54 < .01
Concepts About Print Test (print awareness*; directionality; WL = .52 < .01 awareness of conventions; punctuation; starting points; left & right understanding)
Print Knowledge Task (read words*, sequencing text*, start WL = .66 < .01 reading)
Robinson Test of Writing Vocabulary F = 3.13 .03
Canberra Word Test F = 6.50 < .01
Reading words in all literacy tests F = 7.06 < .01
Literal comprehension F = 3.87 .01
These results showed that clustering students according to phonological awareness results in Preschool, affords considerable predictive purchase on reading words, exhibiting print awareness, writing words and comprehending at the literal level.
Teachers’ perceptions of reading and writing progress are examined first. Then means and standard errors for each of the preschool literacy factors and scores where significance occurred as this allows a closer examination of the four clusters.
Teachers’ perceptions of reading progress and writing progress are shown in Table
125.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 304
Table 125
Means and Standard Errors For Variable Set C With Teachers’ Perceptions – Reading Progress and Writing Progress
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 5 is not in the analysis as the number of students (4) is too small) Student cluster and description N Mean St. Error Reading progress 20 1. ++ onset identification,; ++ final phoneme identification; ++ rhyme -.43 .22 production 2. + syllable counting,; + rhyme detection; + rhyme production 27 -.37 .18 3. – onset identification; - final phoneme identification; - rhyme production 41 .37 .15 4. – syllable counting; - rhyme detection; - rhyme production 21 .03 .21
Writing Progress 1. ++ onset identification,; ++ final phoneme identification; ++ rhyme 20 -.62 .22 production 2. + syllable counting,; + rhyme detection; + rhyme production 27 -.21 .18 3. – onset identification; - final phoneme identification; - rhyme production 41 .17 .15 4. – syllable counting; - rhyme detection; - rhyme production 21 .48 .21
Results showed that Student Cluster 3 received the highest mean score from teachers for reading progress and Student Cluster 4 received the highest mean score for writing progress. Teachers rated Student Cluster 1 lowest for both reading and writing progress.
Means and standard errors for significant results achieved with literacy tasks in
Preschool are now examined in relation to Variable Set C. The first result is with the factor for contextualised reading of environmental print measures and these results are shown in Table 126.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 305
Table 126
Means and Standard Errors For Variable Set C on Contextualised Reading of Environmental Print Measures
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 5 is not in the analysis as the number of students (4) is too small) Student cluster and description N Mean St. Error 1. ++ onset identification,; ++ final phoneme identification; ++ rhyme 20 .55 .17 production 2. + syllable counting,; + rhyme detection; + rhyme production 27 .37 .14 3. – onset identification; - final phoneme identification; - rhyme 41 .07 .12 production 4. – syllable counting; - rhyme detection; - rhyme production 21 -.32 .16
The above table indicates that Cluster 1 for Variable Set C solution showed the highest mean score and performed best on environmental print factor for contextualised reading tasks. These tasks included identification of a food product or a label from a product. For these tasks, colours and shapes found on the product were still visible and the original font size, colour and style of print remained.
Students may have used these to assist with the identification of the product and its name. Students in Cluster 4 achieved the lowest mean score for this measure. It is worth noting that knowing student clusters based on phonological awareness does not offer significant prediction of decontextualised reading on these measures.
The second significant result was shown for letter knowledge. Means and standard errors are shown in Table 127.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 306
Table 127
Means and Standard Errors For Variable Set C on Letter Knowledge Measures
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 5 is not in the analysis as the number of students (4) is too small) Student cluster and description N Mean St. Error 1. ++ onset identification,; ++ final phoneme identification; ++ rhyme 20 1.02 .21 production 2. + syllable counting,; + rhyme detection; + rhyme production 27 .20 .17 3. – onset identification; - final phoneme identification; - rhyme 41 -.26 .14 production 4. – syllable counting; - rhyme detection; - rhyme production 21 -.39 .20
Cluster 1 again showed the highest mean score well above that achieved by any of the remaining three Student Clusters. Cluster 4 achieved the lowest mean score.
The third factor from literacy measures in Preschool that related significantly to
Variable Set C is print awareness, a factor devised from Concepts About Print test.
Mean scores and standard errors for this factor with Variable Set C are shown in
Table 128.
Table 128
Means and Standard Errors For Variable Set C on Print Awareness from CAP
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 5 is not in the analysis as the number of students (4) is too small) Student cluster and description N Mean St. Error 1. ++ onset identification,; ++ final phoneme identification; ++ rhyme 20 1.07 .20 production 2. + syllable counting,; + rhyme detection; + rhyme production 27 2.84 .16 3. – onset identification; - final phoneme identification; - rhyme 41 -.30 .14 production 4. – syllable counting; - rhyme detection; - rhyme production 21 -.56 .19
The result followed the previous pattern with Student Cluster 1 showing the highest mean score and Student Cluster 4 achieving the lowest mean score. The fourth significant result related to two factors from the Print Knowledge Task using the
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 307 rhyme Humpty Dumpty. These factors have been labelled ‘read words’ and
‘sequencing text’. These results are shown in Table 129.
Table 129
Means and Standard Errors for Variable Set C on Print Knowledge Task For ‘Read Words’ Factor and ‘Sequencing Text’ Factor
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.) (Note that Student Cluster 5 is not in the analysis as the number of students (4) is too small) Student cluster and description N Mean St. Error Read words 1. ++ onset identification,; ++ final phoneme identification; ++ rhyme 20 .93 .20 production 2. + syllable counting,; + rhyme detection; + rhyme production 27 .25 .16 3. – onset identification; - final phoneme identification; - rhyme 41 -.31 .14 production 4. – syllable counting; - rhyme detection; - rhyme production 21 -.38 .19
Sequencing text 1. ++ onset identification,; ++ final phoneme identification; ++ rhyme 20 .29 .22 production 2. + syllable counting,; + rhyme detection; + rhyme production 27 .29 .18 3. – onset identification; - final phoneme identification; - rhyme 41 -.20 .15 production 4. – syllable counting; - rhyme detection; - rhyme production 21 -.37 .21
The results followed the same pattern seen in previous results with Student Cluster 1 achieving the highest mean score for reading words and sequencing text. It should be noted that Student Cluster 2 achieved equally as well for sequencing text. Consistent with previous results, Student Cluster 4 achieved the lowest mean score for each of the two factors.
Students were asked to write any words apart from their name in the preschool period and results for the mean scores for each of the student clusters in Variable Set
C are shown in Table 130.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 308
Table 130
Means and Standard Errors For Variable Set C on Robinson’s Test of Writing Vocabulary
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 5 is not in the analysis as the number of students (4) is too small) Student cluster and description N Mean St. Error 1. ++ onset identification,; ++ final phoneme identification; ++ rhyme 20 2.61 .55 production 2. + syllable counting,; + rhyme detection; + rhyme production 27 2.48 1.02 3. – onset identification; - final phoneme identification; - rhyme 41 .63 .15 production 4. – syllable counting; - rhyme detection; - rhyme production 21 .65 .30
Again there is consistency with Student Cluster 1 achieving the highest mean score and Student Cluster 4 achieving the lowest. Finally mean score results for the
Canberra Word Test, reading words in all literacy tests and literal comprehension in the preschool period are shown in Table 131.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 309
Table 131
Means and Standard Errors for Variable Set C on Canberra Word Test, Reading Words in All Literacy Tests and Literal Comprehension
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 5 is not in the analysis as the number of students (4) is too small) Student cluster and description N Mean St. Error Canberra Word Test
1. ++ onset identification,; ++ final phoneme identification; ++ rhyme 20 3.22 .93 production 2. + syllable counting,; + rhyme detection; + rhyme production 27 2.07 .78 3. – onset identification; - final phoneme identification; - rhyme 41 .34 .12 production 4. – syllable counting; - rhyme detection; - rhyme production 21 .55 .15
Reading words in all literacy tasks at preschool
1. ++ onset identification,; ++ final phoneme identification; ++ rhyme 20 12.50 11.67 production 2. + syllable counting,; + rhyme detection; + rhyme production 27 8.29 1.36 3. – onset identification; - final phoneme identification; - rhyme 41 4.07 1.15 production 4. – syllable counting; - rhyme detection; - rhyme production 21 4.50 1.59
Literal comprehension
1. ++ onset identification,; ++ final phoneme identification; ++ rhyme 20 7.05 .35 production 2. + syllable counting,; + rhyme detection; + rhyme production 27 5.96 .28 3. – onset identification; - final phoneme identification; - rhyme 41 6.15 .24 production 4. – syllable counting; - rhyme detection; - rhyme production 21 5.65 .33
Again Student Cluster 1 achieved the highest mean score for each of these results. It also is seen that Student Cluster 4 achieved the lowest for literal comprehension while Student Cluster 3 achieved the lowest mean score for reading words on all literacy tasks in Preschool and for Canberra Word Test.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 310
5.2.10 DISCUSSION OF VARIABLE SET C ASSOCIATIONS
It can be seen that Variable Set C related significantly to Variable Set A and
Variable Set B (described earlier) and to teachers’ perceptions of reading and writing progress as well as several factors devised from literacy task measures completed in the preschool period. Student Clusters achieving the highest and lowest mean scores have been highlighted in the previous section of this chapter and are now presented together in Table 132.
Table 132
Variable Set C (Based on Phonological Awareness) with Significant Preschool Literacy Factors and Scores Depicting the Highest and Lowest Mean Scores
Factor Highest mean result Lowest mean result
Teachers’ perceptions – reading progress Cluster 3 (.37) Cluster 1 ( -.43) Teachers’ perceptions – writing progress Cluster 4 (.48) Cluster 1 (-.62) Environmental print (contextual) Cluster 1 (.55) Cluster 4 (-.32) Letter knowledge and understanding Cluster 1 (1.02) Cluster 4 (-.39) Concepts About Print (print awareness) Cluster 1 (1.07) Cluster 4 (-.56) Print Knowledge Task (read words) Cluster 1 (.93) Cluster 4 (-.38) Print Knowledge Task (sequencing text) Cluster 1 = Cluster 2 Cluster 4 (-.37) (.29) Robinson Test of Writing Vocabulary Cluster 1 ( 2.61) Cluster 4 (.65) Canberra Word Test Cluster 1 (3.22) Cluster 3 (.34) Reading words in all literacy tests Cluster 1 (12.50) Cluster 3 (4.07) Literal comprehension Cluster 1 (7.05) Cluster 4 (5.65)
Student Cluster 1 achieved the highest mean score for all nine significant literacy preschool results. Student Cluster 4 achieved the lowest for seven of the nine results with Student Cluster 3 achieving the lowest for two results. These results showed the potential predictive nature of using Variable Set C based on preschool phonological awareness results as it appeared to show a high consistency in predicting those students who achieved high mean scores and those who achieved low mean scores.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 311
In contrast to these results, Year 1 teachers’ predictions showed a negative correlation with a range of literacy results achieved by the students in Preschool.
Student Cluster 1 displayed a consistent high achievement across a range of literacy skills and yet, Year 1 teachers saw these students as being those making the least progress in reading and writing. These results also align with Variable Set B where teachers also chose those students who performed least well as having the greatest skills.
5.2.11 SUMMARY: CLUSTER ANALYSES OF LITERACY ASSESSMENT
TASK MEASURES IN PRESCHOOL
In addressing the thesis question, ‘How do aspects of students’ literacy knowledge and understanding prior to school relate to one another and students’ background,’
Cluster Analyses reported in this chapter are now considered. Variable Set A
(devised from CAP factors from Preschool), Variable Set B (devised from
Environmental Print and Letter Knowledge factors in measured Preschool) and
Variable Set C (devised from Sutherland Phonological Awareness factors measured in Preschool) are all examined in relation to Cluster Analyses results. All Literacy
Assessment Tasks from Preschool with Cluster Analyses results are presented in
Table 133. It should be noted that some parts of the table are shaded where results are not able to be calculated because that particular test was the selected result used in the formation of the Variable Set. An example of this is - Variable Set A was devised from CAP results in Preschool and so further analyses to ascertain significant relationships were not carried out with CAP results in Preschool.
Similarly, Variable Set B was devised using results from Environmental Print and
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 312
Letter Knowledge, so analyses of these results with Variable Set B were not carried out.
Table 133
Summary of Multivariate Analyses of Variable sets A, B and C with Literacy Measures in Preschool
Literacy Assessment Tasks – Preschool Variable Set A Variable Set B Variable Set C Environmental Print WL = .72 WL = .84
p = <.01 p = .01 contextual = <.01 contextual = .01 Letter Knowledge p = .13 p = <.01
CAP – 6 factors WL = .51 WL = 52
p = <.01 p = <.01 print awareness = .02 print awareness = awareness of <.01 conventions = <.01 starting points = <.01 Phonological Awareness – 2 factors WL = .63 WL = .74
p = <.01 p = <.01 rhyme production, onset rhyme production, onset identification, final identification, final phoneme identification = phoneme identification = <.01 <.01 Print Knowledge Task – 3 factors WL = 2.36 WL = .50 WL = .66
p = <.01 p = <.01 p = <.01 sequencing text = <.01 reading words = <.01 reading words = sequencing text = <.01 <.01 sequencing text = .03 Robinson Test of Writing Vocabulary p = .01 p = <.01 p = .02 Canberra Word Test p = .02 p = <.01 p = <.01
Reading words in all p = <.01 p = <.01 p = <01 tasks Literal Comprehension p =.02 p = .08 p = .03 Inferential p= <.01 p = .17 p = .10 Comprehension Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 313
From Table 133 it can be seen that all results may be predicted from one or more of the Variable Sets. Some results are predicted by all Variable Sets and these include
Environmental Print, Phonological Awareness, Print Knowledge Tasks, Robinson’s
Test of Writing Vocabulary, Canberra Word Test and Reading Words. Overall, it can be seen that each Variable Set A, B and C relates to the others and that each has the potential for predicting student literacy progress. When each variable set is examined in turn it can be seen that none shows greater potential for predicting literacy development and that each is similar. From Table 133 it can be seen that
Variable Set A predicts 8 results, Variable Set B predicts 9 results and Variable Set
C predicts 8 results.
Results from Cluster Analyses appear to have the potential to predict students’ later results. Literacy Assessment measures and the predictive capabilities of each of the variable sets will be tested further with students’ results in May/June and November of Year 1. It is clear that the preschool battery of assessment tasks, all elements of which are related to literacy, in fact comprises a complex set of capabilities, with comparably complex inter-relations. This set is also related in complex ways to background variables measured in this study. This complexity suggests a multiplicity of pathways by which young students become literate, and gives further weight to the notion of school literacy as a multi-faceted set of skills with multiple etiologies.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 314
Chapter Six is a report of results from the second round of Literacy Assessment Task measures conducted with students in May/June of Year 1. Descriptive statistics and correlations are reported in order to examine frequency of results and significant correlations due to school, age and gender.
Chapter 5: Reducing Dimensions: Relationships in the Preschool Data 315
Predicting the Patterns of Early Literacy Achievement: A Longitudinal Study of Transition from Home to School
VOLUME 2
Janelle Patricia Young DipTch; BEd; MEdSt
A thesis submitted in fulfillment of the requirements for the degree of Doctor of Philosophy at Faculty of Education, School of Cognition, Language and Special Education, Griffith University, Brisbane. July 2003 CHAPTER SIX
DESCRIBING AND CORRELATING YEAR 1 (MAY/JUNE) DATA
Data collected from students during the May/June period of Year 1 are reported in this chapter. Results of multivariate and univariate effects due to school, age and gender and descriptive results of the literacy assessment tasks are reported. Data gathered from the students following four months in Year 1 address the fourth contributing research question, ‘How do child, home and school factors relate to literacy development in the first year of school?’
The shaded row of the schema indicates the current section.
CHAPTER CONTENT DESCRIPTION Chapter 4: Describing and Correlating Preschool/Early Year 1 Data 4.1 Parent Survey 1 (November of Preschool) 4.2 Teacher Checklist 1 (March of Year 1) 4.3 Literacy Assessment 1 (November of Preschool). 4.4 Teacher Survey (March of Year 1). Chapter 5: Reducing dimensions: Relationships in the Preschool/Early Year 1 Data 5.1 Factor Analysis of Parent Survey 1;Teacher Checklist 1; Literacy Assessment 1. 5.2 Cluster Analysis based on Literacy Assessment 1 – Preschool period. Chapter 6: Describing and Correlating Year 1 (May) Data 6.1 Literacy Assessment 2 (May of Year 1) Chapter 7: Reducing dimensions: Relationships in the Year 1 (May) Data 7.1 Factor Analyses: Literacy Assessment 2 7.2 Cluster Analysis of Literacy Assessment 2 Chapter 8: Describing and Correlating Year 1 (November ) Data 8.1 Literacy Assessment 3 (November of Year 1) 8.2 Parent Survey 2 8.3 Teacher Checklist 2 Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 9.1 Factor Analysis: Parent Survey 2; Teacher Checklist 2; Literacy Assessment 3 9.2 Cluster Analysis of Literacy Assessment 3
Chapter 6: Describing and Correlating Year 1 (May/June) Data 316 6.1 LITERACY ASSESSMENT TASKS: YEAR 1 (MAY)
6.1.1 INTRODUCTION
Eight literacy assessment tasks were completed by the students in a one-to-one interaction with an adult in May/June of Year 1 (see Appendix L). The eight tasks were most commonly completed in one session and took approximately 45 minutes for each student. Many of the tasks completed in November of the preschool year were used again to ascertain growth in literacy development in the first few months of Year 1. It should be noted that one student from Preschool C did not commence
Year 1 at that school as had been expected, so data for 113 students is reported for
Year 1. Students completed the following tasks:
• Writing own name (retest);
• Robinson’s Test of Writing Vocabulary (Clay, 1985) (retest);
• Letter Knowledge and Identification -lower case only (Clay,1985) (retest);
• Concepts About Print Test (Clay, 1979) (retest);
• Canberra Word Test (Clough, McIntyre & Cowey, 1990) (retest);
• Story Comprehension using the text My Brother John;
• Print Knowledge Task using the nursery rhyme Humpty Dumpty (retest);
• Sutherland Phonological Awareness Test (Subtests 1 to 5) (Neilson, 1999)
(retest).
Chapter 6: Describing and Correlating Year 1 (May/June) Data 317 6.1.2 WRITING OWN NAME
Students were given blank pieces of paper and asked to write their name. If they wrote only their given name, they were prompted to write their surname. Results showed that one student did not write a name, but the remaining 112 students completed the task. Table 134 shows parts of the name written by students.
Table 134
Parts of Their Own Name Written by Students in May/June Year 1
Parts of the name Frequency Percent Valid Percent Given name + surname 41 36.0 36.6 Given name only 70 61.4 62.5 Other 1 .9 .9 Total 112 98.2 100.0 Missing 2 1.8 Total 114 100.0
6.1.2.1. Summary
Thirty-six percent of the students wrote their given name and surname, 62.5% wrote given name only and one student wrote neither. Results need to be examined in the light of the demands placed on the students during the first four months of Year 1.
Some teachers may have demanded students learn to write their given name and surname and others may have required a given name only at this stage of the year and this may account for some of the differences.
6.1.3 ROBINSON’S TEST OF WRITING VOCABULARY
After writing their name on the blank sheet of paper, students were asked to write as many words as possible in a ten-minute period. Not all students used the maximum
Chapter 6: Describing and Correlating Year 1 (May/June) Data 318 time allowed. Only correctly spelt words were scored. Table 135 shows results for this test.
Table 135
Scores for Robinson’s Test of Writing Vocabulary May/June Year 1
Total School A School B School C Total 113 43 33 37 Mean 9.09 10.58 9.69 6.83 SD 6.48 5.99 7.14 5.95
Ninety-four percent of students wrote words for this task. Scores ranged from zero to
32. Some students were more able and confident and wrote many words while 47% wrote seven words or fewer. Size of words written by the students was recorded with three-letter words being the most common words written. Results for the number of students writing different size words were as follows:
• 88 students wrote two-letter words;
• 100 students wrote three-letter words;
• 48 students wrote four-letter words;
• 20 students wrote five-letter words;
• 18 students wrote words with more than five letters.
When results of Robinson’s Test of Writing Vocabulary were compared across schools School C had the lowest mean score (6.83) the highest percentage of students who wrote no words (10.5%). Multivariate analysis for children’s performances on Robinson’s Test of Writing Vocabulary showed no significant school effect (p = .32) or age effect (p = .27). A gender effect was shown [Wilks
Lambda =.89, (6, 107) = 2.17; p = .05; eta squared = .10] with girls writing significantly more words than boys. These results are similar to the Robinson’s Test
Chapter 6: Describing and Correlating Year 1 (May/June) Data 319 of Writing Vocabulary in Preschool where no school or age effect was shown but girls wrote a significantly higher number of words with more than five letters.
6.1.3.1 Summary
The majority of students (93.9%) were able to write at least one word and spell it correctly and the mean score of 9.09 for this task indicated students developing ability to write and spell words accurately compared to a means score of 1.36 in
Preschool.
6.1.4 LETTER KNOWLEDGE AND IDENTIFICATION
Students identified all lower case letters in three ways following the procedure outlined by Clay (1985). First, students named the letter. Then they provided a common sound made by the letter. Finally, they gave a word that started with the letter. Twenty-eight lower-case letters were presented to students using the 26 letters of the alphabet and the additional letter (a), and letter (g) in the font indicated. These two letters are commonly found in children’s published texts in this font, so they were included in the test. Results are presented in Table 136.
Chapter 6: Describing and Correlating Year 1 (May/June) Data 320 Table 136
Results for Knowing Letter Names, Sounds and Words for Each Letter in May/June Year 1
Preschools Mean SD N Total letter names May/June Yr1 School A 25.37 3.10 43 School B 23.30 4.62 33 School C 23.00 6.00 37 Total 23.99 4.74 113 Total letter sounds May/June Yr 1 School A 23.55 4.50 43 School B 19.39 6.06 33 School C 21.62 4.65 37 Total 21.70 5.28 113 Total words for letters May/June Yr 1 School A 21.90 5.99 43 School B 19.84 5.30 33 School C 21.13 5.28 37 Total 21.05 5.58 113
After approximately four months in Year 1, the majority of students in all three settings demonstrated they were learning the alphabetic code. In relation to letter names, a mean score of 23.9 was achieved with the scores ranging from five to 28.
On this task three students (2.7%) achieved a score of less than ten.
Students also demonstrated proficiency knowing the sounds that letters commonly made. Overall, a mean score of 21.7 was achieved with scores ranging from zero to
28. Once again, three students (2.7%) achieved a score of less than ten. The third task required students to give a word that started with the letter named. The overall mean score for this task was 21.05, with scores ranging from three to 28.
A further comparison of results for letter knowledge and identification examined the multivariate effect for school, age and gender. A significant school effect was shown
[Wilk’s Lambda = .76, MVF (6, 216) = 5.22; p = <.01; eta squared = .12].
Chapter 6: Describing and Correlating Year 1 (May/June) Data 321 Univariate analysis of variance clarified the significant results. These results are shown in Table 137.
Table 137
Univariate Analysis of Letter Knowledge and Identification Performances in May/June Year 1 by School
Task Sum of Squares df Mean Square F Sig. Total letter Between Groups 133.97 2 66.98 3.08 .05 names Within Groups 2387.01 110 21.70 Total 2520.99 112
Total letter Between Groups 324.17 2 162.08 6.35 <.01 sounds Within Groups 2807.18 110 25.52 Total 3131.36 112
Total words Between Groups 79.48 2 39.74 1.27 .28 for letters Within Groups 3418.19 110 31.07 Total 3497.68 112
Results showed a significant overall effect for knowing letter names and sounds but post hoc (Scheffe) analysis showed a significant mean score difference between
School A and B only for knowing letter sounds with a significant score of (p =
<.01).
A further analysis of variance examined results of letter knowledge and identification with age. Results did not attain statistical significance (p = .37). A third analysis of variance examined the gender effect. Results showed a significant effect for knowing letter names (F(1,111) = 6.24, p = .01) with results showing the girls achieving a significantly higher mean score (25.03) than the boys (22.85). A
Chapter 6: Describing and Correlating Year 1 (May/June) Data 322 comparison of results for this task in Preschool revealed no significant effect for school, age or gender occurred at that time.
6.1.4.1 Summary
Results for letter knowledge after four months in Year 1 showed the majority of students had learned letter names and letter sounds and they knew words beginning with some particular sounds. When comparing results for school, age and gender effects two statistically significant results occurred. These were a school effect for letter sounds with School A achieving a significantly higher mean score (23.55) than
School B (19.39), and, a gender effect for letter naming with girls achieving a significantly higher mean score (25.03) than boys (22.85).
6.1.5 CONCEPTS ABOUT PRINT TEST (CAP)
In May/June of Year 1 each student completed Clay’s Concepts About Print Test
(CAP) version Sand (Clay, 1979). A description of the twenty-four test items (Clay,
1985) is provided in Chapter 3 of this dissertation. The retest was conducted with an adult sharing the text Sand individually with each student. The text contains a number of deliberate errors that students are asked to identify during the test. Results for the CAP test are shown in Table 138.
Table 138
Scores for Concepts About Print Test May/June of Year 1
Score Total School A School B School C Total 113 43 33 37 Mean 16.69 17.04 16.15 16.75 SD 1.40 2.42 3.08 3.04
Chapter 6: Describing and Correlating Year 1 (May/June) Data 323
A comparison of results for students’ performances on the Concepts About Print
Test in May/June of Year 1 showed no significant school (p = 0.19), age (p = 0.16) or gender (p = 0.12) effects.
6.1.5.1 Summary
In comparing these results with those achieved in Preschool, it was found that no significant effect was shown for school or age. A gender effect was found in
Preschool with girls scoring significantly higher on a number of test items mostly relating to directionality of print.
6.1.6 CANBERRA WORD TEST
The Canberra Word Test, List B (Clough, McIntyre, & Cowey, 1990) was used again with students in may/June of Year 1. This test required students to read words from a list consisting of 15 words commonly found in children's early reading texts.
Students were asked to look at each word in turn, slide down a piece of paper that was covering the words and read each word in turn. All students attempted this task, although not all were able to read words. Results are shown in Table 139.
Table 139
Scores For the Canberra Word Test May/June of Year 1
Score Total School A School B School C Total 113 43 33 37 Mean 9.30 9.60 8.03 10.08 SD 4.04 4.24 4.11 3.55
Chapter 6: Describing and Correlating Year 1 (May/June) Data 324 Further analyses were conducted to ascertain significant effects for school, age and gender. There were no significant differences for school (p = .08), age (p = .21) or gender (p = .16). When comparing these results with those achieved in Preschool, it was found that no significant school, age or gender effect was shown at that time either.
6.1.7 STORY COMPREHENSION
A test of story comprehension was conducted similarly to time one in preschool, but a different story, My Brother John (Church, 1990) (see Appendix M) was read to the students by an adult. Statements were posed to the student who responded with true or not true responses. Four literal, four inferential and two nonsense statements were used (see Appendix N). Results are shown in Table 140.
Table 140
Scores For Story Comprehension in May/June of Year 1
Score Total School A School B School C Total 113 43 33 37 Mean 7.95 7.58 8.09 8.27 SD 1.75 1.67 1.89 1.67
Analysis of variance conducted on story comprehension showed no significant effects due to school (p = .18), age (p = .62) or gender (p = .94). Preschool period results were similar.
Chapter 6: Describing and Correlating Year 1 (May/June) Data 325 6.1.8 PRINT KNOWLEDGE TASK
The Print Knowledge Task based on the rhyme Humpty Dumpty, was used again in
May/June of Year 1. The task consisted of 17 items and students’ performances are shown in Table 141.
Table 141
Scores for Print Knowledge Task May/June of Year 1
Score Total School A School B School C Total 113 43 33 37 Mean 14.53 14.58 13.48 15.40 SD 2.51 2.47 2.90 1.81
Analysis of variance results showed no significant effect for age (p = .49) or gender
(p = .06) but a significant difference due to school (p < .01). School C scored significantly better than School B. Tables 142 and 143 show these results.
Table 142
Univariate Analysis for Print Knowledge Task in May/June of Year 1 by School
Sum of df Mean Square F Sig. Squares Between Groups 64.51 2 32.25 5.49 <.01 Within Groups 645.62 110 5.86 Total 710.14 112
Table 143
Post Hoc Analysis of Variance for Print Knowledge Task May/June of Year 1 with School
Mean Difference (I-J) Std. Error Sig. (I) Schools (J) Schools School C School B 1.92 .58 <.01
Chapter 6: Describing and Correlating Year 1 (May/June) Data 326 6.1.8.1 Summary
Results showed a school effect for the Print Knowledge Task with School C (mean score = 15.40) scoring significantly better than School B (mean score = 13.48).
Although not reaching a significant gender effect, results are trending strongly towards significance (p = .06) with the girls achieving a higher mean score (14.94) than the boys (14.07). When these results are compared to the preschool period it is found that no significant effect was shown for school, age or gender at that time.
6.1.9 SUTHERLAND PHONOLOGICAL AWARENESS TEST
The Sutherland Phonological Awareness Test consists of 11 subtests. The first five
(described in Chapter 4) were re-administered to students in May/June of Year 1.
The subtests consisted of:
• Subtest 1: Syllable counting;
• Subtest 2: Rhyme detection;
• Subtest 3: Rhyme production;
• Subtest 4: Onset identification;
• Subtest 5: Final phoneme production.
Results for each of the subtests are presented in Tables 144 - 148.
Table 144
Scores for Syllable Counting May/June of Year 1
Score Total School A School B School C Total 113 43 33 37 Mean 3.22 3.25 3.48 2.94 SD 1.11 1.04 0.75 1.39
Chapter 6: Describing and Correlating Year 1 (May/June) Data 327 Table 145
Scores for Rhyme Detection May/June of Year 1
Score Total School A School B School C Total 113 43 33 37 Mean 3.68 3.60 3.84 3.62 SD 0.63 0.69 0.44 0.68
Table 146
Scores for Rhyme Production May/June of Year 1
Score Total School A School B School C Total 113 43 33 37 Mean 2.84 2.74 2.90 2.89 SD 1.41 1.44 1.33 1.46
Table 147
Scores for Onset Identification May/June of Year 1
Score Total School A School B School C Total 113 43 33 37 Mean 3.84 3.83 3.66 4.00 SD 0.54 0.48 0.81 0.00
Table 148
Scores for Final Phoneme Production May/June of Year 1
Score Total School A School B School C Total 113 43 33 37 Mean 3.12 3.30 3.15 2.89 SD 1.25 1.10 1.32 1.34
Multivariate analyses of Sutherland Phonological Awareness Subtests examined the effect of school, age and gender. A significant school effect was found and is shown in Table 149.
Chapter 6: Describing and Correlating Year 1 (May/June) Data 328 Table 149
Multivariate Tests for Sutherland Phonological Awareness Tests in May/June of Year 1
Effect Value F Hypothesis df Error df Sig. Eta Squared SCHOOL Wilks' Lambda .84 1.91 10.00 212.00 .04 .08
A further examination of between-subject effects revealed a significant effect occurred on Subtest 4, Onset Identification, between Schools C and B with School C scoring a perfect mean score of 4.00 and School B achieving a mean score of 3.66.
Results for Sutherland Phonological Awareness Tests showed no significant effect for age (p = .92) or gender (p = .66). When comparing these results to the preschool period, it was found that a significant school effect was found on four of the subtests at that time. Preschool C was shown to have achieved a significantly lower mean score than Preschool A or Preschool B and this occurred for all four subtests. These results indicate an improvement for these students on all of these tasks compared to students from the two other schools. No significant age or gender effect was shown for any subtest in Preschool.
6.1.9.1 Summary
Sutherland Phonological Awareness tests results showed a significant effect for school on one subtest, Onset Identification, with School C achieving a significantly higher mean score (4.00) than School B (3.66). No statistically significant effect was found for age or gender. School C was shown to have improved results markedly since preschool. Their results have changed from the lowest mean score on all four
Subtests in Preschool to the highest by May/June of Year 1.
Chapter 6: Describing and Correlating Year 1 (May/June) Data 329 6.1.10 DISCUSSION
Results of Literacy Assessment Tasks in May/June of Year 1 showed students had increased their knowledge and understanding of literacy after approximately four months of instruction. In relation to the thesis question, ‘ How do child, home and school factors relate to literacy development in the first year of school’ the following significant effects were found in the data.
Students were tested on eight different literacy-related tasks. When all subtests within the tasks are considered, students completed 14 tasks in all. Just one student in the study was unable to write his name accurately by May of Year 1. Students’ age did not significantly affect performance on any task despite there being a broad range of age groups across the sample. Some school effects were shown and these occurred with knowing sounds letters make, print knowledge using the rhyme
Humpty Dumpty, and, onset identification - a subtest of the Sutherland Phonological
Awareness Test. Girls outperformed boys significantly on two tasks, naming letters, and Robinson’s Test of Writing Vocabulary.
Although a small number of significant effects were noted in the data, consistent patterns emerged. Gender effects occurred twice, school effects were shown four times and no age effects were demonstrated. It would appear from the literacy measures completed in May/June of Year 1 that some child and school factors had affect early literacy development at this mid-point of the longitudinal timeframe.
Home factors were not addressed in this chapter, but are addressed in Chapter 7.
Chapter 6: Describing and Correlating Year 1 (May/June) Data 330
Principal Component Analyses of the Literacy Assessment Tasks conducted in
May/June of Year 1 are reported in Chapter seven. These analyses allow an examination of the underlying dimensions within these tasks. Cluster Analyses follows where the predictive nature of the literacy tasks conducted in Preschool are examined in the light of the May/June literacy results.
Chapter 6: Describing and Correlating Year 1 (May/June) Data 331 CHAPTER SEVEN
REDUCING DIMENSIONS: RELATIONSHIPS IN THE YEAR 1 (MAY/JUNE) DATA
Principal Component Analysis (PCA) was conducted to investigate underlying factors that may exist within students’ performance data in May/June of Year 1. The following questions are addressed ‘How do child, home and school factors relate to literacy development in the first year of school?’ and ‘How do students’ literacy knowledge and understanding of it in the prior-to-school period predict students’ literacy achievement during the first year of school? Analyses were conducted with
Letter Knowledge, Concepts About Print Test and Sutherland Phonological
Awareness Tests as these were the only literacy tasks from the May/June period that could be subjected to factor analyses.
Following discussion of factor analyses, correlations of these factors with background factors (reported in Chapter 5), age, gender and school are conducted.
Background factors include demographic features of families, parents’ perceptions of home literacy practices and child characteristics and teachers’ perceptions of student classroom conduct and literacy progress. Additionally, factors devised from the May/June literacy measures are analysed with the Variable Sets, A, B and C derived from Cluster Analysis (reported in Chapter 5) to examine predictive capabilities.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 332
The shaded row in the following schema indicates the current section.
CHAPTER CONTENT DESCRIPTION Chapter 4: Describing and Correlating Preschool/Early Year 1 Data 4.1 Parent Survey 1 (November of Preschool) 4.2 Teacher Checklist 1 (March of Year 1) 4.3 Literacy Assessment 1 (November of Preschool). 4.4 Teacher Survey (March of Year 1). Chapter 5: Reducing dimensions: Relationships in the Preschool/Early Year 1 Data 5.1 Factor Analysis of Parent Survey 1;Teacher Checklist 1; Literacy Assessment 1. 5.2 Cluster Analysis based on Literacy Assessment 1 – Preschool period. Chapter 6: Describing and Correlating Year 1 (May) Data 6.1 Literacy Assessment 2 (May of Year 1) Chapter 7: Reducing dimensions: Relationships in the Year 1 (May) Data 7.1 Factor Analyses: Literacy Assessment 2 7.2 Cluster Analysis of Literacy Assessment 2 Chapter 8: Describing and Correlating Year 1 (November) Data 8.1 Literacy Assessment 3 (November of Year 1) 8.2 Parent Survey 2 8.3 Teacher Checklist 2 Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 9.1 Factor Analysis: Parent Survey 2; Teacher Checklist 2; Literacy Assessment 3 9.2 Cluster Analysis of Literacy Assessment 3
7.1 FACTOR ANALYSES: LITERACY ASSESSMENT TASKS MAY/JUNE YEAR 1
7.1.1 PERFORMANCE FACTOR: LETTER KNOWLEDGE 2
Three component tasks, letter naming, knowledge of letter sounds and knowing a word for a particular letter were subjected to Principal Component Analysis. These tasks were a retest of the letter identification tasks conducted in November of the preschool year, but on this occasion only lower case letters were tested. Results showed the extraction of a single factor (named ‘letter knowledge 2’) accounting for
87.7% of the variance. Table 150 shows the component matrix for the factor.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 333
Table 150
Component Matrix for Letter Knowledge 2 May/June of Year 1
Letter Knowledge Tasks Component Total letter sounds .96 Total words for letters .93 Total letter names .91
7.1.2 CORRELATION COEFFICIENTS: LETTER KNOWLEDGE 2
Pearson’s bivariate correlation of the ‘Letter Knowledge 2’ factor with background factors devised from Parent Survey 1 and Teacher Checklist 1 showed significant results. Two significant positive correlations and three significant negative correlations occurred. These correlations are presented in Table 151.
Table 151
Significant Correlations For Letter Knowledge 2 with Background Factors May/June of Year 1
Parents’ Parents’ Teachers’ Teachers’ Teachers’ perceptions - perceptions perceptions – perceptions - perceptions child - enjoy class conduct reading - writing characteristics preschool Letter .23* .21* -.34** -.45** -.22* knowledge 2 ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed)
Positive correlations occurred for the two parent factors. The first related to parents’ perception of their children’s concentration and memory and the second, related to parents’ perception of their children’s enjoyment of Preschool and interest in books.
A sample scatterplot depicting parents’ perceptions of child characteristics with letter knowledge 2 is shown in Figure 19.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 334
2
1
0
-1
-2
-3 Parents' perceptions of child characteristics
-4 -3 -2 -1 0 1 2
Letter Knowledge 2 factor May/June of Year 1
Figure 19. Positive correlations of parents’ perceptions – child characteristics and letter knowledge 2
Three negative correlations were found and all related to teachers’ perceptions. The first related to their perceptions of students’ class conduct including personal organisation, concentration and application to tasks. The second related to their perceptions of students’ reading progress in March of Year 1 and the third related to their perceptions of students’ writing progress in March of Year 1. A sample scatterplot depicting teachers’ perceptions of reading progress with letter knowledge
2 is shown in Figure 20.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 335
2
1
0
-1
-2
-3 etter knowledge 2 factor May/June of Year 1 lL -4 -3 -2 -1 0 1 2 3
Teachers' perceptions - reading
Figure 20. Negative correlation of teachers’ perceptions – reading and letter knowledge 2
7.1.2.1 Summary
Parents’ perceptions of children’s characteristics of concentration, memory, interest in books and writing gathered on Parent Survey 1 in November of the preschool year were closely aligned with results on letter knowledge tasks that the children achieved in May/June of Year 1.
Negative correlations occurred for teachers’ perceptions of class conduct including concentration, memory, application to tasks and following instructions indicating that the students the teachers rated more highly for personal characteristics, did not score highly for alphabetic knowledge. This has resulted in a significant negative correlation. Likewise, teachers’ perceptions of reading and writing progress in
March of Year 1 did not show positive correlations. This is an unexpected result and
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 336
may be interpreted in terms of teachers’ definition of ‘progress’. It is hypothesised that the interpretation of ‘progress’ may vary among the teachers and may depend on the observations of the students early in the school year. If students enter Year 1 displaying few observable literacy-related traits, then any progress may be easily recognised after a few weeks in Year 1, so teachers may rate reading and writing progress highly. By way of contrast, where students enter Year 1 with more developed literacy skills, their progress, while occurring steadily, may not be rated as highly as those students who enter school with fewer observable literacy traits. A second hypothesis is that accurate observations of students’ literacy skills have not been made by teachers in the early weeks of Year 1.
7.1.3 PERFORMANCE FACTOR: CONCEPTS ABOUT PRINT TEST (CAP) 2
Concepts About Print Test consists of 24 test items and results for this retest were subjected to Principal Component Analysis (PCA) to examine underlying factors.
Prior to the PCA, frequency scores for each test item were examined and those where 98% or more of the students scored correctly on the item, were left out of the factor analyses to prevent skewing of the results. Test items left out of the factor analyses included:
• Item 1 (pointing to the front of the book) 99.1% of students gave a correct
response
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 337
• Item 3 (knowing where to start reading) 98.2% of students gave a correct
response.
Principal Component Analysis with the remaining 22 test items was conducted and
eight factors with eigenvalues greater than one emerged. These eight factors
accounted for 63.75% of the variance and the component matrix is shown in Table
152.
Table 152
Rotated Component Matrix for CAP Factors May/June Year 1
CAP Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6 Factor 7 Factor 8 Item Directionality Sequencing Letter Concept Letter Place to Quotation Reading of print of letters Id. of a identification start marks & line left then and words word and reading sequencing right punctuation Cap4 .93 Cap5 .87 -.10 -.10 Cap14 -.57 .38 -.14 .13 .11 -.11 Cap2 .54 .21 .51 .17 .30 Cap13 .85 Cap12 .76 .16 -.15 .20 Cap20 -.12 .54 .21 .10 .43 Cap24 -.13 .42 .25 .18 .38 .14 Cap21 .78 Cap8 .14 .18 .59 -.31 .14 -.14 -.22 -.13 Cap19 .14 .56 .11 .37 Cap23 .19 .50 .36 .22 .29 .20 Cap17 -.15 -.74 .10 .17 Cap22 .61 .26 .25 .18 Cap6 .20 .12 .46 .41 .18 Cap15 .22 .16 .31 -.36 .17 .19 .32 Cap7 .81 -.18 .20 Cap16 .68 .26 -.21 Cap9 .84 Cap18 .75 .16 Cap10 .22 .29 .16 .10 .56 Cap11 .11 .87
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 338
The composition of each of the eight factors was examined in order to name the factors. Composition of each of the factors has been highlighted in Table 152 and names for the factors are presented below.
• CAP factor 1: directionality of print;
• CAP factor 2: sequencing of letters and words;
• CAP factor 3: letter identification;
• CAP factor 4: concept of a word;
• CAP factor 5: letter identification and punctuation;
• CAP factor 6: place to start reading;
• CAP factor 7: quotation marks and line sequencing;
• CAP factor 8: reading left then right.
7.1.4 CORRELATION COEFFICIENTS FOR CONCEPTS ABOUT PRINT
TEST (CAP) 2
Pearson’s bivariate correlation of background factors (demography, parents’ perceptions and teachers’ perceptions) age, gender, school and Concepts About Print factors (1-8) was carried out to ascertain if relationships exist. Eight significant positive correlations and six significant negative correlations occurred. These are shown in Tables 153 and 154 to enable clear placement on the page. No significant correlations occurred for Concepts about Print Factors 1 and 8 and so these factors are not included in the following tables.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 339
Table 153
Correlations of CAP factors with Background Factors May/June of Year 1 (A)
CAP Factor School Mother SES Father SES Parents’ Parents’ factor factor perceptions perceptions of home writing home reading 3. Letter -.023 .14 .05 .23* -.08 identification
4. Concept of a -.87 .25* -.07 .14 -.08 word
5. Letter -.04 -.06 .02 .01 .19* identification & punctuation
6. Place to start .02 -.06 .21* .12 .16 reading
7. Quotation marks .19* .13 -.02 -.14 .19 and line sequencing ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed)
Table 154
Correlations of CAP Factors with Background Factors May/June of Year 1 (B)
CAP Factor Parents’ Parents’ Parents’ Teachers’ Teachers’ perceptions perceptions perceptions perceptions perceptions of who child enjoying – class reading reads characteristics preschool conduct 2. Sequencing of letters -.15 .14 -.07 -.21* -.19* and words
3. Letter identification .24* .25** .05 -.15 -.21*
4. Concept of a word -.10 .06 . 31** -.19* -.11
6. Place to start reading .11 .11 -.03 -.30** -.40** ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed)
Eight significant positive correlations and five significant negative correlations
occurred. All positive correlations related to parents’ perceptions of home literacy
practices or child characteristics, mother SES or father SES factors or school. A
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 340
sample scatterplot depicting the correlation of parents’ perception of enjoying preschool with CAP factor 4 ‘concept of a word’ is shown in Figure 21. It is clear that some range restriction is involved in some of these relationships.
2
1
0
-1 int. in books/enjoy preschool -2
-3
-4
Parents' percept. child's -5 -6 -5 -4 -3 -2 -1 0 1 2
CAP factor 4 May/June of Year 1 (Concept of a word)
Figure 21. Positive correlation of CAP 4 – concept of a word and parents’ perception
– enjoy preschool
All negative correlations related to teachers’ perceptions of students’ conduct or reading progress. A sample scatterplot, depicting teachers’ perceptions of reading progress with CAP Factor 6 – ‘place to start reading’ is shown in Figure 22.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 341
3
ess 2 ogr
1 ading pr e r
0 eptions of c -1 ' per s
-2 Teacher
-3 -3 -2 -1 0 1 2 3
CAP factor 6 May/June of Year 1 (place to start reading)
Figure 22. Negative correlation teachers’ perception – reading and CAP 6 – place to start reading
7.1.4.1 Discussion
It is worth noting that parents’ perceptions were collected in November of the preschool year using Parent Survey 1 and students’ literacy results six months later in May of Year 1 are still positively correlated. By way of contrast, all negative correlations with the CAP factors derived from the May/June CAP test are with teachers’ perceptions of the students’ conduct in class or reading progress. Teachers’ perceptions were derived from data collected from teachers in March of Year 1.
These results are once again unexpected as they were with the students’ literacy results from the preschool period. Results indicated parents’ perceptions of their children’s progress in literacy were more closely related to the results achieved than those predicted by their teachers.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 342
7.1.5 PERFORMANCE FACTOR: SUTHERLAND PHONOLOGICAL
AWARENESS TEST
Students completed a retest of the five subtests of the Sutherland Phonological
Awareness Test in the May/June period of Year 1. These subtests included syllable counting, rhyme detection, rhyme production, onset identification and final phoneme production (reported in Chapter 3). Four tasks were completed for each of the subtests and the students were given practice for each task before commencing the test items to ensure they understood the procedure.
Principal Component Analysis was conducted on the Sutherland Phonological
Awareness Tests to examine underlying factors. Initial analysis showed two factors with an eigenvalue greater than 1.0 accounting for 61% of the variance. The rotated component matrix is shown in Table 155.
Table 155
Rotated Component Matrix for Sutherland Phonological Awareness May/June of Year 1
Phonological awareness subtests Component Component Onset identification .83 -.26 Final phoneme production .71 .36 Rhyme production .63 .38 Syllable counting -.05 .75 Rhyme detection .24 .67
Factor 1 (named ‘onset identification and final phoneme and rhyme production’) loaded heavily on subtests four, five and three. Factor 2 (named ‘syllable counting and rhyme detection’) loaded on subtests one and two. Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 343
7.1.6 CORRELATION COEFFICIENTS: SUTHERLAND PHONOLOGICAL
AWARENESS TEST
Pearson’s bivariate correlation of the calculated background factors, school, age, gender and the two factors for Sutherland Phonological Awareness measures was carried out. Results shown in Table 156 display three significant positive correlations and four significant negative correlations.
Table 156
Correlations of Sutherland Phonological Awareness Factors with Background Factors May/June of Year 1
Factors SES father Parents’ Teachers’ Teachers’ factor perceptions perceptions perceptions child class conduct reading characteristics Onset identification .05 .23* -.22* -.28* and final phoneme and rhyme production
Syllable counting, .22* .24* -.21* -.21* rhyme detection
Results showed positive correlations with SES father factor and the parents’ perception of children’s memory and concentration. Significant negative correlations occurred for two teacher factors. The first was teachers’ perception of student conduct in class and the second related to children’s progress in reading. Once again parents’ perceptions related positively to the children’s results and teachers’ perceptions related negatively.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 344
7.1.7 DISCUSSION
A consistent pattern of correlations occurred. Positive correlations were seen mostly with parents’ perceptions and negative correlations with teachers’ perceptions. These results indicated that parents perceived their children’s concentration and memory accurately in relation to literacy learning in the first few months of Year 1. On the other hand, teachers appeared to be using other criteria when making judgments about literacy progress and these correlated negatively with many of the literacy performance factors completed in May/June of Year 1.
It appears that teachers positively align students’ ability to apply themselves to tasks, their personal organisation, their ability to follow instructions and show good concentration, with progress being made in reading and writing. These criteria have been shown to produce negative correlations with students’ results on literacy tasks in May/June of Year 1. It appears as if Year 1 teachers in March of Year 1 were not judging students’ reading and writing progress in absolute terms, not in line with the literacy results reported from November of Preschool or those shown May/June of
Year 1.
Correlations of background factors and performance factors for May/June of Year 1 revealed most of the positive correlations (9 out of 12) occurred with parents’ perceptions of child characteristics and home literacy practices. All of the negative correlations (13) occurred with teachers’ perceptions of class conduct, progress in reading or progress in writing. Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 345
It also is worth noting that no significant correlations occurred with age or gender and only one positive significant correlation was shown with school. This was with
CAP Factor 7 ‘quotation marks and line sequencing’. One significant correlation was shown between father SES factor and CAP factor 6 ‘ place to start reading’ and one between mother SES factor and CAP factor 4 ‘ concept of a word’.
These results showed no age or gender effect with literacy results from Year 1 testing in the May/June period. It appeared from these results that there was little or no relationship between students’ literacy measures in May/June of Year 1 with school, age, gender or the demography relating to mothers’ or fathers’ education and occupation. Parents appear to show a more accurate perception of their children’s progress in literacy than class teachers in the first half of Year 1. Teachers tended to align children’s conduct in class with progress in literacy, and in this study this relationship has been shown to be negative.
The following section reports Cluster Analyses for Variable Sets, A, B and C where each set is analysed with students’ results from May/June of Year 1. These analyses examined the predictive nature of the Variable Sets devised from selected Literacy
Assessment Task results in Preschool.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 346
7.2 CLUSTER ANALYSES
In order to continue to investigate the predictive nature of literacy tasks from the preschool period, cluster analyses were conducted. Factor scores (reported in
Chapter 5 and this chapter) were used in the analyses. Variable Set A (based on preschool CAP results), Variable Set B (based on Environmental Print and Letter
Knowledge results in Preschool) and Variable Set C (based on Phonological
Awareness in Preschool) were used again.
Multivariate and univariate analyses were conducted with each of the Variable Sets
A, B and C and with each of the factors/scores from Literacy Assessment Tasks completed in May/June of Year 1. Results for each of the Variable Sets are now reported.
The shaded row in the following schema indicates the current section.
CHAPTER CONTENT DESCRIPTION Chapter 4: Describing and Correlating Preschool Data 4.1 Parent Survey 1 (November of Preschool) 4.2 Teacher Checklist 1 (March of Year 1) 4.3 Literacy Assessment 1 (November of Preschool). 4.4 Teacher Survey (March of Year 1). Chapter 5: Reducing dimensions: Seeing relationships in Preschool Data 5.1 Factor Analysis of Parent Survey 1;Teacher Checklist 1; Literacy Assessment 1. 5.2 Cluster Analysis based on Literacy Assessment 1 – Preschool period. Chapter 6: Describing and Correlating Year 1 (May) Data 6.1 Literacy Assessment 2 (May of Year 1) Chapter 7: Reducing dimensions: Seeing relationships in Year 1 (May) Data 7.1 Factor Analyses: Literacy Assessment 2 7.2 Cluster Analysis of Literacy Assessment 2 Chapter 8: Describing and Correlating Year 1 (November ) Data 8.1 Literacy Assessment 3 (November of Year 1) 8.2 Parent Survey 2 8.3 Teacher Checklist 2 Chapter 9: Reducing Dimensions: Seeing Relationships in Year 1 (November) Data 9.1 Factor Analysis: Parent Survey 2; Teacher Checklist 2; Literacy Assessment 3 9.2 Cluster Analysis of Literacy Assessment 3
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 347
7.2.1 VARIABLE SET A
Analyses were carried out with Variable Set A (devised from CAP in Preschool) and factors/scores derived from literacy measures completed in May/June of Year 1 to examine further the predictive nature of Variable Set A. Results showed three non- significant effects. These were for Concepts about Print Test (p = .09), Sutherland
Phonological Awareness Test (p = .07) and Story Comprehension My Brother John
(p = .30) (see Appendix M). Four significant effects occurred and these are shown in
Table 157.
Table 157
Significant Results for Variable Set A With Literacy Tasks Completed in May/June of Year 1
Factors/variables Wilk’s Lambda & F value p value Letter knowledge & identification 2.72 .02 Print knowledge task 4.46 .01 Robinson test of writing vocabulary 5.51 <.01 Canberra word test 3.54 <.01
Means and standard errors of each significant scores/factors were examined so that each of the seven Student Clusters from Variable Set A could be examined more closely. As previously done when examining Variable Set A, Student Cluster 2, in which there are only three students, has been left out of the analyses. Means and standard errors for letter knowledge are shown in Table 158.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 348
Table 158
Means and Standard Errors For Variable Set A on Letter Knowledge Measures in May/June of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 2 is not in the analysis as the number of students (3) is too small). Student cluster and description N Mean St. Error 1. – print awareness; + awareness of conventions; + 27 -.16 .18 left-right 3. – directionality 15 .09 .25 4. ++ print awareness; 24 .42 .20 5. – awareness of conventions; + directionality; 20 -.63 .24 6. – starting points; -- left-right; + awareness of 8 .07 .36 conventions; + punctuation 7. ++ starting points 17 .28 .23
Variable Set A predicted students’ ability to name lower case letters, provide a
sound for each of the letters and give a word that starts with particular sounds/letters.
Student Cluster 4 performed best on letter knowledge in May/June of Year 1 and
Student Cluster 5 was the lowest performing group.
A significant relationship was also shown for Variable Set A and Print Knowledge
Task. Means and standard errors are shown in Table 159.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 349
Table 159
Means and Standard Errors for Variable Set A on Total Score for Print Knowledge Task Measures in May of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 2 is not in the analysis as the number of students (3) is too small). Student cluster and description N Mean St. Error 1. – print awareness; + awareness of conventions; + 27 14.25 .44 left-right 3. – directionality 15 13.71 .62 4. ++ print awareness; 24 16.00 .48 5. – awareness of conventions; + directionality; 20 12.66 .60 6. – starting points; -- left-right; + awareness of 8 14.57 .88 conventions; + punctuation 7. ++ starting points 17 15.23 .56
Variable Set A was shown to predict students’ ability to understand various print related tasks using the rhyme Humpty Dumpty. These tasks included:
• Pointing to words and letters;
• Finding a name in the text;
• Finding a word that begins like ‘had’;
• Matching strips of text to the whole text;
• Recognising a strip of text that is out of order;
• Recognising a strip that is upside down;
• Reading the rhyme and pointing while reading;
• Finding particular words in the text e.g. ‘Humpty’, ‘sat’, ‘horses’, ‘men’.
Student Cluster 4 again showed the highest mean score while Student Cluster 5 was the lowest performing group.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 350
The third task where statistical significance occurred was with Robinson’s Test of
Writing Vocabulary where students were asked to write as many words as they could in a ten-minute period. Means and standard errors are shown in Table 160.
Table 160
Means and Standard Errors for Variable Set A on Total Score for Robinson’s Test of Writing Vocabulary Measures in May of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 2 is not in the analysis as the number of students (3) is too small). Student cluster and description N Mean St. Error 1. – print awareness; + awareness of conventions; + 27 7.74 1.15 left-right 3. – directionality 15 6.57 1.60 4. ++ print awareness; 24 14.52 1.26 5. – awareness of conventions; + directionality; 20 6.60 1.55 6. – starting points; -- left-right; + awareness of 8 6.85 2.27 conventions; + punctuation 7. ++ starting points 17 11.05 1.46
Variable Set A predicted students’ ability to write words. This task was different in nature to the tasks usually conducted in class with their teachers. Some prompting from the adult facilitators was given if students had difficulty thinking of words e.g. the adult would say, ‘Can you think of any names you know?’ or ‘Can you think of any animals?’ etc. Not all students wrote words for the full ten-minute period.
Words were only counted as correct if the students spelt the word accurately.
Student Cluster 4 once again showed the highest mean score and Student Clusters 3 and 5 were the lowest performing groups.
The final literacy assessment measure from the May/June period of Year 1 that showed statistical significance was for the Canberra Word Test where the students
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 351
were asked to read 15 words commonly found in children’s early reading texts.
Means and standard errors are shown in Table 161.
Table 161
Means and Standard Errors for Variable Set A on Canberra Word Test Measures in May of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 2 is not in the analysis as the number of students (3) is too small). Student cluster and description N Mean St. Error 1. – print awareness; + awareness of conventions; 27 9.03 .73 + left-right 3. – directionality 15 8.64 1.01 4. ++ print awareness; 24 11.87 .79 5. – awareness of conventions; + directionality; 20 7.00 .98 6. – starting points; -- left-right; + awareness of 8 7.71 1.43 conventions; + punctuation 7. ++ starting points 17 9.41 .92
Results of children’s performance for reading common words found in children’s early reading texts was predicted by Variable Set A. It should be noted that these words were presented to the students in a list with no assistance from illustrations or the context of a story. Student Cluster 4 once again achieved the highest mean score and Student Cluster 5 was the lowest performing group.
7.2.2 SUMMARY OF VARIABLE SET A ASSOCIATIONS
Variable Set A relates significantly to four of the seven Literacy Assessment task measures from May/June in Year 1. These four measures included naming letters and their associated sounds, demonstrating various print related tasks, writing words without assistance and reading words from a list. This range of tasks is broad and
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 352
demonstrates the general predictive nature of the cluster analysis based on CAP from the preschool period.
Another significant finding was that the original clustering based on CAP shows students who displayed a high level of skills in preschool still maintained those skills in May/June of Year 1. In Chapter 5 it was shown how Student Cluster 4 scored significantly better than other Student Clusters on nine out of ten measures of preschool literacy. On all four significant measures for Variable Set A in the
May/June period of Year 1, Student Cluster 4 again showed the highest mean scores.
The lowest performing students from the preschool period continued to perform least well in May/June of Year 1. In Chapter 5 it was shown that when preschool literacy measures were analysed with Variable Set A, Student Clusters 6, 5 and 3 demonstrated the lowest achievement. This result was shown in the following ways in Preschool:
• Student Cluster 6 showed the lowest achievement on 5 of the 10 measures;
• Student Cluster 5 shows the lowest performance on 3 of the 10 measures;
• Student Cluster 3 shows the lowest performance on 2 of the 10 measures.
In May/June of Year 1 Student Cluster 5 and 3 showed the lowest performance on the four significant measures with Variable Set A. A summary of Student Clusters for highest and lowest performances in May of Year 1 with Variable Set A is shown in Table 162.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 353
Table 162
Variable Set A (Based on CAP in Preschool) with Significant May/June Literacy Assessment Measures Depicting the Highest and Lowest Cluster Mean Scores
Factor/Score Highest Lowest result/Mean score result/Mean score Letter knowledge and identification Cluster 4 (.42) Cluster 5 (-.63) Print knowledge task Cluster 4 (16.00) Cluster 5 (12.66) Robinson’s test of writing vocabulary Cluster 4 (14.52) Cluster 3 (6.57) Canberra word test Cluster 4 (11.87) Cluster 5 (7.00)
As consistency has been demonstrated for results in the Preschool period and in
May/June of Year 1, with Variable Set A, it is worth revisiting the profile of Cluster
4, the highest performing group of students and Cluster 5, the lowest performing group. Table 163 shows these profiles.
Table 163
Standardised Cluster Mean Vectors for Student Groups Within Variable Set A
CAP Factors Cluster Cluster Cluster Cluster Cluster Cluster Cluster 1 2 3 4 5 6 7 N = 27 N = 3 N =15 N = 24 N = 20 N = 8 N = 17 Print awareness -.72 -.32 -.35 1.71 -.36 -.05 -.43
Directionality .31 .65 - 2.13 .11 .64 -.03 .36
Awareness of .66 -.12 -.28 .00 -1.35 .88 .28 conventions
Punctuation -.35 4.64 -.15 -.08 -.12 .62 -.14
Starting points -.27 1.17 .10 -.04 -.41 -1.22 1.24
Left and right .76 .66 -.11 .26 -.19 -2.04 -.42
Cluster 4, consisting of 24 students, has print awareness well above the mean and
well above the result achieved by all other student clusters. Cluster 5, the lowest
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 354
performing cluster of students, demonstrated skills well below the mean for awareness of conventions and above the mean for directionality. These results indicate the relative value of print awareness prior to commencing school as a predictor for success in literacy development five months after commencing Year 1.
7.2.3 VARIABLE SET B
Analyses of variance of May/June literacy measures with Variable Set B (derived from Environmental Print and Letter Knowledge in preschool) were conducted to examine predictive capabilities further. Results showed three non-significant effects and four significant effects for Variable Set B. The non-significant effects were for
CAP (p = .16), Story Comprehension (p = .73) and Sutherland Phonological
Awareness Test (p = .33). Significant effects were shown for Letter Knowledge,
Print Knowledge Task, Robinson’s Test of Writing Vocabulary and Canberra Word
Test and are presented in Table 164.
Table 164
Significant Results for Variable Set B With Literacy Tasks Completed in May/June of Year 1
Factors/variables F value p value Letter knowledge & identification 6.68 <.01 Print knowledge task 6.40 <.01 Robinson’s test of writing vocabulary 7.68 <.01 Canberra word test 9.62 <.01
Means and standard errors of each score/factor were examined where significance occurred so that each of the six Student Clusters from Variable Set B might be examined more closely. As previously done when examining Variable Set B, Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 355
Student Cluster 6 in which there are only 4 students has been left out of the analyses.
Means and standard errors for Letter Knowledge are shown in Table 165.
Table 165
Means and Standard Errors for Variable Set B on Letter Knowledge Measures in May/June of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 6 is not in the analysis as the number of students (4) is too small). Cluster and description N Mean St. Error 1. + contextualised environmental print tasks. 41 -.21 .14 2. – contextualised environmental print tasks; 37 -.39 .16 - decontextualised environmental print tasks; - letter knowledge 3. ++ decontextualised environmental print tasks. 8 .26 .32 4. ++ decontextualised environmental print tasks; ++ letter 9 .83 .30 knowledge; + contextualised environmental print tasks. 5. ++ letter knowledge. 15 .75 .23
Variable Set B predicted students’ ability to name lower case letters, provide a sound for each letter and give a word that starts with a particular sound/letter. Student
Clusters 4 and 5 performed best on letter knowledge in May/June of Year 1 and
Student Cluster 2 was the lowest performing group.
A significant relationship was also shown for Print Knowledge Task using the rhyme, Humpty Dumpty. Means and standard errors are shown in Table 166.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 356
Table 166 Means and Standard Errors for Variable Set B on Print Knowledge Task Measures in May/June of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 6 is not in the analysis as the number of students (4) is too small). Cluster and description N Mean St. Error 1. + contextualised environmental print tasks. 41 14.25 .36 2. – contextualised environmental print tasks; 37 13.31 .40 - decontextualised environmental print tasks; - letter knowledge 3. ++ decontextualised environmental print tasks. 8 16.25 .81 4. ++ decontextualised environmental print tasks; ++ 9 16.77 .76 letter knowledge; + contextualised environmental print tasks. 5. ++ letter knowledge. 15 15.53 .59
Variable Set B predicted students’ ability to complete various print related tasks using the rhyme, Humpty Dumpty. These tasks included:
• Pointing to words and letters;
• Finding a name in the text;
• Finding a word that begins like ‘had’;
• Matching strips of text to the whole text;
• Recognising a strip of text that is out of order;
• Recognising a strip that is upside down;
• Reading the rhyme and pointing while reading;
• Finding particular words in the text e.g. ‘Humpty’, ‘sat’, ‘horses’, ‘men’.
Student Cluster 4 again showed the highest mean score while Student Cluster 2 was the lowest performing group.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 357
The third task where statistical significance was shown for Variable Set B was with
Robinson’s Test of Writing Vocabulary. Means and standard errors are shown in
Table 167.
Table 167
Means and Standard Errors for Variable Set B on Robinson’s Test of Writing Vocabulary Measures in May/June of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 6 is not in the analysis as the number of students (4) is too small). Cluster and description N Mean St. Error 1. + contextualised environmental print tasks. 41 7.94 .94 2. – contextualised environmental print tasks; 37 7.31 1.04 - decontextualised environmental print tasks; - letter knowledge 3. ++ decontextualised environmental print tasks. 8 7.75 2.09 4. ++ decontextualised environmental print tasks; ++ letter 9 16.77 1.97 knowledge; + contextualised environmental print tasks. 5. ++ letter knowledge. 15 14.20 1.52
Variable Set B predicted students’ ability to write words in May/June of Year 1.
Student Clusters 4 and 5 once again showed the highest mean performances and
Student Cluster 2 was the lowest performing cluster.
The final literacy assessment measure from May/June of Year 1 that showed statistical significance with Variable Set B occurred for results on the Canberra
Word Test. Means and standard errors are shown in Table 168.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 358
Table 168 Means and Standard Errors for Variable Set B on Canberra Word Test Measures in May/June of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 6 is not in the analysis as the number of students (4) is too small). Cluster and description N Mean St. Error 1. + contextualised environmental print tasks. 41 8.23 .55 2. – contextualised environmental print tasks; 37 7.71 .61 - decontextualised environmental print tasks; - letter knowledge 3. ++ decontextualised environmental print tasks. 8 9.62 1.23 4. ++ decontextualised environmental print tasks; ++ letter 9 14.00 1.16 knowledge; + contextualised environmental print tasks. 5. ++ letter knowledge. 15 12.40 .90
Variable Set B predicted students’ performance in reading a list of words in
May/June of Year 1. The 15 words in this test are commonly found in beginning reading texts. Student Clusters 4 and 5 once again showed the highest mean score and Student Cluster 2 was the lowest performing group.
7.2.4 SUMMARY OF VARIABLE SET B ASSOCIATIONS
Variable Set B related significantly to four of the seven Literacy Assessment Task measures from the May/June period in Year 1. These four measures included naming letters and their associated sounds, demonstrating various print related tasks, writing words and reading words from a list. This range of tasks was broad and demonstrated the general predictive nature of the cluster analysis based on
Environmental Print and Letter Knowledge from the preschool period.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 359
Another significant finding was that the original clustering based on Environmental
Print and Letter Knowledge showed students who displayed a high level of skills in preschool are still maintaining those skills in May/June of Year 1. In Chapter 5 it was shown how Student Cluster 4 scored significantly better than other Student
Clusters on six out of nine measures of preschool literacy. On all four significant measures for Variable Set B in this period, Student Cluster 4 again showed the highest mean score. The profile of this cluster is above the mean for contextualised environmental print tasks and well above the mean for decontextualised tasks and letter knowledge.
Lowest performing students in preschool also were still performing least well in
May/June of Year 1. In Chapter 5 it was shown that when preschool literacy measures were analysed with Variable Set B, Student Cluster 2 demonstrated the lowest achievement on seven of the nine significant measures in preschool. This
Student Cluster continued to demonstrate the lowest performance and this is shown for all four significant measures with Variable Set B. The profile for this cluster is below the mean for contextualised tasks, decontextualised tasks and letter knowledge.
A summary of Student Clusters for the highest and lowest performances in
May/June of Year 1 with Variable Set B is shown in Table 169.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 360
Table 169
Variable Set B (Based on Environmental Print and Letter Knowledge) with Significant May/June Literacy Assessment Measures Depicting the Highest and Lowest Cluster Mean Scores
Factor/Score Highest Lowest result/mean score result/mean score Letter knowledge and identification Cluster 4 (.83) Cluster 2 (-.39) Print knowledge task Cluster 4 (16.77) Cluster 2 (13.31) Robinson’s Test of Writing Vocabulary Cluster 4 (16.77) Cluster 2 (7.31) Canberra Word Test Cluster 4 (14.00) Cluster 2 (7.71)
7.2.5 VARIABLE SET C
Further analyses were carried out with Literacy measures from May/June of Year 1 and Variable Set C (devised from Phonological Awareness in preschool) to examine further predictive capabilities. Results showed two non-significant effects one for
Concepts about Print Test (p = .17) and one for Story Comprehension (p = .07). Six significant effects were shown and are presented in Table 170.
Table 170
Significant Results for Variable Set C With Literacy Tasks Completed in May/June of Year 1
Factors/variables Wilk’s Lambda p value & F value Letter knowledge & identification 3.58 .01 Phonological awareness factor – (onset .72 <.01 identification, final phoneme and rhyme production) Phonological awareness factor – (syllable counting, .72 <.01 rhyme detection) Print knowledge task 2.76 .04 Robinson’s Test of Writing Vocabulary 9.01 <.01 Canberra Word Test 2.72 .04
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 361
Means and standard errors of each score/factor are examined where significance occurs so each of the five Student Clusters from Variable Set C may be examined more closely. As previously done when examining Variable Set C, Student Cluster 5 in which there are only five students has been left out of the analyses. Means and standard errors for Letter Knowledge are shown in Table 171.
Table 171
Means and Standard Errors for Variable Set C on Letter Knowledge 2 Measures in May/June of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 5 is not in the analysis as the number of students (4) is too small). Student cluster and description N Mean St. Error 1. ++ onset identification,; ++ final phoneme identification; ++ 20 .40 .22 rhyme production 2. + syllable counting,; + rhyme detection; + rhyme production 27 .31 .18 3. – onset identification; - final phoneme identification; - 41 -.27 .15 rhyme production 4. - syllable counting; - rhyme detection; - rhyme production 21 -.28 .21
Variable Set C (devised from phonological awareness in preschool) predicted students’ ability to name lower case letters, provide a sound for each of the letters and give a word that starts with a particular sound/letter. Student Cluster 1 performed best on letter knowledge in May/June of Year 1 and Student Cluster 4 was the lowest performing group.
A significant effect was also shown for Variable Set C with both factors devised from Sutherland Phonological Awareness scores. The first of these entails aspects of onset identification, final phoneme and rhyme production and is shown in Table 172.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 362
Table 172
Means and Standard Errors for Variable Set C With Onset Identification, Final Phoneme and Rhyme Production Factor Measures in May/June of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 5 is not in the analysis as the number of students (4) is too small). Student cluster and description N Mean St. Error 1. ++ onset identification,; ++ final phoneme identification; 20 .38 .22 ++ rhyme production 2. + syllable counting,; + rhyme detection; + rhyme 27 .44 .18 production 3. – onset identification; - final phoneme identification; - 41 -.34 .15 rhyme production 4. – syllable counting; - rhyme detection; - rhyme production 21 -.38 .21
Variable Set C predicted phonological awareness results in May/June of Year 1.
Student Cluster 2 performed best and Student Cluster 4 was the lowest performing group. A significant effect was also shown for the second phonological awareness factor devised from literacy measures in May/June of Year 1. This factor captured aspects of syllable counting and rhyme detection. Means and standard errors are shown in Table 173.
Table 173
Means and Standard Errors for Variable Set C on Syllable Counting and Rhyme Detection Measures in May/June of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 5 is not in the analysis as the number of students (4) is too small). Student cluster and description N Mean St. Error 1. ++ onset identification,; ++ final phoneme identification; ++ 20 .41 .22 rhyme production 2. + syllable counting,; + rhyme detection; + rhyme production 27 .37 .18 3. – onset identification; - final phoneme identification; - 41 .02 .15 rhyme production 4. – syllable counting; - rhyme detection; - rhyme production 21 -.60 .21
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 363
Variable Set C predicted students’ results for the factor containing aspects of syllable counting and rhyme detection. This relationship indicated students’ knowledge of phonological awareness in preschool related to their knowledge in May/June of Year 1.
Student Cluster 1 performed best on syllable counting and rhyme detection factor and
Student Cluster 4 was the lowest performing group. A significant effect also was shown for
Variable Set C with Print Knowledge Task using the rhyme, Humpty Dumpty. Means and standard errors are shown in Table 174.
Table 174
Means and Standard Errors for Variable Set C on Print Knowledge Task Measures in May/June of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 5 is not in the analysis as the number of students (4) is too small). Student cluster and description N Mean St. Error 1. ++ onset identification,; ++ final phoneme identification; ++ 20 15.44 .58 rhyme production 2. + syllable counting,; + rhyme detection; + rhyme production 27 15.07 .47 3. – onset identification; - final phoneme identification; - rhyme 41 13.68 .39 production 4. – syllable counting; - rhyme detection; - rhyme production 21 14.55 .55
Variable Set C predicted students’ ability to understand various print related tasks using the rhyme, Humpty Dumpty. Student Cluster 1 performed best and Student
Cluster 3 was the lowest performing group.
The fifth task where a significant effect was shown relates to results on Robinson’s
Test of Writing Vocabulary where students were asked to write as many words as possible in a 10-minute period. Means and standard errors are shown in Table 175.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 364
Table 175
Means and Standard Errors for Variable Set C on Robinson’s Test of Writing Vocabulary Measures in May of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 5 is not in the analysis as the number of students (4) is too small). Student cluster and description N Mean St. Error 1. ++ onset identification,; ++ final phoneme identification; 20 12.66 1.41 ++ rhyme production 2. + syllable counting,; + rhyme detection; + rhyme 27 13.03 1.15 production 3. – onset identification; - final phoneme identification; - 41 6.92 .97 rhyme production 4. - syllable counting; - rhyme detection; - rhyme production 21 6.35 1.33
Results showed quite a large margin between Student Clusters 1 and 2 and 3 and 4.
Student Cluster 2 once again performed best with a mean score of 13.03 words. The lowest performing group was Student Cluster 4 with a mean score of 6.35.
The final task where a significant effect was shown with Variable Set C was for
Canberra Word Test. Variable Set C predicted students’ ability to read common words from a list in May/June of Year 1. Means and standard errors are shown in
Table 176.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 365
Table 176
Means and Standard Errors for Variable Set C on Canberra Word Test Measures in May/June of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.). (Note that Student Cluster 5 is not in the analysis as the number of students (4) is too small). Student cluster and description N Mean St. Error 1. ++ onset identification,; ++ final phoneme identification; 20 11.27 .92 ++ rhyme production 2. + syllable counting,; + rhyme detection; + rhyme 27 9.81 .75 production 3. – onset identification; - final phoneme identification; - 41 8.21 .63 rhyme production 4. – syllable counting; - rhyme detection; - rhyme production 21 8.85 .88
Student Cluster 1 achieved the highest mean score (11.27) and Student Cluster 3 achieved the lowest mean score (8.21).
7.2.6 SUMMARY OF VARIABLE SET C ASSOCIATIONS
Variable Set C related significantly to all Literacy Assessment Tasks except for
Concepts About Print Test and Story Comprehension using the text My Brother
John. This variable set predicted students’ performance on a wide range of reading and writing tasks five months after school commenced. Tasks included letter knowledge, aspects of phonological awareness, print knowledge, writing words and reading words from a list.
When examining the best performing Student Cluster from Variable Set C in preschool, it was found that Student Cluster 1 performed best for all nine tasks. For
Literacy Assessment Tasks in May/June of Year 1, Student Cluster 1 continued to perform best for four of the seven tasks. Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 366
The lowest performing Student Cluster from Variable Set C in Preschool was
Student Cluster 4 where the lowest performance was noted for seven of the nine tasks. In May/June of Year 1 Student Cluster 4 continued to perform the lowest for four of the seven tasks. The highest and lowest cluster means for all significant literacy tasks in May/June of Year 1 with Variable Set C are presented in Table 177.
Table 177
Variable Set C (Based on Phonological Awareness in Preschool) with Significant May/June Literacy Assessment Measures Depicting the Highest and Lowest Cluster Mean Scores
Factor/Score Highest Lowest result/mean score result/mean score Letter knowledge and identification Cluster 1 (.40) Cluster 4 (-.28) Onset Identification, final phoneme Cluster 2 (.44) Cluster 4 (-.38) production , rhyme production Syllable counting, rhyme detection Cluster 1 (.41) Cluster 4 (-.60) Print knowledge task Cluster 1 (15.44) Cluster 3 (13.68) Robinson’s Test of Writing Vocabulary Cluster 2 (13.03) Cluster 4 (6.35) Canberra Word Test Cluster 1 (11.27) Cluster 3 (8.21)
7.2.7 DISCUSSION: CLUSTER ANALYSES OF LITERACY ASSESSMENT
TASKS MAY/JUNE YEAR 1
Overall results in the May/June period of Year 1 showed students were increasing their knowledge and understanding of literacy after approximately five months of instruction in school. A summary of results for all Variable Sets, A, B and C is presented in Table 178. This summary provides a means by which the thesis
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 367
question, ‘How do child, home and school factors relate to literacy development in the first year of school’ can be addressed.
Table 178
Cluster Analyses With Literacy Assessment Tasks May/June of Year 1
Literacy Assessment Variable Set A Variable Set B Variable Set C Tasks May Year 1 (from CAP- (from (from Sutherland Preschool ) environmental Phonological Awareness print & letter factors in Preschool) knowledge factors in Preschool) CAP – (8 factors) WL = .57 WL = .65 WL = .72 p = .09 p = .16 p = .17
Letter Knowledge 2 (1 p = .02 p < .01 p =.01 factor)
Phonological WL = .84 WL = .91 WL = .72 Awareness (2 factors) p = .07 p = .33 p < .01 onset identification, final phoneme production, rhyme production < .01;
syllable counting, rhyme detection <.01
Print Knowledge task p =.01 p < .01 p =.04 (score)
Robinson Test of p < .01 p < .01 p < .01 Writing Vocabulary (score)
Canberra Word Test p < .01 p < .01 p = .04 (score)
This overview revealed different ways the Variable Sets predicted results in
May/June of Year 1. Some combinations of student capabilities are more predictive
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 368
than others, but nonetheless there is not one ‘best’ pathway. There are dimensions of knowledge and these interplay in complex ways.
It was found that results from the Concepts About Print Test were not predicted by any of the three Variable Sets. Some results were predicted by all Variable Sets and these include letter knowledge, print knowledge task, Robinson’s Test of Writing
Vocabulary and Canberra Word Test. Phonological awareness results were predicted only by Variable Set C which was devised from phonological awareness task results in preschool. Thus it can be seen that each of the Variable Sets, A, B and C has the potential to predict results achieved by students five months after they commence school. As results from literacy measures in November of Year 1 are reported the predictive capabilities of each of the Variable Sets are tested further.
Results from the final Literacy Assessment Task measures conducted with students in November of Year 1 are described in Chapter Eight. These tasks completed in one-to-one interviews with students included reading aloud from graded texts.
Results from Parent Survey 2 (see Appendix S) and Teacher Checklist 2 (see
Appendix V) are also reported. All of these data were collected in November of
Year 1.
Chapter 7: Reducing Dimensions: Relationships in the Year 1 (May/June) Data 369
CHAPTER EIGHT
DESCRIBING AND CORRELATING YEAR 1 (NOVEMBER)
DATA
The final administration of Literacy Assessment tasks took place in November (see
Appendix O) as students in the sample were completing Year 1. These results are
reported in this chapter. Results from Parent Survey 2 (see Appendix S) and Teacher
Checklist 2 (see Appendix V) also are reported. These results address the question
‘How do child, home and school factors relate to literacy development in the first year of school?’
The shaded row on the following schema indicates the current section.
CHAPTER CONTENT DESCRIPTION Chapter 4: Describing and Correlating Preschool Data 4.1 Parent Survey 1 (November of Preschool) 4.2 Teacher Checklist 1 (March of Year 1) 4.3 Literacy Assessment 1 (November of Preschool). 4.4 Teacher Survey (March of Year 1). Chapter 5: Reducing dimensions: Relationships in the Preschool Data 5.1 Factor Analysis of Parent Survey 1;Teacher Checklist 1; Literacy Assessment 1. 5.2 Cluster Analysis based on Literacy Assessment 1 – Preschool period. Chapter 6: Describing and Correlating Year 1 (May) Data 6.1 Literacy Assessment 2 (May of Year 1) Chapter 7: Reducing dimensions: Relationships in the Year 1 (May) Data 7.1 Factor Analyses: Literacy Assessment 2 7.2 Cluster Analysis of Literacy Assessment 2 Chapter 8: Describing and Correlating Year 1 (November ) Data 8.1 Literacy Assessment 3 (November of Year 1) 8.2 Parent Survey 2 8.3 Teacher Checklist 2 Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 9.1 Factor Analysis: Parent Survey 2; Teacher Checklist 2; Literacy Assessment 3 9.2 Cluster Analysis of Literacy Assessment 3
Chapter 8: Describing and Correlating Year 1 (November) Data 370 8.1 LITERACY ASSESSMENT TASKS: YEAR 1 (NOVEMBER)
8.1.1 INTRODUCTION
Students completed four assessment tasks and an oral reading during a one-to-one interaction in November of Year 1 (see Appendix O). Some follow-up retesting was done and new tests were included to assess students’ increasing literacy development. The following were conducted:
1. Ohio Word Test – 20 words - List A (Pinnell, Lyons, Young & Deford, 1987);
2. Dictation and Spelling Test (Clay, 1985, pp.38-40);
3. Concepts About Print Test version ‘Stones’ (Clay, 1979) (retest - alternative
text);
4. Sutherland Phonological Awareness Test (6 subtests)
Subtest 3: Rhyme Production (retest);
Subtest 5: Final Phoneme Identification (retest);
Subtest 6: Segmentation 2;
Subtest 7: Blending;
Subtest 8: Initial Phoneme Deletion;
Subtest 9: Segmentation 2;
5. Oral Reading and miscue analysis using six levels of children’s literature based
on Reading Recovery classification (Department of Education, Victoria, 1997).
8.1.2 OHIO WORD TEST
The Ohio Word Test (Pinnell, Lyons, Young and DeFord, 1987) List A (see
Appendix P) was used. The same method as that used with the Canberra Word Test
Chapter 8: Describing and Correlating Year 1 (November) Data 371 was utilised. Words were shown on a card that was uncovered gradually for students to read the words one at a time. The test was constructed using high frequency words from the Dolch Word List (Dolch, 1948). Results are presented in
Table 179.
Table 179
Scores for Ohio Word Test November of Year 1
Score Total School A School B School C Total 113 43 33 37 Mean 15.55 15.79 13.63 17.00 SD 4.21 4.24 4.91 2.68
An analysis of variance was conducted to examine significant effects. A significant school effect was shown [F(2,110) = 6.17, p=<.01]. This occurred between Schools
C and B with School C scoring a significantly higher mean score. A significant gender effect also occurred with girls outperforming boys [F(1,111) = 3.79, p = .05].
No significant age effect was shown (p= .43).
8.1.3 DICTATION AND SPELLING TEST
Two sentences were dictated (Clay, 1985) and students wrote these down. Form D and Form E were used. Sentences for Form D were “The bus is coming. It will stop here to let me get on.” Sentences for Form E were “The boy is riding his bike. He can go very fast on it” (pp. 38-40). Two scores were allocated, the first was for every correct sound correspondence, and a second was for the correct spelling of words within the sentences. In schools A and C class teachers administered the dictation test in class, while in School B, students completed the dictation task during the one-
Chapter 8: Describing and Correlating Year 1 (November) Data 372 to-one interaction with research assistants. Maximum scores for the tests were as follows: Dictation 1 = 37; Spelling 1 = 12; Dictation 2 = 37; Spelling 2 = 13.
Results are shown in Table 180.
Table 180
Scores for Dictation and Spelling Tests in November of Year 1
Score Total School A School B School C Dictation 1 Mean 31.88 31.87 29.87 33.67 SD 5.52 5.96 6.17 3.61 Spelling 1 Mean 9.59 9.58 8.60 10.48 SD 2.39 2.55 2.35 1.92 Dictation 2 Mean 31.9 32.94 28.84 33.59 SD 5.71 5.03 7.09 3.73 Spelling 2 Mean 8.88 9.38 7.72 9.40 SD 2.49 2.36 2.71 2.11
Multivariate analysis of variance for dictation and spelling examined differences. A significant school effect occurred [Wilk’s Lambda = .80, MFV (8,206) = 2.91; p =
<.01; eta-squared = .10]. One effect occurred between School C and School B for all dictation and spelling tests with School C scoring a significantly higher mean score each time. A second significant school effect was shown between School A and
School B for Dictation 2 and Spelling 2 with School A scoring significantly higher mean scores. No significant age effect (p = .33) or gender effect (p = .51) was shown.
Chapter 8: Describing and Correlating Year 1 (November) Data 373 8.1.4 CONCEPTS ABOUT PRINT TEST (3)
The Concepts About Print Test (Clay, 1985) was used for the third time in
November of Year 1, but for this time an alternative text version Stones (Clay,
1979c) was used. Results are shown in Table 181.
Table 181
Scores for Concepts About Print Test November of Year 1
Score Total School A School B School C Total 113 43 33 37 Mean 18.67 18.76 18.18 19.00 SD 2.27 2.50 2.40 1.81
Univariate analysis of variance examined performance data for significant effects due to school, age and gender. Results showed no significant school (p = .30), age (p
= .67) or gender (p = .97) effect. Results also indicate that after a year of literacy instruction the test is not suitable as a ceiling effect occurs.
8.1.5 SUTHERLAND PHONOLOGICAL AWARENESS TEST
Six subtests of the Sutherland Phonological Awareness test were used with students in November of Year 1. Two subtests, ‘rhyme production’ and ‘final phoneme identification’ were retests while four other subtests ‘segmentation 1’, ‘blending’,
‘initial phoneme deletion’ and ‘segmentation 2’ were used for the first time. Results are shown in Tables 182 – 187
Chapter 8: Describing and Correlating Year 1 (November) Data 374 Table 182
Scores for Rhyme Production November of Year 1
Scores Total School A School B School C Total 113 43 33 37 Mean 3.56 3.60 3.63 3.45 SD 0.83 0.65 0.92 0.93
Table 183
Scores for Final Phoneme Identification November of Year 1
Score Total School A School B School C Total 113 43 33 37 Mean 3.72 3.69 3.72 3.75 SD 0.65 0.55 0.71 0.65
Table 184
Results for Segmentation 1 November of Year 1
Score Total School A School B School C Total 113 43 33 37 Mean 3.51 3.67 3.48 3.35 SD 0.79 0.52 0.93 0.88
Table 185
Results for Blending November of Year 1
Score Total School A School B School C Total 113 43 33 37 Mean 3.90 3.95 3.81 3.91 SD 0.40 0.21 0.63 0.27
Table 186
Results for Initial Phoneme Deletion November of Year 1
Score Total School A School B School C Total 113 43 33 37 Mean 3.32 3.25 2.87 3.43 SD 1.21 1.19 1.40 0.98
Chapter 8: Describing and Correlating Year 1 (November) Data 375 Table 187
Results for Segmentation 2 November of Year 1
Score Total School A School B School C Total 113 43 33 37 Mean 1.96 2.25 2.00 1.59 SD 1.52 1.39 1.67 1.48
Multivariate analysis of variance examined significant effects. Results showed no significant effect due to school (p = .20); age (p = .38) or gender (p = .41).
8.1.6 ORAL READING: ACCURACY AND COMPREHENSION
Five different texts were selected for students to read aloud. Reading Recovery levels of texts (Department of Education, Victoria, 1997) were used and texts classified at level 1, 6, 12, 16, and 24 were used (see Appendix Q). Level 12 was an information text. The remaining texts were fiction. The chosen texts were:
Level 1: The Farm (Butler, 1989a) and A Toybox (Butler, 1989b);
Level 6: Having a Picnic (Garland, 1995);
Level 12: If you like Strawberries, don't read this book (Noonan, 1993);
Level 16: First Flight (McPhail, 1987);
Level 24: Grandpa's Cardigan (Watson, 1993).
Each student commenced by reading the Level 6 text, Having a Picnic by Sarah
Garland. A level 6 text was chosen after examining the current practices relating to the Year 2 Diagnostic Net, an initiative of the Department of Education Queensland where a miscue analysis is used for diagnostic purposes in May of Year 2
(Department of Education Queensland, 1995). It was found that a Level 16 text is
Chapter 8: Describing and Correlating Year 1 (November) Data 376 used at that time and thus to use a Level 6 text in November of Year 1 should prove to be an easy reading task for the majority of students.
Trials with students of the same age had shown that an 85% accuracy rate was a suitable level to determine if a Year 1 student could then be asked to attempt to read the Level 12 text. An 85% accuracy cut-off level was applied for this study. Students progressed through the remaining selected texts as long as they could maintain 85% reading accuracy. If the student did not read that accuracy level on the Level 6 text, then the simpler Level 1 texts The Farm and A Toybox were read by the child.
Students were asked comprehension questions following the reading (see Appendix
R). Results showing the highest level of text read by the students in each setting and presented as a percentage are shown in Figure 23.
Chapter 8: Describing and Correlating Year 1 (November) Data 377 60
50
40
30
Percent Preschools 20 Preschool A
10 Preschool B
0 Preschool C read read read re re ad ad t t t e e e te te xt x x x x t t t t lev le le le lev v v v 1 6 1 1 2 2 6 4
Levels of texts read in November of Year 1
Figure 23. Highest level of text read by the students in each setting in November of Year 1 as a percentage of each school population
Univariate analysis of performance indicated a significant school effect [F(2,110) =
4.58, p = .01] with the students in School C having read significantly more higher level texts than students from School B. Further univariate tests for age (p = .65) and gender ( p = .24) revealed no significant effect.
Univariate analysis for reading accuracy was conducted to ascertain significant differences. Results showed a significant school effect for accuracy scores for reading the Level 6 text, Having a Picnic [F(2,109) = 5.63, p <.01]. When multiple comparisons were examined, results showed a significant difference occurred between School C and School B with School C achieving a higher mean score for reading accuracy.
Chapter 8: Describing and Correlating Year 1 (November) Data 378
Univariate analyses for accuracy of reading on all texts with age showed no significant effects occurred. Univariate analysis of accuracy of reading and gender showed one significant difference occurred for the Level 1 text Toybox [F(1,37) =
7.92, p = <.01]. Results showed male students scored a higher mean score of 95.20% compared to the female students mean score of 88.53%.
Univariate analysis for comprehension revealed no significant school or age effect on any text. A gender effect was shown for Having a Picnic a Level 6 text [F(1,111)
= 3.89, p = .05] with girls achieving a higher mean score than boys.
8.1.7 SUMMARY
Students increased their knowledge and understanding of literacy after one year of instruction. In relation to the thesis question ‘How do child, home and school factors relate to literacy development in the first year of school,’ the following significant effects are summarised.
Three significant gender effects were found:
• Ohio Word Test, where girls outperformed boys;
• Accuracy of reading Level 1 texts The Farm and A Toybox, where boys
outperformed girls; and
• Comprehension of Level 6 text, Having a Picnic, where girls received a higher
mean score than boys.
Chapter 8: Describing and Correlating Year 1 (November) Data 379 Three significant school effects were shown:
• Ohio Word Test - School C consistently outperformed School B;
• Dictation and Spelling - School C consistently outperformed School B;
• Levels of text read and accuracy of reading with the Level 6 text Having a
Picnic -. School C consistently outperformed School B.
These results showed School C had improved performance compared to data collected in preschool where a significant school effect was shown for four subtests of the Sutherland Phonological Awareness tasks with either School A or School B outperforming School C in each instance. School C began to show improvement in the May/June tests when students significantly outperformed School B in Print
Knowledge tasks using the rhyme Humpty Dumpty and on one subtest (onset identification) of the Sutherland Phonological Awareness Tasks. This improvement, particularly in relation to School B, continued and a significant school effect was shown for several literacy tests in November of Year 1.
No significant age effect for any of the tasks completed by the students was shown.
The next section reports results from Parent Survey 2 (see Appendix S) where parents provided data on their perceptions of the learning characteristics of their children, their literacy progress at the end of Year 1 and current home literacy practices. This survey was completed in November of Year 1.
Chapter 8: Describing and Correlating Year 1 (November) Data 380 The shaded row on the following schema indicates the current section.
CHAPTER CONTENT DESCRIPTION Chapter 4: Describing and Correlating Preschool Data 4.1 Parent Survey 1 (November of Preschool) 4.2 Teacher Checklist 1 (March of Year 1) 4.3 Literacy Assessment 1 (November of Preschool). 4.4 Teacher Survey (March of Year 1). Chapter 5: Reducing dimensions: Relationships in the Preschool Data 5.1 Factor Analysis of Parent Survey 1;Teacher Checklist 1; Literacy Assessment 1. 5.2 Cluster Analysis based on Literacy Assessment 1 – Preschool period. Chapter 6: Describing and Correlating Year 1 (May) Data 6.1 Literacy Assessment 2 (May of Year 1) Chapter 7: Reducing dimensions: Relationships in the Year 1 (May) Data 7.1 Factor Analyses: Literacy Assessment 2 7.2 Cluster Analysis of Literacy Assessment 2 Chapter 8: Describing and Correlating Year 1 (November ) Data 8.1 Literacy Assessment 3 (November of Year 1) 8.2 Parent Survey 2 8.3 Teacher Checklist 2 Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 9.1 Factor Analysis: Parent Survey 2; Teacher Checklist 2; Literacy Assessment 3 9.2 Cluster Analysis of Literacy Assessment 3
8.2 PARENT SURVEY 2
Parent Survey 2 (see Appendix S) was returned by 89.5% of parents. It was analysed
first in relation parents’ perceptions of their children’s personal characteristics and interests, then for home literacy practices and finally for perceived literacy progress of their children at the end of Year 1.
8.2.1 PARENTS’ PERCEPTIONS – CHILDREN’S PERSONAL
CHARACTERISTICS AND INTERESTS
Questions 4 to 9 on Parent Survey 2 related to perceptions of their children’s personal characteristics and interests. Question 4 sought a response relating to
children’s enjoyment of school. Results presented as valid percentages are shown in
Table 188.
Chapter 8: Describing and Correlating Year 1 (November) Data 381 Table 188
Percentage Frequency of Parents’ Perceptions of Children’s Personal Characteristics and Interests in November of Year 1
Survey rating Concentration Memory Attitude to Interest in Interest in school Books Writing Excellent 12.7 33.3 30.4 40.2 30.4 Very Good 39.2 42.2 34.3 37.3 40.2 Good 30.4 17.6 26.5 16.7 15.7 Satisfactory 15.7 5.9 7.8 4.9 11.8 Poor 2.0 1.0 1.0 1.0 2.0
Multivariate analyses for personal characteristics and interests were conducted.
Results showed no significant overall effect for school (p = .73), age (p = .16) or gender (p = .80).
Children’s interest in school at the end of Year 1 was sought from parents and results presented as valid percentages are shown in Table 189.
Table 189
Percentage Frequency of Parents’ Perception of Children’s Enjoyment of School in November of Year 1
Always Sometimes Never Missing Total Preschool A 62.8 23.3 0.0 14.0 43 Preschool B 51.5 36.4 0.0 12.1 33 Preschool C 73.7 21.1 0.0 5.2 38 Total Sample 63.2 26.3 0.0 10.5 114
In the opinion of their parents, the majority of children in this study always enjoyed school. Analysis of variance confirmed no significant difference occurred for school
(p = .22), age (p = .19) or gender (p = .21).
Chapter 8: Describing and Correlating Year 1 (November) Data 382 Parents also were asked to rate their children’s overall academic achievement, in reading and writing. Results are shown as valid percentages are in Table 190.
Table 190
Percentage Frequency of Parents’ Perceptions of Children’s Academic and Literacy Achievements
Children’s achievement Excellent Very Good Good Satisfactory Poor Academic achievement 9.8 56.9 24.5 8.8 0.0
Achievement in reading 18.6 43.1 27.5 10.8 0.0
Achievement in writing 16.7 35.3 35.3 12.7 0.0
Multivariate analysis of variance showed no significant effect occurred for school (p
= .20), age (p = .28) or gender (p = .55).
The remaining questions (13-27) on Parent Survey 2 are for reading to Year 1 children at home, types of texts used for reading, listening to children reading aloud and assisting with school reading and writing tasks at home. These results are reported in the following sections.
8.2.2 PARENTS’ PERCEPTIONS - HOME LITERACY PRACTICES
8.2.2.1 Reading to Year 1 Children at Home
Ninety-nine percent of parents indicated they read to their Year 1 child in November of Year 1. One parent from School C reported not reading to his/her child. Similar responses were indicated for the question relating to if the child enjoyed the reading sessions. All but one parent recorded a positive response. Data also were collected for who reads to Year 1 children at home. Categories for collating this information
Chapter 8: Describing and Correlating Year 1 (November) Data 383 were: mother, father, older brother or sister, grandparent and other. Several members of the family read to the Year 1 child. Results for those who read to Year 1 children at home are shown in Table 191. These are expressed as valid percentages.
Table 191
Percentage Frequency of Parents’ Perceptions of Who Reads to Year 1 Children at Home
Family member Total Preschool A Preschool B Preschool C Mother 92.2 89.2 89.7 97.2 Father 68.6 73 65.5 66.7 Brother or sister 41.2 54.1 27.6 38.9 Grandparent 15.7 18.9 17.2 11.1 Other 5.9 0.0 6.9 11.1
Results for who reads to Year 1 children showed that mother is the person nominated most frequently in all three settings. Father also read to Year 1 children in approximately 70% of households. Older siblings and grandparents also were nominated quite frequently. Multivariate analysis of variance showed no significant difference due to school (p = .19), age (p = .41); or gender (p = .55) for who reads to the Year 1 children.
Parents indicated how often children were read to at home and the amount of time spent for each session. Results are presented in Tables 192 and 193 and expressed as valid percentages.
Chapter 8: Describing and Correlating Year 1 (November) Data 384 Table 192
Percentage Frequency of Parents’ Perceptions of How Often Year 1 Children Are Read to at Home
Reading times Total School A School B School C Never 1.0 0.0 3.4 0.0 Occasionally 5.9 10.8 0.0 5.6 1-2 times /week 10.8 24.3 3.4 2.8 3-4 times /week 26.5 21.6 37.9 22.2 5-6 times/week 24.5 16.2 34.5 25.0 Daily 31.4 27.0 20.7 44.4
Table 193
Parents’ Perceptions of Periods of Time Spent Reading to Year 1 Children at Home
Amount of Total School A School B School C reading time < 5 minutes 2.9 5.4 3.4 0.0 6-10 minutes 34.3 40.5 17.2 41.7 11-15 minutes 39.2 27.0 48.3 44.4 16-20 minutes 14.7 16.2 20.7 8.3 21-25 minutes 5.9 5.4 6.9 5.6 >25 minutes 2.9 5.4 3.4 0.0
Multivariate analysis of variance to examine significant differences in the time spent reading to the Year 1 child at home showed a significant school difference [Wilks’s
Lambda = .89, p = .03]. A comparative examination of results for all school settings revealed that School C parents read significantly more often than parents from
School A. The result for School C vs School A was [Scheffe’s: p = .03]. No significant difference was shown for age (p = .78) or gender (p = .22).
8.2.2.2 Texts in the Home
Parents estimated the number of texts that were suitable for their Year 1 children.
Results expressed as valid percentages are in Table 194.
Chapter 8: Describing and Correlating Year 1 (November) Data 385 Table 194
Parents’ Perceptions of Estimates of the Number of Books at Home suitable for Year 1 Children
Number of books for Year 1 children Total School A School B School C at home About 10 5.9 8.1 3.4 5.6 10-30 30.4 24.3 31.0 36.1 30-50 35.3 35.1 34.5 36.1 >50 28.4 32.4 31.0 22.2
Analysis of variance of these estimates showed no significant difference due to school (p = .65), age (p = .99) or gender (p = .23).
Data were provided relating to types of texts read to Year 1 children at home. Six types were specified. They were story picture books, comics, children’s magazines, puzzle books, factual texts and a category for unspecified texts. Most parents indicated they shared more than one type of text with their children. Results, expressed as valid percentages are shown in Table 195.
Table 195
Parents’ Perceptions of Texts Shared at Home with Year 1 Children
Types of texts Total School A School B School C Picture story books 97.1 100.0 96.6 94.4 Comics 3.9 0.0 3.4 8.3 Children’s magazines 10.8 5.4 6.9 19.4 Puzzle books 20.6 13.5 24.1 25.0 Factual texts 41.2 27.0 48.3 50.0 Other unspecified texts 6.9 0.0 6.9 13.9
Multivariate analysis of variance revealed no significant difference for school (p =
.28), age (p = .88) or gender (p = .11).
Chapter 8: Describing and Correlating Year 1 (November) Data 386 8.2.2.3 Listening to Year 1 Children Read at Home
Listening to Year 1 children read at home was a common practice with ninety-nine percent of parents providing a positive response. Most families indicated more than one person in the family listened to the Year 1 child read. Only one parent from
School C indicated their family did not listen to their Year 1 child. Results shown as valid percentages are presented in Table 196.
Table 196
Parents’ Perceptions of People Who Listen to Year 1 Children Read at Home
Family members Total School A School B School C Mother 92.2 89.2 89.7 97.2 Father 62.7 64.9 65.5 58.3 Brother or sister 27.5 32.4 17.2 30.6 Grandparent 9.8 5.4 17.2 8.3 Other 5.9 0.0 10.3 8.3
Results revealed that Mothers (89% - 97%) mostly listen to their Year 1 children read aloud at home. Fathers (58% - 65%) also listen to reading. Multivariate analysis of variance revealed no significant difference due to school (p = .44), age (p = .22) or gender (p = .51) for listening to Year 1 children read aloud.
Further information provided on Parent Survey 2 included how often Year 1 children read aloud at home and the approximate time for each session. Results shown as valid percentages are presented in Tables 197 and 198.
Chapter 8: Describing and Correlating Year 1 (November) Data 387 Table 197
Parents’ Perceptions of How Often Listening to Year 1 Children’s Reading Occurred at Home
Time spent listening to Total School A School B School C Year 1 children read 5 times /week 81.4 67.6 86.2 91.7 3 times/week 13.7 29.7 6.9 2.8 Once/week 2.0 0.0 3.4 2.8 Rarely 2.9 2.7 3.4 2.8 Never 0.0 0.0 0.0 0.0
Table 198
Parents’ Perceptions of Periods of Time Spent Listening to Year 1 Children Reading at Home
Time spent listening to Total School A School B School C reading 0 minutes 2.0 0.0 3.4 2.8 < 5 minutes 25.5 13.5 48.3 19.4 6-10 minutes 45.1 43.2 41.4 50.0 11-15 minutes 16.7 29.7 3.4 13.9 16-20 minutes 7.8 10.8 0.0 11.1 21-25 minutes 1.0 0.0 0.0 2.8 > 25 minutes 2.0 2.7 3.4 0.0
Multivariate analysis of variance examined significant differences for how often
Year 1 children were heard reading aloud at home and how long was spent for each reading session. A significant overall school effect was found [Wilk’s Lambda = .86, p = <.01]. This effect was shown between School A and School B with the parents from School A listening to their children read for significantly longer sessions
[Scheffe’s: p = <.01]. No significant difference was shown for age (p = .61) or gender (p = .26).
Another home task on which parents reported was assisting their Year 1 children to learn sight words at home. Seventy-four percent of parents indicated they assisted
Chapter 8: Describing and Correlating Year 1 (November) Data 388 their children with this task. Results for each school, expressed as valid percentages are as follows: School A = 83.8%; School B = 65.5%; School C = 72.2%. Analysis of variance showed no significant difference due to school (p = .10), age (p = .59) or gender (p = .56) for assisting with sight words at home.
8.2.2.4 Year 1 Children Writing at Home
The final section of Parent Survey 2 relating to home literacy practices sought information from parents about children’s interest in writing and writing habits at home. Results revealed 95.1% of parents indicated children were interested in writing while just five parents gave a negative response. Two of these parents were from School A, two from School B and one from School C.
Ninety-eight percent of parents indicated their child writes at home. Two parents, one from School A and one from School C reported that their children do not write at home. Parents also provided information about how often their child writes at home and results expressed as valid percentages are shown in Table 199.
Table 199
Parents’ Perceptions of Year 1 Children’s Time Spent Writing at Home
Time spent writing at home Total School A School B School C >Once/week 79.4 75.7 79.3 83.3 Once/week 16.7 24.3 20.7 5.6 Occasionally 3.9 0.0 0.0 11.1
Analysis of variance results for the amount of time children spent writing at home time showed no significant effect for school (p = .49), age (p = .21) or gender (p =
.11).
Chapter 8: Describing and Correlating Year 1 (November) Data 389 8.2.3 PARENTS’ PERCEPTIONS OF CHILDREN’S LITERACY PROGRESS
Parents were asked to provide their perceptions of Year 1 children’s overall academic progress and progress in reading and writing using Likert scale responses.
Ratings used for this question were: excellent; very good; good; satisfactory and poor. Multivariate analysis of variance revealed no significant difference for school
(p = .20) age (p = .28) or gender (p = .55).
8.2.4 SUMMARY
In relation to the thesis question ‘How do child, home and school factors relate to literacy development in the first year of school’ the following significant effects were shown. Data from Parent Survey 2 concerning parents’ perceptions of children’s characteristics, interests and home literacy practices in November of Year
1 were very similar across schools, age groups and gender. Generally, the majority of children:
• Enjoy school;
• Are interested in reading and writing;
• Are read to at home;
• Have literary and non-literary types of texts shared with them at home;
• Read aloud to their parents at home;
• Are given help learning sight words at home and
• Write occasionally at home.
In all of the data collected no significant age or gender effects were found and only two significant school effects were shown. The first was for the amount of time spent reading to Year 1 children at home. A significant difference was found with
Chapter 8: Describing and Correlating Year 1 (November) Data 390 School C parents reading more often than parents from School A. This practice may have had an effect on the improved literacy measures found with School C. The second significant effect occurred for time taken to listen to Year 1 children read aloud. The significant result here showed parents at School A listening more often than parents at School B.
The next section reports results from Teacher Checklist 2 (see Appendix V). Class teachers completed this instrument in November of Year 1. Data firstly examined teachers’ perceptions of students’ class conduct in relation to concentration, application to tasks, personal organisation and ability to follow directions. The second set of data provided teachers’ perceptions of students’ progress in literacy.
8.3 TEACHER CHECKLIST 2
Teacher Checklist 2 (see Appendix V) was completed by 10 of the 11 Year 1 teachers with one teacher from School A not completing the checklist. Thirteen students were in this teacher’s class.
Chapter 8: Describing and Correlating Year 1 (November) Data 391 The shaded row on the following schema indicates the current section.
CHAPTER CONTENT DESCRIPTION Chapter 4: Describing and Correlating Preschool Data 4.1 Parent Survey 1 (November of Preschool) 4.2 Teacher Checklist 1 (March of Year 1) 4.3 Literacy Assessment 1 (November of Preschool). 4.4 Teacher Survey (March of Year 1). Chapter 5: Reducing dimensions: Relationships in the Preschool Data 5.1 Factor Analysis of Parent Survey 1;Teacher Checklist 1; Literacy Assessment 1. 5.2 Cluster Analysis based on Literacy Assessment 1 – Preschool period. Chapter 6: Describing and Correlating Year 1 (May) Data 6.1 Literacy Assessment 2 (May of Year 1) Chapter 7: Reducing dimensions: Relationships in the Year 1 (May) Data 7.1 Factor Analyses: Literacy Assessment 2 7.2 Cluster Analysis of Literacy Assessment 2 Chapter 8: Describing and Correlating Year 1 (November ) Data 8.1 Literacy Assessment 3 (November of Year 1) 8.2 Parent Survey 2 8.3 Teacher Checklist 2 Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 9.1 Factor Analysis: Parent Survey 2; Teacher Checklist 2; Literacy Assessment 3 9.2 Cluster Analysis of Literacy Assessment 3
Two different scales for teachers’ responses were included on the checklist. The first scale (excellent, very good, good, satisfactory and variable) was used to rate students’ conduct in class and the second scale (excellent, very good, good, satisfactory, somewhat slow and little development to date) was used for items relating to literacy progress and handwriting development.
8.3.1 TEACHERS’ PERCEPTIONS OF STUDENTS’ CONDUCT IN CLASS:
NOVEMBER YEAR 1
Results for teachers’ perceptions of students’ conduct in class reported as valid percentages are shown in Table 200.
Chapter 8: Describing and Correlating Year 1 (November) Data 392 Table 200
Teachers’ Perceptions of Class Conduct in November of Year 1
Survey Rating Concentration Application to Personal Following Tasks Organisation Instructions Excellent 17 18 15 16 Very Good 30 28 32 33 Good 26 28 30 27 Satisfactory 11 16 14 17 Variable 16 10 9 7
Multivariate analysis of variance results showed no significant difference due to school (p = .28), age (p = .15) or gender (p = .11).
8.3.2 TEACHERS’ PERCEPTIONS OF STUDENTS’ LITERACY PROGRESS:
NOVEMBER OF YEAR 1
Year 1 teachers ranked the following literacy-related items on the checklist using the scale (excellent, very good, good, satisfactory, somewhat slow, little development to date).
Results expressed as valid percentages are shown in Tables 201 and 202.
Table 201
Teachers’ Perceptions of Literacy Progress in November of Year 1 (A)
Survey Rating Interest in Progress in Letter Sight Word Reading Reading Recognition. Vocabulary. Excellent 21 20 26 32 Very Good 39 30 36 24 Good 23 27 26 22 Satisfactory 12 12 10 10 Somewhat Slow 5 11 2 12 Little Dev. to Date 0 0 0 0
Chapter 8: Describing and Correlating Year 1 (November) Data 393 Table 202
Teachers’ Perceptions of Literacy Progress in November of Year 1 (B)
Survey Rating Sound Symbol Interest in Text Writing Handwriting Development Writing Development Excellent 22 17 12 13 Very Good 34 30 28 25 Good 30 32 29 27 Satisfactory 11 14 21 25 Somewhat Slow 3 7 10 10 Little Dev. to 0 0 0 0 Date
Multivariate analysis of variance examined teachers' perceptions of literacy progress to ascertain if significant differences occurred due to school, age or gender. Results showed a significant school effect [Wilks’s Lambda = .56, MFV(16,109) = 3.70; p =
<.01; eta-squared = .24]. Post hoc analysis of variance revealed that significant differences occurred between School A and School C for all three writing variables.
Teachers from School A ranked all writing variables more highly than teachers in
School C. No significant effect was shown for age (p = .63) or gender (p = .57).
8.8.3 SUMMARY
In relation to the thesis question ‘How do child, home and school factors relate to literacy development in the first year of school?’ significant effects found in the data are now summarised. No significant differences were found across schools, age groups or gender for class conduct in November of Year 1. Similar results occurred for teachers’ perceptions of literacy progress with one significant school effect only being shown for interest in writing, text writing development and handwriting where
School A showed significantly higher rankings from teachers than School C.
Chapter 8: Describing and Correlating Year 1 (November) Data 394 Comparing results to Teacher Checklist 1 (see Appendix U) completed in March of
Year 1, it was found that differences occurred. On Teacher Checklist 1 significant gender differences were perceived by teachers for application to tasks and personal organisation with girls perceived more highly. A second significant gender effect was found for handwriting where teachers once again perceived girls more highly than boys. Significant school effects also were shown on Teacher Checklist 1 for six of the eight literacy related items and these were:
• Interest in reading - School C > School A
• Progress in reading - School B > School A; School C > School A
• Sight word development - School C > School A
• Sound/symbol development - School C > School A
• Interest in writing - School B > School C; School A > School C
• Text writing - School B > School C; School A > School C.
Gender differences relating to students’ class conduct as perceived by teachers early in Year 1 have not been maintained at the end of Year 1. No teacher-perceived gender differences for class conduct or literacy-related development were evident in
November of Year 1. Significant school effects relating to reading shown in March of Year 1 also were not maintained by the end of the Year 1. One significant school effect was maintained and this related to writing with School C teachers continuing to perceive interest in writing and text writing at a lower level than teachers from
School A.
Chapter 8: Describing and Correlating Year 1 (November) Data 395 Principal Component Analyses (PCA) and Cluster Analyses relating to Parent
Survey 2, Teacher Checklist 2 and Literacy Assessment Task measures completed in
November of Year 1 are now examined in Chapter 9.
Chapter 8: Describing and Correlating Year 1 (November) Data 396 CHAPTER NINE
REDUCING DIMENSIONS: RELATIONSHIPS IN THE YEAR 1
(NOVEMBER) DATA
Principal Component Analysis (PCA) was conducted on data gathered in November of Year 1. These analyses enabled the examination of underlying factors that may exist within responses to Parent Survey 2 (see Appendix S), Teacher Checklist 2 (see
Appendix V) and Literacy Assessment measures gathered from students in
November of Year 1 (see Appendix O). Responses on Parent Survey 2 and Teacher
Checklist 2 provided a second set of background factors and these enabled further analyses by correlation to examine relationships among sets of factors. Finally,
Variable Sets A, B and C (derived from responses on preschool literacy measures) are examined with factors from Parent Survey 2, Teacher Checklist 2 and Literacy
Assessment measures gathered in November of Year 1 to determine if relationships exist. Questions ‘How do child, home and school factors relate to literacy development in the first year of school’ and ‘How do students’ literacy knowledge and understanding of it in the prior to school period predict students’ literacy achievement during the first year of school?’ are addressed in this chapter.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 397
The shaded row in the following schema indicates the current section.
CHAPTER CONTENT DESCRIPTION Chapter 4: Describing and Correlating Preschool Data 4.1 Parent Survey 1 (November of Preschool) 4.2 Teacher Checklist 1 (March of Year 1) 4.3 Literacy Assessment 1 (November of Preschool). 4.4 Teacher Survey (March of Year 1). Chapter 5: Reducing dimensions: Relationships in the Preschool Data 5.1 Factor Analysis of Parent Survey 1;Teacher Checklist 1; Literacy Assessment 1. 5.2 Cluster Analysis based on Literacy Assessment 1 – Preschool period. Chapter 6: Describing and Correlating Year 1 (May) Data 6.1 Literacy Assessment 2 (May of Year 1) Chapter 7: Reducing dimensions: Relationships in the Year 1 (May) Data 7.1 Factor Analyses: Literacy Assessment 2 7.2 Cluster Analysis of Literacy Assessment 2 Chapter 8: Describing and Correlating Year 1 (November ) Data 8.1 Literacy Assessment 3 (November of Year 1) 8.2 Parent Survey 2 8.3 Teacher Checklist 2 Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 9.1 Factor Analysis: Parent Survey 2; Teacher Checklist 2; Literacy Assessment 3 9.2 Cluster Analysis of Literacy Assessment 3
9.1 FACTOR ANALYSES: NOVEMBER YEAR 1
Factor analyses for Literacy Assessment task measures from November of the
Preschool year and May/June of Year 1 have been conducted and reported in order
to examine the underlying elements within these results. Analysing these data with background factors obtained from parents and teachers also enabled more complex analyses to be conducted. Principal Component Analysis (PCA) of data from
Literacy Assessment Tasks (November Year 1), Parent Survey 2 and Teacher
Checklist 2 are reported. Since orthogonal factors are sought in this exercise,
Varimax Rotation is considered appropriate in that it permits factor axes to move to
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 398
highest-load positions, thus enabling the development of new factors for interpretation, while retaining factorial orthogonality, and thus clarity of interpretation.
9.1.1 BACKGROUND FACTORS: PARENT SURVEY 2
Parent Survey 2 provided data relating to parents’ perceptions of children’s personal characteristics and interests, home literacy practices and perceptions of children’s literacy progress at the end of Year 1.
9.1.1.1 Background Factor: Parents’ Perceptions of Children’s Characteristics:
November of Year 1
Items 5–9 on Parent Survey 2 were subjected to Principal Component Analysis
(PCA). A single factor solution with an eigenvalue greater than one and accounting for 62% of the variance is shown in Table 203.
Table 203
Rotated Component Matrix for the Single-factor Solution Parents’ Perceptions - Child Characteristics 2
Parent survey items Parents’ perception – child’s characteristics and interests 2 Child's interest in writing .84 Child's interest in books .80 Child's attitude to school .78 Child's concentration .75 Child's memory .74
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 399
The heaviest weightings in the single factor come from the child’s interest in writing and interest in books. Similar weightings of almost the same level come from the other three variables namely, child’s attitude to school, concentration and memory.
The single factor is named ‘Parents’ perception - child characteristics and interests
2’.
9.1.1.2 Background Factor: Parents’ Perceptions of Literacy Progress
Items 8 to 12 on Parent Survey 2 sought parents’ perceptions of children’s interest in and progress with reading and writing. Responses on these items were submitted to
Principal Component Analysis (PCA). A single factor solution known as ‘Parents’ perceptions - child’s literacy progress’ was shown. This factor with an eigenvalue greater than one and accounting for 71% of the variance is shown in Table 204.
Table 204
Rotated Component Matrix for the Single-factor Solution for Parents’ Perceptions - Children’s Literacy Progress
Parent survey items Parents’ perceptions – children’s literacy progress Child's achievement in writing .87 Child's achievement in reading .86 Child's interest in writing .83 Child's overall academic achievement in school .82 Child's interest in books .82
Each component contributed almost equally to the factor.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 400
9.1.1.3 Background Factors: Parents’ Perceptions of Home Literacy Practices
Responses to items relating to home literacy practices were submitted to Principal
Component Analysis (PCA). A six-factor solution with eigenvalues greater than one and accounting for 67% of the variance occurred and is shown in Table 205.
Table 205
Rotated Component Matrix for Parents’ Perceptions of Home Literacy Practices Derived from Parent Survey 2
Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6 Mother listens to child read .87 -.13 -.16 Mother reads to child .68 .27 -.12 How often child reads aloud .68 -.34 .10 -.18
Siblings listen to child read .88 Sibling reads to child .85 .14 .12
Father listens to child read .87 -.11 .13 Father reads to child .10 .11 .84 -.21
Child writes at home .82 How often child writes at home .11 .75 -.11
Time spent reading at home -.14 .81 Time spent in each session reading at .11 .80 .15 home
Someone helps child with sight words -.10 -.15 -.20 -.78 How often the child is read to at home -.27 -.10 -.16 .12 .61 Number books at home for Year 1 -.17 -.17 -.19 .46 child
The rotated component matrix revealed the item weightings for each factor. These weightings are:
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 401
• Factor 1: Heavy weightings on mother’s role in reading to and listening to the
child read and how often the child reads at home. This factor is known as
‘Mother reading factor’.
• Factor 2: Heavy weightings on siblings’ role in reading to and listening to the
child read. This factor is known as ‘Sibling reading factor’.
• Factor 3: Heavy weightings on fathers’ role in listening to and reading with his
children. This factor is known as ‘Father reading factor’.
• Factor 4: Heavy weightings on writing at home and how often this is done. This
factor is known as ‘Parents’ perceptions - home writing 2’.
• Factor 5: Heavy weighting on the number of reading sessions each week and the
amount of time spent in for each session. This factor is known as ‘Time reading -
home’.
• Factor 6: Weighs on how often the child is read to at home. This factor is known
as ‘Book practices – home’.
9.1.2 BACKGROUND FACTORS: TEACHER CHECKLIST 2
Teacher Checklist 2 (see Appendix V) sought information from teachers in
November of Year 1. This information related to students’ conduct in class and progress in literacy-related skills.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 402
9.1.2.1 Background Factor: Teachers’ Perceptions of Students’ Class Conduct
The Principal Component Analysis (PCA) is reported in relation to teachers’ perceptions of students’ conduct in class. A single factor solution accounting for
90% of the variance is shown in Table 206.
Table 206
Rotated Component Matrix for Teachers’ Perceptions - Class Conduct 2
Teacher Checklist Item Teachers’ perceptions – class conduct 2 Child's concentration .95 Follows instructions .95 Application to tasks .94 Personal organisation .94
The component matrix revealed a high and almost equal weighting for each of the items contributing to the single factor solution. This factor is known as ‘Teachers’ perception of child conduct 2’.
9.1.2.2 Background Factor: Teachers’ Perceptions of Students’ Literacy
Progress
Principal Component Analysis (PCA) was conducted in relation to teachers’ perceptions of students’ progress in literacy. A single factor solution accounting for
79% of the variance occurred and is shown in Table 207.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 403
Table 207
Rotated Component Matrix for Teachers’ Perceptions - Literacy Progress
Teacher Checklist Items Teachers’ perceptions – literacy progress Sound symbol knowledge .93 Development in letter recognition .92 Estimated progress in reading .91 Knowledge of sight words .88 Text writing development .85 Interest in reading .85 Interest in writing .82
The component matrix for teachers’ perceptions of students’ literacy progress revealed a heavy weighting on sound symbol knowledge, letter recognition, progress in reading and knowledge of sight words. Weightings of a slightly lesser degree were found for text writing development, interest in reading and interest in writing.
This factor is named ‘Teachers’ perception - literacy progress’.
Correlations of background factors derived from Parent 2 and Teacher Checklist 2 are now reported. These correlations enable the examination of relationships between data provided by parents and teachers in November of Year 1.
9.1.3 CORRELATIONS OF BACKGROUND FACTORS
Pearson’s correlation of background factors was carried out to examine significant relationships. The following factor correlations are reported:
• Parents’ perceptions of child characteristics with teachers’ perceptions of
students’ class conduct;
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 404
• Parents’ perceptions of literacy progress with teachers’ perceptions of literacy
progress;
• Parents’ perceptions of home literacy practices with teachers’ perceptions of
literacy progress.
Correlations of parents’ perceptions of child characteristics (i.e. a factor score derived from concentration, memory, interest in books and writing and attitude to school) with teachers’ perceptions of class conduct (i.e. a factor score derived from concentration, application to tasks, personal organisation and ability to follow instructions) showed a significant negative correlation of -.33 which was significant at the .01 level. This means that parents and teachers perceived students’ personal learning characteristics as being different in home and school contexts.
When comparing parents’ perceptions of literacy progress with teachers’ perceptions of literacy progress an even larger significant negative correlation of -.44 which was significant at the .01 level occurred. These results are unexpected, but can be understood if it is considered that parents are judging their own child’s progress only and teachers have the opportunity of judging a student’s progress in the context of a much larger class group. When considering the relationship between factors derived from parents’ perceptions of home literacy practices with teachers’ perceptions of literacy progress towards the end of Year 1, no significant relationship was shown.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 405
These unexpected results occurring with teachers’ perceptions prompted further examination of correlations with background factors. The following correlations were examined:
• Teachers’ perceptions of students’ class conduct with teachers’ perceptions of
literacy progress;
• Parents’ perceptions of child characteristics with parents’ perceptions of literacy
progress;
• Teachers’ perceptions of class conduct with parents’ perceptions of child
characteristics;
• Teachers’ perceptions literacy progress with parents’ perceptions literacy
progress;
• Mother and father socio-economic family background factors (described in
Chapter 5) with teachers’ perceptions of literacy progress;
• Mother and father socio-economic background factors (described in Chapter 5)
with parents’ perceptions of literacy progress. These correlations are shown in
Table 208.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 406
Table 208
Significant Correlations of Background Factors from November of Year 1
Background Teachers Teachers’ Parents’ Parents’ Father SES factors perceptions - perceptions perceptions perceptions – class conduct literacy child literacy 2 progress characteristic progress s Teachers’ 1.00 perceptions – class conduct
Teachers’ .72** 1.00 perceptions – literacy progress
Parents’ -.33** -.36** 1.00 perceptions child characteristic s
Parents’ -.32** -.44** .87** 1.00 perceptions – literacy progress
Father SES -.09 -.15 .18 .22* 1.00 ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed)
It was found that three significant positive correlations existed. The first was between teachers’ perceptions of class conduct and literacy progress with a result of
.72. This result indicated that teachers perceive students who are successfully developing literacy skills are also well organised in class, can follow directions and apply themselves to tasks. Similar results occurred with the background factor ‘class conduct’ from Teacher Checklist 1. These results were reported in Chapter 5.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 407
The second significant positive correlation occurred for parents’ perceptions of child characteristics and parents’ perceptions of literacy progress (.87). The third positive correlation occurred for Father SES factor and parents’ perceptions of literacy progress .22. These results indicated that both parents and teachers perceived children with positive child learning characteristics were also progressing best with literacy learning. Parents’ perceptions also indicated a relationship between father
SES and literacy progress. A sample scatterplot depicting parents’ perceptions of literacy progress and parents’ perceptions of child characteristics is shown in Figure
24.
2
1
0
-1
-2 Parents' perception - children's literacy progress -3 -4 -3 -2 -1 0 1 2
Parents' perceptions of child characteristics Nov. Year 1
Figure 24. Positive correlation of parents’ perception of literacy progress with parents’ perceptions of child characteristics
Negative correlations occurred four times and each of these occurred between teachers’ perceptions and parents’ perceptions. This result indicated parents’ and
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 408
teachers’ perceptions were in fact of the opposite order. All correlations between parents’ perceptions and teachers’ perceptions hold opposite views when it comes to child characteristics and perceptions of literacy progress. A sample scatterplot showing the correlation between teachers’ perceptions of literacy progress and parents’ perceptions of literacy progress is shown in Figure 25.
2
1
s literacy progress 0
-1
perception - children' -2 Parents' -3 -2 -1 0 1 2 3
Teachers' perception - literacy progress Nov Year 1
Figure 25. Negative correlation of teachers’ perception of literacy progress with parents’ perception of literacy progress
This sample scatterplot shows the negative correlation of -.44. One hypothesis to explain this result is that parents are making a judgment about one child’s literacy whereas teachers on the other hand, make judgments about literacy progress after examining a class of students of a similar age performing a range of tasks. These results indicated parents’ perceptions and teachers’ perceptions are of the opposite
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 409
order. An examination of the correlation between parents’ perceptions and teachers’ perceptions of literacy progress and the results of literacy tasks late in Year 1 is included in the next section along with factor analyses derived from with Literacy
Assessment Tasks 3 that were completed in November of Year 1.
9.1.4 PERFORMANCE FACTORS: LITERACY ASSESSMENT TASKS YEAR 1
(NOVEMBER)
The final Literacy Assessment Tasks with the students were completed in November of Year 1. As described in Chapter 8 the tasks included:
1. Ohio Word Test – 20 words - List A (Pinnell, Lyons, Young & Deford, 1987);
2. Dictation and Spelling Test (Clay, 1985, pp.38-40);
3. Concepts About Print Test version ‘Stones’ (Clay, 1979) (retest alternative text);
4. Sutherland Phonological Awareness Test (6 subtests)
Subtest 3: Rhyme Production (retest);
Subtest 5: Final Phoneme Identification (retest);
Subtest 6: Segmentation 2;
Subtest 7: Blending;
Subtest 8: Initial Phoneme Deletion;
Subtest 9: Segmentation 2;
5. Oral Reading and miscue analysis using six Reading Recovery levels of
children’s literature (Department of Education, Victoria, 1997).
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 410
Responses on selected tasks were subjected to Principal Component Analysis in order to examine underlying factors that may exist. This Analysis was successfully conducted with Concepts About Print Test, Sutherland Phonological Awareness Test and the Dictation/Spelling tasks. The remaining two Literacy Assessment Tasks,
Ohio Word Test and the highest level of text read orally by the students also were subjected to correlation analyses with background factors derived from Parent
Survey 2 and Teacher Checklist 2.
9.1.4.1 Performance Factors: Concepts About Print Test
Students completed the Concepts About Print Test for the third time in November of
Year 1 using the alternative version of the children’s text, Stones (Clay, 1979c). An examination of the test scores revealed that a ceiling effect occurred for Items 1, 2,
3, 4, 5, and 7 and so these items were omitted from the Principal Component
Analysis. The analysis showed a seven-factor solution with eigenvalues greater than one and accounting for 62% of the variance. The rotated component matrix is shown in Table 209.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 411
Table 209
Rotated Component Matrix for Concepts About Print in November of Year 1
CAP Item Factor 1 Factor 2 Factor 3 Factor 4 Factor 5 Factor 6 Factor 7 CAP 14 .79 .09 -.08 .01 -.11 -.07 .01 CAP13 .78 .04 .13 .19 .24 .13 .01 CAP12 .67 .07 .17 -.12 .01 .04 .04
CAP22 .05 .78 .04 -.01 -.08 -00. .06 CAP19 .12 .77 .11 .06 -.15 -.05. .01
CAP24 .08 -.21 .65 .15 -.21 .11 -.21 CAP9 -.02 .26 .65 -.08 .09 -.12 .19 CAP20 .20 .30 .63 .12 .14 .06 -.07 CAP6 .02 -.24 .51 .15 .11 .36 .25
CAP21 -.03 .08 .14 .77 .06 -.09 .01 CAP23 .04 -.03 .03 .76 -.14 .04 .07
CAP11 -.12 -.04 .25 .02 .69 -.19 -.40 CAP10 .10 -.14 -.02 -.12 .67 .05 .19
CAP16 .14 .41 -.24 .31 .41 .24 -.05
CAP8 -.01 -.08 .06 -.12 -.03 .83 -.14 CAP15 .35 .21 .05 .35 .02 .46 .09
CAP17 .16 .01 .01 .22 .06 -.21 .68 CAP18 .35 -.16 -.08 .31 -.02 -.24 -.49
The above table shows how the factors derived from CAP have been formed. Each factor is now named and the loading of each is summarised.
• Factor 1: ‘ordering letters and words’ loads on items 14, 13 and 12;
• Factor 2: ‘identifying letters and words’ loads on items 22 and 19;
• Factor 3: ‘print knowledge’ loads on items 24, 9, 20 and 6;
• Factor 4: ‘letter concept’ loads on items 21 and 23;
• Factor 5: ‘left and right sequencing’ loads on items 11 and 10;
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 412
• Factor 6: ‘inverted picture recognition’ loads on items 8 and 15;
• Factor 7: ‘punctuation’ loads on item 17 and negatively on item 18.
9.1.4.2 Correlations: Background Factors and Concepts About Print Test
Pearson's correlation of the November background factors, factor scores derived from Concepts About Print and school, age and gender were conducted to ascertain if any significant relationships exist. Results showed three significant positive correlations and three significant negative correlations and these are shown in Table
210.
Table 210
Significant Correlations for Concepts About Print in November of Year 1
CAP factors Mother Father Teachers’ Parents’ SES SES perceptions perceptions factor factor – literacy - literacy progress progress CAP factor 1:ordering letters and words -.08 .12 -.31** .18 CAP factor 2: identifying letters and -.07 -.06 -.30** .08 words CAP factor 4:letter concept .13 .87 -.14 .23* CAP factor 5: left and right sequencing .22* .12 -.27** .15 CAP factor 7: punctuation .02 .21* .05 .14 ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed)
Significant positive correlations occurred for CAP factor 4 with parents’ perceptions of literacy progress, CAP factor 5 with mother SES factor and CAP factor 7 with father SES factor. A sample scatterplot is shown in Figure 26 for parents’ perceptions of literacy progress with ‘letter concept’ factor.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 413
2
1
0 ildren's literacy progress
-1
-2 Parents' perception - ch -3 -5 -4 -3 -2 -1 0 1 2
Concepts About Print - CAP Factor 4 Nov Year 1
Figure 26. Positive correlation of parents’ perceptions of literacy progress with CAP factor ‘letter concept’
All three significant negative correlations are shown with teachers’ perceptions of literacy progress and these occurred with CAP factor 1 ‘ ordering letters and words’,
CAP factor 2 ‘ identifying letters and words’, and CAP factor 5 ‘left and right sequencing’. Once again teachers’ perceptions showed a significant negative correlation with aspects of the students’ results on Literacy Assessment Tasks and again confirm teachers’ predictions are in fact the opposite of those findings devised from the students’ results on the CAP test in November of Year 1. A sample scatterplot shown in Figure 27 depicts the correlation of teachers’ perception of literacy progress with CAP factor 1 ‘ordering letters and words’.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 414
1 3 ear ov. Y
2 ess N ogr
acy pr 1
0 students' liter
-1 ception - s' per -2 -2 -1 0 1 2 3 Teacher Concept About Print CAP Factor 1 - ordering letters and words
Figure 27. Negative correlation of teachers’ perception – literacy progress and CAP
‘ordering letters and words’ factor
The next section examines factor scores derived from Sutherland Phonological
Awareness Test conducted in November of Year 1.
9.1.4.3 Performance Factors: Sutherland Phonological Awareness Test
Students completed six subtests from the Sutherland Phonological Awareness Test in November of Year 1. Two subtests, rhyme production and final phoneme identification, were retested while four other subtests, segmentation one and two, blending, and initial phoneme deletion were used for the first time.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 415
Principal Component Analysis was conducted to examine underlying factors. The analysis showed a three-factor solution accounting for 69% of the variance. Results are shown in Table 211.
Table 211
Rotated Component Matrix for Sutherland Phonological Awareness in November of Year 1
Phonological Awareness Subtests Component 1 2 3 Blending .83 .01 .09 Rhyme Production .83 -.00 .02 Initial phoneme deletion .08 .89 -.07 Final Phoneme Identification -.09 .74 .36 Segmentation1 -.06 -.09 .85 Segmentation 2 .23 .18 .67
Results showed:
• Factor one loads heavily on subtests for blending and rhyme production and is
named ‘blending rhyme production’;
• Factor two loads heavily on subtests initial phoneme deletion and final phoneme
identification and is named ‘phoneme deletion and identification’;
• Factor three loads on the two subtests for segmentation and is known as
‘segmenting’.
Correlations of Sutherland Phonological Awareness factors with background factors from Parent Survey 2 and Teacher Checklist 2 are now reported.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 416
9.1.4.4 Correlations: Background Factors and Sutherland Phonological
Awareness Test Factors
Pearson’s correlation of November background factors, Sutherland Phonological
Awareness factors, school, age and gender were conducted. Results shown in Table
212 show three significant positive correlations and one significant negative correlation.
Table 212
Significant Correlations for Sutherland Phonological Awareness Test in November of Year 1
Factors SES father Parents’ Teachers’ factor perceptions - perceptions - literacy progress literacy progress Blending and rhyme production .21* .22* .05 Initial phoneme and deletion and .12 .19* -.35** identification ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed)
The first two positive correlations occurred with blending and rhyme production factor and the correlations were shown with SES father factor and parents’ perceptions of children’s literacy progress. The third positive correlation occurred with initial phoneme deletion and identification factor and it also correlated with parents’ perceptions of children’s literacy progress. Once again it is seen that parents’ perceptions of literacy progress related positively with results achieved by the students in November of Year 1.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 417
The significant negative correlation was shown for initial phoneme deletion and identification factor with teachers’ perception of students’ literacy progress. So once again the only significant negative correlation for Sutherland Phonological
Awareness was shown with teachers’ perceptions of students’ literacy progress.
The next section examines factor analyses for dictation and spelling in order to investigate underlying factors within the scores.
9.1.4.5 Performance Factors: Dictation and Spelling
Two sets of sentences, Form D and Form E were used for dictation (Clay, 1985 pp.
38-40). Sentences for Form D were “The bus is coming. It will stop here to let me get on” and the sentences for Form E were “The boy is riding his bike. He can go very fast on it”. These sentences were read to the students who then wrote them down without assistance from adults. Two scores were allocated, the first for every correct sound correspondence and the second for the correct spelling of words within the sentences. Principal Component Analysis was conducted using all four scores.
Results showed a single factor named ‘spelling and dictation’ was extracted and accounted for 82% of the variance. The components of the factor are shown in Table
213.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 418
Table 213
Component Matrix for Spelling and Dictation Factor in November of Year 1
Spelling and Dictation Tasks Component 1 Dictation Part 1 .91 Dictation Part 2 .91 Spelling Part 1 .90 Spelling Part 2 .88
9.1.4.6 Correlations: Dictation and Spelling
Pearson’s correlation of background factors with ‘spelling and dictation’ factor showed one significant positive correlation and one significant negative correlation and these are presented in Table 214.
Table 214
Significant Correlations For Spelling and Dictation Factor in November of Year 1
Factor Parents’ perceptions of literacy Teachers’ perceptions of progress literacy progress Spelling and dictation .37** -.44** factor
A significant positive correlation is shown for parents’ perceptions of literacy progress and ‘spelling and dictation factor. The scatterplot is shown in Figure 28.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 419
2
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0 ildren's literacy progress
-1
-2 Parents' perception - ch -3 -4 -3 -2 -1 0 1 2
Spelling and dictation Factor November Year 1
Figure 28. Positive correlation of parents’ perception –literacy progress and spelling and dictation factor
A significant negative correlation is shown for teachers’ perceptions of literacy progress. A scatterplot for this correlation is shown in Figure 29.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 420
3
2
1
0
-1
-2
Teachers' perception - literacy progress November Year 1 -4 -3 -2 -1 0 1 2
Spelling and dictation factor - November Year 1
Figure 29. Negative correlation of teachers’ perception –literacy progress and spelling and dictation factor
Once again these results showed parents appear to predict children’s results more accurately than teachers do.
9.1.4.7 Performance Indicator: Reading Texts
Year 1 students read aloud from different levels of text in November. As described in Chapters 3 and 8 five levels of text were chosen and these were texts that had a
Reading Recovery text level. Four fiction texts (Levels 1, 6, 16 and 24) and one non- fiction (Level 12) were selected. Texts used for this task were as follows:
Level 1: The Farm and A Toybox (Butler, 1989a & 1989b);
Level 6: Having a Picnic (Garland, 1995);
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 421
Level 12: If you Like Strawberries, don’t read this book (Noonan, 1993);
Level 16: First Flight (McPhail, 1987);
Level 24: Grandpa’s Cardigan (Watson, 1993);
All students commenced reading the Level 6 text and if 85% reading accuracy was achieved then they proceeded to read the Level 12 text and so on. If students could not read the Level 6 text with 85% accuracy then the Level 1 texts were read. In order to provide a reading rank for each of the students, a rank number was entered into the data. The rank numbers were allocated according to the highest level of text read by each student and were as follows:
Level 1 texts – rank number 1
Level 6 text – rank number 2
Level 12 text – rank number 3
Level 16 text – rank number 4
Level 24 text - rank number 5
9.1.4.8 Correlations: Reading Texts
Pearson’s bivariate correlation of background factors was carried out to examine any significant relationships with Reading Rank. Students’ age, gender, family SES factors, parents’ perceptions and teachers’ perceptions were analysed. Results showed six significant positive correlations and two negative correlations and these are presented in Table 215.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 422
Table 215
Significant Correlations with Reading Rank in November of Year 1
Reading rank Reading rank 1.00 Blending and rhyme production .24* Phoneme deletion and identification .35** Ordering letters and words .49** Spelling and dictation .68** Parents’ perceptions = child characteristics .32** Parents’ perceptions – literacy progress .41** Teachers’ perceptions – class conduct -.37** Teachers’ perceptions – literacy progress -.51**
A consistent pattern of correlation results continues in that significant positive correlations occurred with parents’ perception factors and other factors derived from students’ literacy assessment scores while significant negative correlations occurred with teachers’ perceptions.
9.2 CLUSTER ANALYSES: NOVEMBER YEAR 1
In order to continue to investigate the predictive nature of the literacy tasks of the preschool period, cluster analyses were conducted. Factor scores, described earlier in this chapter were used in the analyses. Variable Set A based on preschool CAP results, Variable Set B based on Environmental Print and Letter Knowledge results in Preschool and Variable Set C based on preschool Phonological Awareness were used again.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 423
Multivariate and univariate analyses were conducted with each of the Variable Sets
A, B and C and with responses on each of the Literacy Assessment Tasks from
November of Year 1. Results for Variable Set A are now reported.
The shaded row in the following schema indicates the current section.
CHAPTER CONTENT DESCRIPTION Chapter 4: Describing and Correlating Preschool Data 4.1 Parent Survey 1 (November of Preschool) 4.2 Teacher Checklist 1 (March of Year 1) 4.3 Literacy Assessment 1 (November of Preschool). 4.4 Teacher Survey (March of Year 1). Chapter 5: Reducing dimensions: Relationships in the Preschool Data 5.1 Factor Analysis of Parent Survey 1;Teacher Checklist 1; Literacy Assessment 1. 5.2 Cluster Analysis based on Literacy Assessment 1 – Preschool period. Chapter 6: Describing and Correlating Year 1 (May) Data 6.1 Literacy Assessment 2 (May of Year 1) Chapter 7: Reducing dimensions: Relationships in the Year 1 (May) Data 7.1 Factor Analyses: Literacy Assessment 2 7.2 Cluster Analysis of Literacy Assessment 2 Chapter 8: Describing and Correlating Year 1 (November ) Data 8.1 Literacy Assessment 3 (November of Year 1) 8.2 Parent Survey 2 8.3 Teacher Checklist 2 Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 9.1 Factor Analysis: Parent Survey 2; Teacher Checklist 2; Literacy Assessment 3 9.2 Cluster Analysis of Literacy Assessment 3
9.2.1 VARIABLE SET A
Variable Set A (devised from CAP in preschool) was examined with literacy task measures completed in November of Year 1. These results provided a means by which students with similar profiles in preschool are examined in relation to their literacy results at the end of Year 1. This procedure enabled an examination of these students to ascertain if they remain consistently in the student clusters over time or if
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 424
relevant capabilities had become reconfigured through a period of instruction and development. These analyses allowed an examination of the predictive nature of the
Variable Sets A, B and C.
Correlations of Variable Set A with Literacy Assessment Tasks (November Year 1) showed three non-significant effects and two significant effects. The non-significant effects were for Concepts About Print (p = .24), Sutherland Phonological Awareness
Tests (p = .41), and Spelling and Dictation (p = .18). Two significant effects for
Ohio Word test and Reading Rank are presented in Table 216.
Table 216
Significant Results for Variable Set A with Literacy Tasks completed in November of Year 1
Factors/Variables F value p value Ohio Word test 2.52 .03 Reading Rank 2.79 .02
Means and standard errors of each significant score (as per Table 216) were examined so that each of the seven student clusters from Variable Set A may be examined more closely. As previously done when examining Variable Set A,
Student Cluster two in which there are only three students has been left out of the analyses. Means and standard errors for results on Ohio Word test are shown in
Table 217.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 425
Table 217
Means and Standard Errors for Variable Set A on Ohio Word Test Measures in November of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.) (Note that student cluster 2 is not in the analysis as the number of students (3) is too small). Student cluster and description N Mean St. Error 1. – print awareness; + awareness of conventions; + 27 14.40 .78 left-right 3. – directionality 15 15.07 1.08 4. ++ print awareness; 24 17.82 .84 5. – awareness of conventions; + directionality; 20 14.46 1.04 6. – starting points; -- left-right; + awareness of 8 13.85 1.53 conventions; + punctuation 7. ++ starting points 17 16.41 .98
Variable Set A predicted students’ ability to read words from a list in November of
Year 1. Student Cluster 4 performed best on Ohio Word test and Student Cluster 6 was the lowest performing group.
A significant relationship was shown for the level of text students could read successfully in November of Year 1 and means and standard errors are shown in
Table 218.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 426
Table 218
Means and Standard Errors for Variable Set A on Reading Rank Measures in November of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.) (Note that student cluster 2 is not in the analysis as the number of students (3) is too small). Student cluster and description N Mean St. Error 1. – print awareness; + awareness of conventions; + left- 27 2.25 .27 right 3. – directionality 15 2.35 .38 4. ++ print awareness; 24 3.56 .30 5. – awareness of conventions; + directionality; 20 2.20 .37 6. – starting points; -- left-right; + awareness of conventions; 8 2.14 .54 + punctuation 7. ++ starting points 17 2.58 .35
Variable Set A predicted the level of texts students could successfully read aloud in
November of Year 1. Student Cluster 4 performed best at reading texts at high levels while Student Cluster 6 was the lowest performing group. These results are consistent with those received for Ohio Word Test.
9.2.2 DISCUSSION OF VARIABLE SET A ASSOCIATIONS
Variable Set A related significantly to two of the five Literacy Assessment task measures from November in Year 1. These two measures included reading words from a list (Ohio Word Test) and reading different levels of text. This demonstrated the general predictive nature of the cluster analysis based on Concepts About Print from the preschool period.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 427
Another significant finding was that the original clustering based on CAP (Variable
Set A) showed students who displayed a high level of skills in preschool still maintained those skills in May of Year 1 and November of Year 1. In Chapter 5 it was shown how Student Cluster 4 scored significantly better than other student clusters on nine out of ten measures of preschool literacy. In Chapter 7, Student
Cluster 4 again showed the highest mean scores on all four significant measures in
May/June of Year 1 and now it has been shown that Student Cluster 4 performed best on both significant measures for literacy tasks in November of Year 1.
The lowest performing students from the preschool period continued to perform least well. In the preschool period, Student Cluster 6 performed least well on five measures, Student Cluster 5 performed least well on three measures and Student
Cluster 3 performed least well on two measures. In Chapter 7, when May/June results were reported it was found that Student Clusters 5 and 3 performed least well and in November of Year 1 Student Cluster 6 performed least well on both measures. An overview of these results is shown in Table 219.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 428
Table 219
Variable Set A (based on CAP in Preschool) With Significant Preschool, May/June and November Year 1 Literacy Assessment Measures Depicting the Highest and Lowest Cluster Mean Scores
Factor Highest Mean Lowest Mean Result Result LITERACY ASSESSMENT – PRESCHOOL Environmental print (contextual) Cluster 4 (.77) Cluster 6 (-.56) Phonological awareness (rhyme, onset, final Cluster 4 (1.00) Cluster 5 (-.68) phoneme) Print Knowledge Task (read words) Cluster 4 (.41) Cluster 5 (-.44) Print Knowledge Task (sequencing text) Cluster 4 (.56) Cluster 6 (-.76) Print Knowledge Task (start reading) Cluster 3 (.39) Cluster 5 (-.30) Robinson test of writing vocabulary Cluster 4 (3.52) Cluster 6 (.00) Canberra word recognition test Cluster 4 (3.13) Cluster 3 (.21) Reading words in all tests Cluster 4 (12.48) Cluster 3 (3.00) Literal comprehension Cluster 4 (6.95) Cluster 6 (5.28) Inferential comprehension Cluster 4 (6.65) Cluster 6 ( 4.85) LITERACY ASSESSMENT – MAY YEAR 1 letter knowledge and identification Cluster 4 (.42) Cluster 5 (-.63) print knowledge task Cluster 4 (16.00) Cluster 5 (12.66) Robinson’s test of writing vocabulary Cluster 4 (14.52) Cluster 3 (6.57) Canberra word test Cluster 4 (11.87) Cluster 5 (7.00) LITERACY ASSESSMENT – NOVEMBER YEAR 1 Ohio Word test Cluster 4 (17.82) Cluster 6 (13.85) Reading rank Cluster 4 (3.56) Cluster 6 (2.14)
It can be seen that Variable Set A devised from CAP in preschool demonstrated predictive qualities relating to students’ literacy achievement at the end of Year 1.
The group of students who performed best in preschool (Student Cluster 4) has maintained a high performance level until the end of the Year 1 by achieving the highest means score for 15 of the possible 16 significant measures. Similarly, the least well performing groups (Student Clusters 6, 5 and 3) continued to perform least well at the end of Year 1. Their performances are as follows:
• Student Cluster 6 – performed least well on 7 of the 16 measures;
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 429
• Student Cluster 5 – performed least well on 6 of the 16 measures;
• Student Cluster 3 performed least well on 3 of the 16 measures.
The profiles of the high achieving and low achieving clusters are now revisited in order to examine the skills these students demonstrated in preschool that enabled prediction of their literacy skills after one year of instruction.
Variable Set A was calculated from factors underpinning Concepts About Print Test results in preschool. The ISODATA routine split the students into seven groups accounting for 60.4% of the variance. An examination of the cluster mean vectors
(reported in Chapter 5) enabled a description of each cluster to be made. The highest performing and lowest performing student cluster profiles are shown in Table 220.
Table 220
Profiles of the Best Performing Cluster and Least Well Performing Clusters in Variable Set A
Cluster Profile Best Performing Student Cluster ++ print awareness Cluster 4 (24 students)
Least well performing Student Clusters -- starting points; --left and right Cluster 6 (8 students) progression + awareness of conventions; + punctuation
Cluster 5 (20 students) -- awareness of conventions; + directionality
Cluster 3 (15 students) -- directionality
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 430
Student Cluster 4 demonstrated very high understanding of print awareness. This factor showed a loading from eight items in the Concepts About Print test in the preschool period and was reported fully in Chapter 5. This factor included knowledge of changes in letter order, changes in word order and recognising reversed words e.g. ‘was’ and ‘saw’. Students demonstrating high levels of understanding of this factor also were able to locate pairs of upper and lower case letters, one-to-one correspondence when pointing to words and knowing where to begin reading. Thus it can be seen that a broad range of skills was included in demonstrating high levels of knowledge for print awareness.
The profile for the least well performing clusters is not so well defined. Clusters 6 and 5 were notably the poorest performers, these are examined more closely. There does not appear to be similarity within the profiles of these two clusters. In fact, there appears to be some contradiction in relation to awareness of conventions as cluster 6 demonstrated knowledge above the mean and Cluster 5 demonstrated knowledge well below the mean. The factor ‘Awareness of conventions’ was devised from weightings of three items on the Concepts About Print test. These items included knowing print contains a message, understanding the concept of first and last and knowing the meaning of a full stop.
Student Cluster 6 demonstrated poor understanding of capital letters, identifying first and last letters and knowing the left page is read before the right. Student Cluster 5
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 431
experienced difficulty with knowing where to start reading, understanding left to right progression when reading and understanding the return sweep when reading several lines of print on a page. Thus, Student in both clusters demonstrated poor knowledge and understanding of some concepts associated with learning to read and these were not the same concepts for both clusters. This finding again demonstrates the complexity of learning to be literate and that there is no single pathway of development.
9.2.3 VARIABLE SET B
Analyses of variance were carried out with Variable Set B (derived from
Environmental Print and Letter Knowledge at Preschool) to examine relationships with factors derived from literacy assessment tasks completed by the students in
November of Year 1. Results showed two non-significant effects and three significant effects for Variable Set B. The non-significant effects were for CAP (p =
.10) and Sutherland Phonological Awareness Test (p = .20). Significant effects were shown for ‘Spelling and dictation’ factor, Ohio Word test score and reading rank.
These results are presented in Table 221.
Table 221
Significant Results for Variable Set B with Literacy Tasks Completed in November Year 1
Factors/variables F value p value Spelling and dictation factor 5.12 <.01 Ohio Word test 4.64 <.01 Reading rank 7.63 <.01
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 432
Means and standard errors of each score/factor were examined where significance occurred so that each of the six student clusters from Variable Set B could be examined more closely. As previously done when examining Variable Set B,
Student Cluster 6 where there are only 4 students has been left out of the analyses.
Means and standard errors for ‘Spelling and dictation’ factor are shown in Table
222.
Table 222
Means and Standard Errors for Variable Set B on Spelling and Dictation Measures in November of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.) (Note that student cluster 6 is not in the analysis as the number of students (4) is too small). Cluster and description N Mean St. error 1. + contextualised environmental print tasks. 41 -.26 .15 2. – contextualised environmental print tasks; 37 -.30 .16 - decontextualised environmental print tasks; - letter knowledge 3. ++ decontextualised environmental print tasks. 8 .55 .35 4. ++ decontextualised environmental print tasks; ++ letter 9 .78 .33 knowledge; + contextualised environmental print tasks. 5. ++ letter knowledge. 15 .61 .24
Variable Set B predicted students’ ability to spell words correctly when given a dictation task. Student Cluster 4 performed best on the spelling/dictation task in
November of Year 1 and Student Cluster 2 was the lowest performing group. A significant relationship was shown also for Ohio Word test scores and means and standard errors are shown in Table 223.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 433
Table 223
Means and Standard Errors for Variable Set B on Ohio Word Test Measures in November of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.) (Note that student cluster 6 is not in the analysis as the number of students (4) is too small). Cluster and description N Mean St. error 1. + contextualised environmental print tasks. 41 14.30 .63 2. – contextualised environmental print tasks; 37 14.75 .69 - decontextualised environmental print tasks; - letter knowledge 3. ++ decontextualised environmental print tasks. 8 16.62 1.39 4. ++ decontextualised environmental print tasks; ++ letter 9 19.22 1.31 knowledge; + contextualised environmental print tasks. 5. ++ letter knowledge. 15 17.80 1.01
Variable Set B predicts students’ ability to spell words given as a dictation task in
November of Year 1. Student Cluster 4 showed the highest mean score while
Student Cluster 1 was the lowest performing group. The third task where statistical significance was shown for Variable Set B was for Reading rank devised from the level of text students successfully read aloud in November of Year 1. Means and standard errors are shown in Table 224.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 434
Table 224
Means and Standard Errors for Variable Set B on Reading Rank Measures in November of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.) (Note that student cluster 6 is not in the analysis as the number of students (4) is too small). Cluster and description N Mean St. error 1. + contextualised environmental print tasks. 41 2.41 .21 2. – contextualised environmental print tasks; 37 1.90 .23 - decontextualised environmental print tasks; - letter knowledge 3. ++ decontextualised environmental print tasks. 8 2.75 .47 4. ++ decontextualised environmental print tasks; ++ letter 9 4.33 .44 knowledge; + contextualised environmental print tasks. 5. ++ letter knowledge. 15 3.46 .34
Variable Set B predicted students’ ability to spell words in November of Year 1.
Student Cluster 4 performed best on this task with Student Cluster 2 performing least well.
9.2.4 DISCUSSION OF VARIABLE SET B ASSOCIATIONS
Variable Set B related significantly to three of the five Literacy Assessment task measures from November of Year 1. Four measures were spelling, reading words in a list and reading texts of different levels.
Another significant finding is that the original clustering based on Environmental
Print and Letter Knowledge (Variable Set B) showed students who displayed a high level of skills in preschool maintained those skills in May of Year 1 and November of Year 1. In Chapter 5 it was shown how Student Cluster 4 scored significantly
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 435
better than other student clusters on six out of nine significant measures of preschool literacy. On all four significant measures for Variable Set B in May of Year 1,
Student Cluster 4 showed the highest mean score. In November of Year 1 Student
Cluster 4 performed best on all three significant measures.
The lowest performing students in preschool were still performing least well in
May/June and November of Year 1. In Chapter 5 it was shown that when preschool literacy measures were analysed with Variable Set B, Student Cluster 2 demonstrated the lowest achievement on seven of the nine significant measures in preschool. This student cluster continued to demonstrate the lowest performance and this was shown for all four significant measures with Variable Set B. In November of Year 1, Student Cluster 2 performed least well on two of the three measures. An overview of these results is shown in Table 225.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 436
Table 225
Variable Set B (Based on Environmental Print and Letter Knowledge) With Significant Literacy Factors and Scores Depicting the Highest and Lowest Mean Scores in Preschool, May/June and November of Year 1
Factor Highest result / Lowest result / Mean score Mean score LITERACY ASSESSMENT TASKS – PRESCHOOL CAP - print awareness Cluster 4 (.73) Cluster 2 (-.36 CAP - awareness of conventions Cluster 5 (.61) Cluster 1 (-.40) CAP - starting points Cluster 5 (.71) Cluster 2 (-.30) Sutherland Phonological Awareness (rhyme, onset, final Cluster 4 (.96) Cluster 3 (-.75) phoneme) Print Knowledge Task – reading words Cluster 4 (1.49) Cluster 1 (-.32) Print Knowledge Task – sequencing text Cluster 5 (.40) Cluster 2 (-.53) Robinson’s test of writing vocabulary Cluster 4 (5.89) Cluster 2 (.59) Canberra word test Cluster 4 (7.55) Cluster 2 (.31) Reading words in all literacy tasks Cluster 4 Cluster 2 (2.47) (25.67) LITERACY ASSESSMENT TASKS – MAY YEAR 1 Letter knowledge and identification Cluster 4 (.83) Cluster 2 (-.39) Print knowledge task Cluster 4 Cluster 2 (13.31) (16.77) Robinson’s test of writing vocabulary Cluster 4 Cluster 2 (7.31) (16.77) Canberra word test Cluster 4 Cluster 2 (7.71) (14.00) LITERACY ASSESSMENT TASKS – NOVEMBER YEAR 1 Spelling and dictation Cluster 4 (.78) Cluster 2 ( -.30) Ohio Word test Cluster 4 Cluster 1 (14.30) (19.22) Reading rank Cluster 4 (4.33) Cluster 2 (1.90)
Variable Set B demonstrated predictive qualities relating to students’ literacy achievements in November of Year 1. Student Cluster 4 maintained high performance throughout the longitudinal study from Preschool to the end of Year 1 and this is demonstrated on 13 of the 16 significant measures. Student Cluster 5 performed best for the remaining three significant results. The least well performing
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 437
groups Student Clusters 2, 3 and 1 continued to perform poorly with Student Cluster
2 performing least well on 12 of the 16 significant measures.
The profiles of the high achieving and low achieving clusters are now revisited in order to examine the skills these students demonstrated in preschool that have enabled prediction of their literacy skills after one year of instruction.
Variable Set B was calculated from factors underpinning Environmental Print and
Letter Knowledge results in Preschool. The ISODATA routine split the students into six groups accounting for 77% of the variance. An examination of the cluster mean vectors (reported in Chapter 5) enabled a description of each cluster to be made. The highest performing and lowest performing student cluster profiles are shown in
Table 226.
Table 226
Profiles of the Best Performing Cluster and Least Well Performing Clusters in Variable Set B
Cluster Profile Best Performing Student Cluster ++ decontextualised tasks; Cluster 4 (9 students) ++ letter knowledge; + contextualised tasks.
Least well performing Student Cluster - contextualised tasks; - decontextualised tasks; Cluster 2 (37 students) - letter knowledge.
These profiles demonstrate one cluster where high levels of skills were evident and one cluster where skills were of a lesser degree. The skills demonstrated in this instance related to reading environmental print on grocery items where contextual Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 438
assistance remained and also reading labels where contextual cues had been removed and the words were printed on word cards. The third area where skills were demonstrated involved naming letters, knowing the sounds the letters made and being able to give a word beginning with the sound. The most able students were in
Cluster 4. They demonstrated all of these skills to a high degree. Those in least able cluster demonstrated these skills at levels below the mean.
9.2.5 VARIABLE SET C
Analyses were carried out with Variable Set C (devised from the Sutherland
Phonological Awareness Test administered in preschool) to examine relationships with performances on literacy tasks completed in November of Year 1. Results showed four non-significant effects. These are Concepts About Print test (p = .10);
Spelling and dictation (p = .45); Ohio Word test (p = .62); and Reading rank (p =
.12). One significant result was shown with Phonological Awareness factors [Wilk’s
Lambda = .83, p = .04].
Means and standard errors of each factor are examined where significance occurred so that each of the five student clusters from Variable Set C may be examined more closely. As previously done when examining Variable Set C, Student Cluster 5 in which there are only five students has been left out of the analyses. Means and standard errors for the three factors of phonological awareness derived from
November of Year 1 Literacy Assessment tasks are shown in Tables 227 – 229.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 439
Table 227
Means and Standard Errors for Variable Set C on Blending and Rhyme Production Measures in November of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.) (Note that student cluster 5 is not in the analysis as the number of students (4) is too small). Student cluster and description N Mean St. Error 1. ++ onset identification,; ++ final phoneme identification; ++ 20 .15 .23 rhyme production 2. + syllable counting,; + rhyme detection; + rhyme production 27 .35 .19 3. – onset identification; - final phoneme identification; - rhyme 41 -.11 .16 production 4. – syllable counting; - rhyme detection; - rhyme production 21 -.39 .22
Thus Variable Set C (devised from Sutherland Phonological Awareness in
Preschool) predicted blending and rhyme production measures in November of Year
1. Student Cluster 2 performed best and Student Cluster 4 was the lowest performing group. Significant effects for phoneme deletion and identification are shown in
Table 228.
Table 228
Means and Standard Errors for Variable Set C on Phoneme Deletion and Identification Measures in November of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.) (Note that student cluster 5 is not in the analysis as the number of students (4) is too small). Student cluster and description N Mean St. Error 1. ++ onset identification,; ++ final phoneme 20 -.04 .23 identification; ++ rhyme production 2. + syllable counting,; + rhyme detection; + rhyme 27 .19 .19 production 3. – onset identification; - final phoneme identification; - 41 .08 .16 rhyme production 4. – syllable counting; - rhyme detection; - rhyme 21 -.34 .22 production Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 440
Variable Set C predicted phoneme deletion and identification measures in November of Year 1. The highest performing group was Student Cluster 2 with Student Cluster
4 performing least well. Significant effects were also shown for segmenting. These results are shown in Table 229.
Table 229
Means and Standard Errors for Variable Set C on Segmenting Measures in November of Year 1
(Note that + + = well above the mean; + = above the mean; -- = well below the mean; - = below the mean.) (Note that student cluster 5 is not in the analysis as the number of students (4) is too small). Student cluster and description N Mean St. Error 1. ++ onset identification,; ++ final phoneme identification; ++ 20 .34 .22 rhyme production 2. + syllable counting,; + rhyme detection; + rhyme production 27 .17 .18 3. – onset identification; - final phoneme identification; - 41 -.08 .15 rhyme production 4. – syllable counting; - rhyme detection; - rhyme production 21 -.32 .21
Variable Set C predicted students’ ability to segment words in November of Year 1.
The best performing group was Student Cluster 2 and the least well performing group was Student Cluster 4.
9.2.6 DISCUSSION OF VARIABLE SET C ASSOCIATIONS
Variable Set C related significantly to one of the five Literacy Assessment task measures from November of Year 1. This measure was phonological awareness and included three factors. The factors were ‘blending and rhyme production’, ‘phoneme deletion and identification’ and ‘segmenting’.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 441
Another significant finding was that the original clustering based on Sutherland
Phonological Awareness (Variable Set C) showed students who displayed a high level of skills in preschool (Student Clusters 1 and 2) maintained those skills in
May/June of Year 1 and November of Year 1. The lowest-performing students shown in preschool (Student Clusters 4 and 3) also performed least well in May/June and again in November of Year 1. An overview of these results is shown in Table
230.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 442
Table 230
Variable Set C (Based on Phonological Awareness) with Significant Preschool Literacy Factors and Scores Depicting the Highest and Lowest Mean Scores in Preschool, May/June and November of Year 1.
Factor Highest mean Lowest mean result result LITERACY ASSESSMENT TASKS – PRESCHOOL Environmental print (contextual) Cluster 1 (.55) Cluster 4 (-.32) Letter knowledge and identification Cluster 1 (1.02) Cluster 4 (-.39) Concepts about Print (print awareness) Cluster 1 (1.07) Cluster 4 (-.56) Print Knowledge Task (reading words) Cluster 1 (.93) Cluster 4 (-.38) Print Knowledge Task (sequencing text) Cluster 1 = Cluster Cluster 4 (-.37) 2 (.29) Robinson test of writing vocabulary Cluster 1 (2.61) Cluster 4 (.65) Canberra word test Cluster 1 (3.22) Cluster 3 (.34) Reading words in all literacy tests Cluster 1 (12.50) Cluster 3 (4.07) Literal comprehension Cluster 1 (7.05) Cluster 4 (5.65) LITERACY ASSESSMENT TASKS – MAY YEAR 1 Letter knowledge and identification 2 Cluster 1 (.40) Cluster 4 (-.28) Onset and final phoneme identification and Cluster 2 (.44) Cluster 4 (-.38) rhyme production Syllable counting and rhyme detection Cluster 1 (.41) Cluster 4 (-.60) Print knowledge task Cluster 1 (15.44) Cluster 3(13.68) Robinson’s test of writing vocabulary Cluster 2 (13.03) Cluster 4 (6.35) Canberra word test Cluster 1 (11.27) Cluster 3 (8.21) LITERACY ASSESSMENT TASKS – NOVEMBER YEAR 1 Blending and rhyme production Cluster 2 (.35) Cluster 4 (-.39) Phoneme deletion and identification Cluster 2 (.19) Cluster 4 (-.34) Segmenting Cluster 1 (.34) Cluster 4 (-.32)
Thus, a consistent pattern emerged from the data showing those students who clustered together in preschool because of their high or low level phonological awareness test scores still clustered together in November of Year 1 on their performance of phonological awareness tasks. Student Cluster 1 demonstrates the
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 443
most consistently high level of skills on 14 of a possible 18 of the significant measures. Student Cluster 4 performed least well for 14 of the 18 significant measures.
The profiles of the high achieving and low achieving clusters are now revisited in order to examine the skills these students demonstrated in preschool that enabled prediction of their literacy skills after one year of instruction.
Variable Set C was calculated from factors underpinning Sutherland Phonological
Awareness test results in preschool. The ISODATA routine split the students into five groups accounting for 80.9% of the variance. An examination of the cluster mean vectors (reported in Chapter 5) enabled a description of each cluster to be made. The highest performing and lowest performing Student Cluster profiles are shown in Table 231.
Table 231
Profiles of the Best Performing Cluster and Least Well Performing Clusters in Variable Set C
Cluster Profile Best Performing Student Cluster ++ rhyme, onset & final phoneme. Cluster 1 (20 students)
Least well Performing Student Cluster - rhyme & syllables. Cluster 4 (21 students)
Student Cluster 1 demonstrated a very high level of skill relating to rhyme production, onset identification and final phoneme identification. These skills Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 444
demonstrated students’ ability to isolate phonemes either at the beginning of words or the end of words and to produce rhymes. In contrast, Student Cluster 4 showed skills below the mean for rhyme detection, rhyme production and syllable counting.
Thus it would appear that understanding rhyme and being able to produce rhyming words and detect rhymes has contributed to students’ ensuing literacy skills. Also having the ability to identify and manipulate phonemes at preschool demonstrated students’ early knowledge of phonemes and this has made a positive contribution to literacy development after one year of literacy instruction.
9.2.7 SUMMARY OF CLUSTER ANALYSES PRESCHOOL TO NOVEMBER
YEAR 1
This chapter examined two questions within the thesis.
‘How do child, home and school factors relate to literacy development in the first year of school?’ and
‘How do students’ literacy knowledge and understanding of it in the prior to school period predict students’ literacy achievement during the first year of school?’
Findings from this chapter are now examined in the light of these two thesis questions.
When examining the first question it is essential that the child, home and school factors are identified in order to relate these to students’ literacy development in the first year of school. It was found that while home influences in the data were easily
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 445
identified through home literacy practices defined on Parent Survey 2 and completed in November of Year 1, child and school factors tended to overlap. Child factors included age, socio-economic background and gender (reported in Chapter 8) as well as those traits identified by parents’ perceptions of child characteristics, and parents’ perceptions of literacy progress. School factors included the school attended by the student (reported in Chapter 8) and teachers’ perceptions of class conduct and literacy progress. Teachers’ perceptions of class conduct can also be included as child factors.
The majority of parents in this study perceived their children as showing good to excellent memory skills, concentration skills and interest in school. Parents also perceived their children as being interested in reading and writing. Principal
Component Analysis (PCA) extracted a single factor for parents’ perceptions of child characteristics and a further single factor for parents’ perceived literacy skills.
Results of analyses of these factors revealed a high positive correlation between parents’ perceptions of child characteristics and parents’ perceptions of literacy progress and both of these related positively to students’ scores on literacy tasks in
November of Year 1. Thus child factors as measured in the data, demonstrated a strong influence on children’s literacy development at the end of Year 1.
Principal Component Analysis on home literacy practices extracted a six-factor solution and these factors were analysed with literacy scores and factors from
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 446
November of Year 1. Further analyses with other background factors derived from the Parent Survey 2 and Teacher Checklist 2 showed no significant relationships within the data. Thus home literacy practices in the data collected in November of
Year 1 showed no significant relationship to children’s literacy development at the end of Year 1.
With regard to school factors and their influence on literacy development in
November of Year 1, results showed teachers’ perceptions of class conduct and literacy progress produced a significant negative correlation with students’ measured literacy skills on Literacy Assessment Tasks in November of Year 1. These results showed school influences, as measured in the data, bore little relation to literacy development at the end of Year 1.
The second question ‘How do students’ literacy knowledge and understanding of it in the prior to school period predict students’ literacy achievement during the first year of school’ is now addressed. This question is answered by examining results of cluster analyses. Results showed that students’ skills as measured in November of
Preschool can act as predictors of literacy skills after one year of formal instruction in school. Cluster analyses were completed in three ways using different combinations of results from the preschool period and all Variable Sets A, B and C displayed the predictive nature of the analyses. The strongest predictor was Variable
Set B derived from Environmental Print and Letter Knowledge as it showed a
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 447
significant effect on three measures in November of Year 1. The profile of students in Student Cluster 4, the highest performing cluster, included demonstrating skills well above the mean for decontextualised tasks and letter knowledge and above the mean for contextualised tasks involving print on grocery items.
Home and school factors within the data of this study did not show a significant influence on beginning literacy development in the final period of Year 1. Child factors on the other hand, showed a strong relationship with literacy development.
Literacy achievements in November of Year 1 were predicted by knowledge and understanding of literacy measured in preschool.
Results in this chapter have demonstrated that using factor analyses, multivariate analyses and cluster analyses as a means of predicting students’ literacy growth and development after one year of instruction is possible. All three Variable Sets A, B and C demonstrated predictive capabilities, but the one that showed the most potential, Variable Set B, predicted three from a possible five results in November of
Year 1. This Variable Set was devised from contextual and decontextual factors relating to Environmental Print tasks and Letter Knowledge tasks in the preschool period.
These results also demonstrated there is no ‘best pathway’ or single ‘knowledge factor’ that leads to successful literacy development after one year of instruction.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 448
There are however ‘domains of knowledge’ that interplay in complex ways for individuals who possess unique intrinsic characteristics and partake in a range of personal literacy related- experiences at home and school.
Chapter 9: Reducing Dimensions: Relationships in the Year 1 (November) Data 449
CHAPTER TEN
SUMMARY AND IMPLICATIONS
10.1 FINDINGS
One key question has guided the study, ‘How do young students develop literacy capabilities during the first year of schooling?’ Findings reported in previous chapters are reviewed here and implications drawn for theories of early childhood literacy, research methodology, classroom practice and educational policy.
10.1.1 THE PRIOR-TO-SCHOOL PERIOD
Data gathered from students, parents and teachers in the prior-to-school period were described in Chapter Four. Principal Component Analysis of these data helped in addressing three questions pertinent to the period of literacy development:
‘What knowledge of literacy and understanding of it do students develop in the prior-to-school period?’
‘What aspects of literacy knowledge and understanding do students develop in the prior-to-school period?’
‘How do aspects of students’ literacy knowledge and understanding prior to school relate to one another and students’ background?’
10.1.1.1 Student Data
Preschool students completed a broad range of literacy-related tasks in
November of the preschool year. Tasks included listening comprehension, identification of food products and labels, print awareness, reading and writing
Chapter 10: Summary and Implications 450 words and identifying letters. Analyses of results revealed that some aspects of preschool students’ literacy appeared to be well-established, some were partially understood and some were not understood at all.
Well-established features:
• Recognising food products;
• Recognising labels on food products;
• Comprehending stories;
• Writing own name and naming the letters;
• Recognising letter shapes and configuration;
• Knowing letter names;
• Detecting rhymes in simple words;
• Counting syllables;
• Handling books;
• Knowing directionality of print;
Partially-established features:
• Recognising labels when separated from products;
• Writing words apart from their own names;
• Knowing words starting with particular letters;
• Producing rhyming words;
• Demonstrating knowledge of words that commence with particular sounds.
Little current knowledge:
• Recognising product names printed on cards;
• Knowing letter sounds;
• Identifying onsets;
• Producing final phonemes;
Chapter 10: Summary and Implications 451 • Knowing the function of punctuation marks;
• Knowing letter patterns in common words;
• Knowing the term ‘capital letter’;
• Reading words from lists or texts.
10.1.1.2 Parent Data
Parents completed Parent Survey 1 in November of the preschool year and were asked to provide information relating to their children’s personal learning characteristics and home literacy practices. Generally, parents perceived that:
• Their children had good concentration, memory, interest in books and interest
in writing;
• Younger and middle-age children within the study had greater concentration,
memory, interest in books and interest in writing than older children;
• Girls had greater concentration, interest in books and interest in writing than
boys;
• Boys had better memory than girls.
In relation to parents’ perceptions of home literacy practices:
• Preschool children are read to regularly and are encouraged to take an interest
in writing in almost all (98%) families;
• Girls are more interested in writing than boys;
• Most families visit the local library regularly.
10.1.1.3 Teacher Data
Generally, teachers’ perceptions of students’ adjustment to school, their work habits and progress in literacy were that:
Chapter 10: Summary and Implications 452 • The majority of students adjust well to school and display good work habits;
• Girls, better than boys applied themselves to tasks and personal organisation;
• Children made strong progress in literacy and handwriting although this
varied across schools and for particular aspects of reading and writing;
• Girls have better handwriting than boys;
A particularly noteworthy finding was that teachers’ estimates of young students’ literacy were incommensurate with levels revealed in the formal testing of literacy skills. Teachers’ perceptions were significantly lower.
They were most accurate when applied to students’ book-handling skills and making estimates of home literacy practices. They were least accurate regarding children’s knowledge of environmental print, ability to write their own names, ability to write words, and knowledge of letter names.
10.1.2 REDUCING DIMENSIONS IN THE PRESCHOOL PERIOD
Principal Component Analyses were conducted on Preschool Literacy
Assessment Tasks, Parent Survey 1 and Teacher Survey 1. These were reported in Chapter Five and addressed the following two questions:
‘How do child, home and school factors relate to literacy development in the first year of school?’
‘How do students’ literacy knowledge and understanding of it in the prior-to- school period predict students’ literacy achievement during the first year of school?’
Chapter 10: Summary and Implications 453 Fourteen factors were derived from the Literacy Assessment tasks completed in preschool. A total of eleven background factors also formed, five from parents’ perceptions, four from teachers’ perceptions and two from parents’ education and occupation levels (SES). These factors along with school, age and gender were analysed to investigate relationships.
There were no school effects. One positive effect was shown for each of the following:
• Age - for phonological awareness factor ‘rhyme and syllables’ (.22*);
• Gender – CAP factor ‘awareness of conventions’ (23*);
• Mothers’ SES – for phonological awareness factor ‘rhyme, onset, final
phoneme’ (.22*).
Five positive effects were shown for Fathers’ SES:
• Contextual environmental print factor (.20*);
• Decontextual environmental print factor (.20*);
• Letter Knowledge factor (.26**);
• Awareness of Conventions (.27**);
• Reading words factor from Print Knowledge task (.26**);
• Rhyme and Syllable factor from phonological awareness task (.32**).
Results of correlations of background factors with literacy performance factors from preschool revealed:
• Thirteen significant positive correlations with parents’ perceptions;
• Twenty-three significant negative correlations with teachers’ perceptions.
Chapter 10: Summary and Implications 454 These results indicated parents’ perceptions were more accurate than those of the teachers. It was found that teachers judged students’ literacy progress on personal
“good student” characteristics including ability to concentrate, application to tasks, personal organisation and ability to follow directions and not on literacy performance measures. While perhaps related in a tangential way to how well students would concentrate and apply themselves to literacy learning in an organised way, none of the criteria was as directly literacy related as those that parents had used.
Cluster Analyses with preschool measures were described in Chapter Five. Three
Variable Sets were derived. These were Variable Set A from Concepts About
Print factors; Variable Set B from Environmental Print and Letter Knowledge factors and Variable Set C from Sutherland Phonological Awareness factors.
Students with similar performance profiles in preschool were grouped together.
This allowed comparable multivariate profiles of performance to become visible and enabled trials for predicting students’ literacy achievement throughout Year
1 to be undertaken.
10.1.3 LITERACY DEVELOPMENT AFTER FIVE MONTHS AT SCHOOL
In May/June of Year 1 a second battery of tests was administered to measure students’ literacy performance. A number of these tests were retest measures.
These data were reported in Chapter Six. Principal Component Analysis also was used to examine underlying dimensions. These analyses were reported in Chapter
Seven. Cluster analyses of the three variable sets with May/June factors were
Chapter 10: Summary and Implications 455 also reported in Chapter Seven. These chapters addressed the two questions shown on page 450.
Measures of literacy performance in May/June of Year 1 revealed the following:
Children Writing Own Name
• Almost all students wrote their name;
• Approximately two thirds of students wrote given and surname.
• Approximately one third wrote given name only;
Writing Words
• Almost all students wrote words;
• Approximately half the students wrote 7 words or fewer;
• The mean score for writing words was 9.1;
• Three-letter words were the most common words written;
• No school or age effect was shown for the task;
• A gender effect was shown with girls writing significantly more words than
boys;
Knowledge of Letters – Lower case (28 items)
• Mean score for naming letters was 24;
• Mean score for knowing letter sounds was 22;
• Mean score for providing words for a particular sound was 21;
• A significant school effect shown for knowing letter sounds;
• A significant gender effect shown for letter names (girls > boys);
• No significant effect shown for age.
Chapter 10: Summary and Implications 456 Concepts About Print Test (24 items)
• Similar mean scores were shown for each school with an overall mean score
of 16.7;
• No significant effect was shown for school, age or gender.
Reading Words from a List (15 words)
• Mean score of 9.3;
• No school, age or gender effect shown.
Listening Comprehension (10 questions)
• Mean score of 8;
• No school, age or gender effect shown.
Print Awareness (17 items)
• Mean score of 14.5;
• A significant school effect was shown;
• No age or gender effect shown.
Phonological Awareness (5 subtests – 4 tasks in each subtest)
• Mean scores for subsets: onset identification (3.8); rhyme detection (3.7);
syllable counting (3.2); final phoneme production (3.1); rhyme production
(2.8);
• No significant age or gender effect shown;
• A significant school effect shown for one subtest only (onset identification);
Chapter 10: Summary and Implications 457 10.1.4 REDUCING DIMENSIONS IN MAY/JUNE OF YEAR 1
Principal Component Analyses were conducted May/June Literacy Assessment
Tasks. These analyses investigated underlying dimensions within the data, were reported in Chapter Seven and addressed the same questions (see p. 450).
Eleven factors were derived from Literacy Assessment tasks completed by students in May/June of Year 1. These factors were correlated with the 11 previously-devised background factors, school, age, gender, mother SES and father SES factors to ascertain relationships. One positive effect was shown for:
• School – for CAP factor ‘quotation marks and line sequencing’ (.19*);
• Mother SES - for CAP factor ‘concept of a word’ (.25*).
Two positive effects were shown for:
• Father SES – for CAP factor ‘place to start reading’ ( .21*) and Phonological
Awareness factor ‘syllable counting and rhyme detection’ (.22*).
Further results with parents’ perceptions revealed eight significant positive correlations while teachers’ perceptions showed nine significant negative effects.
Analyses with Variable Sets A, B & C were carried out to examine if these were capable of predicting results in May/June of Year 1. It was found that results from the Concepts About Print Test were not predicted by any of the three
Variable Sets. Performances on Letter knowledge, Print Knowledge Task,
Robinson’s Test of Writing Vocabulary and Canberra Word Test were predicted by all Variable Sets. Phonological awareness results were only predicted by
Variable Set C which was devised from phonological awareness task results in preschool. Thus it can be seen that each of the Variable Sets A, B and C showed
Chapter 10: Summary and Implications 458 potential for predicting results achieved by students five months after they commence school.
10.1.5 LITERACY DEVELOPMENT AFTER ONE YEAR AT SCHOOL
Data were gathered from students, parents and teachers in November of Year 1 and these were reported in Chapters Eight and Nine. Principal Component
Analyses helped to address the questions listed on page 450.
10.1.5.1 Student Data
Students’ measures of literacy performance at the end of Year 1 revealed:
Concepts About Print
• Mean score overall for CAP was 18.7 for 24 items;
• No significant school, age or gender effect shown;
• Test no longer suitable as a ceiling effect occurred.
Reading Words (20 items)
• Mean score of 15.5 was shown for the total group;
• No age effect occurred;
• A school effect shown (School C > School B);
• A gender effect shown (girls > boys).
Spelling Words
• Sound correspondences (dictation) mean scores for the total group were 31.9
from a possible 37 for both Dictation tasks 1 and 2;
• Spelling mean scores overall were 9.6 from a possible score of 12 and 8.9
from a possible score of 13;
Chapter 10: Summary and Implications 459 • Two significant school effects shown with School C > School B on all four
tasks and School A > School B on Dictation task 2 and Spelling Task 2;
• No significant age or gender effect shown.
Phonological Awareness (6 subtests – 4 tasks in each subtest)
• Mean scores for subsets: blending (3.9); final phoneme identification (3.72);
rhyme production (3.56); segmentation 1 (3.51); initial phoneme deletion
(3.32); segmentation 2 (1.96);
• No significant school, age or gender effect shown.
Reading Levelled texts (Reading Recovery levels 1, 6, 12, 16, 24)
• Highest level of text read shown as a percentage for the total group: Level 1
(28%); Level 6 (34%); Level 12 (9%); Level 16 (5%); Level 24 (23%).
• A school effect shown (School C > School B);
• No significant age or gender effect shown;
• Reading accuracy showed a school effect for the Level 6 text (School C >
School B);
• No significant age effect shown;
• One significant gender effect shown with boys scoring a higher mean than
girls on level 1 texts;
• Comprehension of texts revealed no significant school or age effect;
• One gender effect shown for comprehension of the Level 6 text (girls >
boys).
Chapter 10: Summary and Implications 460 10.1.5.2 Parent Data
Parents completed a second survey in November of Year 1 and their perceptions of children’s personal characteristics, literacy achievements and home literacy practices were:
• More than 80% of parents perceived their children had good, very good or
excellent concentration and interest in writing;
• More than 90% of parents perceived their children had good, very good or
excellent memory, attitude to school and interest in books.
• No significant effect was shown for school, age or gender in relation
children’s attitudes and characteristics;
• More than 85% of parents perceived their children were achieving good, very
good or excellent results for reading and writing achievement;
Home literacy practices:
• All except for one parent indicated they read to their Year 1 children in
November of Year 1;
• Family members nominated for reading to Year 1 children included: mother
(92%); father (69%); sibling (41%).
• No significant difference was shown for school, age or gender for who reads
to Year 1 children;
• One third of families read daily to their Year 1 children;
• A quarter of families read 3-4 times and a further quarter read 5-6 times each
week;
• Approximately 40% of families read to Year 1 children for 11-15 minute
periods and a further 34% read for 6-10 minute periods;
Chapter 10: Summary and Implications 461 • A significant school effect was shown for the amount of time spent reading to
children (School C > School A);
• No significant difference (school, age or gender) was shown for the number
of children’s books at home;
• Mother, father and siblings read to the Year 1 children and no significant
difference was shown for school, age or gender.
10.1.5.3 Teacher Data
Year 1 teachers completed a second checklist in November of Year 1 and data related to the children’s personal characteristics and behaviours in school and their attitude towards and achievement in reading and writing.
Teachers’ perceptions showed:
• No significant difference for school, age or gender for class conduct,
concentration, application to tasks, personal organisation and following
instructions;
• No significant age or gender effect for literacy-related development in
reading and writing;
• A significant school effect for all three writing-related variables with children
at School A perceived more highly than children at School C.
10.1.6 REDUCING DIMENSIONS IN NOVEMBER OF YEAR 1
Principal Component Analyses were conducted on student performance data, parent data and teacher data collected in November of Year 1. Underlying dimensions within the data were reported in Chapter Nine and addressed two focal questions listed on page 450.
Chapter 10: Summary and Implications 462 Eleven factors were derived from literacy-related tasks conducted in November of Year 1. A further result used for examining relationships was the highest level of text read by Year 1 students. Eight factors were devised from parents’ perceptions of child characteristics, literacy progress and home literacy practices.
A further two factors were devised from teachers’ perceptions of class conduct and literacy progress. All of these factors were correlated with school, age, gender, mother SES and father SES to determine relationships.
Correlations of parents’ perceptions and teachers’ perceptions showed three significant positive correlations and four significant negative correlations. These results demonstrated both parents and teachers align positive child characteristics with literacy achievement, but their perceptions are of a different order. Two significant negative correlations occurred for teachers’ perceptions of class conduct and these occurred with parents’ perceptions of child characteristics and literacy progress. An additional two significant negative correlations occurred with teachers’ perceptions of literacy progress. These were with parents’ perceptions of children’s characteristics and children’s literacy progress. Thus, these analyses showed how teachers’ perceptions and parents’ perceptions were of the opposite order.
Correlations of performance factors with background factors showed 13 significant positive correlations and seven significant negative correlations. All positive correlations occurred with parents’ perceptions and SES factors while all negative correlations occurred with teachers’ perceptions. Correlations of
Chapter 10: Summary and Implications 463 performance with school, age, gender and SES revealed four positive correlations and these were:
• School – CAP 3 ‘print knowledge (.18*);
• Mother SES – CAP 5 ‘left and right sequencing’ (.22*);
• Father SES – CAP 7 ‘ punctuation’ (.21*);
• Father SES – Phonological awareness (.21*).
All Variable Sets A, B and C derived from the Cluster Analysis demonstrated the predictive nature these sets derived from literacy performance in preschool. The strongest predictor was Variable Set B derived from Environmental Print and
Letter Knowledge as it showed a significant effect on three measures from
November of Year 1. These measures included the highest level of text read by the children.
10.2 IMPLICATIONS
10.2.1 IMPLICATIONS FOR THEORY
An historical review of theoretical models and practices in the early years was presented in Chapter Two. It revealed changing perspectives on literacy acquisition throughout the twentieth century. Theories have oscillated from a maturational perspective to developmental and skills-based perspectives to the current critical theory. Older psychological theories advocated determining children’s intellectual capacity in order to group children for instructional purposes. Later theories placed an emphasis on children’s learning environment and this led to a degree of ‘blame’ being laid on children when their home environment did not match the expectations of the school (Clay, 1998). School
Chapter 10: Summary and Implications 464 personnel at times do not see this as an opportunity to provide ‘make-up opportunities’ (Clay, 1998, p. 234), but tended to lay blame on children and their families (Freebody, Ludwig & Gunn, 1995).
Sociocultural and constructivist theories provided a framework for viewing children differently and taking into account multiple pathways of development.
Personal experiences and interactions and scaffolding of learning by older more experienced others have attracted the attention of theorists (Bruner, 1990;
Vygotsky, 1978). Teachers who perceive intelligence and reasoning are developed abilities rather than innate capabilities perceive the teaching and learning process differently. Clay (1998) suggested three key strategies for teachers who view children as active constructive learners. First, teachers need to observe learners closely. This will reveal that “change will begin at different starting points for different learners; it will proceed in different ways and at different rates” (Clay, 1998 p. 236). Second, teachers are advised to “tune in to individual differences” and third they are advised to “converse with individual learners” who are actively constructing their learning in unique ways (Clay,
1998, p. 236).
Findings from this study illustrate literacy knowledge and understandings prior to school influence later literacy achievements, but there is not strong support for isolating one particular capability in the preschool period that acts as a strong precursor for successful literacy learning. Findings do not support the theory that older students perform better than younger students or that girls achieve significantly better than boys. The educational level and occupation of fathers
Chapter 10: Summary and Implications 465 was shown to have significantly affected more results than the education level and occupation of mothers in the study, but in this study students at the school where fathers’ occupation levels were the highest did not perform best after one year of schooling. The study supports Clay’s theory of early literacy acquisition that students demonstrate different starting points and proceed in different ways at different rates.
10.2.2 IMPLICATIONS FOR RESEARCH METHODOLOGY
While researchers completing longitudinal studies of literacy in the early years have used a range of performance measures and analyses, none has demonstrated the range of data and depth of analyses completed for this study. Some researchers have used correlation, some have utilised Principal Component
Analyses and some have used Cluster Analyses, but none has used all three utilising both performance and background data collected from students, parents and teachers. Results from this study completed with 114 young children in three schools warrant replication to gauge if findings can be substantiated with a much larger sample from a broader range of school contexts.
It has been shown that Principal Component Analyses and Cluster Analyses together provide a new way of examining the predictive nature of children’s literacy skills after one year of instruction in Year 1. These results clearly show relationships between children’s letter knowledge, knowledge of environmental print, phonological awareness and print awareness provide a means by which literacy development after one year of schooling may be predicted.
Chapter 10: Summary and Implications 466 10.2.3 IMPLICATIONS FOR CLASSROOM PRACTICE
Results in this study were that students enter school with a range of literacy- related skills and abilities, many of which were underestimated by teachers in the early weeks of Year 1. Parents appear to perceive their children’s skills somewhat more accurately, possibly because they use different appraisal criteria.
Teachers tend to align literacy progress with characteristics on the periphery of students’ literacy development, such as personal organisation, application to set tasks, ability to follow directions and apparent concentration.
These two results highlight a need for teachers to measure students’ literacy- related skills and abilities in the early weeks of Year 1 and to observe children’s current literacy practices more closely. Two tools would support teachers in rectifying these needs. First, performance instruments would guide them in measuring students’ print awareness and alphabetic knowledge. Second, teachers could be more systematic in their observations of young children and more directed by criteria related directly to literacy. An observation checklist could be designed to meet these needs. With the support of such instruments teachers would be better equipped to make data-driven decisions about what their Year 1 students can do and be better able to plan literacy-related experiences to match students’ developmental needs.
In the years prior to beginning school it is essential that early childhood teachers and parents become aware of the importance of prior-to-school literacy experiences and the relationship these skills have with subsequent literacy achievement. Teaching practices in the prior-to-school year could include
Chapter 10: Summary and Implications 467 planned and incidental experiences with a range of texts where young children are actively and purposefully engaged. Many opportunities could be provided where children role-play reading and writing and include literacy practices in their play. A range of resources could be provided to enable this play to occur.
Print could be used in early childhood centres to demonstrate ways that people use texts to meet their purposes. It is recommended that teachers become ‘model language users’ and frequently demonstrate ways of using and interacting with texts to meet a range of purposes.
10.2.4 IMPLICATIONS FOR POLICY
Educational policies guide practices in schools as they are frequently tied to funding. It is recommended that policy makers heed findings from research that clearly demonstrate commencing school with knowledge and understanding about literacy advantages children. If promotion of early experiences with texts is to be made policy then early childhood centres could include literacy experiences deliberately and explicitly in their programs. Early childhood educators could work with and inform parents of the long-term benefits to be gained from interacting regularly with their children using a range of texts.
There is a need to examine policies and practices in the early years with a view to reflecting research findings. Demonstrating literate practices and providing regular opportunities for young children to interact with texts in centres and at home would be most beneficial. Screening children in the early weeks of school to ascertain their literacy-related understandings is recommended. A preventative rather than interventionist framework would ensure fewer young students faced
Chapter 10: Summary and Implications 468 failure as they learn to be literate. Finally, instructional innovations could be more carefully scrutinized and trialled to ensure long-term learning occurs prior to their adoption as policy.
10.3 LIMITATIONS OF THE STUDY
Only quantitative measures have been used in this study and this is a limitation.
Including qualitative measures in order to study other related variables more closely would have provided greater depth to the data. First, it would be advantageous to interview Year 1 teachers about literacy beliefs and practices and then observe the teaching of literacy in each classroom. This would have provided a focused study of classroom practices associated with early literacy development. Second, qualitative data gathered in the children’s homes may have provided greater depth of understanding relating to home literacy practices.
Interviewing parents about these practices may have strengthened family data and provided deeper insights into the ways young students experienced textual interactions at home.
A broader range of school contexts could have been chosen. Although the three schools originally were approached because it was believed they were significantly different, when the education level and occupations of parents were examined the differences in profile were not as great as was originally perceived.
Studying schools in remote, rural and city areas would have enabled an examination of a broader range of contexts and socio-economic family situations.
A broader comparison of patterns of early literacy achievement may then have been possible.
Chapter 10: Summary and Implications 469 10.4 DIRECTIONS FOR FUTURE RESEARCH
There is now an abundance of research that shows that young children in the prior-to-school period develop a range of literacy-related skills. However, there is still much to be done in relation to understanding best practices to use with young children to enhance their understandings without applying undue pressure on them to achieve.
This study has shown that schools and teachers in the early years fail to identify young children’s developing literacy skills at correct and functional levels. These developing skills have a direct relationship on children’s later achievements in literacy and teachers must be more careful and correct when making judgments about them.
There is a need to extend the work commenced by Raban, Ure and Smith (1999) where professional development in literacy for teachers in the early years was conducted. The extension would widen essential education for teachers and parents and help educators cater for individual students’ needs in literacy. Four achievements would be reflected by this extension. First, early childhood educators would be informed about the importance of young children’s early literacy development in the prior-to-school period. Second, ways of embedding literacy-related opportunities within play would to be explored as part of the dynamic interactions between teachers and students. Third, teachers would develop ways to focus explicitly on measuring children’s early literacy knowledge and understandings in the early weeks of Year 1. Four, teachers’ communication with parents about early literacy development would improve.
Chapter 10: Summary and Implications 470 Young children’s participation in everyday literacy practices at home and in other contexts contributes to early literacy understandings. It would be beneficial if the long-term effects of parent programs could be researched and the relationship of these programs, home practices and young children’s literacy development studied and reported.
Additional research is needed to focus attention on professional development for teachers in the early years where the importance of young children’s developing literacy skills are highlighted. Ways to observe, measure and collate literacy- related skills at the beginning of Year 1 need to be explored as well as ways teachers use this information to guide class planning. Comparative studies in a range of school contexts would extend current knowledge in this field. This research should address the current situation where Year 1 teachers appear not to acknowledge or measure young students’ developing literacy skills and abilities as they enter Year 1.
10.5 CONCLUSIONS
Educators of today are preparing children for a workplace where the extent of communication and technological demands are unknown. There is no doubt that communication technologies and multiple literacy demands in the workplace will continue to expand (Smith, Mikulecky, Kibby, Dreher & Dole, 2000). Those who speculate on the future predict that growth in literacy demands will continue into the 21st century (Moje & Sutherland, 2003). If this is so, then mastery over low level mental processing skills is essential if workers of the future are to develop higher level literacy skills as a tool for thinking and processing ideas (Smith et al,
2000). Life without literacy, makes for social inequality. Limited oral, reading,
Chapter 10: Summary and Implications 471 writing, and communication skills can have serious health and lifestyle consequences as the ability to critique visual and written texts reduces life and work choices.
Statistics relating to children’s literacy skills throughout parts of the English- speaking world (Alloway, Freebody, Gilbert, & Muspratt, 2002; Department for
Education and Employment, 1997; Education Queensland, 2000a; Freebody,
Ludwig, & Gunn, 1995; Lingard, Martino, Mills, & Bahr, 2002; United States
Department of Education, 2002b) commonly reveal that 10%-15% of children experience literacy difficulties. Reasons why children face literacy learning difficulties are many and complex, but research has clearly described the importance of literacy learning in the early years of schooling (Adams, 1990;
Raban, Ure & Smith, 1999; Snow, Burns & Griffin, 1998). Children may experience physical, intellectual, emotional, socio-economic or cultural difficulties during these years and either singly or in combination all are likely to be influential.
A question raised by Labov (2003) remains. “What can be done about healthy children who do not learn to read?” There were a number of these children within the current study. Home life seemed satisfactory and it appeared as if most children received literacy support from parents. However, after twelve months of schooling several healthy children were not reading or writing with the expected proficiency. Labov’s question remains unanswered, however this study has shown that parents perceive their children’s developing literacy understandings in the prior-to-school period quite realistically and that seemingly they are an
Chapter 10: Summary and Implications 472 untapped source of information for Year 1 teachers. Teachers would gain more insightful information relating to children’s language and literacy capabilities as they enter school if they asked parents.
The emphasis adopted by educators relating to early literacy development has been intervention rather than prevention. Societies and school systems seem to treat as inevitable a 10%-15% failure rate during the early years of schooling. It is time to look back at the prior-to–school period and examine the precursors of children’s success in school literacy learning (Clay, 1998). It is not difficult to imagine that doing so is likely to assist in preventing the occurrence of literacy learning difficulties. It seems a more progressive and educationally responsible position than to accept failure as inevitable, or to search for interventions should failure occur.
The application of research findings in schools concerning early literacy development is essential and long overdue. There are a number of studies that have examined children’s prior-to-school literacy knowledge and understandings and the current study expands upon these. Previous studies all reveal that children learn much about written language in the prior-to-school period
(Burgess, Hect & Lonigan, 2002; Hill, Comber, Louden, Rivallend & Reid,
1998; Storch & Whitehurst, 2002) and there is a relationship between early literacy experiences and later literacy achievement in school. This study reported an expansion of previously-held knowledge concerning this relationship. We are now able to predict patterns of children’s literacy achievements in school by knowing the literacy understandings young children have acquired prior to
Chapter 10: Summary and Implications 473 commencing school. Children’s concepts about print, knowledge of the alphabet and environmental print and their phonological awareness in the prior-to-school period have all been shown to be predictors of later literacy achievement.
Knowing the predictors should be a mark of caring parents and professional teachers.
Teachers in the early years need to know about and act on this information.
Ensuring that young children are given opportunities to interact with a wide range of texts is essential. Teachers in early childhood care and education settings need professional development relating to ways of including literacy experiences for young children. Further, professional development is needed for teachers in the early years of primary school to alert them to the importance of knowing literacy skills and understandings that young children bring to school and using this information to guide planning.
Determining young children’s skills must incorporate more than a teacher’s non- systematic observation. It requires an informed and focused measurement of children’s knowledge of oral language, reading and writing. At the present time,
South Australia is the only State in Australia that has mandated a School Entry
Assessment. It consists of an observation checklist of a child’s initiative, social relations, creative representation, language and literacy, logic and mathematics combined with the preschool summative report and information from parents
(Department of Education Training and Employment, 2002). While this process is noteworthy, it does not advocate focused measurement of children’s skills.
Research into patterns of literacy development needs to be sustained and school
Chapter 10: Summary and Implications 474 entry assessments and program initiatives need systematic evaluation and reporting of results. There has been widespread adoption of literacy programs and interventions in Australia in the past without adequate evaluation of effectiveness (de Lemos, 2002).
Several general implications can be drawn from this study. First, there is a need to focus attention on prevention of literacy learning difficulties in the early years rather than continue with the present practice of intervention once failure becomes evident. Prevention strategies include educating early childhood teachers and examining the precursors of literacy success to ensure that appropriate literacy-related practices are embedded in prior-to-school programs.
Second, the development of School Entry Literacy Assessment instruments is recommended. Using these instruments along with professional development for teachers in the early years is essential. Trials should focus on the effects of educating teachers about children’s early literacy understandings, measuring children’s pre-existing literacy knowledge the application of such specific knowledge as teachers plan and implement literacy learning programs.
There is a need to examine ‘educational myths’ in relation to early literacy development. These include a belief that all children from low socio-economic backgrounds will face literacy learning difficulties. A second myth relates to a belief that girls will always make more rapid progress than boys. A third belief is that children who commence school at an older age will face fewer literacy learning difficulties. A number of longitudinal studies of early literacy including the current study, have shown these beliefs are not always substantiated by
Chapter 10: Summary and Implications 475 research results (Heath, 1983; Purcell-Gates, 1996; Teale, 1986; Tett &
Crowther, 1998).
Educators have for a number of years been concerned about measuring children’s literacy in the early years as the fear of ‘labelling children’ endures. However, the time has come to examine the statistics with a different view and ask a difficult question about why 10%-15% of children remain locked into a possible lifetime of learning difficulties. Clay (1979a) raised this very issue more than two decades ago:
There is an unbounded optimism among teachers that children who are
late in starting will indeed catch up. Given time, something will happen!
A temporary backwardness will eventually be relieved by suitable
teaching and children may even grow out of it themselves! In particular,
there is a belief that the intelligent child who fails to learn to read will
catch up to his intelligent classmates once he has made a start. Do we
have any evidence of accelerated progress in late starters? There may be
isolated examples that support this hope, but correlations from a follow-
up study of 100 children two and three years after school entry lead me to
state rather dogmatically that where a child stood in relation to his age-
mates at the end of the first year at school was roughly where one could
expect to find him at 7.0 or 8.0. (p. 13).
Clay’s words warn educators not to be complacent when young children are slow in learning to be literate. Current researchers acknowledge the continuity between ‘early developmental differences and later ones’. But, they also confirm
Chapter 10: Summary and Implications 476 that data from a number of studies ‘suggest the pattern of across-age continuities is not entirely simple or straightforward’ (Scarborough, 2001, p. 103). There is
‘recognition that the preschool years play a critical role in children’s long-term literacy success’ (Neuman & Dickinson, 2001, p. 5). This study demonstrates the complex interplay of children’s cultural and social experiences at home and in community and that multiple pathways emerge as children strive to meet the literacy demands in school.
Further research needs to be done with preschool children in order to understand the range of prior-to-school precursors of successful early literacy development.
Professional development and research with teachers in the early years needs to determine ways in which children’s early acquired knowledge and understandings about literacy may be measured, acknowledged and utilized.
Literacy-related experiences in the early years and instructional innovations need to be scrutinized and trialled widely prior to widespread adoption so that learning to be literate may be supported and not impeded. No simple solution is available and 10%-15% of children are still struggling with learning to be literate. There is an urgent need to look beyond short-term educational interventions and investigate ways of integrating programs, policies and services offered by many agencies for families and children in order to improve the chances for all children to become literate.
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