External Task-Repetition: the Role of Modality, Written Corrective Feedback and Proficiency

UNIVERSIDAD DE MURCIA

ESCUELA INTERNACIONAL DE DOCTORADO

External Task-repetition: The Role of Modality, Written Corrective Feedback and Proficiency. A Comparative Study

Repetición Externa de la Tarea: el Papel de la Modalidad, la Respuesta al Escrito, y la Competencia Lingüística. Un Estudio Comparativo

D. Alberto José Sánchez López 2018

TABLE OF CONTENTS

ACKNOWLEDGMENTS ...... I Roadmap to the reader...... III PART I. THEORETICAL BACKGROUND ...... 1 CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING...... 2 I.1. GENESIS OF TASK-BASED LANGUAGE AND TEACHING...... 2 I.2. THE CONCEPT OF TASK...... 3 I.3. LANGUAGE LEARNING THROUGH TASKS...... 6 I.4 THEORETICAL UNDERPINNINGS FOR TASK-BASED LANGUAGE AND TEACHING...... 8 I.5 OUTPUT PRODUCTION ACROSS MODALITIES: ORAL AND WRITTEN LANGUAGE...... 12 CHAPTER II. TASK REPETITION AND LANGUAGE LEARNING...... 32 II.1 RATIONALE FOR TASK REPETITION IN THE ORAL MODALITY...... 33 II.2. TASK REPETITION IN WRITING: NEED TO EXPAND RESEARCH AND TENETS...... 35 II.3. MEDIATING FACTORS IN TASK REPETITION: THE CASE OF LEARNER PROFICIENCY. .36 CHAPTER III. ANALYSIS OF RELEVANT EMPIRICAL RESEARCH...... 38 III.1. RESEARCH ON TASK-MODALITY EFFECTS...... 38 III.2. RESEARCH ON TASK REPETITION IN THE ORAL MODALITY...... 40 III.3. RESEARCH ON TASK REPETITION IN WRITING...... 44 III.4 RESEARCH ON WRITTEN CORRECTIVE FEEDBACK...... 46 PART II. THE EMPIRICAL STUDY ...... 53 CHAPTER IV. AIMS, HYPOTHESES AND RESEARCH QUESTIONS...... 54 IV.1. HYPOTHESES...... 55 IV.2. RESEARCH QUESTIONS...... 55 V. METHOD...... 57 V.1 PARTICIPANTS...... 57 V.2. TASK AND PILOTING...... 58 V.3. INSTRUMENTS AND DATA COLLECTION PROCEDURES...... 60 V.4. DATA CODING AND ANALYSES...... 63 VI. RESULTS ...... 75 VI.1. TASK REPETITION ACROSS MODALITIES (ORAL/WRITING) AS MEDIATED BY PROFICIENCY...... 75 VI.2. TASK REPETITION AS MEDIATED BY DIFFERENT TYPES OF WCF AND PROFICIENCY...... 90 VII. DISCUSSION...... 118 VII.1. TASK REPETITION ACROSS MODALITIES...... 118 VII.2. TASK REPETITION AS MEDIATED BY WCF...... 128

VIII. CONCLUSION...... 135 VIII.1. SUMMARY OF THE RATIONALY OF THE STUDY...... 135 VIII.2. SYNTHESIS OF MAIN FINDINGS...... 136 VIII.3. CONTRIBUTION OF OUR RESEARCH...... 138 VIII. 4. PEDAGOGICAL IMPLICATIONS...... 140 VIII.5. LIMITATIONS TO OUR STUDY AND FUTURE RESEARCH...... 141 REFERENCES ...... 144 RESUMEN ...... 162

ACKNOWLEDGMENTS

I am very grateful to all those people who supported me during the process of writing the present doctoral dissertation. Having them beside me gave me the necessary strength to carry on. Therefore, they deserve the thoughts and feelings I shall render in the following lines.

First and foremost, I cannot really express my gratitude to my supervisor, Rosa M. Manchón Ruiz, and my co-supervisor, Roger Gilbert Guerrero. I would like to thank them for giving me the opportunity of conducting my research with them, for tutoring and guiding me throughout these years and for their thorough revisions of the present manuscript. Should any errors remain, these are entirely my own. Rosa and Roger have been role models both professionally and personally, who have helped me to grow in these two facets of life. I really appreciate their help and support at every stage of this process and their companionship at international conferences where I had the opportunity to meet their colleagues and other scholars, whose comments were always stimulating and thought-provoking. Also, I wish to thank the rest of colleagues in the research group, most of them in the University of Murcia and some others in the University of Barcelona, who were always supportive and treated me as another fellow member of the group. It was a pleasure to learn from them all. Special thanks to Lena Vasylets, who always welcomed me in the University of Barcelona and trained me in data analysis and, to Javier Marín and Miguel Ángel Pérez, without whom statistical analysis would have been much harder and time-consuming. I also want to show my gratitude the rest of PhD students I met along the way, who were always willing to lend a helping hand when necessary and shared hilarious moments and laughs in conferences, Jose Ángel Mercader, Sophie McBride, Belén Moreno, María Dolores Mellado and, especially, Belén González, who endured stressful moments with me during this summer and always relieved the pressure with her gentle touch.

I also would like to thank Ministerio de Economía y Competitividad (FFI2012-35839 and FFI2016-79763-P) and Fundación Séneca (19463/PI/14) for financing my attendance to international conferences and my training for data analysis in the University of Barcelona.

Last but not least, I am grateful to all my family and friends, particularly my parents, Mercedes and Arnelio, who understood my academic, professional and personal situation and never stopped believing in me. They were always there to listen and had some piece of advice to cheer me up in difficult moments. I thank them all for their patience, understanding and encouragement during these five years.

Roadmap to the reader. Throughout the world, millions of learners are asked to speak and write in their second language classroom. It is a well-known fact by now that the type of task and the conditions under which it is performed will largely determine oral, written and learning outcomes in general, while language learners and language teachers alike contrive to make the most out of them. From their struggle to master and to teach how to master a language, stems the importance of investigating tasks both in oral and written domains and exploit the language learning opportunities the two modalities afford. Ours is, therefore, a further building block on the trailbreaking path initiated previously by some scholars (see Byrnes & Manchón, Eds., 2014a) to make writing practices more central in the pursuit of second language acquisition.

The present doctoral dissertation is organised in two parts with eight chapters in total. Part I comprises three chapters that offer the necessary background to the empirical study that is presented in Part II, which again consists of five chapters.

In Chapter I, the theoretical underpinnings for Task-Based Language Learning and Teaching is presented as the necessary background for our study, with a special emphasis on the language learning possibilities of output production in the two modalities. Additionally, the concept of task is also addressed. Moving onto Chapter II, the rationale for task repetition, which is the key construct under study in this thesis, is presented as it was theorised in the oral mode. Following, we problematise the concept of task repetition in its application to the written mode, and we pay special mention to the potentially mediating role of the learner variable of second language (L2) proficiency given the scant attention this variable has received in previous empirical research on task repetition. Chapter III summarises the relevant empirical research in which to situate our own study. Four main research strands are reviewed: research on modality- related effects, research on task repetition in the oral modality, research on task repetition in writing and research on written corrective feedback.

Part II contains the empirical research. Chapter IV contains a description of the aims, hypotheses and research questions guiding our study. Chapter V offers a detailed description of the methodology employed in both the pilot and the main study in terms of participants and data collection and analyses procedures. The main results obtained are reported in Chapter VI and subsequently discussed in Chapter VII, which we do in connection with the theoretical predictions and findings in previous research. Finally, in Chapter VIII some overall conclusions are presented, the main limitations of the study are acknowledged and suggestions for future research are suggested.

III

PART I. THEORETICAL BACKGROUND

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING.

I.1. GENESIS OF TASK-BASED LANGUAGE AND TEACHING. During the late 1970´s and the early 1980´s, the Communicative Language Teaching (CLT) approach introduced a new perspective about how languages should be taught – and are best learned. It mainly involved a differentiation between what Widowson (1978) called “usage” i.e. the capacity to use language accurately, and “use” i.e. the capacity to use language meaningfully and appropriately in the construction of discourse (Ellis, 2003. Emphasis added).

Not much later, Howatt (1984) distinguished between a weak and a strong version within CLT. The weak version defended that the components of communicative competence should be identified and serially taught, whereas the strong version advocated that “language is acquired through communication” (Howatt, 1984: 279). This strong version within CLT involved providing learners with opportunities in which to be exposed to how language is used for the communication of meaning, breaking with the assumption that language structures should be mastered before they could be used for communicative purposes. One of the approaches within this strong version that has attracted most of the scholar attention in the field of second language acquisition (SLA) in the recent years is the task-based approach to language teaching and learning (TBLT), to which we now turn. Being the present study framed within the TBLT framework, it is relevant to outline its foundational principles to fully understand the rationale and aims of our research.

In the last three decades, TBLT concerns have experienced an increasing interest and tasks have, therefore, become a central aspect in SLA-oriented research. It has been widely considered as a useful approach able to create optimal learning conditions (Bygate, 2016; García Mayo, 2007; Robinson, 2011; Robinson & Gilabert, 2007; Samuda & Bygate, 2008; Van den Branden, 2016). As Cook (2010) affirms: “it [TBLT] reconceptualizes communicative language teaching as tasks rather than the language cognition-based syllabuses of communicative language teaching” (p. 4). Tasks, to be defined in a forthcoming section, are considered the core for instruction in TBLT and they may serve a double purpose both in terms of pedagogy and research. In the words of, as argued by Candlin's, tasks “serve as a compelling and appropriate means for realizing certain characteristic principles of communicative language teaching and learning, as well as serving as a testing ground for hypotheses in pragmatics and SLA” (Candlin, 1987: 5).

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING.

Therefore, tasks are used not only a means to promote language learning but also as a way in which tasks themselves are tested in terms of their suitability for teaching and used in addition to examine the tenets on which TBLT is sustained, tenets which will be discussed later in section I.4.

At this point it is relevant to differentiate between a strong and a weak version within TBLT, usually referred to as task-based and task-supported approaches respectively. The former relies entirely on a syllabus built around tasks, prompting focus on meaning and, to a lesser extent, a focus on form – attention to problematic forms that arise incidentally in communication while focusing on meaning (Long, 1991) – through (unfocused) tasks, leaving out any role for grammar instruction whereas the latter incorporates tasks that are specifically designed to focus on language (syntax or lexis) to a more traditional syllabus (Ellis, 2009a). Samuda and Bygate (2008) already introduced this distinction and even offered a third possibility, which they referred to as the “task-referenced” approach, in which the emphasis is on the use of tasks to measure target achievement and to assess the outcome of instruction. The next section introduces the notion of task and delves into necessary distinctions to understand the nature of the construct.

I.2. THE CONCEPT OF TASK. In order for learners to be provided with opportunities to experience how language is used in communication (Ellis, 2003) as in a natural, real-world setting and promote language development, pedagogic tasks need to be designed so as to meet distinctive characteristics. Tasks have been defined and depicted in numerous ways. For our purposes here, we regard tasks as pedagogic tasks. Pedagogic tasks are derived from needs analysis and they prepare learners for the performance of target tasks i.e. what people may need to do in the real world in the second language. Pedagogic tasks happen in instructional contexts and are designed to promote maximal learning opportunities. What follows is a characterisation of tasks based on previous proposals of what a task is, especially those by Bygate and colleagues (Bygate, Skehan & Swain, 2001; Samuda & Bygate, 2008). According to these scholars, the defining characteristics of tasks are the following:

1. Meaning is primary (Nunan, 1989; Skehan, 1998b): there has to be a focus on meaning over form since tasks should be designed to use language pragmatically (Ellis, 2003) and to communicate content (Ellis, 2000). This includes processing of both semantic (what we want to say with our utterances explicitly) and pragmatic meaning (what is implied

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING.

by our utterances) (Ellis, 2009a) since the learners may use both linguistic and non- linguistic resources to complete the task. 2. The task needs to present learners with a “gap” to prompt them to communicate (e.g. need to convey certain information) so that they engage learners in the kind of information processing leading to second language (L2) acquisition (Ellis, 2009a). 3. There has to be a connection to real-world activities (Skehan, 1998b) or, at least, tasks should elicit the type of language and communicative behaviour that stems from real- world tasks (Ellis, 2000, 2003). 4. Learners should resort to their own linguistic and non-linguistic resources to fulfil the task (Ellis, 2009a). 5. A task may involve any language skill: receptive (reading, listening) or productive (speaking or writing) or even a combination of different types of skills. (Ellis, 2003). 6. The outcome of the task is not merely language use. In other words, language use is not the pursued end, it is not the intended outcome of the task, but a means to achieve that end, which should ultimately be communicative (Ellis, 2003; Nunan, 1989).

This characterisation could be summoned in Ellis´ (2003) words:

A task is a workplan that requires learners to process language pragmatically in order to achieve an outcome that can be evaluated in terms of whether the correct or appropriate propositional content has been conveyed. To this end, it requires them to give primary attention to meaning and to make use of their linguistic resources, although the design of the task may predispose them to use particular forms. A task is intended to result in language use that bears a resemblance, direct or indirect, to the way language is used in the real world. Like other language activities, a task can engage productive or receptive, and oral or written skills, and also various cognitive processes (p. 16).

Building on the summarised definition of task by Ellis (2003), there are a number of differentiations to be made which are relevant to comprehend the wide variety of perspectives from which we can consider tasks. Tasks can be or various types but, first of all, it is pertinent to distinguish between a task and a situational-grammar exercise. A situational-grammar exercise is a de-contextualised activity with a clear and explicit focus on forms (see later), whether syntactic or lexical, deprived from any communicative purpose. Tasks, on the contrary, are an activity wherein a message (meaning) is to be conveyed in either direction (productive or

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. receptively) triggered by an ultimate communicative goal. In a similar fashion, we can distinguish between unfocused tasks, designed to provide learners an environment where to use language in general in communication, and focused tasks, which are directed at using certain linguistic features (Ellis, 2009a). Tasks could also be classified as being input-providing or output- prompting, the former dealing with reading or listening as a mean to present learners new language as input, the latter dealing with making learners attempt to communicate either in speaking or in writing, that is, to produce output. Related to this last classification is that of tasks as being transactional or non-referential (Skehan, 2003). This differentiation makes reference to certain tasks in which learners are engaged in transmission or exchange of information. A further final distinction considers the concepts of “outcome” and “aim”. The (non-linguistic) outcome of a task comprises what learners arrive at when they have accomplished the task while the aim of a task is the pedagogic purpose of the task i.e. meaning-focused language use.

A further differentiation originally introduced by Breen (1987) that should be made is that of “task-as-workplan” and “task-as-process”. Breen´s definition of these two terms follows:

Any language learning task will be reinterpreted by a learner in his or her own terms. This implies that a pre-designed task – the task-as-workplan – will be changed the moment the learner acts upon it. The task-as-workplan will be redrawn so that the learner can relate to it in the first place and, thereby, make it manageable. When considering what happens during language learning tasks, we can initially distinguish between the original task-as-workplan and the actual task-in- process. It is the latter which generates typically diverse learning outcomes and the quality and efficacy of any task must be traced directly to its use during teaching and learning. (Breen, 1987: 24–5).

Therefore, task-as-workplan is connected to the intention of the task designer, what (s)he had in mind i.e. the goals of the task, the language to be used or the intended outcome. Task-as-process relates to the actual performance of the learners while completing the task, which may or may not coincide with task-as-workplan. The concept of task-as-process is then linked to what Pauline Foster labelled as un-pre-focused tasks (2009), tasks where the learning outcomes are “incidental, unpredictable and individual” (p. 249) making it difficult to address specific target features (as in focused tasks), especially if these are new to the learners. Task-as- process depends on learners´ performance of the task, which is derived from how learners conceptualise it. This is highly individual since every learner may account for a single

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. conceptualisation of the task and therefore can make learning outcomes unpredictable. This has several implications for the efficiency of tasks, both focused or unfocused, but research has shown how manipulating certain implementation variables tasks can be led to be performed in predictable ways (see Foster & Skehan, 1996) through manipulating pre-task and/or post-task cycles. However, Samuda and Bygate (2008) insisted on the importance of studying both task- as-workplan and task-as-process as a single entity, for the interest in one of them raises from the connectedness to the other. Consequently, the way in which learners engage with and approach task completion and the ways wherein they may modify and re-interpret the task (understood as task-as-workplan) should also become a primary concern for both pedagogy and research. This is an important point when it comes to task-modality issues given than task conceptualization is an important construct in writing research and one that needs to be taken into consideration when theorizing and researching tasks in the written modality (Manchón, 2014b), as we will see in a later section.

I.3. LANGUAGE LEARNING THROUGH TASKS. Willis (1996) suggested several conditions for language learning through tasks and these are enhanced by the different characteristics the task at hand may meet. In the first place, learners need to be exposed to language through input. This can be best done through meaning- based listening or reading tasks to enhance noticing, given that conscious noticing in necessary to trigger acquisition (Schmidt, 1990, 2001). Prabhu also suggested that “intensive exposure caused by the effort to work out meaning-content is […] a condition which is favourable to the subconscious abstraction– or cognitive formation– of language structure” (1987: 71). These claims echo Krashen´s suggestion that “comprehensible input” is necessary for acquisition (1982). However, it has been posited that this input needs to be rich (in terms of language) and real (authentic). A second condition relates to (language) use understood as output production, which has been claimed to be essential for language development since it “encourages intake” (p.13). The dichotomy use/usage is one of paramount importance. As stated earlier, usage makes reference to the knowledge learners have about language whereas use is related to how learners convey meaning communicatively in the construction of discourse. Learners should be provided with opportunities to produce output in a variety of situations as acquisition takes place mainly through communication (Schmidt, 2001; Doughty, 2001). One of the main goals for TBLT, then, is to create contexts where communication can be enhanced at different stages of learner development (Ellis, 2009a). SLA researchers started to investigate the role of producing output in language development when it became apparent that input alone could not promote

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING.

L2 development by its own (Swain, 1985). Language production and practice are thought to ease cognitive processing demands when building meaning-form mappings and tasks are considered to provide learners with an environment in which such linguistic production and practice may take place. In the third place, the role of motivation has also been credited in TBLT. Not only should it be geared towards the processing of input, but also towards the production of output and this can be best promoted through setting achievable goals which, in turn, may prompt students to look for exposure and use outside the classroom. Finally, although some scholars have criticised TBLT for relegating– or even neglecting– the role of instruction within this approach (Swan, 2005), it does consider instruction as a necessary condition for L2 learning where “it is generally accepted that instruction which focuses on language form can both speed up the rate of language development and raise the ultimate level of learners´ attainment” (Willis, 1996: 15). The preferred way to cope with instruction from a TBLT perspective is through Focus on Form (FoF) stages (Long, 1991) which implies conscious attention to problematic forms while engaged in the communication of meaning. Instruction, then, has to stress the noticing of forms in input so that learners are able to confirm/disconfirm their hypotheses about language and raise awareness of language form rather than an automatic production, bearing in mind that the acquisition of L2 syntax has been claimed to follow certain developmental sequences whose patterns cannot easily be traced or predicted (Pienemann, 1998).

Therefore, TBLT emerges as a site where it is possible to combine traditional approaches to language teaching with more innovative techniques and methodology creating the adequate environment for learning to take place inducing students to use language meaningful and communicatively. Essentially, all four conditions stated above need to be met if we are to achieve the ultimate goal of second language (L2) acquisition. Each of them in isolation will fail in such endeavour. Therefore, they should be regarded as interdependent, mutually-inclusive conditions which need to be balanced to master any L2. Another condition for L2 learning not mentioned in Willis (1996), is attention. The role that attention plays in L2 learning has been addressed, albeit differently, by the different SLA theories that have mainly illustrated TBLT theoretical underpinnings. We are now going to look into the cognitivist framework that more specifically informs TBLT tenets i.e. the Output Hypothesis (Swain, 1985), the Noticing Hypothesis (Schmidt, 2001) and the Focus on Form (FoF) paradigm (Long, 1991) and the way in which these have attributed to attention its potential role in language development and learning. It should also be noted that these learning affordances have traditionally been theorised and research with respect to oral tasks, and, as it will be explained in section I.5, these assumptions have been problematised in the case of writing regarding the differential

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. characteristics and differential nature of writing tasks.

I.4 THEORETICAL UNDERPINNINGS FOR TASK-BASED LANGUAGE AND TEACHING. TBLT has drawn upon several theoretical rationales and SLA theories in order to justify how language learning and acquisition through a TBLT approach can be best achieved. Prabhu´s procedural syllabus (1987) constituted one of the initial theoretical/pedagogical foundations for TBLT. It rejected any explicit grammar instruction and encouraged learner-learner interaction, placing special emphasis on mass exposure to the second language and the creation of opportunities for learners to engage in (individual) communication in the classroom. The syllabus was not specified in linguistic terms. Rather, it was more an account of different tasks designed to encourage problem-solving activities rather than a proper (traditional) syllabus since Prabhu himself (1982) had claimed that linguistic forms were best learned while learners attend to meaning, one of the main principles of TBLT. The task cycle comprised the pre-task, task and feedback stages. During the pre-task stage, the nature of the task was to be explained to the learners and relevant language was brought in before inciting preliminary attempts to the task. The proper task stage comprised actual performance and, finally, during the feedback stage learners were informed of how well they had performed in the task. Beretta and Davies (1985) evaluated Prabhu´s project and corroborated Prabhu’s hypothesis on the appropriacy of the approach to acquire grammatical forms and use them communicatively. However, certain drawbacks regarding the evaluation methods which may distort these results of the evaluation should be taken into account (Allwritght, 1988, reviewed in Ellis, 2009a), issue which the authors themselves already acknowledged. It becomes apparent that Prabhu drew on claims made by Swain in her Output Hypothesis (1985) due to his reliance not only on input, but mainly on output production.

Another main theoretical tenet in TBLT, concerns the role of interaction in promoting language development. For Long (1989), interaction within a task can trigger two different situations. On the one hand, tasks can provide a context where input can be addressed and tailored to the learner’s needs more easily and, on the other, they can create an environment where to attend to problematic forms in input and/or output. Focus on form (FoF) can likely occur while learners negotiate meaning and is thought to foster meaning-form mappings and eventually induce interlanguage change as it “overtly draws students´ attention to linguistic elements as they arise incidentally in lessons whose overriding focus is on meaning or communication” (Long, 1991: 46). He also suggested that encouraging FoF in the classroom will

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. probably speed up the rate of learning and achieve higher levels of L2 acquisition. On the contrary, it had already been claimed that grammar instruction (attention to forms, see later) was inefficient and detrimental for L2 acquisition after Krashen´s distinction between learning and acquisition (Krashen, 1981). He asserted that grammar instruction could only have an impact on the learned system (explicit knowledge) and not on the acquired system (implicit knowledge). Adopting a non-interface position (explicit knowledge not being of help to develop implicit knowledge), Krashen ruled out any role for formal instruction on acquisition. Research had revealed that focusing solely on meaning and mere exposure to language were insufficient for developing L2 competence integrally (García Mayo, 2011). It was then assumed that there might be an interface between explicit and implicit knowledge (DeKeyser, 2001, 2007) and, as a consequence, changes in the explicit system due to instruction could, in turn, induce changes in the implicit system. Long established the dichotomy focus on forms vs. focus on form. The former related to the traditional way of grammar teaching, presenting items in isolation within a non-communicative context while the latter, already accounted for in earlier lines, was defined by Long (1991) as a procedure whereby learners´ attention is directed towards “linguistic elements as they incidentally arise in lessons whose overriding focus is on meaning and communication” (p. 46). It has already been mentioned that the preferred way to deal with instruction within a TBLT approach is through focus on form as “some kind of grammar instruction within a communicative approach” may be beneficial for learners (García Mayo, 2007: 16). Focus on form herein a task-based perspective has been implemented through interaction (negotiation), planning and through feedback strategies. However, learners´ online focus on form with its potential to foster language development may be more likely to take place during writing than during speech production due to the time constrains that characterise oral communication, as we shall see in the next chapter along with the rest of characteristics which differentiate both modalities of production.

Attention to form is then thought to be necessary for language learning (Schmidt, 1990, 2001). Schmidt stressed the roles that attention and noticing play in language acquisition. In his Noticing Hypothesis (1990, 1993, 2001), he assumed that it is attention what allows learners to notice problems in their interlanguages, i.e. differences between what they need to produce and what they are actually able to produce as well as the difference between what they can produce and more proficient users of the language produce. This noticing activity is directly connected to output production and the process of “noticing the hole” (Swain, 1998) in connection with the consciousness-raising function of the Output Hypothesis discussed below. When learners encounter problems while communicating, they notice them, increasing the

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. likelihood to pay greater attention to subsequent input. On condition that learners attend to future input when receiving it, Schmidt claimed that they would “notice the gap” between what they produce and proficient target language (TL) users produce. The issue of noticing the gap between production and input will be studied in connection with written corrective feedback (WCF) later.

These last assumptions underline the importance of noticing and attention processes and how engaging in these processes when producing language can assist language development and, in turn, language learning. Swain started to question Krashen´s claims that acquisition could be attained simply though exposure to comprehensible input. Krashen even claimed that that linguistic production is the result of acquisition and not a facilitator factor (Krashen, 1989). Swain (1984, 1985) problematized this hypothesis based on her own experience and research in immersion programmes in Canada where learners exhibited great control over their receptive skills while not being able to show such mastery when speaking in French. This was taken as evidence to question whether mere access to comprehensible input was the necessary and sufficient condition for language learning to proceed, as originally posited by Krashen. Instead, she claimed that providing learner with opportunities to not only receive language but also produce language would lead to development of these skills and to shift from lexical to syntactical processing of incoming input and resulting output. Generally, the Output Hypothesis (Swain, 1985) claimed that attention to language aspects while producing output can be conducive to language development. Swain, in her initial formulation of the Output Hypothesis (1985), affirmed that producing output can assist language development and learning in a number of ways because of several functions of output, namely, noticing (consciousness-raising), hypothesis-testing and metalinguistic functions, all three thought to be conducive to language development and learning. These three different functions suggested support this claim and through them learners are able to reflect on language and engage in focus on form processes. This is particularly the case when learners are encouraged to produce what has been labelled as “pushed output” – a more precise, coherent and appropriate output, thought to be potentially conducive to learning (Swain, 1985).

The noticing, consciousness-raising function, may be as much related to input as to output, i.e., learners notice a difference between what they want to say and what they are actually able to say (noticing the hole) as a result of their attention to linguistic aspects of their production and consequently they may look for ways whereby to fill that gap in incoming input. In the case of writing, for example, this would mean to pay attention to written corrective feedback (WCF). In contrast, – the other two functions of output, namely the hypothesis-testing

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. and the metalinguistic functions, are more closely related to output production and not input processing. These functions prompt learners to focus on form, reflect on language and engage in syntactic processing when producing output and in this way can promote learning and acquisition. In the words of Swain (1985): “output […] extends the linguistic repertoire of the learner as he or she attempts to create precisely and appropriately the meaning desired” (p. 252) by forcing the learner “to pay attention to the means of expression needed” (p. 249). She also argued that output production may prompt learners to engage in a kind of syntactic processing with beneficial effects on linguistic development, as some other scholars have also suggested occurs when producing output in the written mode (Manchón, 2013) as we will discuss in later sections. That is, learners may face problems when trying to convey their intended meaning while producing output. Two potential outcomes with potential benefits for language development may derive as a result of learners´ engagement in the consciousness- raising function. In the first place, learners may look for solutions in their linguistic repertoire and through hypothesis testing and reflecting on their own language they may find a solution for the problem (metalinguistic function). However, learners may not have sufficient knowledge to solve the problem themselves. As a consequence, when they notice a hole in their interlanguage due to the fact that they did not have the necessary resources to express what they wanted to say, they may feel more disposed to receive incoming input to solve their language problem. In the case of writing, this would likely be in the form of written corrective feedback.

Output production relies at the heart of TBLT´s tenets supporting the claim that language is acquired while communicating meaning. Furthermore, it may lead learners to engage in focus on form processes as stated above. It is important to note that the original formulation of the Output Hypothesis addressed output production in general, disregarding a potential mediating role of the modality of production. Yet, different modalities of production imply different cognitive processing demands for L2 learners and, consequently, language production in speaking and writing may result in different learning opportunities as we shall see when reviewing how the models of language processing in speaking and writing along with their distinguishing characteristics relate to these different learning opportunities.

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING.

I.5 OUTPUT PRODUCTION ACROSS MODALITIES: ORAL AND WRITTEN LANGUAGE. Producing output entails both speech production and writing activity. Also, if we consider the characterisation of what a task is offered in previous sections and most accounts on task definitions (Bygate, Skehan and Swain, 2001; Ellis, 2000; 2003; 2009a; Nunan, 1989; Samuda and Bygate, 2008; Skehan, 1998b), they suggest, either explicitly or implicitly, that these encompass both modalities of production. Furthermore, TBLT claims to be concerned with “the various domains of lifetime endeavour outside the language classroom” (Robinson, 2011: 11) and the execution of complex tasks in the real world (Skehan, 1998b). However, the bulk of research on SLA-TBLT oriented issues has tended to concentrate on the study of oral language which has been set as the default mode, thus almost ignoring the role that writing may play in language development and learning when implementing a task-based approach (Manchón, 2014b). Other scholars have also echoed the prominence of orality in the fields of SLA and TBLT, as reflected in the following words by Bygate, van den Branden and Norris (2014)

Owing to the deeply engrained assumptions about the psycholinguistics of second language acquisition and about the immediacy of oral language processing, SLA as a field has generally privileged oral language as a site for both studying and for promoting language learning. In this respect, TBLT research has largely incorporated those same assumptions into empirical approaches into task-based learning. But on exploring closely the role or writing tasks and their rich potential to foster second language learning and use, it may start to appear less axiomatic that the oral mode should be the privileged site for second language learning and hence for TBLT (p. ix).

The trend within SLA research regarding the focus on oral language has started to change and new avenues for research are growing rapidly (see Byrnes & Manchón Eds., 2014a) within what Manchón (2011a) named the “writing-to-learn-language” dimension (WLL). This emergent cognitively-oriented strand of research within L2 writing studies intends to shed light on how literacy practices may promote language development and L2 learning, hence connected to SLA aims; as opposed to the “learning-to-write” (LW) dimension whose main focus is connected to how learners acquire literacy practice in the L2, which has usually been the focus of research interest in L2 writing studies.

The line of research within the WLL dimension represents a key trend in SLA-L2 writing interfaces. Cumming (1990) suggested that writing practices would direct learners to engage in

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. processes conducive to language learning and acquisition alluding to differential characteristics of writing such as the need for (self-)monitoring or the metalinguistic problem-solving activity inherent to the act of writing. As he himself suggested:

composition writing might function broadly as a psycholinguistic output condition wherein learners analyse and consolidate second language knowledge that they have previously (but not yet fully) acquired […] Composition writing elicits an attention to form-meaning relations that may prompt learners to refine their linguistic expression – and hence their control over linguistic knowledge (1990: 483).

These assumption in a way initiated the WLL dimension of L2 writing, stressing the paramount role that literacy practices play in L2 learning given that it creates an optimal context for learners to learn and use L2 forms. Writing emerges then as a site for linguistic reflection and processing, knowledge transformation and consolidation of target language (TL) forms (Cumming, 1990). It is through communicative writing acts that learners are able to expand, polish and proceduralise their L2 knowledge, which in turn may lead to language acquisition. It makes sense, then, to explore the language learning opportunities that different modalities of production provide to L2 learners and, as a consequence, to add writing to TBLT preoccupations at the levels of theory, research and practice.

Apart from the language learning potential written practices offer, some scholars (Manchón, 2014b) have also pointed out other reasons why it makes sense to incorporate writing to SLA and TBLT preoccupations. This addition, it has been claimed, may need a rethinking and expansion of current conceptualisations of constructs (e.g task) and explore “more diverse and necessarily more complex communicative events” (p. 4) than those who have usually been at stake in TBLT research so as to give credit for the complex nature of the meaning- making activity written practices encompass. This expansion of constructs and understandings would be beneficial both to SLA-TBLT theorising and research providing new insights into language development, learning and acquisition. Byrnes and Manchón (2014b) commented on several areas which would benefit from this rethinking. In the first place, core tenets in TBLT should be problematised along with certain theoretical predictions. This relates mainly to the issue of cognitive complexity and the need to address the degree of problem-solving in writing since the processing demands posed by different types of tasks used in speech production may greatly differ when applied to writing. Secondly, and related to this last aspect regarding the

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. different processing demands of different types of tasks across modalities, the range of tasks needs to be enlarged to account for the distinctive nature of meaning-making in writing since it should not be taken for granted that tasks designed for speaking necessarily can be applied to writing exactly in the same way and expect the very same outcomes. Moreover, task conditions also have to receive due attention, above all, the differential temporal dimension of writing is to be acknowledged in that it may derive in distinct learning opportunities. Last but not least, certain methodological aspects have to be reviewed, mostly the applicability of complexity, accuracy and fluency measures (CAF) which have been widely used to measure performance in oral production. The suitability of the CAF measures across modalities will need to be tested and surely adjusted when referring specifically to complexity and fluency.

It has been mentioned in earlier sections that different modalities of production may entail different learning opportunities due to their differential characteristics. What follows is an account of two models for language processing in the two modalities. In the first place, Levelt´s (1989) model for speech production will be presented with an emphasis on how the characteristics of oral production interact with the different stages involved and their impact on language development and learning. Then, Kellogg’s (1996) and Haye´s (2012a) models for composing processes will be explained in connection with the distinctive features of the written mode and the learning possibilities that writing practices offer.

Being the present dissertation a comparative study of task repetition (to be addressed in a forthcoming chapter) across modalities, it is relevant for the purposes of our research to explain and understand the differential nature of speech production and writing, whose characteristics are likely to provide a different context and diverse learning opportunities as we shall see.

I.5.1. THE NATURE SPEECH PRODUCTION. In this section we review Levelt´s model for speech production as a necessary background for comprehending the nature of oral output production and how its characteristics may impact language learning. Also, it supports the basis on which the claim for embracing task repetition to foster language development was made, issue which will be tackled in the next chapter of the present dissertation.

Levelt´s model of language processing for speech production (1989) conceives three phases: conceptualization, formulation and articulation, as shown in Figure 1 below. Figure 1 also accounts for the processes involved in message reception. However, we are primarily concerned with speech production processes and have therefore marked the most relevant

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING.

Figure 1. Levelt´s model for speech production as in Bygate (1996).

stages for our purposes in our study. Conceptualization deals with the content of the message, that is, the meaning to be communicated whose information is drawn from several long-term memory stores. Once it has been developed, the message is encoded into language, that is, the meaning is transformed into form. For that purpose, the formulator selects the adequate language from lexical and grammatical stores and the message is linguistically encoded. And finally, articulation is concerned with realising the message into an utterance. Additionally, a monitor thought to work within conceptualization, checks for appropriacy of both meaning and form and makes adjustments both covertly (prior to articulation) and overtly (subsequently to articulation).

These phases are likely to be fulfilled one at a time and consecutively. Therefore, L2 learners have to struggle with creating a message, finding language so as to create adequate meaning-form mappings to express their intended meaning and actually uttering the message in order to convey his/her own ideas under the time constrains that characterize immediate oral communication. Bygate (2001) even adds a further problematic factor: the irregularities and redundancy of languages that suggests pose specific problems for L2 learners who may reduce

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. their work at certain phases in order to accomplish the speaking process. The temporal issue of speech production processing is related to Skehan´s Limited Attentional Capacity Model (1998). Skehan´s model contends that attentional resources are limited and that learners are not able to pay attention to the three dimensions of performance at the same time. Furthermore, he suggests that learners would prioritize meaning over form what would lead to greater fluency at the expense of complexity and accuracy. In some cases, fluency can be accompanied by either complexity or accuracy, but never both, what suggests a competitive relation between these two dimensions referred to as trade-offs.

The purported time pressure along with other characteristics of oral language, such as its ephemeral and evanescent nature pose different problems to L2 learners and have different effects on linguistic performance. Oral language is “here one minute and gone the next” (White, 1981:2 as cited in Nunan, 1989) what makes it difficult for L2 learners to FoF and pay attention to language itself and the language processes thought to be conducive to development and learning commented in the previous section. The elusive, fleeting, short-lasting nature of oral language and also the fact that it is time-constrained makes it difficult for speakers to monitor their production in contrast to what may happen in written production, where there is ample time and such timed-nature may have implications for language learning (Cumming, 1990; Manchón 2011a; Williams 2012), as it will be reviewed in next sections. Consequently, speakers´ opportunities for language development and learning during speaking decrease as compared to writing. These purported characteristics of oral language may also interfere with the different functions mentioned in the Output Hypothesis namely, the consciousness-raising, hypothesis testing and metalinguistic functions. To start with the latter, “metalinguistic problem solving [may be] more transparent in composing than in conversation” (Cumming, 1990: 487). The cognitive overload speakers meet themselves face to face with is likely to result in scarce opportunities to reflect on language since they have to do so online while devoting much attention to other aspects of the oral task, such as planning the rest of the utterance and encoding it into appropriate and adequate language, administering interlocutor´s reactions or processing other interlocutor´s input (recasts or even body language) and monitoring subsequent production accordingly at the same time. Therefore, writing may be a more propitious environment than speaking for the deployment of metalinguistic L2 knowledge (Ellis, 2003; Wolff, 2000) where time pressure and the impermanent nature of oral language may represent a drawback for linguistic reflection. These characteristics of oral language may hinder hypothesis-testing alike. Not only may learners struggle with putting their L2 knowledge to the test appropriately– retrieving and analysing explicit knowledge, even less implicit knowledge–

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. resorting to the language forms they know will meet the task requirements, which may result in turn in a simplified version of their output, but also, they may fail to notice the holes in their L2 system, in connection with the consciousness-raising function of the Output Hypothesis, regarding the language with which they intended to convey their message since, more often than not during speech production, attention necessarily needs to be divided to the different processes in a parallel manner. What is more, it is plausible that they miss subsequent input in the form of (corrective) feedback or even they may not consider it as being so.

To summarise, the characteristics of oral language, i.e. time-constrained, short-lasting, fleeting nature and impermanence may represent certain disadvantages while producing oral output. However, these drawbacks have been tackled by introducing different task implementation variables in the task cycle such as pre-task planning or task repetition, the latter being studied with in the present research and addressed in a forthcoming chapter.

I.5.2. THE NATURE OF L2 WRITING: THE ROLE OF ATTENTION. Archibald and Jeffery (2000) proposed four main areas in writing: the process, the product, the context and the teaching of writing. For our purposes here, we will focus on the first two, although it is not our intention to overlook the importance of the other two areas since writing is indeed a social phenomenon (Manchón, 2013) and the teaching of writing and L2 writing is of great importance in both second language (SL) and foreign language (FL) settings. In what follows we will synthesize relevant theoretical positions on the manner in which the different psycholinguistic processes involved in writing and the action (or reaction) taken upon the written product i.e. written corrective feedback, may promote language development. For this purpose, we will start by characterising writing and will do by discussing well known models of writing (essentially Kellogg, 1996; Kellogg, Whiteford, Turner, Cahill & Mertens, 2013; and Hayes, 2012a; 2012b). On the basis of it, we will then identify the characteristics that make writing a unique environment for language development and learning, making then reference to relevant positions in the field of L2 writing and second language acquisition. We will then discuss the role of written corrective feedback as an inherent part of the composing process and its learning potential in this process.

Kellogg´s model (1996; see also, Kellogg et al., 2013) proposed six different processes and subprocesses i.e. planning, translating, reviewing (divided into reading and editing) and motor output processes (programming and execution). Similarly to what will be discussed in Haye´s model (1996, 2012a, 2012b) below, through planning processes learners plan the content

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. of their message which is linguistically encoded into language (translating). Motor output processes, programming and execution, are in charge of getting ideas into the written text through motor movements. Reviewing the written text comprises both reading and editing, if needed. These processes are not developed in a linear fashion. Rather, “the process of writing involves recursive operations of planning, sentence generation and reviewing during the drafting of a text” (Kellogg et al., 2013: 161). The issue of recursivity within the writing processes will receive due attention later in this section. Hayes´ is one of the latest and most influential attempts to modelling writing (1996, 2012a, 2012b) and is shown in figure 2 below. He describes four different processes (marked in figure 2 above)– planning (proposer in Hayes, 2012a),

translating, transcribing and evaluating. Through planning processes, writers formulate the content of the message they intend to convey. First, learners engage in goal setting, generation and organisation of ideas. This plan serves as input for translation, which turns the pre-planned message into surface structure as linguistic knowledge drawn from several grammatical and lexical stores is retrieved. Writers then evaluate if their linguistic choices meet the goals set during planning processes and revise if needed. Finally, transcribing deals with the proper

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. linguistic encoding after translating the message to the surface structure. As can be withdrawn from figure 2, revision processes may take place at any moment throughout the different processes mentioned, not only at the translating stage but also, while planning and transcribing ideas into text. Hayes´ model reports adequately the importance of planning processes in composing by affirming that these entail per se a complete writing process (2012a) and the text written so far since it interacts with translating and transcribing processes and may be altered upon revision. This interaction among processes suggests that they are recursive in nature.

The processes involved in writing take place in a cyclical manner, resulting in the recursive nature of writing processes. It is a two-way interaction between reflection and text production processes that take place at the same time in one same piece of writing (Galbraith, van Waes & Torrance, 2007, studied via Manchón, 2014b). Moreover, Manchón (2014b) adds that “writers necessarily have to engage in continuous decision-making with respect to the distribution of attentional resources among the various goals pursued and aspects of text production processes competing for attention” (p. 35). Therefore, writers have to switch back and forth continuously during writing and engage in the different processes concurrently depending on their actual needs or goals at each stage of the composing process. This relates to Manchón´s re-shaping of the construct of “internal task repetition”, to be dealt in the next chapter. It is not a matter of one-at-a-time completion of stages as in spoken production.

In what follows we present several characteristics of written language which potentially facilitate language learning i.e. the availability of time, permanence and visibility of the written text and the problem-solving nature of writing.

Attention to meaning and form: The availability of time and the role of attentional resources.

Importantly for our purposes, it has been posited that simultaneous engagement in both the creation of meaning and in linguistic processing can potentially enhance L2 learning (Cumming, 1990; Nitta & Baba, 2014). This parallel attention to both meaning and form is more likely to occur in writing tasks since, by definition, these are not hindered by the same time constraints as oral tasks do (Manchón, 2011a, 2013; Williams, 2012). As a consequence, more attentional resources and greater access to long-term memory and working memory are at learners´ disposal during writing than during speech production, thus increasing the possibilities to focus on form, test learners´ hypothesis, reflect on language and engage in syntactic processing, all four processes thought to be conducive to language learning and acquisition as mentioned earlier (Manchón, 2013; Swain, 1985). Other authors, such as Wong (2001), also

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. support the argument that learners are able to focus on form and on meaning at the same time in writing but not in speaking. It results, for instance, in what Kormos (2014) calls extensive online planning i.e. planning the content of the output while giving it a linguistic form, more likely to be achieved in the written mode given the ample time on task most forms or writing offer. More precisely, Manchón and Williams (2016) claim that focusing in form and meaning at the same time is not only a possibility in writing. Rather, they argue that production processes may require focusing on form and meaning and that this simultaneous attention is potentially facilitative of L2 development. This doubled attention to form and meaning at the same time is more likely to be achieved in writing due to the fact that during writing learners count on greater time available and this permits them to devote attentional resources to both form and meaning.

In relation to attentional resources and tasks, it is relevant to make explicit reference to Skehan´s Limited Attentional Capacity Model (1998) and to Robinson´s Cognition Hypothesis (2001). These two theories suggest different predictions regarding the allocation of attentional resources during task completion and their resulting effect on different dimensions of task performance (Complexity, Accuracy, Fluency – CAF). As stated before, Skehan´s model suggested that learners´ attentional resources are limited and that they are not able to pay attention to the three dimensions of performance at the same time, prioritizing meaning over form resulting, in turn, in greater fluency at the expense of complexity and accuracy. On the contrary, Robinson´s Triadic Componential Framework suggests that learners have available different attentional resource pools to which the different dimensions of cognitive complexity belong. He, then, proposes that increasing the cognitive demands of the task along resource- directing (vs. resource-dispersing) variables may direct learner´s attention to form (Gilabert, 2007) leading to greater complexity and accuracy. On the other hand, if the cognitive demands of the task are increased along the resource-dispersing variables these two dimensions are expected to decrease (Robinson & Gilabert, 2007). However, despite the abundant research testing both models (Grandfelt, 2008; Kormos, 2014; Kuiken & Vedder, 2011; Kuiken & Vedder, 2012; Tavakoli, 2014) there is no clear support for one over the other yet.

Following from this, it may be argued that the greater availability of time of writing tasks permits cognitive resources to be freed-up and, along with greater access to attentional resources that most types of writing entail (with the exception of computer-mediated synchronous writing interchange), they enhance the possibilities not only to focus on meaning, but also on form that, as mentioned earlier, it is a process thought to assist language development and learning (Cumming, 1990; Nitta & Baba, 2014). As a consequence, learners would be able to test their hypotheses about new language forms they may not have completely mastered yet while

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. processing meaning at the same time. The fact that writers are more in control of their attentional resources also allows them to potentially engage in problem-solving strategies, as we shall see later (Manchón & Roca de Larios, 2007). The off-line nature of most writing activities somehow imposes less time constrains to learners who are able to devote more time to planning, retrieving linguistic knowledge, shaping output, identifying holes in their L2 repertoire and/or processing input i.e. feedback. This slower pace at which writing takes place, allows writers for pauses where to plan, revise, reflect and “opens up the space for emergent language users to take the needed extra time in order to search all available knowledge (implicit or explicit)” (Ortega, 2012: 406). In addition, having access to extra time may assist learners to notice holes in their linguistic repertoires since they are more likely to become aware of or their language shortcomings and problems (Swain, 1998) making them access and analyse their explicit knowledge or even process their implicit knowledge (Manchón & Williams, 2016) in search for a solution, making it more explicit and available for subsequent production. This attention to formal aspects of language is potentially conducive to language development. Should they be unable to do so, they may be willing to consult external sources or even receive input in the form of written corrective feedback.

Finally, the personal pace at which writers can communicate when writing, at least in individual writing conditions, may also boost learner motivation (Manchón, 2013). In words of Leki, “pen and paper […] are patient, and flexible. They adapt to any level of proficiency and bear any alteration or adjustments the writer might care to make” (2001: 206). Therefore, writing renders itself as a more suitable teaching-learning medium of language instruction where learners can work at their own level without restraining the rest of their partners.

The permanence and visibility of writing.

Another characteristic of written language, its permanence and visibility, is likely to prompt learners to reflect on language as well, contributing to the production of the aforementioned “pushed output” (Swain, 1985), a more “precise, coherent and appropriate” form of output that accounts for greater learning opportunities. This permanence of the written text and the feeling that it may be externally judged may prompt learners to set up higher goals and demand more of themselves (Leki, 2001; Manchón 2013) when writing encouraging deeper engagement in FoF processes and language reflection leading to development and, in turn, to language learning since this form of output induces learners to pay attention to language concerns, test their L2 hypotheses and raise their metalinguistic awareness during as well as after production. The

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. pursuit of these higher goals set due to the permanent nature of written output is enhanced by the greater availability of time referred to previously. Having more time on task, learners can deploy more and more complex linguistic resources to meet their goals and in order to do that, they need to reflect on language, as outlined above, and engage in processes leading to language development.

Also, the permanent nature of writing will make it easier for learners to compare their explicit knowledge to their output production prompting them to reflect on language and focus on form as well as engaging in the process of cognitive comparison (Manchón & Williams, 2016). In the same way, this extra time may allow learners to compare their output to subsequent input i.e. written corrective feedback. The permanence and visibility of written corrective feedback along with the greater availability of time to process it is likely to result in greater opportunities for reflection.

The problem-solving nature of writing.

Worth mentioning is also the problem-solving nature of writing. Manchón and Roca de Larios (2007) suggest that writing in L2 elicits deep problem-solving behaviour with potential learning benefits if learners engage in meaningful and challenging L2 production not only through consolidating already acquired linguistic knowledge but also generating new knowledge (Cumming, 1990, Swain & Lapkin, 1995). Once more, this is related to the temporal dimension of written language production, among other factors. Theoretically, having more time to devote to the different processes in written production would prompt writers to engage in deeper problem-solving than would speakers during speech production, in which speakers may feel the need to deter problem-solving and embrace problem-avoiding strategies (Manchón & Roca de Larios, 2007) so as to successfully complete the task. As a consequence, this would result in a reduction of learning opportunities of speakers over writers. A first stage within the problem- solving activity while writing implies that writers need to decide which attentional devices to devote to the different demands the task may be imposing on the learner. This deeper linguistic processing induced by the problem-solving nature of L2 writing is likely to lead learners to engage in several language learning processes such as noticing, metalinguistic reflection or retrieval and analysis of both explicit and implicit knowledge (Manchón & Williams, 2016).

An inherent part of writing which has even been framed as another subprocess within writing practice is written corrective feedback (Manchón & Williams, 2016). As Nunan (1989) emphasised, “the writing teacher who subscribes to the product approach will be concerned to

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. see that the end product is readable, grammatically correct and obeys discourse conventions” (36, emphasis added). However, when the written product is not grammatically correct, teachers may well respond to it through written corrective feedback, which, as we shall see in the next section, enhances different cognitive processes leading to language development intensified by its defining characteristics.

As it has been discussed in the previous sections, the nature and characteristics of oral and written language create different environments for output production and, in turn, may result in diverse opportunities for language development and learning. These theoretical predictions have been tested in different strands of empirical research, which are to be discussed in forthcoming chapter III. Research on modality-related effects has shown differential effects of mode on language performance, as we shall see later. Oral output production has also been studied in connection to task repetition, an implementation variable with which enhanced focus on form stages are associated (Bygate, 1996). With respect to writing, it has been posited that literacy practices may help learners to analyse and consolidate previously acquired second language knowledge (Cumming, 1990; Manchón, 2011a). Moreover, the importance of written corrective feedback and its potential to promote language development, to be dealt with in the next section, should not be overlooked.

I.5.2.1. THE LANGUAGE LEARNING POTENTIAL OF WRITTEN CORRECTIVE FEEDBACK. An inherent part of writing which has even been framed as another subprocess within writing practice is written corrective feedback (Manchón & Williams, 2016). As Nunan (1989) emphasised, “the writing teacher who subscribes to the product approach will be concerned to see that the end product is readable, grammatically correct and obeys discourse conventions” (36, emphasis added). However, when the written product is not grammatically correct, teachers may well respond to it through written corrective feedback, which, as we shall review in the present section, enhances different cognitive processes leading to language development.

WCF has been explored from different perspectives in the fields of L2 writing and SLA. From the lens of the field of L2 writing, WCF was aimed at dimensions of writing to make learners become better writers. That is, it was provided in order to teach learners how to organise ideas, the typology of different types of written texts or to develop their arguments consistently. On the contrary, the position from SLA was to regard WCF as a tool with a potential for language learning, due to the fact that it directs learners´ attention to form, as will be discussed later in this section. However, some SLA scholars have objected to such a view. Truscott (1996)

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. questioned the purported benefits associated with the provision and processing of written corrective feedback (WCF), and this has led to an intense debate in the field (Ferris, 1999, 2003, 2004; Truscott, 1996, 2007). Truscott (1996, 2007) based his opposing views about the ineffectiveness and damaging character of CF under three major claims. Firstly, he argued that, even if learners may momentarily uptake certain information from input, it is impossible to retain it a made it available for future use, may be because of his views on the dichotomy learning vs acquisition we referred to earlier. A second point relates to learners´ readiness (Pienemann, 1989), a concept already mentioned earlier as well. Truscott assumed that a learner is not able to acquire a form if (s)he (or his/her interlanguage) is not “ready” for it, that is, the form is far beyond the learner´s actual linguistic development. To support this argument, he affirmed that learners incorporate new forms in connection to previously acquired knowledge and if the new input is too complex to be incorporated to the learner´s system, it will not be taken as uptake. Furthermore, he claimed that tuning feedback to learners´ developmental readiness was an extremely demanding even impossible task to accomplish and the practice should, therefore, be abandoned. Finally, he questioned the teachers´ ability to provide corrective feedback accurate, consistent and systematically to their learners. The answer to Truscott´s claims did not wait long. Ferris (1999, 2003, 2004) counter-argumented most of Truscott´s claims on the grounds of the research evidence on which he drew to support his opinions, that not all teacher correction is flawless and inconsistent suggesting that “error correction-that which is selective, prioritized, and clear-can and does help at least some student writers” (1999: 4) and offered an account of research showing the effective nature of corrective feedback to dismount Truscott´s viewpoint.

This controversy is also connected to the differentiation between learning and acquisition coined by Krashen (1982), to which we made reference earlier. Krashen does not see a role in acquisition for the learning that comes from instruction nor, in the same way, for the learning derived from corrective feedback unless the learner has previously acquired (not learnt) the form on which corrective feedback is provided (Bitchener and Ferris, 2012). Again, assuming an interface position (Dekeyser, 2001, 2007) and the possibility of explicit knowledge aiding in the development of implicit knowledge through practice, we are led to consider corrective feedback as a facilitator factor which can lead to language acquisition. Practice then is thought to be the intervening factor in converting controlled (explicit) knowledge to automatic (implicit) knowledge (Anderson, 1993) which is the knowledge system L2 learners mostly draw on when they reach the stage of L2 acquisition. The question if corrective feedback is conducive to language learners may well not be the most adequate. It has much more theoretical and applied

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. sense to ask ourselves how it can bring about beneficial effects (Evans, Hartshorn, McCollum and Wolfersberger, 2010). Nowadays, most researchers do acknowledge that feedback can play a facilitating role in language development and contribute to language learning and, thus, this is the perspective we adopt. Much at the heart of the feedback debate relies the distinction between the two different dimensions of WCF, which becomes pertinent at this point. Manchón (2011a, 2013) differentiated between feedback for accuracy and feedback for acquisition. The former relates to feedback directed at promoting immediate accuracy in the short term whereas the latter aims at developing language learning understood as the consolidation of linguistic knowledge. That is, feedback directed at promoting durable changes in learners´ interlanguage and, in that way, assist acquisition.

Attention in language learning through written corrective feedback.

It has already been mentioned that a necessary pre-requisite for WCF to be effective– and for learning in general, is learner´s attention. As Schmidt (2001) points out: attention is what allows speakers to become aware of a mismatch or gap […] between what they produce and what proficient target language speakers produce. (p. 6). Ellis (1995) even claimed that there cannot be acquisition without noticing, and there cannot be noticing without attention. Schmidt (1990) established three different levels of awareness. In the first level, there is awareness at the level of perception, which may be conscious or not. At this stage, learners may apperceive some salient form in input, whether consciously or unconsciously, but there is nothing beyond this apperception. Second level would be awareness at the level of noticing, which is conscious and involves focal awareness. Finally, there is awareness at the level of understanding, which is conscious and even implies conscious analysis between what has been noticed in the input and prior knowledge (even that knowledge gained from previous encounters with input dealt with at the level of understanding). If learners notice a hole in their interlanguage (IL) when producing output, they may be more receptive to incoming input. Consequently, if learners are provided with written corrective feedback and devote attention to it, it may eventually become intake and be internalised in the learner´s linguistic system. Additionally, learners do need to pay attention to the feedback provided in order to notice the difference between their output and the TL norms and conventions as well, so as to become aware of the mismatch (noticing the gap). Despite paying conscious attention, they also have to go beyond mere detection of errors (awareness at the level of detection) and engage in a deeper processing of the input they have been provided with (awareness at the level of understanding)

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING.

(Qi & Lapkin, 2001) if this input is to be converted into intake and incorporated to the learner´s explicit knowledge system. O´Brien also claimed that it is a must that learners “act” on feedback in order to be effective (2004: 13). This is more likely to be achieved when processing CF in the written modality due to the greater availability of time to process input which also allows for more ample opportunities to engage in the process of “cognitive comparison” (Manchón, 2013: 100), a process whereby learners notice new knowledge in the input. Therefore, if learners internalise new knowledge from written corrective feedback, this newly gained explicit knowledge is available for subsequent output productions providing that learners reflect on language and engage in focus on form processes during the composing process. The detached temporal dimension of writing facilitates the retrieval of this explicit knowledge as opposed to the immediate, time-constrained nature of speech production. Having more time on task, learners are able to do this and also test their hypothesis about the new linguistic forms incorporated from the WCF received. These predictions go in line with the aforementioned interface position and its claims regarding the possibility of explicit knowledge assisting in the development of implicit knowledge though practice i.e. output production.

Interactionist accounts on CF have majorly arisen from oral language. However, as a form of output production on which feedback can be provided, certain inferences are to be made. They made references to both positive and negative evidence while negotiating meaning in interaction and contended more specifically that it is negative evidence (“negative feedback” – Long: 1996:414) the one leading to L2 development. Also, it emerged the claim that if learners are to incorporate linguistic forms to their L2 system, they need to pay attention to form and structure when receiving input, which in this context would mean to pay attention to negative evidence i.e. negative feedback. In this sense, it is CF what makes learners focus, pay attention to form (Bitchener, 2012; Bitchener and Ferris, 2012) whether in oral or written format.

The role of explicitness in written corrective feedback.

An important variable to take into account when providing feedback is the degree of explicitness, considered a crucial factor to make it beneficial for learners (Sheen, 2010). García Mayo (2007), drawing on evidence from the domain of oral CF, also suggested that feedback saliency is more likely to be noticed by learners and therefore assist L2 acquisition and Bitchener and Ferris (2012) claimed that it was high proficiency learners who were able to take greater advantage of oral CF than low-proficiency learners. This is so because of the ephemeral and impermanent nature of oral language (including oral CF). Advanced learners haver greater

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. linguistic resources and are able to process linguistic information more easily while low- proficient learners would struggle to notice feedback in the immediacy of oral communication due to the cognitive overload of having to conceptualise, encode and produce speech. Sachs and Polio (2007) similarly suggested that the more prominent visual saliency of written corrective feedback is a feature that can contribute to turn learner´s input into intake. The written modality emerges then as an environment in which not only is CF permanent and always explicit but also learners are able to notice and engage in its processing more easily at their own pace due to the offline nature of writing. Notwithstanding, it has also been affirmed that less explicit types of written corrective feedback “may not be sufficient for relatively low proficiency learners who need written CF with more explanation and illustration” (Bitchener and Storch, 2016). Linking this time issue to the different levels of awareness that Schmidt proposed (see above), the detached time nature of written corrective feedback processing may allow learners go further the level of noticing and engage in awareness at the level of understanding, analysing and processing information in input (WCF) enjoying greater possibilities to consolidate pre-existing knowledge or internalise new one in the form of new hypotheses to be tested in forthcoming opportunities for production. Thus, due to the nature and characteristics of WCF, it can modify and shape learners´ interlanguage and facilitate acquisition as it has been posited that learners´ engagement with feedback is related to subsequent uptake (Ellis, 2010; Storch & Wigglesworth, 2010). As stated earlier, WCF is always explicit but there are certain forms of WCF, like metalinguistic explanation, which are more explicit than others (e.g. circling of errors) in that they supply learners with more information about the source of the error and how to correct it. However, this dichotomy explicitness-implicitness of WCF should not be regarded as a matter of either/or but as a continuum from a higher to a lower degree of explicitness.

Languaging and linguistic reflection through written corrective feedback processing.

As stated before, the processing of input in the form of written corrective feedback is key if learners are to incorporate new knowledge to their L2 system. Depth of processing constitutes an important variable in bringing about language learning through writing and WCF processing (Manchón & Vasylets, in press). It is predicted that greater retention of WCF is likely to occur when learners engage in the process of awareness at the level of understanding (Schmidt, 1990, 2001) we made reference to earlier, rather than awareness at the level of detection (mere detection of errors). Awareness at the level of understanding involves conscious linguistic processing and reflection on the nature of and possible solution to language problems

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING.

(indirect forms of WCF do not provide a correct form for errors) if a correct form has not been provided through direct forms of WCF (Cerezo, Manchón & Nicolás-Conesa, in press). However, Manchón (2011a) suggested that it might be necessary some short of pedagogical intervention to foster “deep processing behaviour” (p. 58) when learners are provided with feedback for acquisition. The processes of awareness at the level of understanding is associated with hypothesis testing and rule formulation, and metacognition (Leow, 2001; Manchón & Leow, 2004 as cited in Cerezo, Manchón & Nicolás-Conesa, in press), which are claimed to lead to language learning on condition that learners engage in explicit, intentional processing (Bitchener, 2016, 2017; Bitchener & Storch, 2016; Polio, 2012). Such processing is endowed by the greater availability of time during writing and WCF processing and the greater saliency and permanence of both the written output and WCF (Cerezo, Manchón & Nicolás-Conesa, in press).

Scope of written corrective feedback.

Before moving on, we should make reference to certain distinctions within the field of WCF. The first of these comprehends unfocused WCF, sometimes referred to as comprehensive, and focused WCF, also known as selective. On the one hand, unfocused WCF targets every error in a learner´s text, disregarding typology. This is perhaps the most widespread approach to WCF in L2 classrooms worldwide. Even so, learners expect their all errors to be corrected (Ferris, 1995, Ferris and Roberts, 2001; Leki, 1991). On the other, focused WCF are corrections directed to one or more specific error categories E.G. the English article. This is partly connected Pienemann´s notion of readiness mentioned above. It could be the case that adapting WCF tailoring it to learners´ developmental stage results in more effective learning than forcing learners to focus on a wide range of errors, which may overwhelm their processing capacity, mostly if they are low proficiency learners (Bitchener, 2012). Moreover, if WCF is provided on one single (or a few) error category, learners will probably make greater use of their attentional resources to focally attend to such feedback while at the same time understanding why it is an error and how to correct it (Bitchener and Storch, 2016).

Types of feedback.

Similarly, we can distinguish between different types of feedback namely direct, indirect or metalinguistic explanation and, additionally, we will review self-initiated (self-correction) WCF. This distinction is essential for our study since the use of direct, indirect and self-correction

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. comprise some of the methodological conditions explored in the study to be reported later. Bitchener and Storch (2016) define direct feedback as “a correction that not only calls attention to the error but also provides a specific solution to the problem” (p. 148, emphasis added). Indirect WCF, on the contrary, indicates where an error has occurred “through circling, underlining, highlighting, or otherwise marking it at its location in a text, with or without a verbal rule reminder or an error code, and asking students to make corrections themselves” (Ferris, 2002: 63). Finally, metalinguistic explanation “explains and/or exemplifies accurate target-like uses of linguistic forms or structures” (Bitchener, 2012: 355). This form of feedback could be beneficial insofar it provides new (or not yet fully acquired) knowledge and raises awareness about explicit grammatical rules (Bitchener and Storch, 2016). It has been posited that many teachers combine both direct and indirect WCF strategies (Hendrickson, 1980 via Bitchener and Storch, 2016) but it has been also claimed that less proficient L2 writers may fail to provide corrections on their own errors (Brown, 2007; Ferris, 2002). Therefore, indirect forms of WCF may be more adequate for relatively advanced L2 learners whose linguistic repertoire may be sufficient to provide corrections for their erroneous written utterances (Bitchener, 2012; Bitchener and Ferris, 2012; Bitchener and Storch, 2016).

Indirect forms of feedback have been claimed to be more engaging since they promote deeper linguistic reflection and problem-solving (Bitchener, 2012; Bitchener and Ferris, 2012; Lalande, 1982) and this sets a favourable scenario for long term acquisition. However, as rightly noted by Bitchener and Ferris (2012), if we understand acquisition as the internalisation of new knowledge, indirect feedback has a very limited role to play. Advocates of direct WCF suggest several reasons why it may be more helpful than other types of feedback. Firstly, it reduces learners´ confusion and anxiety they may encounter when interpreting indirect feedback, these forms actually provide enough information to correct the errors and to confirm/refute hypotheses possibly tested, and it is more immediate (Bitchener and Ferris, 2012).

Source of written corrective feedback.

Usually, WCF is teacher-driven and, mostly, instructors are the source for WCF provision. However, there are other possible sources such as peer feedback or self-correction. Through the latter procedure, learners must either correct, edit their work, or both. Ideally, in a similar way as with indirect WCF, self-correction should be a way of promoting engagement and motivation while attempting to put to the test one´s own knowledge in the search for errors in a previously written text. Yet, learners who are not confident enough in their linguistic knowledge or ability

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. may feel overwhelmed and even discouraged with such task. Some ways to tackle this issue as suggested in Bitchener and Ferris (2012) are strategy training for self-edition, focus on target forms previous to self-correction or the use of additional resources.

Mediating factors in the processing of written corrective feedback.

Another issue that may mediate the potential beneficial effects WCF theory accounts for is learner variables (Bitchener & Storch, 2016). Learner-external variables, context and setting, whether FL or SL, can make a difference mainly in connection with other learner-internal variables such as beliefs, aims and goals. Regarding learner-internal variables we should further differentiate between those of a cognitive nature (working memory and language learning ability) and those of a motivational-affective nature (goals and interest and attitudes and beliefs). Working memory is of limited capacity, which means that the amount of information it can process at a given moment is finite. It involves processes such as noticing, hypothesising and restructuring. Language learning aptitude is a “special ability for learning languages” (Bitchener & Storch, 2016: 27) which may make it easier for learners to engage in the various stages of cognitive processing such as processing input (WCF) or engaging in problem-solving. The specific goals set by each language learner regarding the purpose of their learning trigger motivation (intrinsic or extrinsic) and it is motivation what fuels why learners decide to do a given activity, for how long and the amount of effort the will put in it. Learners who established their goal properly will count on higher motivation than those with less established goals. Finally, attitudes and beliefs regarding language learning in general or to particular aspects of the process can potentially mediate whether the learner engages in the language learning process or not. For example, if learners regard WCF as potentially unhelpful it is likely that they will not attend to it, impeding the rest of the cognitive processes in the following stages conducive to language learning. It may be the case that for learners to consolidate and proceduralise knowledge they have to hold a motivated learning behaviour.

As evidenced above, different variables have been shown to mediate effects of WCF, explicitness, type of WCF, range of errors on which it is provided or learner variables. However, written corrective feedback is regarded as a facilitator factor helping L2 development provided that learners pay attention to and engage in WCF processing with potential language learning effects. WCF is then thought to lead learners into engaging in FoF processes leading to increased performance, mostly in terms of accuracy measures, language reflection and encourages explicit knowledge analysis and re-structuring. In the oral mode, FoF processes have been fostered in

CHAPTER I. TASK-BASED LANGUAGE LEARNING AND TEACHING. different ways. One of the implementation variables designed to do so, task repetition, is to be reviewed in the following chapter.

CHAPTER II. TASK REPETITION AND LANGUAGE LEARNING.

Task repetition (TR) has attracted plenty of attention within TBLT-oriented research which has even become one of the central lines of research lines in TBLT empirical research agenda. Fruitful research has been carried out under this paradigm in the oral mode (e.g. Ahmadian, 2011; Ahmadian & Tavakoli, 2010; Balehgizadeh & Derakshesh, 2012; Bygate, 1996, 2001; Bygate & Samuda, 2005; Fukuta, 2015; Gass, Mackey, Álvarez-Torres & Fernández-García, 1999; Hawkes, 2012; Kim & Tracy-Ventura, 2013; Lynch & Maclean, 2000, 2001; Mojavezi, 2013; Van de Guchte, Braaksma, Rijlaarsdam & Bimmel, 2015). In contrast, task repetition in writing has received minimal scholarly attention. To the best of our knowledge, only Baba and Nitta (2014), Nitta and Baba (2014; 2015; in press) and Amiryousefi (2016) have put claims in the task repetition literature to the empirical test in the written modality.

According to Ellis (2012), TR entails repeating the task “without any changes to the task, or by modifying the design of the task or by manipulating one of the other implementation variables” (p. 202). More recently, further distinctions have been introduced and a tripartite classification of TR has been proposed (Manchón, 2014c), namely: exact task repetition, procedural task repetition and content task repetition. Exact task repetition would correspond to Ellis´ definition mentioned above, i.e. a task is repeated with no changes applied to the task. In procedural TR, the 2 iterations of the task involve the same procedure with a change of content, whereas in the case of content task repetition the content is maintained across iterations of the task and the procedures vary. We shall see how these TR modalities have been implemented in empirical studies in the next section. For our purposes in the study to be reported in the present dissertation, we operationalised task repetition as exact task repetition. That is, a task which is repeated with no alterations of content or procedures.

Another important distinction originally introduced by Bygate (2006) is that of “internal” and “external” task repetition. He defined “internal task repetition” as the repetition “encouraged by the demands of processing the input material and/or of preparing the intended task outcome” (p.173). On the other hand, he defined “external task repetition” as basically “repetition where the task requires students to repeat their talk” (p.173, emphasis added). These definitions exclusively make reference to speaking, evidence of the emphasis on oral language in TR matters. As we will see later, Manchón (2014b) has expanded this dual distinction in its application to writing.

CHAPTER II. TASK REPETITION AND LANGUAGE LEARNING.

In the sections that follow we first present the psycholinguistic rationale for TR in the oral mode. This is followed by an analysis of current expansion of current concepts and tenets in the field of TR in their application to writing, including a synthesis of relevant positions on expected learning outcomes of TR in the writing modality. Finally, the last sub-section will be devoted to the analysis of relevant variables that have received minimal attention in the TR empirical literature, with a special emphasis on learner proficiency.

II.1 RATIONALE FOR TASK REPETITION IN THE ORAL MODALITY. In order to counteract the effects of time pressure as well as the effects of the rest of the characteristics of speech on oral production mentioned in the previous chapter, Bygate (1996) explored the task implementation variable of task repetition (TR). Bygate (1996) assumed that when learners perform a task for the first time, they divide their attentional resources among the various aspects of the task demanding attention i.e. content, language and production. Learner´s familiarity with the task at hand therefore becomes a key issue. Through task repetition learners have already encountered the task once and, depending on the type of repetition learners engage with during the second iteration of the task they are already familiar with the content of the task, the procedures or even both. This familiarity with a task has been claimed to result in higher fluency and accuracy in the L2 (Foster, 2009). Along the same lines, Bygate (2001) suggests that when learners repeat a task, they “draw on the conceptual structuring of the information and on encodings which they have previously used” (p. 253), and this reduces the cognitive demands of the task, freeing up attentional resources which can then be strategically devoted to other aspects of the task. Again, this is connected to Skehan´s Limited Attentional Capacity Model (1998). It is claimed that in the first encounter with the task, learners prioritise meaning (resulting in increased fluency) over form. In second iteration with the task, learners need to devote less attention to the conceptualisation of the message i.e. meaning and are able to pay greater attention to form. Similarly, Bygate and Samuda (2005) suggest that when learners repeat a task, they have an “opportunity […] to rework their language” (p. 114) and claim that a shift in attention from content to form could promote language development and thus have potential learning effects. There is to say that, even though the term may evoke behaviourist (repetitive) drills, TR does not entail verbatim (word-for-word) repetition (Ahmadian, 2012). As Bygate (in press) also suggests, “when a task is repeated participants choose their own language to express their meanings and this language can vary” as there can be “additions or omissions” (p. 1-2). In this way, task repetition has been claimed to foster a shift in attention from meaning to form, prompting learners to engage in focus on form processes

CHAPTER II. TASK REPETITION AND LANGUAGE LEARNING. leading to increased performance (Bygate, 1996; 2001; 2006; in press). The first encounter with the task has been regarded as a sort of plan for language learners on which they can draw in the second iteration of the task leading them into a more sophisticated and appropriate performance (Ahmadian, 2011; Amiryousefi, 2016; Ellis, 2015). As Bygate suggested (1996: 141):

on the first occasion they [learners] will spend more effort than normal on the content of what they want to say, and on finding as quickly as possible word that will express the meanings. If learners the repeat a speech activity […] this will lead them to have to allocate less attention to the content and, enable them to allocate more attention to how the content is expressed.

Consequently, if learners repeat a task, their performance should improve in a number of ways: they may improve fluency, pay greater attention to accuracy, both in terms of adhering to TL norms and intended meaning, or they may work on the complexification and sophistication of the message.

In the domain of writing, there might be further possibilities to the ones mentioned by Bygate (2001). Thus, apart from focusing on form, learners may direct their attentional resources to other aspects of the task, such as idea generation or text organisation. Whatever the focus may be, the general claim is that TR emerges as a site with a real potential for language development. It may induce FoF, which could not be activated during the first encounter with the task due to the characteristic time-constrained nature of oral performance. It may even be the case that in a subsequent execution of a previous oral task learners could pay attention to both form and meaning just as writers do when composing a written text, creating optimal conditions for language learning and acquisition. As Bygate (2006) suggests, task repetition may help learners in creating meaning-form mappings, schematizing, internalising and mastering language so that it shapes and re-shapes the learner´s linguistic system. To sum up, TR sets a “particularly useful context for learning” (Bygate, 2006: 172) since it helps learners to create meaning-form mappings leading to increased performance with an assumed potential for language development and learning. Additionally, Bygate also suggested that task repetition could help learners i) receive all the pertinent feedback on their production since “not all relevant feedback can be provided to a learner on a single iteration of a task”, ii) process and analyse the feedback provided as “not all [feedback can] be integrated into a learner´s attention

CHAPTER II. TASK REPETITION AND LANGUAGE LEARNING. or memory on a single occasion” and iii) put into practice the new input received in a previous encounter with the task “in the context of upcoming iterations” (Bygate, in press: 12). These last assumptions make reference only to task repetition in the oral domain, but the situation may well not the same in writing, as Manchón (2014b, 2014c) suggested. In the next section, task repetition tenets are problematised in relation to the distinctive nature of the written modality.

II.2. TASK REPETITION IN WRITING: NEED TO EXPAND RESEARCH AND TENETS. The theoretical rationale for task repetition was laid out with oral language in mind and has been theorised “on account of the limitations that the on-line nature of oral communication imposes on the allocation of attentional resources” (Manchón, 2014c: 18) mostly, on linguistic processing. In contrast, it has been claimed that the distinctive temporal dimension of written communication presents a unique environment when implementing TR in the written modality. Thus, most forms of writing take place off-line, which means that the limited linguistic processing referred to above due to the timed-constrained nature of oral language do not apply to written output, which allows writers more time on task, which they can devote to engage in various focus on form processes during the first encounter with the task. As a consequence, learners can be more in control of their attentional resources while writing, which they can allocate to different aspects of the task concurrently, paying attention not only to meaning, but also to form during the first iteration of the task. This may result in enhanced performance as compared to tasks in the oral modality. Additionally, having the opportunity to engage in TR after completing the writing task already, enables learners to further engage in language reflection processes and may result in deeper linguistic processing. Furthermore, the first encounter with an oral task while engaged in TR has been claimed to act as a planning condition (Ahmadian, 2011, Ellis, 2015) upon which increased performance is achieved in the repetition of the task. However, due to the greater availability of time during writing, learners are able to plan their production from the very first encounter with the task. Williams (2012) suggested that planning may result in greater accuracy as a consequence of attentional resources been freed up. Therefore, the greater possibilities to plan production as a result of engaging in task repetition in writing should bring about greater increased performance and greater language development.

In addition, and with respect to writing tasks, the research on task repetition (TR) has completely ignored the role that written corrective feedback (WCF) may play as a form of TR, an issue that is related to Bygate´s (2006) distinction between “internal task repetition” and

CHAPTER II. TASK REPETITION AND LANGUAGE LEARNING.

“external task repetition”. Manchón´s reconsideration of these concepts expanded the definitions of both internal and external task repetition in reference to writing tasks (2014b) She claimed that “internal task repetition” also derives from “the distinctively timed nature and internal dynamisms of composing processes” (p.12) that are influenced by two interrelated factors. First, the interaction between reflection and text generation processes that takes place cyclically and, secondly, the recursive nature of writing processes. It is this cyclical and recursive nature of writing what enables writers to continuously shift back and forth among the different writing processes while composing, resulting in this “internal task repetition” i.e. repetition which consists of going through the same steps at different stages of the writing cycle – likely to induce learners into engaging in FoF processes which, in turn, may lead to language development and learning. The definition of “external task repetition” introduced by Bygate in reference to oral tasks can be easily adapted in the writing domain. Yet, it should be also adapted to encompass inherent features of written language and composing processes. Following Manchón (2014b), “external task repetition” should also be viewed as “the result of the revision processes that necessarily follow from the processing of feedback received on one´s own writing” (p.11). As she claimed herself (2014c), “the rationale for the provision and processing of feedback in writing is precisely to engage the learner in a form of task repetition […] in which his/her attention is drawn toward those dimensions of the task in need of improvement” (p. 21). In this way, WCF is what makes learners focus on form (while revising the previously written text) in the written modality while this focus on form stage is addressed through TR in speech production. Moreover, research on WCF, as we shall see in the forthcoming chapter, is claimed to report greater gains that those achieved by merely repeating the same writing tasks.

Bearing in mind the above discussion, it appears that the different characteristics and the different processing demands of both modalities of production, oral and writing, may well result in different effects on TR. Nevertheless, most of these claims are untested assumptions in need of empirical validation, hence the relevance of the present PhD dissertation with its focus on the effects of exact external task repetition across modalities, looking at the same time into the effect of different types of WCF in TR in writing.

II.3. MEDIATING FACTORS IN TASK REPETITION: THE CASE OF LEARNER PROFICIENCY. There are a number of variables which may influence potential outcomes of tasks. These include the learning context, the type of task to be repeated and learner factors (Ellis, 2012; Hayes, 2012a; Manchón, 2014b; Robinson, 2007a; 2011) and these factors are likely to mediate

CHAPTER II. TASK REPETITION AND LANGUAGE LEARNING. potential learning effects of task repetition as well. TR has been studied across different learning contexts, both second (SL) and foreign language (FL) settings, arriving at similar results. Likewise, the range of tasks types used in the different studies analysing the effects of this implementation variable has also been rather wide, as it will be discussed in the next chapter. However, to the best of our knowledge, learner variables have not received due attention in this respect. Very few studies have reported information regarding learner related variables and, those who have, have mainly focused on the motivational aspect of TR (Hawkes, 2009; Nitta & Baba, 2014). Other factors, i.e. proficiency level of the participants, have hardly been addressed as variables in studies of task repetition. Bygate (in press) claimed that TR would function in the same way across levels of proficiency on the basis of previous studies (Bygate, 2001; Lynch & Maclean, 2000, 2001), which included participants at different proficiency levels. However, none of these studies investigated the effects of proficiency as a variable per se. Conversely, research in SLA- TBLT in general, and in TR in particular, has tended to control for such variable to eliminate “noise” since learner proficiency is likely to impact L2 participants´ performance and obscure the effects of the independent variables researchers desired to shed light on (Mojavezi, 2013). Interestingly, it makes much theoretical sense to study the impact of learner proficiency on task repetition for one main reason. When learners engage in task repetition, they have an opportunity to monitor their previous production and in so doing, they are likely to reflect on their explicit knowledge, at least partially (Ellis, 2005). More proficient learners are expected to count on a wider explicit knowledge than lower proficiency learners and reflection on it would lead to a more increased performance upon task repetition.

Mojavezi (2013) put this claim to the empirical test and found that higher proficiency participants were able to take further advantage of the repetition of an oral narrative task in terms of fluency, complexity and accuracy. However, being this the only study which addressed the effects of proficiency and bearing in mind the claims made by Bygate (in press), it cannot be confidently affirmed that proficiency plays a mediating role on task repetition. To shed further light on the issue and advance research in this domain, proficiency was included as an independent variable in our study in an attempt to elucidate its potential mediating effects on task repetition in both oral and writing tasks and, in the latter, as mediated by the availability (or lack of) of different types of WCF.

CHAPTER III. ANALYSIS OF RELEVANT EMPIRICAL RESEARCH.

The research on TBLT of relevance for the present dissertation mainly involves studies on task modality effects and task repetition. Our research is concerned with the differential nature of speaking and writing in task repetition. A synthesis of relevant empirical of research on task-modality effects and on task repetition in the oral and written modality will provide the necessary background for the rationale for the present study in terms of aims pursued. Additionally, a synthesis of relevant empirical research on written corrective feedback is presented.

III.1. RESEARCH ON TASK-MODALITY EFFECTS. Certain design features and conditions of performance can be fostered so as to direct learners’ attention at specific aspects of the language in an attempt to provide them with opportunities for language development and learning and to enhance their overall communicative competence. Despite the relevance of task design in TBLT preoccupations, oral and written modes as task design variables have received little attention in research (Gilabert, Manchón & Vasylets, 2016). Table 2 below summarises relevant research on task modality effects on language performance.

Table 1. Overview of research on modality effects. Study Findings Ellis (1987). Greater accuracy in writing (only dimension studied). Ellis & Yuan (2005). Greater complexity (syntactic and lexical) and accuracy in writing. Grandfelt (2008). Greater lexical complexity in writing. Greater accuracy in speaking. Similarity in syntactic complexity (subordination). Kormos (2014). Greater lexical variety and range, NP complexity and accuracy in writing. Similar amount of subordination. Higher cohesion in writing. Kuiken & Vedder (2011). Greater complexity (syntactic and lexical) in writing. Similarity in accuracy.

CHAPTER III. ANALYSIS OF RELEVANT EMPIRICAL RESEARCH.

Tavakoli (2014). Grater syntactic complexity in writing (only dimension studied). Vasylets, Gilabert & Higher lexical and syntactic complexity in writing. Similarity in Manchón (2017). accuracy. More ratio of idea units in speaking but higher ratio of extended idea units in writing. Yu (2009). Greater lexical complexity (variety) in speaking (only dimension studied). Zabildea (2017). Greater lexical complexity and accuracy in writing. Greater syntactic complexity in speaking.

All the studies listed above found higher lexical complexity in writing than in the oral modality (Ellis & Yuan, 2005; Kormos, 2014; Kuiken and Vedder, 2011; Vasylets et al., 2017; Zabildea, 2017) with the exception of Yu (2009). The results regarding syntactic complexity and accuracy seem to be less clear-cut. Although most studies have reported greater syntactic complexity in the written mode (Ellis & Yuan, 2005; Kuiken &Vedder, 2011; Tavakoli, 2014; Vasylets et al., 2017), Zabildea (2017) reported that speaking elicited greater syntactic complexity while Grandfelt (2008) found similarity in this dimension. Kormos (2014) did find an advantage in the written mode for syntactic complexity but only in one of the measures in the study (NP complexity, not in the subordination measure). Accuracy was found to be higher in writing in the majority of the studies (Ellis, 1987; Ellis & Yuan, 2005; Kormos, 2014; Zabildea, 2017) while Vasylets et al. (2017) and Kuiken and Vedder (2011) found similar accuracy rates in both modes. On the contrary, Grandfelt (2008) found greater accuracy in speaking than in writing. The purported higher complexity and accuracy in the written mode could be explained in terms of its differential characteristics, which are likely to foster deeper linguistic processing and reflection and greater engagement in focus on form processes. The self-paced offline nature of the written mode and, most importantly, the greater availability of time of most forms of writing allow for greater linguistic introspection and restructuring, which entails “change and development in the interlanguage system” (Skehan & Foster, 1999:97 cited in Manchón & Vasylets, in press). The studies reviewed in this section, despite certain contradictory findings which lead us to treat them with due care, indicate that writing has the potential to create the necessary conditions for language learning. However, as Gilabert et al. (2016) suggest, greater language learning potential may derive from the combination of the two modes instead of focusing on exploiting the effects of only one.

CHAPTER III. ANALYSIS OF RELEVANT EMPIRICAL RESEARCH.

III.2. RESEARCH ON TASK REPETITION IN THE ORAL MODALITY. As mentioned earlier, the vast majority of empirical research on task repetition has focused on the study of oral language. Most studies have reported increases in different dimensions of performance as measured in CAF measures. Table 2 presents a summary of research on task repetition in speech production.

Table 2. Overview of research of TR in the oral modality. Study Setting Type of TR Time lapse Findings Ahmadian (2011). FL Exact TR Every 2 weeks Fluency and (over 6 syntactic months). complexity. Ahmadian & Tavakoli FL Exact TR and 1 week. Fluency and (2010). planning complexity. Baleghizadeh & FL Exact TR and FoF Not stated. Accuracy (only Derakshesh (2012) dimension studied). Bygate (1996). SL Exact TR Accuracy. Bygate (2001). SL Exact and Every two Fluency and procedural TR weeks (Over complexity. 10 weeks). Bygate & Samuda (2005). SL Exact TR and 10 weeks. “Framing” planning (additional language). Fukuta (2015). FL Exact TR 1 week. Accuracy and lexical complexity. Gass, et al., (1999). FL Exact and 2/3 days (final Overall procedural TR repetition 1 improvement in week later). CAF. Hawkes (2012) FL Exact TR and FoF Immediate TR. Accuracy (only dimension studied).

CHAPTER III. ANALYSIS OF RELEVANT EMPIRICAL RESEARCH.

Hu (in press) FL Procedural TR 1 week. Accuracy and fluency (certain measures). Kim (2013) FL Exact and 2 days. Increased FoF procedural TR (LREs). Kim & Tracy-Ventura FL Exact and 1 day. Complexity and (2013) procedural TR accuracy of the past tense forms. Kobayashi & Kobayashi FL Exact and Immediate TR. Overall (in press). procedural TR improvements. Lynch & Maclean (2000, FL Procedural TR Immediate TR. Fluency and 2001). accuracy. Sheppard & Ellis (in FL Exact and Immediate and Fluency and press). procedural TR 2 weeks apart complexity. (T3&T4). Van de Guchte et al. FL Exact and 2 weeks. No effects of TR (2015). procedural TR in oral production.

Perhaps the most influential study on task repetition has been Bygate´s (1996). In his pilot study, Bygate (1996) found that task repetition affected both lexical and grammatical accuracy. Since then, much research has been conducted upon Bygate´s claim that task repetition actually leads to increased performance and, in that way, may assist language development. Overall, the studies in table 2 above reported gains in fluency and different dimensions of complexity. On the contrary, the dimension of accuracy seemed to be little affected due to TR and beneficial effects in this area of performance appeared to be mediated by FoF stages implemented during the TR cycle (Baleghizadeh & Derakshesh, 2012; Hawkes, 2012), what Lynch (in press) labelled as “enhanced” task repetition i.e. task repetition preceded by some sort of pedagogical intervention.

The majority of these studies have tested the efficacy of exact TR, albeit in different ways. Ahmadian (2011), Bygate (1996) and Fukuta (2015) studied exact TR in isolation arriving at different conclusions. As stated before, Bygate (1996) reported more accurate performance

CHAPTER III. ANALYSIS OF RELEVANT EMPIRICAL RESEARCH. upon TR while Ahmadian (2011) and Fukuta (2015) reported gains for fluency and syntactic complexity and for fluency and lexical complexity respectively. Other studies also analysed the effects of exact TR as mediated by FoF stages (Baleghizadeh & Derakshesh, 2012; Hawkes, 2012) finding increased accuracy and exact TR complemented with planning conditions (Ahmadian & Tavakoli, 2010; Bygate & Samuda, 2005) finding higher fluency and complexity for the former and increased performance in terms of framing (use of additional language) for the latter.

Researchers have explored potential effects of other forms of task repetition. Lynch and Maclean (2000; 2001) examined the use of procedural task repetition during an in-class task through which learners of different levels of proficiency were able to benefit from immediate TR improving their performance on both fluency and accuracy. Other studies have compared exact TR to procedural TR (Bygate, 2001; Gass et al., 1999; Kim & Tracy-Ventura, 2013; Van de Guchte et al., 2015) and the results reported have also been mixed. Gass et al. (1999) found overall gains in the triad CAF while Van de Guchte et al. (2015) did not report beneficial effects for oral TR while acknowledging that certain FoF had taken place as evidenced in the different post-tests administered to participants. However, these results should be treated with careful consideration due to the fact that they did not gather online production data (from the actual main task performance and repetition of the task) but collected their data for analysis from the different post-test later administered to the participants. Kim and Tracy-Ventura (2013) on the other hand reported higher complexity and partial accuracy (they did not report gains in overall accuracy, only gains in accuracy for the past tense forms) due to task repetition but claimed that “findings do not provide strong support in favour of one task repetition treatment over the other” (p. 837). Finally, Bygate (2001) reported overall gains in complexity too as well as in fluency measures.

More recently, research on task repetition has shifted its focus from studying which areas of performance benefit the most from TR to the analysis of the effects on learners in terms of their perceptions and/or engagement with the task. Ahmadian, Mansouri and Ghominejad (2017) compared both teachers and learners´ perception on the usefulness of exact TR. Their results showed that learners and instructors considered that learners performed better in terms of fluency and the use of more accurate language. Regarding engagement with TR, learners acknowledged being actively engaged with the task when performing it a second time, even though their teachers seemed to hold a contrasting view. Qiu and Yi Lo (2016) also studied engagement with tasks through task repetition and task content familiarity on EFL intermediate learners. They reported that task content familiarity when performing a task resulted in greater “behavioural” engagement (production of more words– in other studies operationalised as a

CHAPTER III. ANALYSIS OF RELEVANT EMPIRICAL RESEARCH. measure for fluency). On the contrary, their results also showed TR resulted in less “behavioural” and “cognitive” engagement as operationalised in terms of word count and self-repairs respectively. However, this result appeared to be mediated by learner´s prior familiarity with the content of the task. Engagement with task repetition can also be triggered by motivational factors. A number of studies have claimed that repeating a task resulted in decreased motivation (Hawkes, 2009; Nitta & Baba, 2014). However, further research is needed to shed further light on possible mediating factors and effects of learners´ active engagement with an implementation variable such as task repetition.

Overall, all these studies account for gains in language performance. However, the results of these studies should be looked at from various perspectives. First, the learning settings in which they took place, SL (Bygate, 1996, 2001; Bygate & Samuda, 2005) as opposed to FL setting (Ahmadian, 2011; Ahmadian et al., 2017; Ahmadian & Tavakoli, 2010; Baleghizadeh & Derakshesh, 2012; Fukuta, 2015; Gass et al., 1999; Hawkes, 2012; Lynch & Maclean 2000, 2001; Qiu & Yi Lo, 2016; Van de Guchte et al., 2015). Second, the time lapse between the first encounter with the task and its repetition, which that ranges from immediate TR (Hawkes, 2012; Lynch & Maclean, 2000; 2001), few days (Gass et al., 1999), or one week (Ahmadian & Tavakoli, 2010; Fukuta, 2015, Qiu & Yi Lo, 2016) to TR throughout several weeks (Bygate, 2001; Bygate & Samuda, 2005; Ahmadian, 2011; Van de Guchte et al., 2015). In the third place, another important variable, the different tasks used i.e. information-exchange (Kim, 2013a; Kim & Tracy- Ventura, 2013), narratives (Ahmadian, 2011; Ahmadian & Tavakoli, 2010; Baleghizadeh & Derakshesh, 2012; Bygate, 2001; Gass et al., 1999; Qiu & Yi Lo, 2016), interview tasks (Bygate, 2001), poster carousel (Lynch & Maclean, 2000, 2001), description/comparison tasks (Van de Guchte et al., 2015) or conversations about different topics (Hawkes, 2012). In addition, the different operationalisations of language development throughout these studies mostly in terms of CAF measures but also in terms of the use of target structures (Hawkes, 2012; Van de Guchte et al., 2015) or behavioural and cognitive engagement (Qiu & Yi Lo, 2016), which may be some of the possible reasons for disparity in research findings across studies. Moreover, further research is needed in order to tackle the effects on accuracy when TR is implemented without FoF stages along with the relative effectiveness of different types of task repetition on performance and, more importantly regarding the effects of content TR, which no study, to the best of our knowledge, has addressed yet. Finally, evidence from the studies reported above suggest that the effects of task are not carried onto new contexts (Gass et al., 1999) and similarly the effects are not sustained over time (Kim & Tracy-Ventura, 2013). Furthermore, only two of the studies discussed above have opted for a longitudinal design (Ahmadian, 2011; Bygate,

CHAPTER III. ANALYSIS OF RELEVANT EMPIRICAL RESEARCH.

2001). Therefore, more extensive research is needed so as to gather new evidence of the effects of TR in the long term and if, most importantly, TR can actually lead to language acquisition.

III.3. RESEARCH ON TASK REPETITION IN WRITING. Task repetition in writing has scarcely been studied, one of the reasons we argued before for conducting further research in this direction. The rather limited number of studies conducted, which are presented in Table 3 below, have mainly addressed the effects of exact and procedural task repetition.

Table 3. Overview of research of TR in writing. Study Setting Type of TR Time lapse Findings Amiryousefi (2016) FL Exact and Once a week Fluency procedural TR. (over 6 (procedural TR); weeks). Fluency and accuracy (exact TR). Baba & Nitta (2014) FL Exact and Once a week Fluency (only (Case study: 2 procedural TR. (over 30 variable studied). participants) weeks). Nitta & Baba (2014) FL Exact and Once a week Fluency (short procedural TR. (over 30 term); weeks). Complexity (procedural TR in the long term). Nitta & Baba (2015) FL Exact and Once a week Fluency and (Case study: 2 procedural TR. (over 30 complexity. participants) weeks). Nitta & Baba (in press) FL Exact and Once a week Fluency and (Case study: 2 procedural TR. (over 30 complexity. participants) weeks).

CHAPTER III. ANALYSIS OF RELEVANT EMPIRICAL RESEARCH.

All these studies report beneficial effects for TR in writing, mostly in the area of fluency. The results regarding the rest of areas of performance -accuracy and complexity- appear to be more mixed. In two different case studies, Nitta and Baba (2015; in press) also reported overall gains in the areas of lexical and syntactic complexity complementing the increases in fluency while Amiryousefi (2016) found that exact TR resulted in more fluent and accurate performance. On the contrary, Nitta and Baba (2014) claimed that the effects of TR may be limited to the area of fluency in the short term and that procedural TR resulted in a gradual complexification due to massed repetition over a long period of time. It is relevant to mention that only two of these studies were designed form a truly developmental perspective (Amiryousefi, 2016; Nitta & Baba, 2014). On the other hand, Baba and Nitta (2014) studied more specifically the emergence of phase transitions of fluency when writing while Nitta and Baba (2014; in press) studied the development of what they labelled as the “L2 self” and the benefit of engaging in self-reflection when implementing TR in writing respectively. Due to this, these results should be considered cautiously but also because of the fact that the studies conducted by Nitta and Baba (2014; 2015; in press) did not measure accuracy and Baba and Nitta (2014) only addressed the area of fluency. Therefore, the effects of written task repetition on accuracy, as in the oral modality, cannot be taken for granted. Also, the different time lapse for which these studies reported gains due to task repetition (30 weeks) is very different from the time lapse in Amiryousefi (2016), in which tasks were repeated once a week for six weeks and even the medium for writing was different (pen and paper as opposed to computer-mediated writing). Therefore, these results need to be complemented with more robust findings. Even more, there are a number of questions which still await an answer. The effects of content task repetition in writing is yet unknown since, to the best of our knowledge, no studies addressing this issue have been conducted. Additionally, task repetition in the written modality needs to expand the range of tasks used so far, which is limited to narratives. Different types of task may yield very different effects not only in the short term, but also in the long run (ref. needed). Apart from this, none of the studies incorporated WCF stages, which as stated in previous sections, is an inherent part of the writing process and one that may bring about beneficial effects as it induces learners to focus on form. This gap in research on task repetition in writing stresses the need to incorporate L2 writing studies to TBLT research frameworks, as suggested by Manchón (2014b), who also emphasised the need to include written corrective feedback in the task repetition cycle. Ours is, then, a pioneering attempt to not only expand research in TR in the written mode so as to provide more robust findings to existing research, but also to study task repetition in the written modality as mediated by different types of WCF. In the next section, WCF studies are reviewed in order to

CHAPTER III. ANALYSIS OF RELEVANT EMPIRICAL RESEARCH. understand what effects are to be expected when implementing WCF stages during the task repetition cycle.

III.4 RESEARCH ON WRITTEN CORRECTIVE FEEDBACK. Research on written corrective feedback has evolved around three main trends recently identified in Manchón and Vasylets (in press). The first of these trends has investigated the effects of WCF on text revisions and, to a lesser extent, on longer term retention. Secondly, depth of WCF processing has been pointed out as a very relevant research trend given the likelihood of promoting language learning through writing and WCF processing. The third research trend we made reference to revolves around the interaction between depth of processing and the nature of revisions. Our research is framed within the first of the research trends purported above. A general claim regarding the fact that WCF results in increased accuracy has emerged. However, there is much less agreement on the long-term effects of WCF on retention, an issue related to the dichotomy “feedback for accuracy” (short term effects of WCF) vs “feedback for acquisition” (long term effect of WCF) (Manchón, 2011a). As rightly stressed by some scholars (Bitchener & Storch, 2016; Truscott, 2007), immediate revisions do not necessarily entail L2 development, learning and/or acquisition.

The starting point of written corrective feedback research.

Early studies on written corrective feedback (Kepner, 1991; Robb, Ross and Shortreed, 1986; Semke, 1984; Sheppard, 1992, studied here via Bitchener, 2012, 2016; Bitchener and Ferris, 2012; Truscott, 1996) failed to report positive effects on the usefulness of written corrective feedback (WCF). Nonetheless, these studies have been criticised for different flaws in their design variables, e.g. lack of a control group, and execution, administration of different writing tasks for measurement (Bitchener, 2012, 2016; Bitchener and Ferris, 2012). Prior to Truscott´s article in Language Learning (1996), little research had been carried out on the issue. It was thanks to his drastic position regarding the ineffectiveness and detrimental effects of WCF that abundant research started to flourish and studies with more rigorous designs were implemented. An overview of this research is presented in table 4 – studies regarding the effects of WCF in the short term (revision), and table 5– studies addressing the effects of WCF on retention (longer term). Most of these studies show (but see Truscott and Hsu, 2008 for different claims) the beneficial nature of written corrective feedback (Adams, 2003; Bitchener, 2008;

CHAPTER III. ANALYSIS OF RELEVANT EMPIRICAL RESEARCH.

Bitchener & Knoch, 2008, 2010a, 2010b; Bitchener, Young & Cameron, 2005; Coyle & de Larios, 2014; Ellis, Sheen, Murakami & Takashima, 2008; Ferris, 2006; Frear, 2012; Guo, 2014 as reviewed in Bitchener & Storch, 2016; Sachs & Polio, 2007; Sánchez & Manchón, 2014; Santos, López-Serrano, Manchón, 2010; Sheen, 2007; Sheen, Wright & Moldava, 2009; Shintani & Ellis, 2013; Shintani, Ellis & Suzuki, 2014; Stefanou, 2014 as reviewed in Bitchener & Storch, 2016; Storch & Wigglesworth, 2010; Van Beuningen, de Jon & Kuiken, 2008, 2012).

Table 4. Research on written corrective feedback on revision (Feedback for accuracy). Study WCF treatment Effects in the short term (revision). Adams (2003). Reformulation (direct) alone Greater accuracy in the and reformulation with reformulation + SR stimulated recall (SR). condition. Cerezo, Manchón & Nicolás- Unfocused error correction Improved accuracy. Conesa (in press). (EC) and highlighting with error codes (indirect). Coyle & Roca de Larios Reformulation and models Greater accuracy in (2014). (indirect). reformulation condition. Sachs & Polio (2007). Unfocused EC (direct) and Greater accuracy in EC reformulation. condition. Sánchez & Manchón (2014). Reformulation and Overall increased accuracy. unfocused circling (indirect). Greater lexical accuracy in reformulation condition and greater syntactic accuracy for indirect WCF. Santos, López-Serrano & Unfocused EC and Greater accuracy in EC Manchón (2010). reformulation. condition. Storch & Wigglesworth Reformulation and editing Greater accuracy in indirect (2010). symbols (indirect). WCF condition.

CHAPTER III. ANALYSIS OF RELEVANT EMPIRICAL RESEARCH.

Table 5. Research on written corrective feedback on retention (feedback for acquisition). Study WCF treatment Effects in the short Effects in the long term term (revision). (retention). Bitchener (2008). Focused EC +/- Improved accuracy. Improved accuracy. metalinguistic explanation (ME). Bitchener et al. Focused EC +/- ME. Improved accuracy. Improved accuracy in (2005). certain target forms (English article and past simple forms). Bitchener & Knoch Focused EC +/- ME. Improved accuracy Improved accuracy in (2008). in certain target certain target forms forms (English (English article). article). Bitchener & Knoch Focused EC +/- ME. Improved accuracy Improved accuracy in (2010a). in certain target certain target forms forms (English (English article). article). Bitchener & Knoch Written ME, oral and Improved accuracy Improved accuracy in (2010b). written ME and in certain target certain target forms circling. forms (English (English article) for article). direct WCF. Ellis et al. (2008). Focused/unfocused Improved accuracy. Improved accuracy. EC. Frear (2012). Focused/unfocused Improved accuracy Greater accuracy for EC and underlining in certain target focused WCF groups, (indirect). forms (regular past especially focused EC tense). for certain target forms (regular past tense). Guo (2014). Focused EC +/- ME, Greater accuracy in No effects found. underlining (indirect) direct WCF and editing symbols. conditions. Sheen (2007). Focused EC +/- ME. Improved accuracy. Improved accuracy. Sheen et al. (2009). Focused/Unfocused Improved accuracy. Improved accuracy for

CHAPTER III. ANALYSIS OF RELEVANT EMPIRICAL RESEARCH.

EC. the English article only in the focused group. Shintani & Ellis EC +/- ME. Greater accuracy for Improved accuracy. (2013). EC+ME condition. Shintani et al. Focused EC and Improved accuracy Greater accuracy in EC (2014). focused ME. in certain target condition (only forms (hypothetical hypothetical conditional). conditional). Stefanou (2014). Focused EC+/- ME. Improved accuracy. Improved accuracy. Truscott & Hsu Unfocused Improved accuracy. No effects found. (2008). underlining. Van Beuningen et al. Unfocused EC and Improved accuracy. Greater accuracy in (2008). editing symbols. direct WCF condition. Van Beuningen et al. Unfocused EC and Improved accuracy. Greater grammatical (2012). editing symbols. accuracy in direct WCF condition and greater non-grammatical accuracy for indirect WCF.

In the next sections we examine research on WCF from two different angles. On the one hand, we will discuss the results of research following either focused or unfocused approaches and, on the other, the findings regarding different degrees of WCF explicitness will be featured.

Scope of the WCF: Focused and unfocused WCF.

Truscott and Hsu (2008) claimed that unfocused WCF was ineffective because, even if learners in their study improved their accuracy on a text revision, this improvement was not carried over to a new text. Unlike Truscott and Hsu (2008), Van Beuningen et al. (2008, 2012) reported that unfocused correction led to more accuracy in both revision and the writing of a new piece of writing. Similarly, Sánchez and Manchón (2014) reported gains in accuracy under an unfocused approach. Apart from the fact that learners well have a preference for all their errors to be corrected (Ferris, 1995; Ferris and Roberts, 2001; Leki, 1991), as we suggested

CHAPTER III. ANALYSIS OF RELEVANT EMPIRICAL RESEARCH. earlier, there are a number of other reasons to provide unfocused WCF. Instructors may feel ethically compelled to correct all errors leaners make and even fear the possibility of reinforcing non-target language forms if they do not provide feedback on erroneous forms their learners may be testing hypotheses on.

Other studies have compared the relative effectiveness of both unfocused and focused approaches. Ellis et al. (2008) reported gains in accuracy for the two conditions while Sheen et al. (2009) found an advantage of the focused approach over unfocused corrections. Nevertheless, authors (refs. Needed) commented on possible shortcomings of these studies, such as the fact that frequency of the feedback was higher in the focused condition in the first case and unsystematic corrections were provided in the second. These methodological considerations explain why the question regarding the effectiveness of one approach over the other still remains unanswered.

On the other hand, several studies have investigated the effectiveness of the focused approach alone and have provided mixed results. Bitchener et al. (2005) found that written CF targeting the use of the English article and the past simple was effective for uptake and retention, but it was not when targeting prepositions (see also Ferris, 2006). In a similar fashion, other studies by Bitchener (2008), Bitchener and Knoch (2008, 2010a, 2010b), Sheen (2007) and Sheen et al. (2009) which also targeted different uses of the English article showed increased accuracy in the used of the target structure in the immediate post-tests and delayed post-tests. It may seem then, that certain types of error are more “treatable” than others through WCF due to their perceived difficulty (Bitchener and Storch, 2016: 53). Theoretically, it has been argued that focused approaches to WCF can be more beneficial in that they direct learners´ attention to discrete items to which they can pay greater attention to and engage in the process of awareness at the level of understanding and as a consequence, be able to transform input, WCF, into intake. Furthermore, it has also been posited that learners at low levels of proficiency would be able to do this more easily since their cognitive processing capacity in the L2 may not be developed enough so as to deal with huge amount of corrections, feeling thus overwhelmed and cognitively overloaded.

Explicitness of the WCF.

Questions have also been raised concerning the type of WCF, i.e. direct or indirect, that is likely to produce greater gains in accuracy, regardless of whether they followed a focused or an unfocused approach. Recent studies (Bitchener & Knoch, 2010b; Van Beuningan et al. 2008,

CHAPTER III. ANALYSIS OF RELEVANT EMPIRICAL RESEARCH.

2012), show the positive effects of both direct and indirect feedback in the short term showing a more significant long-term effect only for direct feedback. Similarly, Sánchez and Manchón (2014) reported beneficial effects for both types of feedback. However, results showed that grammar errors were more amenable to correction than indirect, whereas lexical errors were more successfully targeted through direct WCF. In contrast, Storch and Wigglesworth (2010), observed greater gains for indirect (editing symbols) over direct feedback (reformulations). Coyle and de Larios (2014) also studied compared direct (error correction) to indirect (models) WCF and found greater advantage of direct over indirect forms of WCF.

Other studies have focused only on the effects of direct feedback alone. Bitchener (2008) and Bitchener and Knoch (2008, 2010a) explored the effects of direct focused correction with and without metalinguistic input finding no difference between any of the treatment conditions. Other studies analysing the effects of the same types of feedback (Bitchener et al., 2005; Sheen, 2007; Shintani and Ellis, 2013) found, in contrast, that the groups who received metalinguistic input performed better than those who received only error correction. In contrast, Adams (2003) reported that reformulation with stimulated recalls was more effective than reformulation alone. Santos, López-Serrano and Manchón (2010) and Sachs and Polio (2007) reported a clear advantage of error correction over reformulation. All the previous studies overall account for improvements upon receiving and processing WCF in the short term. The effectiveness of feedback for accuracy we could argue is well documented. A number of studies have addressed the long-term effects of WCF, exploring the beneficial effect of what Manchón (2011a) labelled feedback for acquisition. However, as rightly stated by Bitchener and Storch (2016), we should be cautions to claim that durable beneficial effects of WCF in the long term, as evident in delayed post-tests for example, are a prove for acquisition since explicit knowledge takes time and practice to develop implicit knowledge, which should be evidenced by “consistent accuracy on multiple occasions and in multiple contexts over time” (p. 43). Nonetheless, the following account of longitudinal, shown in table X below, WCF studies will serve as a building block on the subject.

Shintani and Ellis (2013), Shintani et al. (2014) and Stefanou (2014) reported beneficial effects for the groups receiving WCF as compared to those who did not over a period of three (Shintani & Ellis, 2013) and four weeks (the last two). Other studies, such as Bitchener and Knoch (2008), Ellis et al. (2008), Sheen et al. (2009) and Sheen (2007) elevated the time lapse between post-tests and delayed post-tests up to 12, 10, 9 and 8 weeks respectively and also found that learners receiving WCF outperformed learners in control groups. Finally, two other much more ambitious studies, Bitchener (2008) and Bitchener and Knoch (2010a) reported beneficial effects

CHAPTER III. ANALYSIS OF RELEVANT EMPIRICAL RESEARCH. for WCF in the long run over a period of 24 and 40 weeks respectively. On the contrary, other studies have reported much less powerful results. Frear (2012) reported gains in the short term for all groups receiving WCF while only those in the focused error correction did so in the post- test. Similarly, Guo (2014) found improved accuracy in immediate post-test but learners failed to improve their accuracy over time. Bitchener and Knoch (2010b) also arrived at mixed results in the different WCF treatment conditions in the 10-week delayed post-tests.

Conclusion.

As a whole, these studies lend some support to the hypothesis that WCF can promote language development. However, the results appear to be rather mixed and a number of questions are still awaiting an answer in future research. In the first place, there is no clear answer to which approach to WCF provision, focused or unfocused, is more beneficial as evidence form research has reached diverse conclusions. Furthermore, the question regarding the potential relative effectiveness of different types of WCF i.e. direct or indirect, is still an empirical question and further research is needed to ascertain whether certain types of errors are better targeted under a focused or an unfocused approach and using direct or indirect WCF. Similarly, the studies addressing the degree of explicitness of direct WCF have yielded dissimilar results and more research is needed in that direction. Finally, although some of the longitudinal studies discussed above have reported that WCF may promote durable changes in learners´ knowledge, diverse and conflicting results have been obtained. Therefore, the question of whether WCF can actually lead to L2 acquisition is still an empirical question.

PART II. THE EMPIRICAL STUDY

CHAPTER IV. AIMS, HYPOTHESES AND RESEARCH QUESTIONS.

Our research is guided by two primary aims. First, we intend to contribute to expand L2 writing studies within a TBLT framework, a line of research that has been claimed to represent a welcome development in both fields (Manchón, 2014b). In essence, this research avenue is concerned with exploring the instrumental role that writing may play in the acquisition of second languages (Cumming, 1990; Harklau, 2002; Manchón, Roca de Larios & Murphy, 2009; Qi & Lapkin, 2001; Storch, 1998a, 1999, 2001). The relevance of including writing in SLA and TBLT preoccupations is justified by the tenet of maximizing learning opportunities too, which should therefore explore the language opportunities all language modalities afford (Manchón, 2014c). Following from this, there is no sound reason to develop strands of research which explore the phenomenon of second language acquisition i.e. TBLT and the cognitive line of research within L2 studies that intends to shed light on the language learning potential of writing (Manchón, 2011a). In short, our study is intended as a further building block in previous attempts at making L2 writing more central in TBLT and SLA preoccupations. Specifically, we explore the modality- related effects of TR by analysing the effects of modality (written/oral) on language performance quantified in CAF measures as well as to provide new empirical data to the almost non-existent research comparing L2 performance between oral and written task repetition. It is anticipated that the results obtained will shed further light on the effects of task repetition on language performance as well as to the role that modality may exert on it.

Secondly, and more specifically, our study seeks to add to the scarce but growing body of research on task repetition in the domain of writing, which will help to better understand the nature of written language in such a context. The available empirical findings of studies on task repetition so far suggest that task repetition in speaking may greatly differ from task repetition in writing (Bygate, 1996, 2001; Bygate & Samuda, 2005; Nitta & Baba, 2014). The scarcity of such empirical findings of task repetition in the written domain (Nitta & Baba, 2014) calls for further studies in order to elucidate whether or not the implications drawn from task repetition in speaking are applicable to writing. Additionally, the role that written corrective feedback (WCF), considered as an inherent part of written practice and even one process per se within the writing process (Manchón & Vasylets, in press), will also be addressed due to previous calls to study TR in combination with written corrective feedback (Ellis, 2009a; Manchón, 2014b). WCF is indeed a crucial element when implementing task repetition in the written modality. What is more, we expect to evaluate if such mediating role is determined by the nature of the WCF provided i.e. direct/indirect.

CHAPTER IV. AIMS, HYPOTHESES AND RESEARCH QUESTIONS.

In view of the preceding discussion, the present PhD dissertation analyses the effects of modality (written/oral) and different types of WCF i.e. direct, indirect and self-correction on language performance as measured by different complexity, accuracy and fluency measures (CAF). In order to do so, English as a foreign language (EFL) high school and university learners at different levels of proficiency performed a decision-making task and engaged in task repetition within a seven-day lapse. Lastly, the role of proficiency when implementing task repetition will also be analysed, been the potential benefits of task repetition claimed to be mediated by proficiency (Mojavezi, 2013).

IV.1. HYPOTHESES. Based on the theoretical and empirical research reviewed in previous sections, the following hypotheses guided the present study:

H1. Modality will play a role when implementing task repetition and different effects on language performance will be found in writing from those found in the oral modality. The direction of these potential different effects was not predicted given the lack of research of studies on task repetition comparing modalities of language production.

H2. Provision of and engagement with written corrective feedback processing during the task repetition cycle in writing will lead to better performance than mere task repetition (or self- correction).

H3. The nature of the written corrective feedback provided i.e. direct/indirect– will result in different effects on language performance when implementing task repetition in writing and the differences observed will be proficiency-mediated. No direction of the influence was hypothesized given the contradictory findings of previous research.

H4. Proficiency will play a role when implementing task repetition. Higher proficiency learners will benefit the most from task repetition.

IV.2. RESEARCH QUESTIONS. In order to achieve our aims and confirm or refute our hypotheses, the following research questions guided our study:

CHAPTER IV. AIMS, HYPOTHESES AND RESEARCH QUESTIONS.

RQ1. Does task repetition across modalities (oral, writing) result in any quantitative differences in learner´s performance as quantified by different complexity, accuracy and fluency (CAF) measures? Are any potential observed differences mediated by proficiency?

RQ2. Does task repetition in writing as a function of written corrective feedback impact learners´ performance quantified by CAF measures when they repeat the exact same task? Are any potential observed differences found mediated by proficiency?

RQ3. Does task repetition in writing as a function of WCF type (direct, indirect) affect learners´ performance quantified by CAF measures when they repeat the exact same task? Are any potential observed differences mediated by proficiency?

CHAPTER V. METHOD.

V. METHOD.

V.1 PARTICIPANTS. A total of 66 participants (male n=29, female n=37) learning English as a Foreign Language (FL) participated in the study. Prior to their participation they all signed a consent form. Participants were of two different proficiency levels proficiency, which was measured using the standardised Oxford Placement Test (OPT). According to the scores obtained in the OPT, they were divided into two main groups of low and high proficiency. Participants who scored 18-29 marks in the OPT were at an A2 level of proficiency according to the Common European Framework of Reference for Languages (CEFRL). These participants were part of the low proficiency group. The participants who scored slightly higher in the OPT (30, 31 or 32 marks), what was labelled as an A2+ level of proficiency, were also included in this group. Low proficiency participants were studying 3rd and 4th year of Secondary Education (n=35) and attended four hours of English per week. They came from two different state high schools in Murcia and Cartagena, both of a similar sociocultural environment (middle class). They all were teenagers and their ages ranged between 14 and 16.

The high proficiency group of participants (n=31) scored 40 marks or more in the OPT. This score indicates that their level of proficiency was B2 or above according to the CEFRL. These participants came from a state university in Murcia, where they were enrolled either in their 1st year of a degree in English studies or in a Master´s Degree on EFL Teacher training at the time of data collection. University participants in the study were adults whose ages ranged between 18 to 25.

Participants were also asked to complete a demographic questionnaire about their language abilities, skill preferences and past foreign language learning experience, including information such as the age at which they had started learning English and whether they attended extracurricular lessons of English. The information in this questionnaire was then used to allocate participants purposely in each of the different treatment conditions according to profile so as to ensure the highest inter-group homogeneity possible i.e. homogeneity among groups. This procedure, despite its low ecological validity given that lack of homogeneity is the norm in language classrooms worldwide, offers greater reliability for the results and contributes to the internal validity of the study since it is expected that every group would behave in the same way under the same circumstances. While assuming a certain degree of group internal

CHAPTER V. METHOD. variability, the treatment should be regarded as the sole cause of potential intergroup differences, if any were to be found.

Five groups were created in which further discrimination between high (H) and low (L) proficiency participants was made:

• task repetition in the oral mode (G1: H n=6; L n=8) • task repetition in writing (G2: H n=7; L=8), • task repetition with the provision and processing of direct WCF (G3: H n=6; L n=7) • task repetition with the provision and processing of indirect WCF (G4 H n=6; L n=7) and • task repetition in writing with a self-correction of errors stage self-correction (G5: H n=6; L n=5).

V.2. TASK AND PILOTING. The task used for our study was taken from Gilabert (2005, 2007). In his study, Gilabert designed a decision-making task labelled as the Firechief Task in two different versions, i.e. simple and complex, which are shown in figures 3 and 4 respectively. These two picture prompts show a building in flames in which different people need to be rescued. According to the instructions in Gilabert (2005, 2007), to complete the task participants have to indicate the actions they would take in order to save each of the people in the picture, to determine the sequence of their actions and to justify their decisions. It is important to mention that in the complex version of this task, the people showed in the picture hold specific roles (old man, pregnant woman, etc) and that decisions taken previously may condition the following ones.

Besides, the resources of which participants can make use to save the people in the picture (firemen truck, helicopter) are much more limited in the complex version than in the simple one. Consequently, these two tasks are thought to pose different degrees of complexity to learners and the differences in complexity in both tasks were independently measured and validated in Révész, Michel and Gilabert (2016). To decide the version of the task to be used in our research, both tasks were piloted with EFL high-school low proficiency learners studying 3rd and 4th year of secondary education from a similar background as those high-school low proficiency participants in our research.

CHAPTER V. METHOD.

Figure 3. Firechief task. Simple version (Gilabert, 2005; 2007).

Figure 4. Firechief task. Complex version (Gilabert, 2005; 2007).

CHAPTER V. METHOD.

Piloting was carried out so as to ensure that none of the versions of the tasks, simple or complex, was too demanding for our low proficiency participants resulting in diminished production either orally or in writing. The participants production of both the simple and complex versions of the task was holistically assessed, concluding that both versions of the task were suitable for our purposes. Importantly, the complex version of the task elicited more production both in the oral modality and in writing, this being the reason why we decided to conduct our study using the complex version of the Firechief Task.

V.3. INSTRUMENTS AND DATA COLLECTION PROCEDURES. Participants underwent a two-session production task either orally or in writing. Data collection session structure can be viewed in the following table:

Table 6. Session structure. (Note: WRP- Written production; SP- Speech Production; TR- Task Repetition).

Day 1 - Time 1 Day 4 Day 8 - Time 2

G1 SP (No treatment) TR

G2 WRP (No treatment) TR

G3 WRP Feedback processing (direct) TR

G4 WRP Feedback processing (indirect) TR

G5 WRP Noticing/Self correction TR

To perform the task, participants were handed the DIN A4 coloured picture prompt which is shown in Figure 4 above with the following instruction:

1) Decide on the actions you would take to save everyone. 2) Explain the sequence in which you would take the actions. 3) Justify your decisions. The instructions were written in Spanish to facilitate complete understanding and were available for the participants during task completion. They were given 30 seconds to read the instructions and to familiarise with the picture. In Gilabert’s (2007) study, piloting of the tasks showed that 30 second was enough to get an overall idea of the situation in the task. The lack of planning time provision was decided upon in order to maximize cognitive effort and have

CHAPTER V. METHOD. learners stretch their interlanguage to the best of their possibilities. Cognitive complexity was manipulated along reasoning demands, and so in order to avoid the confounding effects of planning time (which would have merged with those of reasoning demands), no pre-task planning time was provided. Participants in the oral repetition group (G1), performed the task individually in a classroom and were recorded using a computer with an integrated microphone and a voice-recording programme. Participants in the writing conditions were handed a blank sheet of paper on which to write their compositions. They also were provided with the DIN A4 coloured picture prompt and were afforded the 30 seconds to familiarise with the picture. They all performed the task in the same room at the same time. In both cases, participants were not allowed to communicate with the researcher, teacher or peers once they had started.

The repetition of the task (T2) took place a week later. All groups were asked to perform the same task and we followed the same procedures as in time 1 the week before. All participants completed the task in the same modality (oral/written) in which they had done it previously in time 1.

Additionally, participants in groups 3, 4 and 5 (writing condition with feedback and/or self- correction) completed an in between session (day 4). They were handed a photocopy of their compositions back. Group 3 received direct written corrective feedback in the form of error correction (EC) and group 4 received indirect written corrective feedback in the form of highlighting (HL) on them. EC entails marking an error in a learner´s text and actually providing the correct form. On the other hand, when providing written corrective feedback in the form of HL, only a mark on the erroneous part of the learner´s text is done, being the learner in this case the one who should provide the correct form. An example of EC and HL can be seen below in figures 5and 6 respectively.

Figure 5. Sample of EC.

CHAPTER V. METHOD.

Figure 6. Sample of HL.

They were also provided with a sheet of paper in which a feedback processing table was printed (see Table 7 below) and were asked to analyse the feedback provided. This feedback processing table was designed to enhance noticing of errors and instil participants to go beyond noticing at the level of detection, engaging in deeper noticing processes i.e. noticing at the level of awareness and noticing at the level of understanding, which may lead to greater uptake and, consequently, to the expansion of explicit knowledge, as outlined in our literature review.

To achieve this, as can be seen from the table, participants did not only have to write the error committed, but also to analyse it and say what type of error it had been (grammar,

Table 7. Feedback-processing table.

Name: Sheet number:

LANGUAGE PROBLEMS

Identify the Which kind of problem is it? (Write an Why is it a Solution problem in “X”) problem? your text Grammar Lexis Spelling

lexis, spelling) and explain why it was an error. The table was intended to encourage deep feedback-processing due to previous claims and findings about the more beneficial effects of noticing with understanding (Qi & Lapkin, 2001, Santos, López-Serrano & Manchón, 2010). On the other hand, participants in group 5 did not receive any feedback on their writings. Instead, they were only provided with the feedback-processing table and were commanded to find as many errors in their compositions as possible and to provide corrections for those errors. This

CHAPTER V. METHOD. can also be regarded as a focus on form stage even if learner´s attention is not directed towards any specific error and had to resort to their own linguistic resources to find, analyse and provide a correct form for the errors that they had committed in their compositions.

Unlimited time was afforded in participants´ first encounter with the task as well as in its repetition for both modalities of production. Apparently, lack of pre-task planning time makes learners stretch their interlanguages imitating real life situations where more often than not, people do not have the time to plan their production. Giving participants unlimited time on task, allowed them to access their linguistic resources available. Lack of access to pre-task and on-line planning time may have resulted in overwhelming “resource-dispersing” conditions (Robinson, 2001; 2005) and, in turn, in a highly reduced and erroneous production. This way, we intended to balance the cognitive load participants had to face when performing the task. Despite taking into account this temporal dimension in our study, we did not investigate them in depth since the analysis of these aspects was far beyond our scope.

V.4. DATA CODING AND ANALYSES.

V.4.1. TRANSCRIPTION OF DATA. Participants´ oral and written performance was transcribed for analysis. The data set for this study consisted of the 132 transcriptions of participants´ production. In oral data, fillers were eliminated, and false starts were only transcribed when they consisted of meaningful chunks, otherwise, they were eliminated as well, as it is a standard procedure in the literature. Contractions were split as a rule in all types of transcriptions (words such as don´t were split into do not; words such as can´t were transcribed as cannot). On the contrary, other transcription decisions were adapted to each dimension in order to be as faithful as possible to what actually L2 learners produced.

• For the analyses of fluency and accuracy, participants´ production was transcribed exactly in the same way as they had expressed themselves when doing the tasks, word by word. • Regarding the analyses of syntactic complexity, native words and expressions were translated into English (e.g. camión de bomberos – firemen truck), lexical inventions were substituted for the target equivalent in English (e.g. extinctor – extinguisher) and the transcriptions were parsed to avoid ambiguity and the possibility of distorting results while analysing them using the tools for syntactic analyses.

CHAPTER V. METHOD.

• Finally, for the analyses of lexical complexity, native language words and expressions (e.g. camión de bomberos) as well as lexical inventions (e.g. extinctor) were eliminated, misspellings were corrected (EG. man – men, in cases of ambiguity, these were given the most favourable interpretation) and existing words in English not used correctly were also eliminated (EG. plant – “planta” in Spanish, instead of floor).

V.4.2 CAF MEASURES FOR L2 DEVELOPMENT. Data were then analysed in terms of different complexity, accuracy and fluency (CAF) measures. Table 8 below presents an overview of the CAF measures used in our research and the tools used for their analyses. Language performance in both oral and written modalities was assessed using the same CAF measures. Research on task repetition has reached very diverse and different conclusions. Different operationalizations of CAF measures have been used across studies. Consequently, in this study all three CAF dimensions were analysed by using the measures that have become in an attempt to make the analysis comparable between modes as well as to previous studies in the literature.

V.4.2.1. COMPLEXITY. Complexity is generally regarded as a very complex construct which consists of multiple “sub-constructs, dimensions, levels and components” (Norris and Ortega, 2009; Bulté and Housen, 2012, 2014: 43; GRAL group, 2013). Following Bulté and Housen´s (2012) taxonomic model of L2 complexity, we decided to study the dimension referred to as linguistic complexity. This sub-dimension is composed by system complexity (i.e. lexical complexity) and structural complexity (i.e. morphological, syntactic and phonological complexity). Of these four, we will analyse the constructs of lexical complexity and syntactic complexity, which have also been typically the ones selected in most task-based studies. The study of complexity, understood as lexical and/or syntactic complexity, has been criticised for its narrows scope, usually including very few measures resulting in a reduced representation of performance within this area (Bulté and Housen, 2012, 2014; Ortega, 2012). To address this issue, we conceptualised lexical and syntactic complexity as summoning different sub-constructs and selecting the appropriate measures to capture performance and development in these different areas.

CHAPTER V. METHOD.

Table 8. CAF measures used in the analyses.

Dimension Construct Measure Tool

Lexical Lexcical variety D-Value (Malvern & Richards, 2002). D-tools (lognostics.co.uk) complexity

Lexical richness Guiraud Index (Guiraud, 1954). Spreadsheet software

Advanced Guiraud Index (Daller, van Hout & Lexical sophistication RANGE (Heatley, Nation & Coxhead, 2002) Treffer-Daller, 2003)

Syntactic Overall syntactic Web-based L2 Syntactical Complexity Analyzer (Lu, 2010, 2011; Lu Mean length of T-unit complexity complexity & Haiyang, 2015).

Web-based L2 Syntactical Complexity Analyzer (Lu, 2010, 2011; Lu Subordination Dependent clauses/T-unit & Haiyang, 2015).

Web-based L2 Syntactical Complexity Analyzer (Lu, 2010, 2011; Lu Coordination T-units/Sentence & Haiyang, 2015).

Sub-clausal complexity Number of modifiers/noun phrase Coh Metrix 3.0 (McNamara, Graesser, McCarthy, & Cai, 2014).

Syntactic diversity STRUTt value Coh Metrix 3.0 (McNamara, Graesser, McCarthy, & Cai, 2014).

Computerised Language ANalisis (CHILDES database: Accuracy General accuracy Total errors/100 words childes.psy.cmu.edu)

Total errors/T-unit

CHAPTER V. METHOD.

Computerised Language ANalisis (CHILDES database: Specific accuracy Morpho-syntactic errors/100 words childes.psy.cmu.edu)

Computerised Language ANalisis (CHILDES database: Lexical errors/100 words childes.psy.cmu.edu)

Computerised Language ANalisis (CHILDES database: Spelling errors/100 words (only for writing) childes.psy.cmu.edu)

Computerised Language ANalisis (CHILDES database: Morpho-syntactic errors/T-unit childes.psy.cmu.edu)

Computerised Language ANalisis (CHILDES database: Lexical errors/T-unit childes.psy.cmu.edu)

Computerised Language ANalisis (CHILDES database: Spelling errors/T-unit (only for writing) childes.psy.cmu.edu)

Fluency Speed fluency Words/minute Word processor software.

Syllables/minute Word processor software.

CHAPTER V. METHOD.

Lexical complexity measures.

Lexical complexity was studied through the degree of variety, richness and sophistication L2 learners´ texts exhibited. Lexical variety was analysed using D-value (Malvern & Richards, 2002) which is a corrected version of the traditional type/token ratio no longer used as a measure for lexical diversity (see below lexical richness) because of its sensitivity to text length. The tool is available at the web lognostics.co.uk. D-value was devised to compensate for the text-length dependency of the existing measures for lexical diversity and has been widely used in the literature (see for example Kim & Tracy-Ventura, 2013; Kormos, 2014) to type on the relationships between types and token. The value is arrived at by calculating the mean of type- token ratios at different text lengths randomly. This measurements project different empirical curves and the equation used to find the best fit among these curves provides the index for D- value. This may derive in slightly different results each time we analyse the same text. To compensate for this, all texts were analysed three times and then the mean D-value was calculated. We also studied lexical richness. It has been defined as “variation in and number of word types used” in the text (Bulté & Housen, 2014: 49). We calculated lexical richness through the Guiraud Index (Guiraud, 1954). Guiraud index is a type-token measure which was designed to compensate for text length introducing in its calculation the square root of the total of words in the text. However, it fails to compensate for text length since still the value for Guiraud index decreases as the text extension increases (Jarvis, 2002). Despite this fact, it has typically been used as a measure for lexical variety since it highly correlates with D-value. The measure, thus, captures lexical variety but still taps into the construct of fluency. As a consequence, following Bulté and Housen´s definition (2014), Guiraud index is a more appropriate measure for the construct of lexical richness and has recently been used in this sense in empirical studies (Vasylets, et al., 2017). Lexical sophistication was analysed with the aid of automatic tools as well. It has been defined as “the proportion of relatively unusual or advanced words” (Read, 2000: 203) that a learner´s text exhibit. RANGE software (Heatley, Nation & Coxhead, 2002) was used for the calculation of Advanced Guiraud index (Daller, van Hout & Treffer-Daller, 2003) which accounts for lexical sophistication. It calculates the proportion of words that fit into the different frequency bands, the 1k, 2k, etc. most common words in English (Laufer & Nation, 1995). The higher the band a word is in, the more complex or more sophisticated it is considered. It has been previously suggested that Advanced Guiraud should be calculated using what Laufer (1995) denominated “beyond 2000” (words not in the list of the 2000 most common words in English). However, this approach was criticised in terms of the lack of fit for learners at low levels of proficiency, as they usually tend to produce very few low frequency words (Meara and Bell,

CHAPTER V. METHOD.

2001). To be able to capture any changes in the lexical sophistication of our low proficiency participants, we considered words to be sophisticated if they were not part of the first frequency band, what we could label as a “beyond 1000” approach to lexical sophistication.

Syntactic complexity measures.

Syntactic complexity has been defined as “the range of forms that surface in language production and the degree of sophistication if such forms” (Ortega, 2003:492). Norris and Ortega (2009) claimed that syntactic complexity should be studied from different perspectives which they identified under five different sub-constructs: i) overall complexity, ii) complexity via subordination and iii) subclausal complexity, iv) complexity via coordination and v) syntactic variety and sophistication. The measures selected for our research were intended to gauge complexity at these different tiers of syntax. For the analysis of syntactic complexity measures we used the Web-based L2 Syntactical Complexity Analyzer (Lu, 2010, 2011; Lu & Haiyang, 2015). This online software analyses written English language samples and provides up to fourteen different measures achieving high reliability scores (Lu, 2010). According to Norris & Ortega´s (2009) suggestions, we looked into the construct studying different dimensions of syntactic complexity. The selected measures for our study were an overall measure of complexity such as the mean length of t-unit (MLT), a subordination measure such as dependent clauses per t-unit (DC/T), and a measure of coordination such as t-unit/sentence (T/S). Having been the analysis of coordination mostly ignored in SLA up to date, we decided to include this measure due to previous calls on its relevance when dealing with learners at beginning stages of L2 development (Bardovi-Harling, 1992) since it is a more sensitive index when trying to capture complexification at lower levels of L2 development. Additionally, other online software, Coh Metrix 3.0 (McNamara, Graesser, McCarthy, and Cai, 2014), was used to analyse further syntactic complexity measures such as noun phrase complexity (sub-clausal complexity) and an innovative measure (STRUTt) hardly used in previous research (see Nitta and Baba, 2014; Mazgutova & Kormos, 2015 for notable exceptions) which was operationalised as syntactic variety. STRUTt value accounts for sentence syntax similarity. Therefore, the higher the value in this measure, the more similar (i.e. less varied) the syntactic structures used by a given participant are. In this sense, we should bear in mind that this measure is reversely-coded. This measure was included in our analyses following Bulté and Housen´s consideration that an integral part of syntactic complexity is related to the variety of syntactic structures in L2 learners´ repertoire (2012). With this range of syntactic complexity measures, we intended to cover from

CHAPTER V. METHOD. the broadest (sentence level) to the most narrow (sub- clausal level) categories of the syntax spectrum.

V.4.2.2. ACCURACY MEASURES AND ERROR CODING. Accuracy has been referred to as the “ability to be free from errors while using language to communicate (Wolfe-Quintero, Inagaki and Kim, 1998: 33). We defined an error as any deviation from the norm which would not be produced by native or proficient users of the target language, as adapted from Lennon (1991). The analysis of accuracy is not either a straightforward topic on which researchers agree upon. Much has been argued about the type and which specific measures would best capture performance within this construct (Evans, Hartshorn, Cox, Martin, 2014; Polio, 1997; Wolfe-Quintero et al., 1998). We contemplated accuracy as linguistic accuracy and followed previous indications that it should be measured through both general and specific measures. The former measures have been claimed to “expand the researcher´s understanding of the production as a whole” while the latter ones should address particular linguistics features “if we are to fully understand language development (Evans et al., 2014: 34). More specifically, we preferred to use measures which account for the total number of errors to measures that count error-free units (EFT-units, EFC) since this type of measures do not account for the total number of them and compromise the entire unit even if only one single error occurred (Kuiken &Vedder, 2007; Polio, 1997). Furthermore, it has been suggested that it is unlikely to find error-free units when dealing with low-proficiency learners (Kuiken & Vedder, 2007) as was the case in our research. Adapting Bardovi-Harling and Bofman categories (1989), we differentiated between morpho-syntactic errors and lexical errors. Additionally, in the written modality, spelling errors were also counted and computed separately i.e. not included in the total error count, since that would have distorted the results when comparing oral and written modalities. Accuracy then, was observed using general measures such as total errors per 100 words and total errors per T-unit and specific measures morpho-syntactic, lexical and spelling errors per 100 words and morpho-syntactic, lexical and spelling errors per T-unit which count the total number of errors. An example of error coding can be found in the table 6 below. Examples 1-3 show isolated errors in context while examples 4-7 show multiple errors in one single sentence, whether different or of the same type. As stated before, when misspellings occurred, as in example number 3, we acknowledged the most favourable scenario, in spite of the fact that this error could be considered to be of a morpho-syntactic type (word inflection). Besides, in examples 6 and 7 (plan and breath, respectively) we find instances of multiple errors in one single word/position. When this

CHAPTER V. METHOD. occurred, all errors were counted as such and categorised accordingly, as shown in Table 9 below.

Table 9. Error coding examples.

Example Error coding (MSE – Morpho-syntactic error; LEXE – Lexical error; SPE – Spelling error)

1. Later, I´d rescue the man who is MSE in the first MSE – Wrong preposition. floor

2. There wouldn´t be an LEXE extintor, so they´ll LEXE – Lexical invention have to carry one.

3. We have to SPE safe all the people. SPE – (Most favourable scenario)

4. I would help MSE people on the first floor and MSE – article omission. SPE downsters. SPE – omission of vowel i.e. downstairs.

5. First MSE for help the kids, I´m going to use the MSE – wrong preposition. LEXE camion de bomberos. LEXE – native language interference upon a lexical cluster.

6. I will save the people who MSE was MSE in the MSE – Number agreement. MSE thirth LEXE SPE plan MSE – wrong preposition.

MSE – word inflection.

SPE – omission of consonant i.e. plant.

LEXE – word choice (i.e. floor)

7. There isn´t too much oxygen and it´s more MSE – Wrong verb form after adjective. difficult MSE SPE breath. SPE – omission of vowel (i.e. breathe).

Errors were manually coded using CLAN (Computerised Language ANalisis) program, part of Child Language Database Exchange System (CHILDES) available at childes.psy.cmu.edu,

CHAPTER V. METHOD. and later computed and analysed. Both inter-rater and intra-rater reliability scores were calculated. Apart from the researcher, two additional independent coders coded 11,43% of the data, pertaining to the low proficiency group of participants. Inter-rater reliability with coder 2 achieved 98,57% while with coder 3 it reached 100% of the total error count as shown in Tables 10 and 11 below.

Table 10. Coding of errors (sorted by error type) by coders 1 and 2. Spelling errors not counted for oral data.

Lexical errors Morpho-syntactic errors Spelling errors

Coder 1 Coder 2 Coder 1 Coder 2 Coder 1 Coder 2

Sample 1 3 3 5 5 1 1

Sample 2 5 5 18 18 10 9

Sample 3 6 6 9 9 - -

(Oral data) (Oral data)

Sample 4 6 6 7 7 - -

(Oral data) (Oral data)

Table 11 Coding of errors (sorted by error type) by coders 1 and 3.

Lexical errors Morpho-syntactic errors Spelling errors

Coder 1 Coder 3 Coder 1 Coder 3 Coder 1 Coder 3

Sample5 4 4 4 4 0 0

Sample6 8 8 23 23 3 3

Sample7 3 3 11 11 4 4

Sample8 8 8 15 15 2 2

CHAPTER V. METHOD.

Additionally, the researcher underwent intra-rater reliability scores on 12,90% of the data belonging to the high proficiency group of participants. As can be seen in table 12 below, intra-rater scores arrived at 100%.

Table 12. Coding of errors (sorted by error type) by coder 1 (Intra-rater). Spelling errors not counted for oral data.

Lexical errors Morpho-syntactic errors Spelling errors

CODER 1 Coding 1 Coding 2 Coding 1 Coding 2 Coding 1 Coding 2

Sample 1 4 4 7 7 1 1

Sample 2 3 3 3 3 0 0

Sample 3 4 4 12 12 1 1

Sample 4 0 0 2 2 0 0

Sample 5 1 1 10 10 0 0

Sample 6 2 2 2 2 0 0

Sample 7 8 8 8 8 (Oral data) (Oral data)

Sample 8 4 1 4 1 (Oral data) (Oral data)

V.4.2.3. FLUENCY MEASURES. Schmidt defined fluency as “the processing of language in real time” (1992: 358) without the need for constant conscious attention. Characterising fluency as the easiness with which information from memory stores (both lexical and syntactic) is accessed, we are led to think that this information retrieval is, or at least should be, gradually automatized. This may indicate that the lexical or syntactic information referred to above is, albeit partially, proceduralised. This way, we should view fluency as a temporal phenomenon (Wolfe-Quintero, Inagaki and Kim, 1998) more specifically labelled as “the number of words and structures accessed in a given time span” (Chenoweth and Hayes, 2001). Fluency was operationalised in our research as what Skehan referred to as speed fluency (2009). Therefore, the measures selected are text-based measures which account for speech rate, that is, the number of words or syllables that fit in a

CHAPTER V. METHOD. given unit of measure. Fluency was then analysed using both the total number of words over the total number of minutes (words per minute) and the total number of syllables over the total number of minutes (syllables per minute). Despite the fact that these two measures may delve into the same construct, we considered appropriate to include the syllables per minute measure bearing in mind that in many languages there is a tendency for longer words, i.e. with more syllables, to exist. For this purpose, we used software which counts words. Once the word count had been carried out, words were manually separated into syllables and counted.

V.4.3. STATISTICAL ANALYSES. To shed light on the different research questions that guided our research, different statistical analyses on different group combinations were carried out. A summary of these is shown in Table 13 below. As can be seen from the table, the same kind of statistical analyses (but with different factors) was carried out for each study/experiment to find out the areas of language performance (operationalised as CAF measures) over which TR in the different conditions yielded significant results. One analysis aimed at finding out a possible TR effect across modalities as mediated by proficiency. For this purpose, a mixed analysis of variance (ANOVA) with a 2x2x2 factorial design was done. Task repetition was the within-subject factor at two different levels (T1 and T2) while we counted on two between-subject factors i.e. proficiency (at two different levels: low/high) and modality group (at two different levels: oral/writing). The second analysis targeted a possible effect of TR in writing mediated by different WCF treatment conditions (no feedback, direct WCF, indirect WCF and self-correction) and proficiency. A mixed ANOVA this time with a 2x4x2 factorial design was carried out. Again, task repetition was the within-subject factor at two different levels (T1 and T2) and also two between-subject factors i.e. proficiency (at two different levels: low/high) and feedback group (at four different levels, representing the four different conditions studied: no feedback, direct WCF, indirect WCF and self-correction). Univariate analyses were preferred, and the results reported were based on assumed sphericity. A pre-requisite for these kinds of tests is to comply with the sphericity assumption, which in this case would indicate that the variances of the differences between all combinations of related groups (levels) are equal. To confirm this assumption, Mauchly´s sphericity tests should be run. However, since the within-subject factor in our research comprised only two levels, this test was deemed unnecessary and we proceeded to run univariate tests directly.

CHAPTER V. METHOD.

Table 13. Statistical analyses. Between-subject Dependent variables Analysis RQs addressed Within-subject factor(s) Test & design factor(s)

RQ 1. Does TR across modalities (oral, Lexical complexity: D-value; Guiraud; Advanced Guiraud. writing) result in any quantitative Proficiency (Levels: 2): Syntactic complexity: High differences in learner´s performance as Mean length of T-unit; DC/T-unit; T- Task repetition (Levels: Low unit/sentence; NP complexity; STRUTt. 1. TR across modalities as quantified in different complexity, 2): Mixed ANOVA Accuracy: mediated by proficiency T1: first test Modality group 2x2x2 accuracy and fluency (CAF) measures? Total errors/100 words; total errors/T-unit; T2: second test (Levels:2): Are potential observed differences morpho-syntactic errors/100 words; G1. TR orally. morpho-syntactic errors/T-unit; lexical G2. TR in writing. mediated by proficiency? errors/100 words; lexical errors/T-unit; Fluency: Words/minute; syllables/minute. RQ2. Does TR in writing as a function of

written corrective feedback affect Lexical complexity: learners´ performance quantified in Proficiency (Levels: 2): D-value; Guiraud; Advanced Guiraud. CAF measures when they repeat the High Syntactic complexity: Mean length of T-unit; DC/T-unit; T- exact same task in writing? Are Low unit/sentence; NP complexity; STRUTt. potential observed differences found Modality group (Levels: Accuracy: Task repetition (Levels: Total errors/100 words; total errors/T-unit; mediated by proficiency? 4): 2. TR in writing as mediated 2): Mixed ANOVA G2. TR in writing. morpho-syntactic errors/100 words; by +/- WCF and proficiency RQ3. Does TR in writing as a function of T1: first test 2x4x2 G3. TR in writing with morpho-syntactic errors/T-unit; lexical T2: second test WCF type (direct, indirect) affect direct WCF. errors/100 words; lexical errors/T-unit; spelling errors/100 words; spelling learners´ performance measured in G4. TR in writing with indirect WCF. errors/T-unit CAF measures when they repeat the G5 TR in writing with Fluency: Words/minute; syllables/minute. exact same task in writing? Are self-correction. potential observed differences found mediated by proficiency?

CHAPTER VI. RESULTS.

VI. RESULTS

Results will be reported according to each of the research questions that guided our study. In the first place, the results with respect to the role that modality exerts on task repetition as a function of two proficiency levels will be presented, followed by the results regarding task repetition in writing with or without the availability of different forms of written corrective feedback as mediated by proficiency levels.

VI.1. TASK REPETITION ACROSS MODALITIES (ORAL/WRITING) AS MEDIATED BY PROFICIENCY. The first of our research questions asked whether task repetition performed in different modalities, i.e. orally or in writing, would result in quantitative differences in terms of CAF measures and if these differences would be mediated by proficiency (low vs. high proficiency). The analyses were conducted on the data from group 1 (TR orally) and group 2 (TR in writing). We will show the results according to each of the dependent variables subsumed under the triad CAF, that is complexity, understood as both syntactic and lexical complexity, accuracy and fluency.

Syntactic complexity.

Tables 14 (low proficiency) and 15 (high proficiency) below present the descriptive statistics for the measures of syntactic complexity, which were mean length of T-unit (MLT), dependent clauses per T-unit (DC/T), the measure for coordination (T/S), the measure for sub- clausal complexity (NPC) and the measure for syntactic variety (STRUTt –which accounts for sentence syntax similarity – reversely coded measure).

As shown in Table 14 below, low proficiency participants in the oral mode decreased in MLT (time 1=150.29; time 2=148.25) and DC/T (time 1= 2.85; time 2= 2.47), while they were able to perform better in the rest of the measures, T/S (time 1= 13.10; time 2= 13.37), NPC (time 1= .73; time 2= .78) and STRUTt (time1= .11; time 2= .13) as a consequence of task repetition. On the other hand, low proficiency writers were able to increase their performance only in the measures of T/S (time 1= 7.77; time= 8.91) and NPC (time 1= .19; time2= .23) while their performance decreased in the rest of the measures, that is, MLT (time 1= .180.85; time2= 157.30), DC/T (time 1= 4.33; time2= 1.79) and STRUTt (time 1= .16; time2= .15).

CHAPTER VI. RESULTS.

High proficiency participants in the oral modality were only able to increase their production in terms of syntactic variety, STRUTt (time 1= .11; time2= .13), while were unable to do so in the rest of the measures, namely MLT (time 1= 173.05; time2= 148.25), DC/T (time 1= 4.40; time2= 2.67), T/S (time 1= 12.30; time2= 12.05) and NPC (time 1= .78; time2= .72). In a similar way as low proficiency writers, high proficiency writers were able to increase their syntactic complexity in terms of coordination, T/S (time 1= 11.09; time2= 12.80), and sub-clausal complexity, NPC (time 1= .86; time2= .89), but failed to do so in the rest of the measures, MLT (time 1= 187.36; time2= 173.67), DC/T (time 1= 5.43; time2= 2.03) and STRUTt (time 1= .10; time2= .09). It is relevant to note that writers, regardless of their level of proficiency, performed in the same way in the repetition of the task in terms of syntactic complexity while speakers of different levels of proficiency behaved quite differently. Although these are evident tendencies, only significant results were found in one of the measures, DC/T (F (1, 25) = 5.33, MSe = 10.86, η2 = .18, p = .03) in one of the factors under analysis (repetition) as it is going to be reported in the next lines.

In the analyses of the within-subject factors, only one significant result was found in the factor repetition: MLT (F (1, 25) = 1.04, MSe = 1460.19, η2 = .04, p = .32); DC/T (F (1, 25) = 5.33, MSe = 10.86, η2 = .18, p = .03); T/S (F (1, 25) = .70, MSe = 10.52, η2 = .03, p = .41; NPC (F (1, 25) = .25, MSe = .01, η2 = .01, p = .62); STRUTt (F (1, 25) = .05, MSe = .00, η2 = .00, p = .82. The interaction repetition*proficiency was not statistically significant: MLT (F (1, 25) = .06, MSe = 1460.19, η2 = .00, p = .81); DC/T (F (1, 25) = .40, MSe = 10.86, η2 = .02, p = .82); T/S (F (1, 25) = .00, MSe = 10.52, η2 = .00, p = .99); NPC (F (1, 25) = 1.50, MSe = .01, η2 = .06, p = .23); STRUTt (F (1, 25) = .01, MSe = .00, η2 = .00, p = .92). Similarly, no statistically significant differences were found in the interaction repetition*group: MLT (F (1, 25) = .68, MSe = 1460.19, η2 = .03, p = .42); DC/T (F (1, 25) = 1.21, MSe = 10.86, η2 = .05, p = .28); T/S (F (1, 25) = .68, MSe = 10.52, η2 = .03, p = .42); NPC (F (1, 25) = .79, MSe = .01, η2 = .03, p = .38); STRUTt (F (1, 25) = .83, MSe = .00, η2 = .03, p = .37), and this was the case also for the triple interaction repetition*proficiency*group: MLT (F (1, 25) = .06, MSe = 1460.19, η2 = .00, p = .81); DC/T (F (1, 25) = .02, MSe = 10.86, η2 = .00, p = .89); T/S (F (1, 25) = .10, MSe = 10.52, η2 = .00, p = .76); NPC (F (1, 25) = .87, MSe = .01, η2 = .03, p = .36); STRUTt (F (1, 25) = .03, MSe = .00, η2 = .00, p = .86).

CHAPTER VI. RESULTS.

Table 14. Descriptive statistics. Syntactic complexity measures. Low proficiency participants.

Low MLT DC/T T/S NPC STRUTt

prof.

T1 T2 T1 T2 T1 T2 T1 T2 T1 T2

Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD

Oral 150.29 71.64 148.25 53.01 2.85 4.42 2.47 5.47 13.10 6.38 13.37 2.21 .73 .19 .78 .13 .11 .08 .13 .04

Written 180.85 52.99 157.30 61.40 4.33 5.52 1.79 3.83 7.77 6.17 8.91 5.36 0.91 .19 .95 .23 .16 .14 .15 .06

Table 15. Descriptive statistics. Syntactic complexity measures. High proficiency participants.

High MLT DC/T T/S NPC STRUTt

prof.

T1 T2 T1 T2 T1 T2 T1 T2 T1 T2

Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD

Oral 173.05 25.77 148.25 53.02 4.40 5.89 2.67 4.93 12.30 1.61 12.05 1.60 .78 .13 .72 .13 .11 .04 .13 .05

Written 187.36 50.04 173.67 19.10 5.43 6.16 2.03 3.52 11.09 5.04 12.80 1.79 .86 .07 .89 .15 .10 .03 .09 .02

CHAPTER VI. RESULTS.

In order to understand the significant result reported above in the measure of DC/T (factor repetition), we should look into Table 16 below, which shows the confidence intervals at 95% and the means for T1 and T2 for each of the dependent variables in the factor repetition. The mean value for all groups for DC/T in T1 as shown in Table 16 below is 4,25. This value falls beyond the upper limit in the confidence interval at 95% of T2 (3.98), which indicates that there has been a significant decrease in performance from T1 to T2. As seen in Tables 14 and 15 above, all groups decreased in performance from T1 to T2 in DC/T, especially in the case of the writing groups. In conclusion, task repetition was not found to not yield positive results in terms of syntactic complexity, and it resulted in a significant reduction of subordination (DC/T), more pronounced in the written mode.

Table 16. Confidence intervals 95% and means for factor repetition. Syntactic complexity.

Confidence interval 95% Measure Repetition Mean Lower limit Upper limit 1 4.25 2.14 6.36 DC/T 2 2.24 .51 3.98 1 11.07 9.00 13.13 T/S 2 11.78 10.52 13.04 1 172.89 151.94 193.83 MLT 2 162.59 143.61 181.57 1 .82 .76 .88 NPC 2 .84 .77 .90 1 .12 .09 .15 STRUTt 2 .12 .11 .14

Statistically significant results were found in between-subject factors. Statistically significant results were obtained for NPC (F (1, 25) = 7.78, MSe = .04, η2 = .24, p = .01) in the factor group. No significant results were found in the factor proficiency: MLT (F (1, 25) = 1.07, MSe = 3926.43, η2 = .04, p = .31); DC/T (F (1, 25) = .22, MSe = 39.51, η2 = .01, p = .65); T/S (F (1, 25) = .80, MSe = 28.87, η2 = .03, p = .38); NPC (F (1, 25) = .30, MSe = .04, η2 = .01, p = .59); STRUTt (F (1, 25) = 3.02, MSe = .01, η2 = .11, p = .10). Significant results were found in the factor group, albeit only in one measure: MLT (F (1, 25) = .73, MSe = 3926.43, η2 = .03, p = .40); DC/T (F (1, 25) = .03, MSe = 39.51, η2 = .00, p = .86); T/S (F (1, 25) = 3.25, MSe = 28.87, η2 = .12, p = .08); NPC (F (1, 25) = 7.78, MSe = .04, η2 = .24, p = .01); STRUTt (F (1, 25) = .07, MSe = .01, η2 = .00, p = .07). No significant findings were found in the factor proficiency*group either: MLT (F (1, 25) = .12, MSe = 3926.43, η2 = .01, p = .73); DC/T (F (1, 25) = .00, MSe = 39.51, η2 = .00, p = .95); T/S (F (1,

CHAPTER VI. RESULTS.

25) = 2.70, MSe = 28.87, η2 = .10, p = .11); NPC (F (1, 25) = .20, MSe = .04, η2 = .01, p = .66); STRUTt (F (1, 25) = 2.59, MSe = .01, η2 = .09, p = .12).

Table 17. Confidence intervals 95% and means for factor group. Syntactic complexity.

Confidence interval 95% Measure Group Mean Lower limit Upper limit DC Oral 3.10 .63 5.57 Written 3.40 1.03 5.77 T Oral 12.70 10.59 14.82 Written 10.14 8.12 12.17 MLT Oral 160.68 136.04 185.32 Written 174.79 151.18 198.41 NPC Oral .75 .67 .83 Written .90 .83 .98 STRUTt Oral .12 .09 .15 Written .12 .10 .15

To understand the significant result reported above in the measure of NPC (factor group), we have to look at Table 17 above. Table 17 shows the confidence intervals at 95% and the means for the oral and written groups for each of the dependent variables in the factor group. As we can see, the mean value for the written groups in the measure of NPC (.90) falls beyond the upper limit of the confidence interval at 95% for the oral groups (.83). This indicates that writers used more complex language in terms of NPC (sub-clausal complexity) than speakers did. Therefore, upon the light shed by these results, the writing mode emerges as a site which fosters the use of more complex language in terms of syntactic complexity than the oral modality. This is a worth-mentioning modality-related effect showing an advantage of the written modality over speech production which will be further addressed in the Discussion section.

Lexical complexity

Tables 18 and 19 show the descriptive statistics for the different measures of lexical complexity i.e. lexical diversity (D), lexical richness (G) and lexical sophistication (LS), for both proficiency groups (Table 18 for low proficiency participants and Table 19 for high proficiency participants).

CHAPTER VI. RESULTS.

Table 18. Descriptive statistics. Lexical complexity measures. Low proficiency participants.

Low D G LS prof.

T1 T2 T1 T2 T1 T2

Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD

Oral 22.35 6.98 24.10 8.83 4.60 .72 4.72 .93 .33 .13 .39 .30

Written 22.54 12.43 17.40 10.48 4.05 1.14 4.01 .86 .34 .24 .34 .18

Table 19. Descriptive statistics. Lexical complexity measures. High proficiency participants.

High D G LS prof.

T1 T2 T1 T2 T1 T2

Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD

Oral 33.75 9.35 31.88 10.32 5.56 .87 5.46 1.05 .48 .27 .62 .46

Written 45.24 9.65 48.02 13.63 7.18 1.15 7.12 1.23 1.02 .56 .99 .51

Low proficiency participants decreased their performance in terms of lexical complexity in all the three measures in the written modality –D (time 1= 22.54; time2= 17.40), G (time 1= 4.05; time2= 4.01) and LS (time 1= .86; time2= .34). In the oral mode, low proficiency participants increased in lexical richness, G (time 1= 4.60; time2= 4.72) and lexical variety, D (time 1= 22.35; time2= 24.10) while they decreased in lexical sophistication, LS (time 1= .93; time2= .39). High proficiency writers decreased in the areas of lexical richness, G (time 1= 7.18; time2= 7.12), and lexical sophistication, LS (time 1= 1.02; time2= .99), while they augmented their performance in terms of lexical diversity, D (time 1= 45.24; time2= 48.02). High proficiency participants in the oral group only increased in LS (time 1= .48; time2= .62) while they reduced their performance in lexical complexity in terms of D (time 1= 33.75; time2= 31.88) and G (time 1= 5.56; time2= 5.46).

CHAPTER VI. RESULTS.

Despite these tendencies, no significant results were found in any within-subject factor. Thus, no significant results were found in the factor repetition in any measure: D (F (1, 23) = .12, MSe= 42.32, η2 = .01, p= .73); G (F (1, 23) = .93, MSe= .26, η2 = .039, p = .35); LS (F (1, 23) = .71, MSe= .04, η2 = .03, p = .41), in the factor repetition*proficiency: D (F (1, 23)= .36, MSe= 42.32, η2 = .02, p = .55); G (F (1, 23)= .13, MSe= .26, η2 = .01, p = .72); LS (F (1, 23)= .04, MSe= .04, η2 = .00, p = .85); or the factor repetition*group: D (F (1, 23)= .10, MSe= 42.32, η2 = .00, p= .76); G (F (1, 23)= 1.07, MSe= .26, η2 = .05, p= .31); LS (F (1, 23)= 1.13, MSe= .04, η2 = .05, p = .30). No significant results were found in the factor repetition*proficiency*group: D (F (1, 23) = 2.62, MSe= 42.32, η2 = .10, p = .12); G (F (1, 23) = 1.41, MSe= .26, η2 = .06, p = .25); LS (F (1, 23) = .24, MSe= .04, η2 = .01, p = .63). As a consequence, we can conclude that task repetition does not yield any significant results regarding lexical complexity with regard to the results in the present study.

Statistically significant results were found in the between-subject factors in our study, namely proficiency (low vs. high) and group (oral vs. writing). In the factor proficiency, significant results were found in the three measures for lexical complexity: D (F (1, 23) = 24.20, MSe= 180.60, η2 = .51, p = .00; G (F (1, 23) = 25.87, MSe= 1.80, η2 = .529, p = .00); LS (F (1, 23) = 10.60, MSe= .225, η2 = .315, p = .00). On the contrary, no significant results were found in the factor group: D (F (1, 23) = 2.06, MSe= 180.60, η2 = .08, p = .16); G (F (1, 23) = 2.86, MSe= 1.80, η2 = .110, p = .11); LS (F (1, 23) = 2.80, MSe= .23, η2 = .11, p = .11). Significant results were found in the factor proficiency*group in the measures D (F (1, 23) = 5.37, MSe= 180.60, η2 = .08, p = 0.3 and G (F (1, 23) = 7.71, MSe= 1.80, η2 = .25, p = .01). but not in the measure for lexical sophistication: LS (F (1, 23) = 3.34, MSe= .23, η2 = .13, p = .08). To explain these results, we should look into Table 20 below, which shows the confidence intervals at 95% and means for the interaction group*proficiency.

Table 20. Confidence interval 95% and means for interaction group*proficiency. Lexical complexity.

Measure Proficiency Group Mean Confidence interval 95% Lower limit Upper limit D Low Oral 23.23 15.20 31.25 Written 19.97 13.02 26.92 High Oral 32.81 24.79 40.84 Written 46.63 39.20 54.06 LS Low Oral .36 .08 .64 Written .34 .10 .59 High Oral .55 .26 .83

CHAPTER VI. RESULTS.

Written 1.00 .74 1.27 G Low Oral 4.66 3.86 5.46 Written 4.26 3.57 4.95 High Oral 5.51 4.71 6.31 Written 7.15 6.41 7.90

As shown in Table 20, the effect for the factor proficiency indicates that high proficiency participants used more complex language than low proficiency participants in all the measures of lexical complexity, as could be expected. Similarly, the interaction group*proficiency shows that high proficiency writers used more complex language than high proficiency speakers in terms of both lexical diversity, D (oral= 32.81; written= 46.63) and richness, G (oral= 5.51; written= 6.41). This is a significant result since the mean values for high proficiency speakers in the measures of D (32.81) and G (5.51) are below the lower limit of the confidence interval high proficiency writers (D= 39.20; G= 6.41). Once more, this is a modality-related effect showing an advantage of the writing mode over the oral mode regarding the use of more complex linguistic items, this time concerning lexical aspects of language. Consequently, it could be assumed that writing prompts learners to use more complex language both in terms of syntactic and lexical complexity than the oral mode. This issue will be dealt with more in depth in the Discussion section.

Accuracy.

Tables 21, 22, 23 and 24 below show the descriptive statistics for accuracy measures. These are LEXE/100w (lexical errors per 100 words), MSE/100w (morpho-syntactic errors per 100 words), TOTALE/100w (total errors per 100 words), LEXE/T (lexical errors per T-unit), MSE/T (morpho-syntactic errors per T-unit) and TOTALE/T (total errors per T-unit). Tables 21 and 22 show results for low proficiency participants while Tables 23 and 24 present results for high proficiency participants.

CHAPTER VI. RESULTS.

Table 21. Descriptive statistics. Accuracy measures. Low proficiency participants (1).

Low LEXE/100w MSE/100w TOTALE/100w prof.

T1 T2 T1 T2 T1 T2

Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD

Oral 4.40 2.92 6.02 5.30 11.06 4.42 9.18 3.70 15.45 6.30 15.21 6.92

Written 4.38 3.39 6.60 7.25 12.52 5.62 13.96 8.81 16.90 7.13 20.55 15.18

Table 22. Descriptive statistics. Accuracy measures. Low proficiency participants (2).

Low LEXE/T MSE/T TOTALE/T prof.

T1 T2 T1 T2 T1 T2

Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD

Oral .68 .52 .86 .72 1.63 .33 1.38 .50 2.31 .77 2.23 .94

Written .61 .46 .88 .90 1.76 .81 1.87 1.05 2.37 1.06 2.74 1.80

As shown in Tables 21 and 22 above, task repetition did not yield positive results in learners of low level of proficiency in the written modality. They produced more errors in the measures of LEXE/100w (time1= 4.38; time 2= 6.60), MSE/100w (time1= 12.52; time 2= 13.96), TOTALE/100w (time1= 16.90; time 2= 20.55), LEXE/T (time1= .61; time 2= .88), MSE/T (time1= 1.76; time 2= 1.87) and TOTALE/T (time1= 2.37; time 2= 2.74) in T2 than in T1. Therefore, we can conclude that task repetition in the written mode does not foster greater accuracy for learners of low levels of proficiency. On the contrary, low proficiency participants in the oral mode, were able to decrease their rate of errors in MSE/100w (time1= 11.06; time 2= 9.18), and

CHAPTER VI. RESULTS.

MSE/T (time1= 1.63; time 2= 1.38), reducing as a consequence their rate of errors in the measures of TOTALE/100w (time1= 15.45; time 2= 15.21), and TOTALE/T (time1= 2.31; time 2= 2.23), as well, due to task repetition. However, they increased their rate of errors in the measures for LEXE/100w (time1= 4.40; time 2= 6.02) and LEXE/T (time1= .68; time 2= .86). Low proficiency speakers were more accurate than low proficiency writers, except for the measures of LEXE/100w and LEXE/T in T1.

Table 23. Descriptive statistics. Accuracy measures. High proficiency participants (1).

High LEXE/100w MSE/100w TOTALE/100w prof.

T1 T2 T1 T2 T1 T2

Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD

Oral .01 .01 .00 .01 0.4 0.3 0.3 0.2 .05 .02 0.4 .02

Written .01 .01 .00 .01 .03 0.1 0.2 .01 .04 .02 .03 .01

Table 24. Descriptive statistics. Accuracy measures. High proficiency participants (2).

High LEXE/T MSE/T TOTALE/T prof.

T1 T2 T1 T2 T1 T2

Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD

Oral .16 .16 .12 .11 .76 .50 .46 .24 .92 .43 .58 .25

Written .19 .12 .13 .13 .59 .22 .41 .16 .78 .30 .53 .18

On the other hand, high proficiency participants, regardless of modality of production, were able to decrease their error rate from T1 to T2 in all the measures o as a result of task

CHAPTER VI. RESULTS. repetition. High proficiency speakers reduced their errors in LEXE/100w (time1= .01; time 2= .00), MSE/100w (time1= .04; time 2= .03), TOTALE/100w (time1= .05; time 2= .04), LEXE/T (time1= .16; time 2= .12), MSE/T (time1= .76; time 2= .46) and TOTALE/T (time1= .92; time 2= .58) and high proficiency writers also increased in accuracy in the measures of LEXE/100w (time1= .01; time 2= .00), MSE/100w (time1=.04; time 2= .03), TOTALE/100w (time1= .04; time 2= .03), LEXE/T (time1= .19; time 2= .13), MSE/T (time1= .59; time 2= .41) and TOTALE/T (time1= .78; time 2= .53). Furthermore, contrarily to low proficiency participants, high participants in the written mode were more accurate than high proficiency speakers except for the measure of LEXE/T both in T1 and T2, where speakers were more accurate, and in the measure of LEXE/100w, in which all high proficiency participants were equally accurate.

While the results in the descriptive statistics showed certain tendencies, no statistically significant results were found in the within subject factors. No significant results were found in the factor repetition: LEXE/100w (F (1, 25) = 2.00, MSe = 6.62, η2 = .07, p = .17); MSE/100w (F (1, 25) = .02, MSe = 7.85, η2 = .00, p = .87); TOTALE/100w (F (1, 25) = .54, MSe = 19.14, η2 = .02, p = .47); LEXE/T (F (1, 25) = .89, MSe = .12, η2 = .03, p = .36); MSE/T (F (1, 25) = 3.15, MSe = .11, η2 = .11, p = .09); TOTALE/T (F (1, 25) = .25, MSe = .30, η2 = .01, p = .62) in the factor repetition*proficiency: LEXE/100w (F (1, 25) = 2.01, MSe = 6.62, η2 = .07, p = .17); MSE/100w (F (1, 25) = .02, MSe = 7.85, η2 = .00, p = .89); TOTALE/100w (F (1, 25) = .55, MSe = 19.14, η2 = .02, p = .46); LEXE/T (F (1, 25) = 2.26, MSe = .12, η2 = .08, p = .15); MSE/T (F (1, 25) = .88, MSe = .11, η2 = .03, p = .36); TOTALE/T (F (1, 25) = 2.27, MSe = .30, η2 = .08, p = .14), or in the factor repetition*group: LEXE/100w (F (1, 25) = .05, MSe = 6.62, η2 = .00, p = .83); MSE/100w (F (1, 25) = 1.24, MSe = 7.85, η2 = .05, p = .28); TOTALE/100w (F (1, 25) = .71, MSe = 19.14, η2 = .03, p = .41); LEXE/T (F (1, 25) = .04, MSe = .12, η2 = .00, p = .84); MSE/T (F (1, 25) = 1.80, MSe = .11, η2 = .07, p = .19); TOTALE/T (F (1, 25) = .89, MSe = .30, η2 = .03, p = .36). No significant results were found in the factor repetition*proficiency*group either: LEXE/100w (F (1, 25) = .05, MSe = 6.62, η2 = .00, p = .83); MSE/100w (F (1, 25) = .1.24, MSe = 7.85, η2 = .05, p = .28); TOTALE/100w (F (1, 25) = .71, MSe = 19.14, η2 = .03, p = .41); LEXE/T (F (1, 25) = .09, MSe = .12, η2 = .00, p = .77); MSE/T (F (1, 25) = .51, MSe = .11, η2 = .02, p = .48); TOTALE/T (F (1, 25) = .39, MSe = .30, η2 = .02, p = .54). We can conclude that task repetition does not yield significant positive effects in terms of accuracy regardless of modality of production and proficiency level of the participants.

Significant results were found in between-subject factors, reported in the following lines. Significant results were found in the factor proficiency: LEXE/100w (F (1, 25) = 18.92, MSe = 21.59, η2 = .43, p = .00); MSE/100w (F (1, 25) = 60.52, MSe = 32.05, η2 = .71, p = .00); TOTALE/100w (F (1, 25) = 49.04, MSe = 84.17, η2 = .66, p = .00); LEXE/T (F (1, 25) = 13.38, MSe

CHAPTER VI. RESULTS.

= .40, η2 = .35, p = .01); MSE/T (F (1, 25) = 31.30, MSe = .56, η2 = .56, p = .00); TOTALE/T (F (1, 25) = 29.72, MSe = 1.41, η2 = .54, p = .00). However, no significant results were found for the factor group: LEXE/100w (F (1, 25) = .01, MSe = 21.59, η2 = .00, p = .91); MSE/100w (F (1, 25) = 1.08, MSe = 32.05, η2 = .04, p = .31); TOTALE/100w (F (1, 25) = .48, MSe = 84.17, η2 = .02, p = .49); LEXE/T (F (1, 25) = .00, MSe = .40, η2 = .00, p = .99); MSE/T (F (1, 25) = .24, MSe = .56, η2 = .01, p = .63); TOTALE/T (F (1, 25) = .95, MSe = 1.41, η2 = .00, p = .76). Finally, no significant results were found in the proficiency*group either: LEXE/100w (F (1, 25) = .01, MSe = 21.59, η2 = .00, p = .91); MSE/100w, (F (1, 25) = 1.09, MSe = 32.05, η2 = .04, p = .31); TOTALE/100w (F (1, 25) = .49, MSe = 84.17, η2 = .02, p = .49); LEXE/T (F (1, 25) = .02, MSe = .40, η2 = .00, p = .90); MSE/T (F (1, 25) = 1.12, MSe = .56, η2 = .04, p = .30); TOTALE/T (F (1, 25) = .35, MSe = 1.41, η2 = .01, p = .56).

To understand these results, we should look into Table 25 below showing the confidence intervals for the factor proficiency. As the table shows, higher proficiency participants were significantly more accurate than low proficiency participants, a result which is consistent regardless of modality of production and across all measures for accuracy since the mean value for high proficiency participants in the measures of LEXE/100w (.01), MSE/100w (.03), TOTALE/100w (.04), LEXE/T (.15), MSE/T (.56) and TOTALE/T (.70) are under the lower limit of the confidence interval of low proficiency participants LEXE/100w (3.66), MSE/100w (9.62), TOTALE/100w (13.69), LEXE/T (.53), MSE/T (1.39) and TOTALE/T (1.98),

Table 25. Confidence intervals at 95% and means for factor proficiency. Accuracy measures.

Confidence interval 95% Measure Proficiency Mean Lower limit Upper limit Low 5.35 3.66 7.04 LEXE/100w High .01 -1.87 1.89 Low 11.68 9.62 13.74 MSE/100w High .03 -2.26 2.33 Low 17.03 13.69 20.37 TOTALE/100w High .04 -3.68 3.76 Low .76 .53 .99 LEXE/T High .15 -.11 .40 Low 1.66 1.39 1.93 MSE/T High .56 .25 .86 Low 2.41 1.98 2.85 TOTALE/T High .70 .22 1.18

CHAPTER VI. RESULTS.

Fluency.

Tables 26 and 27 below show the descriptive statistics for the fluency measures i.e. words/minute and syllables/minute for both low (Table 26) and high proficiency participants (Table 26). All groups were able to improve their fluency from time 1 to time 2 regardless of modality under which task repetition took place or proficiency level of the participants. Low proficiency participants in the oral modality increased from T1 to T2 in the measure of words/minute (time 1= 39.66; time 2= 54.73) and the measure of syllables/minute (time 1= 49.57; time 2= 68.84). Low proficiency writers also increased their fluency from T1 to T2 in both the measure of words/minute (time 1= 5.18; time 2= 7.55) and the measure of syllables/minute (time 1= 6.45; time 2= 9.40). In a similar way, high proficiency participants increased their fluency in the oral mode in words/minute (time 1= 90.61; time 2= 112.80) and syllables/minute (time 1= 111.14; time 2= 131.84) and in writing in both measures too, words/minute (time 1= 12.76; time 2= 18.60) and syllables/minute (time 1= 15.56; time 2= 24.21). Regarding statistical analyses run on our within-subject factor, repetition, significant results were found in the factor repetition in the measure of words/minute (F (1, 25) =29.675, MSe=62.206, η2 = .543, p = .00) and in the measure of syllables/minute (F (1, 25) =52.4747, MSe=45.125, η2 = .677, p = .00). Significant results were found as a result of task repetition. However, to reach to a more fine- grained explanation of these results we should look more closely to the rest of the factors and interactions.

Table 26. Descriptive statistics for fluency measures. Low proficiency participants. Low Words/minute Syllables/minute proficiency

T1 T2 T1 T2

Mean SD Mean SD Mean SD Mean SD

Oral 39.66 23.56 54.73 23.13 49.57 28.48 68.84 27.50

Written 5.18 3.10 7.55 3.58 6.45 3.68 9.40 4.00

CHAPTER VI. RESULTS.

Table 27. Descriptive statistics for fluency measures. High proficiency participants. High Words per m. Syllables per m. proficiency

T1 T2 T1 T2

Mean SD Mean SD Mean SD Mean SD

Oral 90.61 16.85 112.80 13.19 111.14 21.82 131.84 18.73

Written 12.76 3.28 18.59 7.15 15.66 5.05 24.21 9.66

Significant results were found in the factor repetition*group in the measure of words/minute (F (1, 25) = 12.117, MSe = 62.206, η2 = .326, p = .002). This was also the case for the measure of syllables/minute (F (1, 25) = 16.054, MSe = 45.125, η2 = .391, p = .00). This interaction shows that the group (i.e. modality) in which task repetition is carried out plays a role when analysing its effects on fluency.

No significant results were found in the factor repetition*proficiency, since results were significant in neither the measure of words/minute (F (1, 25) = 1.065, MSe = 62.206, η2 = 0.60, p = .217) nor the measure of syllables/minute (F (1, 25) = .981, MSe = 45.125, η2 = .038, p = .331). This implies that the effect reported in the previous factor (repetition*group) is not affected by proficiency, implying that this variable does not have a mediating role when implementing task repetition in the written modality nor orally.

Finally, no significant results were found in the factor repetition*proficiency*group in any of the measures: words/minute (F (1, 25) = .193, MSe= 62.206, η2 = .008, p = .664; syllables/minute (F (1, 25) = .345, MSe= 45.125, η2 = .014, p = .562) confirming the result previously mentioned regarding the lack of a role for proficiency on task repetition. It is modality (i.e. group) the variable which mediates positive results for task repetition as long as fluency measures are concerned.

In order to understand the results reported above, we have to look at the confidence intervals in the factor repetition*group, shown in Table 28 below. Only the groups which performed task repetition in the oral modality were able to increase their fluency rate significantly regardless of proficiency level since the mean value for their performance in time 2 (words/minute= 83.76; syllables/minute= 100.34) is higher than the upper limit of the confidence interval for time 1 (words/minute= 73.34; syllables/minute= 90.49). On the other hand, although there is a tendency to increase fluency in the writing groups (words/minute time

CHAPTER VI. RESULTS.

1= 8.97; time 2= 13.07 and syllables/minute time 1= 11.05; time 2= 16.81), this increase does not reach significance. Therefore, task repetition fosters a significant increase in fluency in the oral modality but not in writing and these effects are not mediated by proficiency.

Table 28. Confidence intervals 95% and means for factor repetition*group. Fluency measures. Confidence Interval 95% Measure Group Time Mean Lower limit Upper limit 1 65.14 56.94 73.34 Oral 2 83.76 75.89 91.64 Words/minute 1 8.97 1.11 16.83 Written 2 13.07 5.53 20.62 1 80.35 70.22 90.49 Oral 2 100.34 90.57 110.11 Syllables/minute 1 11.05 1.34 20.77 Written 2 16.81 7.44 26.17

Significant results were found in the between-subject factors. In the factor group, significant results were found in both the measure of words/minute (F (1, 25) = 33.10, MSe= 355.83, η2 = .57, p = .00) and syllables/minute (F (1, 25) = 20,52, MSe= 595.95, η2 = .45, p = .00. as well as in the factor proficiency in both measures too: words/minute (F (1, 25) = 40.92, MSe= 355.83, η2 = .62, p = .00); syllables/minute (F (1, 25) = 140.10, MSe= 595.95, η2 = .85, p = .00). Finally, significant results were also found in the interaction group*proficiency: words/minute (F (1, 25) = 161.65, MSe= 355.83, η2 = .87, p = .00); syllables/minute (F (1, 25) = 15.16, MSe= 595.95, η2 = .38, p = .00).

Table 29. Confidence intervals 95% for between-subject factors. Fluency measures. Confidence Interval 95% Measure Proficiency Group Mean Lower limit Upper limit Oral 47.19 37.48 56.91 Low Written 6.37 -3.35 16.08 Words/minute Oral 101.70 90.49 112.92 High Written 15.68 5.29 26.06 Oral 59.21 46.64 71.78 Low Written 7.93 -4.64 20.49 Syllables/minute Oral 121.49 106.97 136.00 high Written 19.93 6.50 33.37

CHAPTER VI. RESULTS.

To understand the significant results found in the between-subject factors, we should look into Table 29 above, which shows the confidence intervals at 95% and the mean values for the between-subject factors i.e. proficiency and group. On the one hand, the significant result for the factor group indicates that speakers were more fluent than writers. On the other, the effect for the factor proficiency would imply that high proficiency participants were more fluent than low proficiency participants, but the interaction group*proficiency reveals that the significant effect for proficiency is only found in the oral groups. That is, high proficiency speakers were significantly more fluent than low proficiency speakers since the mean values for high proficiency speakers (words/minutes= 101.70; syllables/minute= 121.49) are higher than the upper limit of the confidence intervals of low proficiency speakers (words/minutes= 56.91; syllables/minute= 71.78) whereas the mean values for high proficiency writers (words/minutes= 15.68; syllables/minute= 19.93) fall within the lower and upper limits of the confidence intervals for low proficiency writers (words/minute= -3.35 – 16.08; syllables/minute= -4.64 – 20.49) and, therefore, did not reach significance.

To summarise, no significant results were found in the area of accuracy due to task repetition. Similarly, no significant effect for lexical complexity was found. On the other hand, significant differences were found in the area of syntactic complexity. More precisely, this significant result relies on the significant reduction in the measure for subordination across groups from time 1 to time 2, being this decrease much more marked for writing groups. Regarding fluency, significant results were found which mainly point out that task repetition leads to a more significant fluent performance. However, this effect was only found for learners who engaged in task repetition in the oral modality regardless of proficiency level.

Regarding modality-related effects, significant results were found in the areas of lexical and syntactic complexity. These results indicate that the written mode prompts the use of more complex language in terms of lexical diversity and lexical richness by high-proficiency learners and more complex language in terms of subclausal complexity across proficiency levels.

VI.2. TASK REPETITION AS MEDIATED BY DIFFERENT TYPES OF WCF AND PROFICIENCY. Our second research questions asked whether task repetition performed in the written mode as mediated by the presence or absence of different types of written corrective feedback would result in quantitative differences in terms of CAF measures and if these differences would be proficiency dependent (low vs. high proficiency). Results will be presented according to each

CHAPTER VI. RESULTS. of the dependent variables pooled under the triad CAF, precisely complexity, understood as both syntactic and lexical complexity, accuracy and fluency.

Syntactic complexity.

Tables 30 (low proficiency) and 31 (high proficiency) below present the descriptive statistics for the measures of syntactic complexity in our study i.e. mean length of T-unit (MLT), dependent clauses per T-unit (DC/T), the measure for coordination (T/S), the measure for sub- clausal complexity (NPC) and the measure for syntactic variety (STRUTt – sentence syntax similarity, that is, reversely coded measure).

As can be withdrawn from the Tables 30 and 31 below, task repetition in writing yielded minimal differences when compared to performance in T1 in terms of syntactic complexity. With regard to low proficiency learners, those in the writing condition were able to perform better in terms of coordination (T/S) (time 1= 7.77; time 2= 8.91) and sub-clausal complexity (NPC) (time 1= .91; time 2= .95). In a similar fashion, participants in the Direct WCF group performed better in the measures of subordination (DC/T) (time 1= .54; time 2= 1.77), coordination (T/S) (time 1= 10.22; time 2= 10.66) and sub-clausal complexity (NPC) (time 1= .83; time 2= .94). On the other hand, participants in the indirect WCF group only increased in coordination (T/S) (time 1= 10.78; time 2= 12.46) while those in the self-correction group only did so in the area of subordination (DC/T) (time 1= .64; time 2= 2.96). We should remark that the groups who increased in subordination (DC/T) performed better in T2 since their score for that measure in T1 was very low. High proficiency learners behaved very much alike upon task repetition as far as syntactic complexity is concerned. Participants in the writing group increased in coordination (T/S) (time 1= 11.09; time 2= 12.80) and subclausal complexity (NPC) (time 1= .86; time 2= .89). Participants in the direct WCF group did better in terms of coordination (T/S) (time 1= 11.61; time 2= 12.16) and subclausal complexity (NPC) (time 1= .83; time 2= .84) as opposed to those in the indirect WCF group who only increased in subclausal complexity (NPC) (time 1= .84; time 2= .89). Learners in the self-correction group, on the other hand, only increased their rate of coordination (T/S) (time 1= 12.07; time 2= 12.29).

Despite the tendencies shown above, no statistically significant results were found for any factor. No significant effects were found in the factor repetition: MLT, (F (1, 44) = 3.05, MSe = 672.00, η2 = .07, p = .08); DC/T , (F (1, 44) = 2.12, MSe = 11.64, η2 = .05, p = .15); T/S, (F (1, 44) = 1.19, MSe = 7.37, η2 = .03, p = .28); NPC, (F (1, 44) = 1.48, MSe = .01, η2 = .03, p = .23); STRUTt, (F (1, 44) = 1.01, MSe = .00, η2 = .02, p = .32). Similarly, no significant results were found in the

CHAPTER VI. RESULTS. factor repetition*proficiency either: MLT, (F (1, 44) = .17, MSe = 672.00, η2 = .00, p = .68); DC/T , (F (1, 44) = .96, MSe = 11.64, η2 = .02, p = .33); T/S, (F (1, 44) = .00, MSe = 7.37, η2 = .00, p = .96); NPC, (F (1, 44) = 1.00, MSe = .01, η2 = .00, p = .76); STRUTt, (F (1, 44) = .75, MSe = .00, η2 = .02, p = .39). Additionally, no statistically significant differences were found in the factor repetition*group: MLT, (F (3, 44) = .64, MSe = 672.00, η2 = .04, p = .59); DC/T , (F (3, 44) = 1.56, MSe = 11.64, η2 = 1.00, p = .21); T/S, (F (3, 44) = .49, MSe = 7.37, η2 = .03, p = .69); NPC, (F (3, 44) = .83, MSe = .01, η2 = .05, p = .48); STRUTt, (F (3, 44) = 1.03, MSe = .00, η2 = .07, p = .39). No significant differences were found in the factor repetition*proficiency*group: MLT, (F (3, 44) = .15, MSe = 672.00, η2 = .01, p = .93); DC/T , (F (3, 44) = .52, MSe = 11.64, η2 = .03, p = .67); T/S, (F (3, 44) = .33, MSe = 7.37, η2 = .02, p = .80); NPC, (F (3, 44) = .83, MSe = .01, η2 = .05, p = .48); STRUTt, (F (3, 44) = .35, MSe = .00, η2 = .02, p = .79).

As evidenced in the results reported above, no significant results were found for task repetition in the written modality in terms of syntactic complexity regardless of proficiency level (low vs. high) or implementation condition (+/- WCF provision and processing).

Regarding between subject factors, significant results were found in the factor proficiency, albeit only in certain measures: MLT, (F (1, 44) = 16.47, MSe = 2715.69, η2 = .27, p = .00); DC/T , (F (1, 44) = 3.95, MSe = 37.04, η2 = .08, p = .05); T/S, (F (1, 44) = 3.62, MSe =18.30, η2 = .08, p = .06); NPC, (F (1, 44) = .19, MSe = .05, η2 = .00, p = .67); STRUTt, (F (1, 44) = 14.07, MSe = .03, η2 = .24, p = .00). On the contrary, no significant differences were found in the factor group: MLT, (F (3, 44) = .67, MSe = 2715.69, η2 = .04, p = .57); DC/T , (F (3, 44) = .15, MSe = 37.04, η2 = .01, p = .93); T/S, (F (3, 44) = .51, MSe =18.30, η2 = .03, p = .68); NPC, (F (3, 44) = .92, MSe = .05, η2 = .06, p = .44); STRUTt, (F (3, 44) = .47, MSe = .03, η2 = .03, p = .71); and no significant results were found in the factor proficiency*group either: MLT, (F (3, 44) = 1.08, MSe = 2715.69, η2 = .07, p = .37); DC/T , (F (3, 44) = .35, MSe = 37.04, η2 = .02, p = .79); T/S, (F (3, 44) = 1.05, MSe =18.30, η2 = .07, p = .38); NPC, (F (1, 44) = .49, MSe = .05, η2 = .03, p = .69); STRUTt, (F (3, 44) = .34, MSe = .03, η2 = .02, p = .80).

CHAPTER VI. RESULTS.

Table 30. Descriptive statistics for syntactic complexity measures. Low proficiency participants.

Low MLT DC/T T/S NPC STRUTt

proficiency

T1 T2 T1 T2 T1 T2 T1 T2 T1 T2

Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD

Written 180.85 52.99 157.30 61.40 4.33 5.52 1.79 3.83 7.77 6.17 8.91 5.36 .91 .19 .95 .23 .16 .14 .15 .06

Direct WCF 149.95 32.58 143.80 28.85 .54 .30 1.77 3.64 10.22 4.34 10.66 .83 .83 .19 .94 .23 .11 .04 .16 .06

Indirect WCF 141.15 33.71 127.27 33.20 2.64 5.77 .36 .24 10.78 4.79 12.46 2.55 .81 .11 .81 .17 .13 .07 .17 .05

Self- 130.41 16.40 129.73 38.71 .64 .25 2.96 5.80 10.85 .83 9.84 5.24 .84 .20 .80 .11 .13 0.5 .13 .02 correction

CHAPTER VI. RESULTS.

Table 31. Descriptive statistics for syntactic complexity measures. High proficiency participants.

High MLT DC/T T/S NPC STRUTt

proficiency

T1 T2 T1 T2 T1 T2 T1 T2 T1 T2

Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD

Written 187.36 50.04 173.67 19.10 5.43 6.16 2.03 3.52 11.09 5.04 12.80 1.79 .86 .07 .89 .15 .10 .03 .09 .02

Direct WCF 202.60 56.77 189.48 56.58 5.65 7.86 4.04 5.46 11.61 1.64 12.16 2.48 .83 .16 .84 .09 .10 .01 .10 .03

Indirect WCF 188.05 38.84 183.49 22.05 3.93 5.12 2.92 5.92 11.19 .92 11.16 .56 .84 .17 .89 .22 .11 .02 .12 .03

Self- 183.05 26.05 187.30 41.15 5.43 5.23 4.86 6.70 12.07 1.28 12.29 2.29 .81 .14 .79 .05 .10 .02 .10 .03 correction

CHAPTER VI. RESULTS.

To understand the significant results reported above in the between-subject factor proficiency we should look into Table 32 below showing the means and confidence intervals at 95% for such factor.

Table 32. Mean and confidence intervals 95% for factor Proficiency. Syntactic complexity measures.

Measure Proficiency Mean Confidence interval 95% Lower limit Upper limit DC/T Low 1.88 .18 3.58 High 4.29 2.54 6.03 T/S Low 10.19 8.99 11.38 High 11.80 10.57 13.02 MLT Low 145.06 130.55 159.57 High 186.91 172.03 201.80 NPC Low .86 .80 .92 High .84 .78 .91 STRUTt Low .14 .13 .16 High .10 .09 .12

As shown in Table 32 above, the mean values for high proficiency participants for the measures of subordination (DC/T) (4.29), overall syntactic complexity (MLT) (186.91) are higher than the value of the upper limit in the confidence interval for low proficiency participants while the mean value for syntactic variety (STRUTt) (.10) is below the lower limit – reversely coded measure. This indicates that the results were found to be significant. The measure of coordination (T/S) resulted almost significant (p=.06) and even the mean value for high proficiency participants in this measure (11.80) is higher than the upper limit in the confidence interval of low proficiency participants (11.38), but we should not consider this a significant result. On the other hand, participants at the two levels of proficiency performed very similarly in the measure for sub-clausal complexity (NPC) (.86 – low proficiency; .84 – high proficiency). It may be the case that high proficiency participants reached a task-related ceiling effect in coordination and sub-clausal complexity and therefore did not perform significantly better than low proficiency participants in these two dimensions of syntactic complexity.

Lexical complexity.

Tables 33 and 34 below (Table 33 for low proficiency participants and Table 34 for high proficiency participants) show the descriptive statistics for the different measures of lexical

CHAPTER VI. RESULTS. complexity i.e. lexical diversity (D), lexical richness (G) and lexical sophistication (LS). It can be depicted that task repetition in the written modality yields very subtle changes regarding lexical complexity. Regarding low proficiency learners, only participants in the direct WCF and self- correction groups were able to increase their lexical variety (D), but to a very reduced extent while there was a general decline in lexical richness (G) in all groups. Regarding lexical sophistication, only participants in the indirect and self-correction groups were able to increase their performance, being such increase more marked in the self-correction group, mainly due to the fact that their performance in T1 was much more reduced. Participants in the different groups seem to have favoured different aspects of lexical complexity. Participants who received direct WCF seem to have made use of greater lexical diversity due to task repetition whereas those who received indirect WCF showed greater sophistication. On the other hand, participants in the self-correction group favoured these two aspects of lexical complexity while learners in the writing group did not increase their lexical complexity at all. This may indicate the beneficial effects of performing FoF stages prior to engaging in the repetition of a task in the written modality by low proficiency learners.

With respect to high proficiency learners, the emerging picture is very similar to that of low proficiency participants explained above. All groups seem to have taken advantage in some area of lexical complexity. The writing group increased in lexical diversity (D), the direct WCF group did so in lexical richness (G), while the indirect WCF and the self-correction groups increased lexical sophistication as a consequence of task repetition. Apart from the areas mentioned, the groups decreased their performance in lexical complexity in general terms. However, it should be noted that the results on lexical complexity upon task repetition in writing, whether positive or not, are rather limited for high proficiency participants too.

CHAPTER VI. RESULTS.

Table 33. Descriptive statistics for lexical complexity measures. Low proficiency participants.

Low D G LS prof.

T1 T2 T1 T2 T1 T2

Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD

Written 22.54 12.43 17.40 10.48 4.05 1.14 4.01 .86 .34 .24 .34 .18

Direct WCF 27.30 13.55 27.91 11.80 4.97 1.17 4.81 1.10 .46 .23 .44 .23

Indirect WCF 26.13 7.79 24.84 5.64 4.90 .52 4.82 .66 .37 .24 .46 .42

Self-correction 25.08 6.69 25.68 4.44 4.83 .49 4.80 .29 .40 .12 .47 .25

CHAPTER VI. RESULTS.

Table 34. Descriptive statistics for lexical complexity measures. High proficiency participants.

High D G LS prof.

T1 T2 T1 T2 T1 T2

Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD

Written 45.24 9.65 48.02 13.63 7.18 1.15 7.12 1.23 1.02 .56 .99 .51

Direct WCF 45.44 9.26 44.43 9.36 7.14 1.00 7.22 1.42 .93 .54 1.11 .54

Indirect WCF 40.78 7.61 38.40 5.28 6.93 1.13 6.50 .66 .83 .29 .80 .30

Self-correction 56.33 11.40 55.00 11.30 8.12 .92 7.81 1.12 1.32 .22 1.25 .43

CHAPTER VI. RESULTS.

Significant results in the factor repetition were found in one of the measures: D (F (1, 44) = .63, MSe = 32.15, p = .43, η2 =.01); G (F (1, 44) = 5.09, MSe = .17, p = .03, η2 =.10); LS (F (1, 44) = .53, MSe = .03, p = .47, η2 = .01). No other significant results were found in any other factor as can be seen as follows in the results for the factor repetition*proficiency: D (F (1, 44) = .13, MSe = 32.15, η2 =.00, p = .72); , (F (1, 44) = .00, MSe = .17, η2 =.00, p = .96); LS (F (1, 44) = .16, MSe = .03, η2 = .00, p = .69), the results for the factor repetition*group: D (F (3, 44) = .11, MSe = 32.15, η2 =.01, p = .95); G (F (3, 44) = .44, MSe = .17, η2 =.03, p = .73); LS (F (3, 44) = .42, MSe = .03, η2 = .03, p = .74) and the results for the factor repetition*proficiency*group: D (F (3, 44) = 1.23, MSe = 32.15, η2 =.08, p = .31); G (F (3, 44) = 1.41, MSe = .17, p = .25, η2 =.09); LS (F (3, 44) = .1.37, MSe = .03, η2 = .09, p = .26).

To be able to understand the significant result reported above, we should look into Table 35 below, which presents the means and confidence intervals for the factor repetition of the three measures regarding lexical complexity.

Table 35. Mean and confidence intervals 95% for factor repetition. Lexical complexity measures. Measure repetition Mean Confidence interval 95% Lower limit Upper limit D 1 36.11 33.20 39.01 2 35.21 32.46 37.97 LS 1 .71 .61 .81 2 .73 .63 .84 G 1 6.07 5.79 6.35 2 5.89 5.61 6.17

As reported above, the measure for lexical richness (G) yielded a significant result. Strikingly, when looking at the mean values for both T1 (36.11) and T2 (35.21) of this measure, we can see that they are between the lower or upper limits for T1 (33.20-39.01) and T2 (32.46- 37.97). Therefore, we are facing a false positive result, claim which can also be reinforced by the low effect size (η2 =.10) reported for this result. Since no other significant results were reported, we could argue that task repetition in the written mode does not result in beneficial effects in terms of lexical complexity.

The results pertaining the between subject factor in our research are reported in the following lines. Significant results were found in the factor proficiency: D (F (1, 44) = 73.67, MSe = 169.20, η2 = .63, p = .00), G (F (1, 44) = 165.59, MSe = 1.79, η2 = .68, p = .00), LS (F (1, 44) =

CHAPTER VI. RESULTS.

42.29, MSe = .23, η2 = .49, p = .00). No significant results were found in the factor group: D (F (3, 44) = 1.84, MSe = 169.20, η2 = .11, p = .15), G (F (3, 44) =1.28, MSe = 1.79, η2 = .08, p = .29), LS (F (3, 44) = 1.14, MSe = .23, η2 = .07, p = .34), or in the factor proficiency*group: D (F (3, 44) = 2.13, MSe = 169.20, η2 = .12, p = .11), G (F (3, 44) =1.18, MSe = 1.79, η2 = .08, p = .33) LS, (F (3, 44) = .92, MSe = .23, η2 = .06, p = .44).

Table 36 below (means and confidence intervals for the factor proficiency) shows that high proficiency learners used more complex language in terms of lexical complexity than low proficiency learners since the mean values for high proficiency participants (D= 42.99; G= 6.87; LS= .89) are higher than the upper limit of the confidence intervals of low proficiency participants (D= 28.23; G= 5.08; LS= .54).

Table 36. Mean and confidence intervals 95% for factor Proficiency. Lexical complexity measures.

Measure Proficiency Mean Confidence interval 95% Lower limit Upper limit D Low 24.61 20.99 28.23 High 46.71 42.99 50.42 LS Low .41 .28 .54 High 1.03 .89 1.17 G Low 4.71 4.33 5.08 High 7.25 6.87 7.64

Accuracy.

Tables 37, 38, 39 and 40 show the descriptive statistics for accuracy measures. These are LEXE/100w (lexical errors per 100 words), MSE/100w (morpho-syntactic errors per 100 words), SPE/100w (spelling error per 100 words), TOTALE/100w (total errors per 100 words), LEXE/T (lexical errors per T-unit), MSE/T (morpho-syntactic errors per T-unit), SPE/T (spelling error per T-unit) and TOTALE/T (total errors per T-unit). The tables are separated by proficiency level (low proficiency – Tables 37 and 38, high proficiency – Tables 39 and 40).

Low proficiency participants in the different groups performed quite differently in terms of accuracy. Participants in the writing group were only able to reduce their spelling errors (SPE/100w time 1 =2.17, time 2= 1.43; SPE/T time 1= .31, time 2= .23) from T1 to T2) while they increased their error rate of both lexical (LEXE/100w time 1 4.38, time 2= 6.60; LEXE/T time 1=

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.61, time 2= .88) morpho-syntactic errors (MSE/100w time 1= 2.17, time 2= 1.43; MSE/T time 1= 1.76, time 2= 1.87) and total errors (TOTALE/100w time 1= 16.90, time 2= 20.55; TOTALE/T time 1= 2.37, time 2= 2.74). Participants in the direct WCF group seemed to favour lexical aspects, as evidenced in the reduction from T1 to T2 in the measures of lexical errors per 100 words (LEXE/100w time 1= 5.07, time 2= 1.94), much more marked than in the rest of the groups, and lexical errors per T-unit (LEXE/T time 1= .76, time 2= .28). It is thanks to the decrease in the measures of lexical errors that the general measures for accuracy (TOTALE/100w and TOTALE/T) were also positively affected (TOTALE/100w time 1= 15.96, time 2= 14.09; TOTALE/T time 1= 2.29, time 2= 2.05). The indirect WCF was also able to reduce the number of lexical errors from T1 to T2 (LEXE/100w time 1= 6.64, time 2= 4.36; LEXE/T time 1= .93, time 2= .57). Moreover, the indirect WCF group did reduce morpho-syntactic errors (MSE/100w time 1= 12.90, time 2= 8.07; MSE/T time 1= 1.76, time 2= .95), reason why their increased performance in the general measures for accuracy (TOTALE/100w time 1=21.06, time 2= 13.90; TOTALE/T time 1= 2.89, time 2= 1.72) was much more marked for this group. Similarly, the self-correction group also reduced errors from T1 to T2 across measures (LEXE/100w time 1= 7.20, time 2= 5.50; LEXE/T time 1= .87, time 2= .61; MSE/100w time 1= 10.99, time 2= 10.94; MSE/T time 1= 1.33, time 2= 1.16; SPE/100w time 1= 1.91, time 2= 1.79; SPE/T time 1= .30, time 2= .14; TOTALE/100w time 1=20.56, time 2= 17.82; TOTALE/T time 1= 2.49, time 2= 1.92).

There is an observable general tendency for high proficiency participants to increase their accuracy rate from T1 to T2, although the differences are quite subtle since the error frequency in T1 was very low. More specifically, spelling errors (SPE) seemed to be less amenable to change upon TR whereas lexical errors (LEXE) and morpho-syntactic errors (MSE) did decrease from T1 to T2, being this decrease more marked for those groups who received and processed direct or indirect WCF across measures: written group (LEXE/100w time 1= .01, time 2= .00; LEXE/T time 1= .19, time 2= .13; MSE/100w time 1= .03, time 2= .02; MSE/T time 1= .59, time 2= .41; SPE/100w time 1= .00, time 2= .00; SPE/T time 1= .08, time 2= .02; TOTALE/100w time 1=.04, time 2= .03; TOTALE/T time 1= .78, time 2= .53); direct WCF group (LEXE/100w time 1= .01, time 2= .00; LEXE/T time 1= .28, time 2= .10; MSE/100w time 1= .04, time 2= .01; MSE/T time 1= .73, time 2= .22; SPE/100w time 1= .00, time 2= .00; SPE/T time 1= .05, time 2= .02; TOTALE/100w time 1= .05, time 2= .02; TOTALE/T time 1= 1.07, time 2= .34); indirect WCF group (LEXE/100w time 1= .01, time 2= .00; LEXE/T time 1= .23, time 2= .11; MSE/100w time 1= .04, time 2= .01; MSE/T time 1= .76, time 2= .24; SPE/100w time 1= .00, time 2= .00; SPE/T time 1= .06, time 2= .06; TOTALE/100w time 1= .06, time 2= .02; TOTALE/T time 1= 1.04, time 2= .38); self-correction group (LEXE/100w time 1= .01, time 2= .00; LEXE/T time 1= .11, time 2= .10; MSE/100w time 1=

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.02, time 2= .02; MSE/T time 1= .33, time 2= 35; SPE/100w time 1= .00, time 2= .00; SPE/T time 1= .06, time 2= .05; TOTALE/100w time 1= .03, time 2= .03; TOTALE/T time 1= .50, time 2= .49).

However, upon statistical analyses, no significant results were found for all of these tendencies. Regarding within-subject factors, significant effects were found in the factor repetition: LEXE/100w, (F (1, 44) = 3.14, MSe = 3.06, η2 = .07, p = .08); MSE/100w, (F (1, 44) = .41, MSe = 7.21, η2 = .09, p = .08); SPE/100w, (F (1, 44) = .82, MSe = .85, η2 = .02, p = .37); TOTALE/100, (F (1, 44) = 1.96, MSe = 13.69, η2 = .04, p = .37); LEXE/T, (F (1, 44) = 9.94, MSe = .06, η2 =.18, p = .00); MSE/T, (F (1, 44) = 8.48, MSe = .16, η2 = .16, p = .01); SPE/T, (F (1, 44) = 1.79, MSe = .02, η2 = .04, p = .19); TOTALE/T, (F (1, 44) = 16.19, MSe = .27, η2 = .27, p = .00). No significant results were found in the factor repetition*proficiency: LEXE/100w, (F (1, 44) = 3.10, MSe = 3.06, η2 = .07, p = .08); MSE/100w, (F (1, 44) = .37, MSe = 7.21, η2 = .01, p = .55); SPE/100w, (F (1, 44) = .80, MSe = .85, η2 = .02, p = .38); TOTALE/100, (F (1, 44) = 1.88, MSe = 13.69, η2 = .04, p = .18); LEXE/T, (F (1, 44) =1.32, MSe = .06, η2 =.03, p = .18); MSE/T, (F (1, 44) = .68, MSe = .16, η2 = .02, p = .41); SPE/T, (F (1, 44)= .12, MSe = .02, η2 = .0, p = .73); TOTALE/T, (F (1, 44) = .01, MSe = .27, η2 = .00, p = .91). On the other hand, significant effects were found in the interaction repetition*group: LEXE/100w, (F (3, 44) = 3.27, MSe = 3.06, η2 = .18, p = .03); MSE/100w, (F (3, 44) = 1.87, MSe = 7.21, η2 = .11, p = .15); SPE/100w, (F (3, 44) = .80, MSe = .85, η2 = .05, p= .50); TOTALE/100, (F (3, 44) = 2.52, MSe = 13.69, η2 = .15, p = .07); LEXE/T, (F (3, 44) = 4.21, MSe = .06, η2 =.22, p = .01); MSE/T, (F (3, 44) = 3.33, MSe = .16, η2 = .19, p = .03); SPE/T, (F (3, 44) = .60, MSe = .02, η2 = .04, p = .61); TOTALE/T, (F (3, 44) = 4.01, MSe = .27, η2 = .22, p = .01).

Significant results were found in the factor repetition*proficiency*group: LEXE/100w (F (3, 44) = 3.27, MSe = 3.06, η2 = .18, p = .03); MSE/100w (F (3, 44) = 1.85, MSe = 7.21, η2 = .11, p = .15); SPE/100w (F (3, 44) = .80, MSe = .85, η2 = .05, p = .50); TOTALE/100 (F (3, 44) = 2.51, MSe = 13.69, η2 = .15, p = .07); LEXE/T (F (3, 44)= 2.54, MSe = .06, η2 =.15, p = .07); MSE/T (F (3, 44) = 1.99, MSe = .16, η2 = .12, p = .13); SPE/T (F (3, 44) = .67, MSe = .02, η2 = .04, p = .57); TOTALE/T (F (3, 44) = 2.54, MSe = .27, η2 = .15, p = .07).

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Table 37. Descriptive statistics for accuracy measures. Low proficiency participants.

Low LEXE/100w MSE/100w SPE/100w TOTALE/100w proficiency

T1 T2 T1 T2 T1 T2 T1 T2

Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD

Written 4.38 3.39 6.60 7.25 12.52 5.62 13.96 8.81 2.17 2.96 1.43 1.19 16.90 7.13 20.55 15.18

Direct WCF 5.07 3.15 1.94 1.64 10.30 9.23 11.10 10.42 .60 .61 1.05 1.11 15.96 10.70 14.09 11.73

Indirect WCF 6.64 2.79 4.36 3.25 12.90 8.19 8.07 5.90 1.51 1.34 1.17 1.26 21.06 9.77 13.90 7.95

Self- 7.20 5.77 5.50 5.76 10.99 7.13 10.94 9.93 2.38 1.91 1.38 1.79 20.56 12.10 17.82 16.92 correction

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Table 38. Descriptive statistics for accuracy measures. Low proficiency participants.

Low LEXE/T MSE/T SPE/T TOTALE/T proficiency

T1 T2 T1 T2 T1 T2 T1 T2

Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD

Written .61 .46 .88 .90 1.76 .81 1.87 1.05 .31 .43 .23 .20 2.37 1.06 2.74 1.80

Direct WCF .76 .58 .28 .24 1.45 1.23 1.64 1.73 .09 .08 .14 .17 2.29 1.52 2.05 1.97

Indirect WCF .93 .50 .57 .55 1.76 1.23 .95 .65 .21 .18 .20 .20 2.89 1.55 1.72 1.13

Self- .87 .61 .61 .54 1.33 .79 1.16 .96 .30 .17 .14 .17 2.49 1.23 1.92 1.58 correction

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Table 39. Descriptive statistics for accuracy measures (I). High proficiency participants.

High LEXE/100w MSE/100w SPE/100w TOTALE/100w proficiency

T1 T2 T1 T2 T1 T2 T1 T2

Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD

Written .01 .01 .00 .01 .03 0.1 0.2 .01 .00 .00 .00 .00 .04 .02 .03 .01

Direct WCF .01 .01 .00 .00 .04 .01 .01 .00 .00 .00 .00 .00 .05 .02 .02 .01

Indirect WCF .01 .01 .00 .00 .04 .01 .01 .01 .00 .01 .00 .00 .06 .03 .02 .02

Self- .01 .01 .00 .01 .02 .01 .02 .01 .00 .01 .00 .00 .03 .02 .03 .01 correction

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Table 40. Descriptive statistics for accuracy measures (II). High proficiency participants.

High LEXE/T MSE/T SPE/T TOTALE/T proficiency

T1 T2 T1 T2 T1 T2 T1 T2

Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD Mean SD

Written .19 .12 .13 .13 .59 .22 .41 .16 .08 .10 .02 .03 .78 .30 .53 .18

Direct WCF .28 .20 .10 .12 .73 .34 .22 .06 .05 .05 .02 .04 1.07 .55 .34 .16

Indirect WCF .23 .26 .11 .10 .76 .39 .24 .27 .06 .07 .04 .06 1.04 .66 .38 .27

Self- .11 .11 .10 .10 .33 .11 .35 .16 .06 .08 .05 .05 .50 .17 .49 .21 correction

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To understand the results reported along the previous lines, we should look into Table 41 below which displays the means and confidence intervals at 95% for the interaction repetition*proficiency*group, showing the means for the different groups across measures for the two proficiency levels. To enable an easy and straightforward location of the significant data in the Table 41, significant decreases in error rate have been marked in green while significant increases in error rate in have been marked in red.

Table 41. Mean and confidence intervals 95% for factor repetition*proficiency*group. Accuracy measures.

Measure Proficiency Group Repetition Mean Confidence interval 95% Lower limit Upper limit LEXE/100w Low WR 1 4.38 2.46 6.30 2 6.60 4.02 9.19 DWCF 1 5.07 3.01 7.12 2 1.94 -.82 4.71 IWCF 1 6.64 4.59 8.70 2 4.36 1.59 7.13 SC 1 7.20 4.77 9.63 2 5.50 2.22 8.77 High WR 1 .01 -2.04 2.07 2 .01 -2.76 2.78 DWCF 1 .01 -2.21 2.23 2 .01 -2.98 2.99 IWCF 1 .01 -2.21 2.23 2 .01 -2.98 2.99 SC 1 .01 -2.21 2.22 2 .01 -2.98 2.99 MSE/100w Low WR 1 12.52 8.59 16.45 2 13.96 9.40 18.51 DWCF 1 10.30 6.10 14.50 2 11.10 6.23 15.97 IWCF 1 12.90 8.70 17.10 2 8.07 3.20 12.94 SC 1 10.99 6.02 15.96 2 10.94 5.18 16.71 High WR 1 .03 -4.17 4.23 2 .02 -4.85 4.90 DWCF 1 .04 -4.50 4.57 2 .01 -5.25 5.27 IWCF 1 .04 -4.50 4.58 2 .01 -5.25 5.27

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SC 1 .02 -4.52 4.56 2 .02 -5.24 5.28 SPE/100w Low WR 1 2.17 1.19 3.14 2 1.43 .76 2.11 DWCF 1 .60 -.44 1.64 2 1.05 .33 1.77 IWCF 1 1.51 .47 2.55 2 1.47 .75 2.20 SC 1 2.38 1.15 3.61 2 1.38 .52 2.23 High WR 1 .00 -1.04 1.04 2 -1.076E-16 -.72 .72 DWCF 1 1.388E-16 -1.12 1.12 2 5.551E-17 -.78 .78 IWCF 1 .00 -1.12 1.13 2 .00 -.78 .78 SC 1 .00 -1.12 1.13 2 -7.633E-16 -.78 .78 TOTALE/100w Low WR 1 16.90 11.86 21.94 2 20.56 13.80 27.32 DWCF 1 15.96 10.57 21.35 2 14.09 6.86 21.32 IWCF 1 21.06 15.67 26.45 2 13.90 6.67 21.13 SC 1 2056 14.19 26.94 2 17.82 9.26 26.37 High WR 1 .05 -5.34 5.44 2 .03 -7.20 7.26 DWCF 1 .05 -5.77 5.87 2 .02 -7.79 7.83 IWCF 1 .06 -5.76 5.87 2 .02 -7.79 7.83 SC 1 .03 -5.79 5.85 2 .03 -7.78 7.84 LEXE/T Low WR 1 .61 .32 .90 2 .88 .55 1.21 DWCF 1 .76 .45 1.06 2 .28 -.07 .62 IWCF 1 .93 .62 1.24 2 .57 .22 .92 SC 1 .87 .50 1.23 2 .61 .20 1.02

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High WR 1 .19 -.12 .49 2 .13 -.22 .48 DWCF 1 .28 -.05 .62 2 .10 -.28 .47 IWCF 1 .23 -.10 .57 2 .11 -.27 .48 SC 1 .11 -.22 .45 2 .10 -.28 .47 MSE/T Low WR 1 1.76 1.20 2.31 2 1.87 1.25 2.48 DWCF 1 1.45 .85 2.05 2 1.64 .99 2.29 IWCF 1 1.76 1.16 2.35 2 .95 .30 1.61 SC 1 1.33 .62 2.03 2 1.16 .39 1.94 High WR 1 .59 -.00 1.19 2 .41 -.25 1.06 DWCF 1 .73 .09 1.38 2 .22 -.48 .93 IWCF 1 .76 .11 1.40 2 .24 -.47 .94 SC 1 .33 -.31 .97 2 .35 -.36 1.05 SPE/T Low WR 1 .31 .16 .45 2 .23 .13 .33 DWCF 1 .09 -.07 .24 2 .14 .03 .24 IWCF 1 .21 .06 .36 2 .20 .10 .31 SC 1 .30 .12 .48 2 .14 .02 .26 High WR 1 .08 -.08 .23 2 .02 -.08 .13 DWCF 1 .05 -.11 .22 2 .02 -.09 .14 IWCF 1 .06 -.10 .23 2 .04 -.07 .15 SC 1 .06 -.11 .22 2 .05 -.06 .16 TOTALE/T Low WR 1 2.37 1.63 3.10 2 2.74 1.88 3.60

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DWCF 1 2.29 1.51 3.08 2 2.05 1.13 2.98 IWCF 1 2.89 2.11 3.68 2 1.72 .80 2.64 SC 1 2.49 1.57 3.42 2 1.92 .83 3.00 High WR 1 .85 .07 1.64 2 .55 -.37 1.47 DWCF 1 1.07 .22 1.92 2 .34 -.66 1.34 IWCF 1 1.05 .20 1.90 2 .38 -.61 1.38 SC 1 .50 -.35 1.35 2 .49 -.50 1.49

As depicted in Table 41 above, only low proficiency participants in the direct and indirect WCF groups significantly decreased their error rate from T1 to T2 in the measure of lexical errors per 100 words (LEXE/100w). This is evident when looking at the mean values for T2 (direct WCF group time 2= 1.94; indirect WCF group time 2= 4.36) which are lower than the lower limit in the confidence intervals in time 1 (direct WCF group= 3.01; indirect WCF group= 4.59). The writing group, in contrast, augmented the number of errors committed from T1 to T2 in this same measure. Since the mean value for T2 (6.60) is higher than the higher limit in the confidence interval in time 1 (6.30), a significant decrease in accuracy was found for this group. In a similar way, the participants who were able to reduce the number of errors significantly from T1 to T2 in the measure of lexical errors per T-unit were low proficiency participants in the direct and indirect WCF groups since their mean values in time 2 (.28 and .57 respectively) are lower than the lower limit in the confidence interval in time 1 (.45 and .62 respectively). Additionally, low proficiency participants in the indirect WCF group were also able to increase their accuracy significantly from T1 to T2 in the measure of morpho-syntactic errors per 100 words (MSE/110w) (mean value in time 2= 8.07, lower than lower limit of confidence interval in time 1= 8.70) and in the measure of morpho-syntactic errors per T-unit (MSE/T) (mean value in time 2= .95 lower than lower limit of confidence interval in time 1= 1.16). As a consequence, their accuracy in the measure of total errors per 100 words (TOTALE/100w) (mean value in time 2= 13.90 lower than lower limit of confidence interval in time 1= 15.67) and the measure of total errors per T-unit (TOTALE/T) (mean value in time 2= 1.72, lower than lower limit of confidence

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CHAPTER VI. RESULTS. interval in time 1= 2.11) also increased significantly. High proficiency participants did not seem to take advantage of task repetition with or without different types of WCF and no significant results were found in the area of accuracy for these participants. However, there is to say that their error rate in T1 was actually rather low, fact which may quite have influenced the lack of significant results in this respect. In any case, results show the beneficial effects of receiving and processing WCF, at least, for low proficiency learners. These issues will be dealt with more in depth in the Discussion section.

With regard to between-subject factors, only significant results were found in the factor proficiency: LEXE/100w (F (1, 44) = 39.72, MSe = 17.40, η2 = .47, p = .00; MSE/100w (F (1, 44) = 51.04, MSe = 64.09, η2 = .54, p = .00); SPE/100w (F (1, 44) = 29.95, MSe = 1.91, η2 = .41, p = .00); TOTALE/100 (F (1, 44) = 62.35, MSe = 126.40, η2 = .59, p = .00); LEXE/T (F (1, 44) = 23.19, MSe = .31, η2 =.35, p = .00); MSE/T (F (1, 44) = 23.16, MSe = 1.18, η2 = .35, p = .00); SPE/T (F (1, 44) = 15.66, MSe = .04, η2 = .26, p = .00); TOTALE/T, (F (1, 44) = 31.08, MSe = 2.25, η2 = .41, p = .00). However, no significant results were found in the factor group: LEXE/100w (F (3, 44) = .52, MSe = 17.40, η2 = .03, p = .67); MSE/100w (F (3, 44) = .18, MSe = 64.09, η2 = .01, p = .91); SPE/100w, (F (3, 44) = .77, MSe = 1.91, η2 = .05, p = .52); TOTALE/100 (F (3, 44) = .18, MSe = 126.40, η2 = .01, p = .91); LEXE/T, (F (3, 44) = .20, MSe = .31, η2 =.01, p = .90); MSE/T (F (3, 44) = .50, MSe = 1.18, η2 = .03, p = .68); SPE/T (F (3, 44) = .88, MSe = .04, η2 = .06, p = .46); TOTALE/T (F (3, 44) = .16, MSe = 2.25, η2 = .01, p = .92). No significant effects were found in the factor proficiency*group either: LEXE/100w (F (3, 44) = .52, MSe = 17.40, η2 = .03, p = .67); MSE/100w (F (3, 44) = .18, MSe = 64.09, η2 = .01, p = .91); SPE/100w (F (3, 44) = .77, MSe = 1.91, η2 = .05, p = .52); TOTALE/100, (F (3, 44) = .18, MSe = 126.40, η2 = .01, p = .91); LEXE/T (F (3, 44) = .40, MSe = .31, η2 =.03, p = .76; MSE/T (F (3, 44) = .24, MSe = 1.18, η2 = .02, p = .87); SPE/T (F (3, 44) = .63, MSe = .04, η2 = .04, p = .60); TOTALE/T (F (3, 44) = .08, MSe = 2.25, η2 = .00, p = .97).

To understand the results reported above, we should into Table 42 below which shows the means and confidence intervals for the between-subject factor proficiency. As it is illustrated in Table 42, high proficiency participants were significantly more accurate than low proficiency participants across the different measures for accuracy since the mean value in the different measures (LEXE/100w= .01; MSE/100w= .03; SPE/100w=.00; TOTALE/100w= .04 LEXE/T= .16; MSE/T= ..45; SPE/T=.05; TOTALE/T= .66) are lower than the lower limit in the confidence intervals of low proficiency participants (LEXE/100w= 4.05; MSE/100w= .9.12; SPE/100w= 1.11; TOTALE/100w= 14.48; LEXE/T= .53; MSE/T= 1.19; SPE/T=.15; TOTALE/100w= 1.89).

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Table 42. Mean and confidence intervals 95% for factor Proficiency. Accuracy measures.

Measure Proficiency Mean Confidence interval 95% Lower limit Upper limit LEXE/100w Low 5.21 4.05 6.37 High .01 -1.18 1.20 MSE/100w Low 11.35 9.12 13.58 High .03 -2.26 2.31 SPE/100w Low 1.50 1.11 1.88 High .00 -.39 .40 TOTALE/100w Low 17.61 14.48 20.74 High .04 -3.18 3.25 LEXE/T Low .69 .53 .84 High .16 -.01 .31 MSE/T Low 1.49 1.19 1.79 High .45 .14 .76 SPE/T Low .20 .15 .26 High .05 -.01 .10 TOTALE/T Low 2.31 1.89 2.73 High .66 .23 1.08

Fluency.

As shown in Tables 43 (low proficiency) and 44 (high proficiency) below, task repetition in the written modality yielded positive results across groups and proficiency levels. Low proficiency participants increased their fluency from T1 to T2 in the measure of words/minute (written – time 1= 5.18, time 2=7.55; Direct WCF – time 1= 5.74, time 2= 7.50; Indirect WCF – time 1= 5.10, time 2= 7.25; Self-correction – time 1= 4.13, time 2= 8.14) and in the measure of syllables/minute (written – time 1= 6.45, time 2=9.40; Direct WCF – time 1= 7.15, time 2= 9.38; Indirect WCF – time 1= 6.32, time 2= 8.92; Self-correction – time 1= 5.17, time 2= 10.34). High proficiency participants also augmented in fluency from T1 to T2 in the measure of words/minute (written – time 1= 12.76, time 2= 18.59; Direct WCF – time 1= 10.77, time 2= 12.36; Indirect WCF – time 1= 10.36, time 2= 12.37; Self-correction – time 1= 10.15, time 2= 10.64 and in the measure of syllables/minute (written – time 1= 16.66, time 2= 24.21; Direct WCF – time 1= 13.45, time 2= 15.68; Indirect WCF – time 1= 13.04, time 2= 16.10; Self-correction – time 1= 13.34, time 2= 14.16). It is remarkable the fact that this increase was much more pronounced for low proficiency participants in the writing and the self-correction groups. That is, participants whose attention was not explicitly directed to form took much greater advantage

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CHAPTER VI. RESULTS. of task repetition than those who did, in terms of fluency as operationalised by words/minute and syllables/minute.

Table 43. Descriptive statistics for fluency measures. Low proficiency participants. Low Words/minute Syllables/minute proficiency

T1 T2 T1 T2

Mean SD Mean SD Mean SD Mean SD

Written 5.18 3.10 7.55 3.58 6.45 3.68 9.40 4.00

Direct WCF 5.74 2.11 7.50 1.81 7.15 2.63 9.38 2.02

Indirect 5.10 1.55 7.25 1.69 6.32 1.78 8.92 1.98 WCF Self- 4.13 1.81 8.14 1.88 5.17 2.15 10.34 2.62 correction

Table 44. Descriptive statistics for fluency measures. High proficiency participants. High Words per minute Syllables per minute proficiency

T1 T2 T1 T2

Mean SD Mean SD Mean SD Mean SD

Written 12.76 3.28 18.59 7.15 15.66 5.05 24.21 9.66

Direct WCF 10.77 4.12 12.36 3.08 13.45 5.59 15.68 3.52

Indirect 10.36 4.63 12.37 3.97 13.04 3.43 16.10 4.87 WCF Self- 10.15 2.52 10.64 2.51 13.34 4.57 14.16 3.37 correction

Significant results were found in the factor for the two measures words/minute (F (1, 44) = 26.01, MSe = 6.26, η2 =.37, p = .00) and syllables/minute (F (1, 44) = 33.78, MSe = 9.01, η2 = .43, p = .00). No significant results were found in the factor repetition*proficiency in any measure: words/minute (F (1, 44) = .01, MSe = 6.26, η2 =.00, p = .93); syllables/minute (F (1, 44) = .13, MSe = 9.01, η2 = .00, p = .72), as well as no significant effects were found in the factor repetition*group in any measure: words/minute (F (3, 44) = 1.33, MSe = 6.26, η2 = .08, p = .28); syllables/minute (F (3, 44) = 1.94, MSe = 9.01, η2 = .12, p = .14). Significant results were found in the factor repetition*proficiency*group albeit in only one of the measures: words/minute (F

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CHAPTER VI. RESULTS.

(3,44) = 2.08, MSe = 6.26, η2 =.12, p = .12; syllables/minute (F (3, 44) = 9.01, MSe = 9.01, η2 = .17, p = .04).

To comprehend the results reported above, we should consider the information in Tables 45 and 46 below, which present the means and confidence intervals at 95% for the factors repetition (Table 45) and repetition*proficiency*group (Table 46). From Table 45, we can see that repetition yields significant results since the means at T2 (words/minute= 10.55; syllables/minute= 13.52) are higher than the upper limits of the confidence intervals at T1 (word/minute= 8.89; syllables/minute= 11.15). If we look into Table 46, we will be able to find out which group(s) increased their performance significantly in terms of fluency.

Table 45. Mean and confidence intervals 95% for factor repetition. Fluency measures. Measure Repetition Mean Confidence interval 95% Lower limit Upper limit Words/minute 1 8.03 7.17 8.89 2 10.55 9.50 11.60 Syllables/minute 1 10.07 8.99 11.15 2 13.52 12.19 14.86

Low proficiency participants in the writing and the self-correction groups and high proficiency participants in the writing group were the ones whose performance in terms of fluency improved significantly from T1 to T2. Regarding the measure words/minute, the mean value for low proficiency participants in the writing (7.55) and the self-correction groups (8.14) in T2 is higher than the upper limit of the confidence interval in T1 (7.35 and 6.88 respectively) whereas the mean value for high proficiency participants in the writing group in T2 (18.59) is also higher than the upper limit of the confidence interval in T1 (15.09). Also, in the measure syllables/minute, the mean value for low proficiency participants in the writing (9.40) and the self-correction groups (10.34) in T2 is higher than the upper limit of the confidence interval in T1 (9.18 and 8.62 respectively) while the mean value for high proficiency participants in the writing group in T2 (24.21) is also higher than the upper limit of the confidence interval in T1 (18.58).

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Table 46. Mean and confidence intervals 95% for factor repetition*proficiency*group. Fluency measures.

Measure Proficiency Group Repetition Mean Confidence interval al 95% Lower limit Upper limit Words/minute Low WR 1 5.18 3.00 7.35 2 7.55 4.91 10.20 DWCF 1 5.74 3.42 8.07 2 7.50 4.67 10.32 IWCF 1 5.10 2.78 7.43 2 7.25 4.42 10.08 SC 1 4.13 1.38 6.88 2 8.14 4.80 11.49 High WR 1 12.76 10.44 15.09 2 18.59 15.77 21.42 DWCF 1 10.77 8.26 13.28 2 12.36 9.30 15.41 IWCF 1 10.36 7.85 12.87 2 12.37 9.32 15.42 SC 1 10.15 7.64 12.66 2 10.64 7.59 13.69 Syllables/minute Low WR 1 6.45 3.72 9.18 2 9.40 6.03 12.77 DWCF 1 7.15 4.23 10.07 2 9.38 5.78 12.99 IWCF 1 6.32 3.40 9.24 2 8.92 5.32 12.52 SC 1 5.17 1.71 8.62 2 10.34 6.08 14.61 High WR 1 15.66 12.74 18.58 2 24.21 20.61 27.82 DWCF 1 13.45 10.29 16.60 2 15.68 11.79 19.57 IWCF 1 13.04 9.89 16.20 2 16.10 12.20 19.99 SC 1 13.34 10.19 16.50 2 14.16 10.27 18.05

Regarding between-subject factors, only significant results were found in the factor proficiency in both measures: words/minute (F (1, 44) = 53.33, MSe = 16.81, η2 = .55, p = .00); syllables/minute (F (1, 44) = 55.52, MSe = 28.07, η2 = .56, p = .00). No significant effects were

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CHAPTER VI. RESULTS. found in the factor group: words/minute (F (3, 44) = 2.37, MSe = 16.81, η2 = .14, p = .08); syllables/minute (F (3, 44) = 2.07, MSe = 28.07, η2 = .12, p = .12) or in the factor proficiency*group: words/minute (F (3, 44) = 2.17, MSe = 16.81, η2 = .13, p = .11); syllables/minute (F (3, 44) = 1.99, MSe = 28.07, η2 = .12, p = .13).

Table 47. Mean and confidence intervals 95% for factor proficiency. Fluency measures. Measure Proficiency Mean Confidence interval 95% Lower limit Upper limit Words/minute low 6.32 5.18 7.47 high 12.25 11.08 13.42 Syllables/minute low 7.89 6.42 9.37 high 15.70 14.19 17.22

The results reported concerning the factor proficiency indicate that, as could be expected, low proficiency participants were significantly less fluent than high proficiency participants, as evidenced in Table 47 above, showing the means and confidence intervals for low and high proficiency participants in the two measures for fluency. The mean value for high proficiency participants in the measure words/minute (12.25) and syllables/minute (15.70) in T2 is higher than the upper limit of the confidence interval in the measures words/minute (6.32) and syllables/minute (7.89) of low proficiency participants, which indicate that the significant results found correspond to these groups.

To summarise, no significant results were found for task repetition in the written modality in terms of both syntactic and lexical complexity regardless of proficiency or +/- WCF condition. Regarding accuracy, significant results were found for low proficiency learners. More precisely, low proficiency participants in the direct and indirect WCF groups were able to reduce their lexical errors (LEXE/100w and LEXE/T) due to the combined effect of TR and WCF processing. Additionally, learners in the indirect WCF group were also able to reduce their morpho-syntactic errors (MSE/100w and MSE/T) and total errors per T-unit (TOTALE/100w and TOTALE/T). from T1 to T2. On the contrary, no significant effects were found for high proficiency participants in terms of accuracy as a result of TR, regardless of +/- WCF condition. Finally, with respect to fluency, significant results were found. More specifically, low proficiency participants in the written and self-correction groups significantly increased fluency from T1 to T2 while only high proficiency participants in the written group were able to do so. In the next chapter we will

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CHAPTER VI. RESULTS. discuss the significant results presented in this chapter in the light of the theoretical predictions and the overview of previous research reviewed in chapters I, II and III.

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CHAPTER VII. DISCUSSION.

VII. DISCUSSION.

In the present chapter we will discuss the results presented in the previous section and contrast and compare them against the theoretical predictions suggested in our literature review and with those results previous research has yielded. In addition, we will assess the relevance of the insights obtained in terms of their potential contribution to the field.

The structuring of the information is as follows. First, the different results reported regarding task repetition across modalities will be discussed, with special emphasis on the task- modality effects found. This will help us assess the way in which the two modalities represent different sites for language development and, as a result, may prompt diverse opportunities for learning. Second, the results with respect to task repetition in writing as mediated by the provision (or lack of) and processing of different types of written corrective feedback will be discussed. This will help us assess the mediating role that WCF may have in task repetition in the written mode and draw conclusions as to the purported distinctive nature of task repetition in writing.

It should be noted that the results regarding the effects of proficiency alone will not be addressed since they point in the direction of the obvious and expected findings, suggesting that high proficiency participants outperformed low proficiency participants in both modalities. The effects of proficiency will be discussed as long as they interact with any other factor i.e. repetition or group.

VII.1. TASK REPETITION ACROSS MODALITIES.

VII.1.1. TASK REPETITION IN SPEAKING AND WRITING. Our first research question asked whether task repetition in the different modalities (oral/writing) would result in quantitative differences in terms of CAF measures and if these differences would be mediated by proficiency level (high/low). As reported in the Results section, the effects on task repetition varied across modalities. This means that the purported language gains that may derive from task repetition are modality-related. This should be related to Manchón´s claims (2014c) that the increased performance which results from engaging in task repetition relies on the on-line nature of speech production. The immediacy of oral output imposes certain constrains on the allocation of attentional resources, most importantly, on linguistic processing, which may prompt learners to prioritise meaning (over form) in the first encounter with the task. It is then due to task repetition that they are able to shift their attention

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CHAPTER VII. DISCUSSION. from meaning to form, resulting in increased performance. She (Manchón, 2014b) also argued that task repetition “possesses unique qualities in the environment of writing” (p. 11) mainly due to the nature of linguistic processing in the act of meaning-making through writing (Byrnes & Manchón, 2014b), which are derived from the distinct characteristics of writing, namely, the greater availability of time, the permanence of the written text as well as WCF and the problem- solving nature of writing (Manchón, 2014). Also, Byrnes and Manchón (2014b) suggested that the tenets theorised with oral language in mind do not necessarily account to writing, a claim which has been addressed in Byrnes and Manchón (2014c) and Nitta and Baba (2014) in relation to task repetition.

Furthermore, no effects were observed in relation to the mediating role of proficiency in either mode. Therefore, in the light shed by the results in our study, out first hypothesis regarding the differential effects of task repetition across modes is confirmed. On the contrary, our hypothesis number four (which predicted that higher proficiency participants would benefit more than low proficiency ones) from task repetition, was rejected.

In what follows we elaborate on the significance of these two overall tendencies in our data with a more detailed analysis of the CAF constructs investigated in our study.

Fluency.

As stated in the Results chapter, the area of fluency was the only one that was found to benefit from task repetition across modalities, as evident in the significant results found in the interaction repetition*group in both measures: words/minute, (F (1, 25) = 12.12, MSe = 62.21, η2 = .33, p = .00); syllables/minute, (F (1, 25) = 16.05, MSe = 45.12, η2 = .39, p = .00). Figures 5 and 6 below show that this significant result across modalities is in effect a function of the increased performance of both oral groups (high and low proficiency). This result goes in line with findings in previous research concerning language gains of task repetition in the oral modality in terms of fluency (Ahmadian, 2011; Ahmadian & Tavakoli, 2010; Bygate, 2001; Gass et al., 1999; Hu, in press; Kobayashi & Kobayashi, in press; Lynch & Maclean, 2000, 2001; Sheppard & Ellis, in press). Importantly, our study contributes to previous research by providing new empirical evidence of the same effects in an under-researched population, low-proficiency learners, who were also able to benefit from task repetition and engage in more fluent performance. In contrast, none of the writing groups, regardless of proficiency, improved their

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CHAPTER VII. DISCUSSION. fluency from T1 to T2 significantly. This finding is significant from two perspectives. One the one

Figure 5. Fluency means (words/minute) by group. TR across modalities

Figure 6. Fluency means (syllables/minute) by group. TR across modalities.

hand, it points to the modality-dependency of task repetition effects: repeating a task in writing does not result in more fluent performance, as measured by the number of words written, a finding that can be interpreted from various perspectives. The first one is that, given the time pace of writing and the resulting lower demands on attentional resources (as compared to speaking), L2 writers may be in a position to make fuller use of their L2 resources in the first

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CHAPTER VII. DISCUSSION. iteration of the task when writing than when speaking. Therefore, repeating a task may not result in writing more. A second reason may be related to the very task used in our study: again, bearing in mind the time issue just mentioned, the writers in our study may have been able to complete the task in full during the first iteration and they may have had nothing else to report. However, an empirical question is whether the same would happen should task complexity be involved. The prediction (see Vasylets et al., 2017) would be that task complexity might play a role because L2 writers might not be able to fulfil all goals in the first iteration of the task. Therefore, a question for further research would be to look into the modality-dependency of task repetition effects as potentially mediated by the complexity of the task.

Following from the above, the results obtained regarding fluency in writing are also relevant because they are not in line with those reported in the scarce research done to date on task repetition in the written mode (Amiryousefi, 2016; Baba & Nitta, 2014; Nitta & Baba, 2014; 2015, in press). All these previous studies report increases in fluency along with increased performance in the areas of accuracy (Amiryousefi, 2016) or complexity (Baba & Nitta, 2014; Nitta & Baba, 2014; 2015, in press). However, we should be cautious when comparing our results with those in the studies mentioned because of differences in methodology: the different tasks used (narratives vs decision-making task in our study) may have prompted different effects for written fluency due to task repetition. Similarly, no effects were found with respect to the mediating role of proficiency on TR in fluency: both high and low-proficiency participants who engaged in TR in the oral mode increased their fluency while TR in writing did not lead to increased fluency irrespective of proficiency level. This confirms Bygate´s claim that task repetition would function in very similar ways across proficiency levels (in press), although it contradicts Mojavezi´s finding of the potential mediating role of proficiency on task repetition (2013). Given these contradictory findings, further research is therefore needed on the mediating role of proficiency (in combination with task type) in bringing about potential task repetition effects.

Accuracy and complexity.

No significant results were found in the remaining areas of performance investigated in our study. Some participants (mostly high proficiency learners) reduced their error rate from T1 to T2 although this decrease in errors did not reach statistical significance. Similarly, complexity, both lexical and syntactic complexity, did not benefit from task repetition in either modality. As reported in the Results section, statistical analyses did not show any significant results for lexical

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CHAPTER VII. DISCUSSION. complexity whereas only the measure for subordination resulted significant for syntactic complexity in the factor repetition, DC/T (F (1, 25) = 5.33, MSe = 10.86, η2 = .18, p = .03). However, as can be seen in Figure 7 below, this significant result is due to the reduction in subordination from T1 to T2 of all groups. This reduction was more pronounced in the writing groups, which therefore contributed to a higher extent to the significant decrease. These results contradict findings in previous research, where generally gains in fluency due to task repetition in the oral modality have been accompanied by gains in some other dimension of performance, be it accuracy (Hu, in press; Lynch & Maclean, 2000; 2001), complexity (Ahmadian, 2011; Ahmadian & Tavakoli, 2010; Bygate, 2001; Sheppard & Ellis, in press) or overall gains aside from

Syntactic Complexity: subordination

5,432

4,331 4,395

2,852 2,67 2,48 2,03 1,79

DC/T TIME 1 (SUBORDINATION) DC/T TIME 2 (SUBORDINATION)

LP Writers HP Writers LP Speakers HP Speakers

Figure 7. Subordination means by group. TR across modalities. fluency (Gass et al., 1999; Kobayashi & Kobayashi, in press). Similarly, our results regarding accuracy also contradict other studies which have reported gains in this area due to enhanced focus on form during the second iteration of the task (Bygate, 1996; Baleghizadeh & Derakshesh, 2012; Hawkes, 2012). The same applied to the written mode since the available empirical research has yielded significant improvement in accuracy (Amiryousefi, 2016) or complexity (Nitta & Baba, 2014; 2015; in press) in addition to fluency. Again, there is no trace in our data of a moderating role for proficiency in task repetition regarding accuracy or complexity, which is in line with Bygate´s prediction regarding the lack of potential mediating effects of proficiency (in press). More precisely, Bygate (in press) argues that task repetition would function in the same

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CHAPTER VII. DISCUSSION. way across proficiency levels and that “changes across iterations in various aspects of language are likely to arise irrespective of proficiency level” (p. 8) and cites research on task repetition where participants of different levels of proficiency participated and similar patterns of performance were found (see Lynch & Maclean, 2000; 2001 for an example).

Globally, it is evident in our data that TR repetition in writing did not yield positive results as compared to speaking, confirming previous predictions regarding the differential characteristics of the two modes of production, which pose different processing demands and, as a consequence, may potentially result in different effects for TR in the two modalities (Manchón, 2014c). As mentioned above regarding fluency, the off-line nature of writing may have prompted learners to make use of their full linguistic resources in the very first iteration with the task, limiting the room for improvement after engaging in task repetition. In this way, our data can be interpreted as suggesting that task repetition did not foster a greater focus on form during the second iteration of the task. Much to the contrary, it could be suggested that the participants in our study seemed to have had enough time to reflect on language, engage in linguistic processing and focus on form when performing the task for the first time and, consequently, their second performance, the repeated task, did not show significant improvements in terms of CAF measures. Therefore, potential benefits of task repetition in writing may be moderated by variables not targeted in the present study. It may be the case that for task repetition in writing to foster increased performance, it needs either massed repetition (Nitta & Baba, 2014) or to be complemented with some sort of external intervention in the form of WCF provision and processing stages as Manchón (2014b) already suggested, engaging learners not only in task repetition, but in enhanced task repetition (Lynch, in press). WCF has been claimed to act as a trigger of a special type of task repetition in the written mode in that it may foster attention to form claimed to result in increased accuracy (see Bitchener, 2012, Bitchener & Ferris, 2012; Bitchener & Storch, 2016). We shall come back to the role of WCF in TR below when we discuss our data on TR in the written mode with and without the availability of WCF.

Finally, the unconstrained open-ended nature of the task used in our study (i.e. the fact that learners had plenty of possibilities of completing the task in many different ways) may have led learners to conceptualise the task differently in the repeated performance, they conceptualised the task-as-process differently from how they did in time 1, as other scholars have previously suggested may occur when learners are presented the same task again (de Jong & Tillman, in press). The fact that task repetition does not entail verbatim, word-for-word repetition and the openness of the task used, may have given our learners the opportunity to

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CHAPTER VII. DISCUSSION. approach the task in a different way in time 2, resulting in a “new” version of the task at hand. This would also explain the lack of positive results for task repetition in the written mode and points to the need to study task repetition from the light of propositional complexity (Bulté & Housen, 2012; 2014), by which it is meant the number of ideas present in a text and the embedded complexity in each of these ideas. The relevance of taking this dimension of complexity into account is evident if we consider that learners may change, add or eliminate content to their production due to task repetition, as Bygate and Samuda (2005) reported in what they labelled as “framing” (additional content to the narratives upon repetition of the task). However, this assumption cannot be corroborated since we did not gather data regarding learners´ conceptualisation of the task at times 1 and 2 so as to confirm this prediction.

Regarding the results in the oral modality, learners were able to perform the task more fluently during the second iteration with the task. They were already familiar with the task, which has been claimed to result in greater fluency (Foster, 2009). Similarly, it seems that participants drew on encodings i.e. meaning-form mappings, that they had previously used and this resulted in increased performance in terms of fluency. These meaning-form mappings are stored in learners´ long-term memory and are available for future use when repeating the task. In this way, task repetition appeared to foster more rapid access to grammatical and lexical stores and retrieval of linguistic knowledge allowing learners to make the necessary meaning- form connections more easily when repeating the task. This is precisely one of the basic assumptions in the field of task repetition. Bygate (1996, 2001) suggested that having already performed the task once helped learners to access previously used information faster and also work on further complexification of the message, engaging in focus on form processes resulting not only in more fluent but also in more complex performance. In contrast, task repetition in the oral modality did not seem to foster greater focus on form by our participants, as evident in the lack of positive results in the areas of complexity and accuracy. It is possible that the task used in our study may be more complex than those used previously in research (e.g. picture description or personal narratives) and this greater task complexity made difficult for our participants to shift their attention from meaning to form in the second encounter with the task because they may have still been paying attention to the conveyance of their meaning. Similarly, as it may have been the case in the written mode, speakers may have conceptualised the task in a different way given the unconstrained, open-ended nature of the Firechief task. Task-as- process i.e. how learners conceptualise the task at hand (Breen, 1987), may have been different at times 1 and 2 and therefore the resulting performance was neither more complex nor more accurate. This raises the issue of studying the effects that different types of task may create

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CHAPTER VII. DISCUSSION. when implementing task repetition. Task-related effects on task repetition emerge then as a new venue of research worth exploring in future research agendas.

Finally, it is worth pointing out that the time lapse between the first performance and the repeat performance in our study (1 week) is not considered to have had any impact on our results. Our prediction is based on the consideration that other studies have reported gains in the different dimension of performance (CAF) with a similar time lapse between performance in the 2 iterations of the task in both speaking (Ahmadian & Tavakoli, 2010; Fukuta, 2015; Hu, in press) and writing (Amiryousefi, 2016; Baba & Nitta, 2014; Nitta & Baba, 2014; 2015; in press).

VII.1.2. TASK MODALITY EFFECTS. Several modality-related effects were found while we were actually looking into something else i.e. the effects of task repetition are worth commenting on related to the areas of fluency and syntactic and lexical complexity.

First, speakers were significantly more fluent than writers, as evident in the significant results obtained in the factor group, words/minute (F (1, 25) = 33.10, MSe= 355.83, η2 = .57, p= .00) and syllables/minute (F (1, 25) = 20,52, MSe= 595.95, η2 = .45, p= .00). This somewhat expected result simply evidences that speech takes less time to produce than a written text and, as previously noted by Williams (2012), this finding should not be taken as a limitation of the written mode, but simply as an artefact of this modality of language production.

Much more interesting are the results concerning syntactic and lexical complexity. As for syntactic complexity, significant results were found in the measure for sub-clausal complexity (number of modifiers per noun phrase) in the factor group, NPC, [F (1, 25) = 7.78, MSe = .04, η2 = .24, p= .01], as shown in Figure 8 below. This indicates that participants in the groups that performed the task in the written modality used greater nominalisation than participants that did so in the oral modality. This finding is in line with predictions already made (Norris & Ortega, 2009) and findings in previous research, which also found greater noun phrase complexity in writing than in speaking (Kormos, 2014).

As for lexical complexity, the results obtained were found to be mediated by proficiency. Significant results were found in the factor proficiency*group in the measures for lexical diversity and lexical richness, D (F (1, 23) = 5.37, MSe= 180.60, η2 = .08, p= 0.3) and G (F (1, 23) = 7.71, MSe= 1.80, η2 = .25, p= .01) respectively. This result can be interpreted as suggesting that writers were able to use more complex language than speakers in terms of lexical variety and

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CHAPTER VII. DISCUSSION. lexical richness. Interestingly, this effect was only found in the group of high proficiency participants.

Lexical Complexity

46,632

32,183

23,225 19,969

4,259 7,153 4,659 5,509

LEXICAL VARIETY (D) LEXICAL RICHNESS (GUIRAUD)

LP Writers HP Writers LP Speakers HP Speakers

Figure 8. Means for lexical complexity measures across oral and writing groups. Interaction proficiency*group.

Globally considered, modality-related effects found in our study suggest, in line with previous research, that writing elicits more complex language in terms of lexical (Ellis & Yuan, 2005; Grandfelt, 2008; Kormos, 2014; Kuiken & Vedder, 2011; Vasylets, et al., 2017) and syntactic complexity (Ellis & Yuan, 2005; Kormos, 2014; Kuiken & Vedder, 2011; Tavakoli, 2014; Vasylets, et al., 2017; Zabildea, 2017). It is likely that the differential nature of oral and written output production may be the reason for this advantage of writing over speaking. More specifically, and also in line with arguments presented in previous sections, the greater availability of time that characterizes writing makes easier for learners to be more in control of their attentional resources and allocate their attention on form, leading to more complex performance. This extra time that the written mode allows as compared to the immediate, time- constrained nature of most forms of oral output, may prompt writers to engage in deeper linguistic processing, search their different syntactic and lexical knowledge stores and access their explicit knowledge resulting in increased performance in terms of complexity. It may also be even the case that writers access their implicit knowledge for inspection and analysis (Manchón & Williams, 2016) due to this extra time available as compared to the oral mode. Also, the permanence of the text written so far permits writers to evaluate their own text, reflect on

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CHAPTER VII. DISCUSSION. language and revise where appropriate, engaging in “cognitive comparison” between the language already produced i.e. written, and learners´ L2 knowledge (Manchón, 2013). The pace at which writing takes place and the permanence of the written text allow for plenty of possibilities of engaging in these processes. All these processes have been claimed to foster language development and learning (see Cumming, 1990; Manchón, 2011b) and are considered as key findings in support of the view that language modes may foster distinct opportunities for language learning. In the words of Bygate, Van den Branden & Norris (2014: ix):

Tasks […] are intended to have a material impact on the kinds of meaning-making processes that students engage in, at the same time contextualising and motivating the language features they work with. It follows from this fundamental idea that written as opposed to oral tasks can be expected to open up distinct meaning-making spaces—textual and interpersonal, as well as semantic—for teaching and learning.

In line with these predictions, the insights obtained in our own study provide further support to the view that the written modality may serve as a greater catalyst for the processes involved in language development and may create greater language learning opportunities than the oral mode. This explains why it has already been suggested that the view that the oral mode is the “privileged site for second language learning” (Bygate, Van den Branden & Norris, 2014: ix) should be problematised and, instead, open new research agendas in which the language learning affordances of all language modalities are in focus. Byrnes and Manchón (2014c) argue that these new research agendas need to take into account the differential characteristics of oral and written language and constructs and tenets theorised in and for the oral modality should be expanded to be made to apply to the written mode. This would revitalise the fields of TBLT and L2 writing and arise new implications for theory and research.

Our study provides evidence of the relevance of moving along this research path, in our case studying potential task-modality effects on learning of task repetition. We did so by looking into the phenomenon across proficiency levels, which is somewhat an advancement from previous research given that the bulk of previous research on task repetition had payed scant attention to low proficiency L2 users. However, as mentioned in a previous section, the findings in our study need further empirical validation in new studies that also look into the task type- dependency of potential effects of task repetition.

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CHAPTER VII. DISCUSSION.

VII.2. TASK REPETITION AS MEDIATED BY WCF. Our second and third research questions asked whether task repetition in the written modality would result in quantitative differences as a result of the availability (or lack of) of different types of written corrective feedback (direct and indirect WCF) as well as whether any observed differences were mediated by proficiency. The findings obtained will be interpreted from the perspective of the light they shed on TR in writing, which, as discussed in the literature review, has been claimed to be crucially linked to the availability of WCF (Manchón, 2014b).

Fluency.

The dimension of fluency in writing (words and syllables per minute) was found to be significantly influenced by TR in writing, as reported in the Results section. Significant results were found in the factor repetition for the two measures words/minute (F (1,44) = 26.01, MSe = 6.26, η2 =.37, p= .00), and syllables/minute (F (1, 44) = 33.78, MSe = 9.01, η2 = .43, p = .00) Yet,

Fluency: syllables/minute (Low proficiency).

10,34 9,4 9,38 8,92

7,15 6,45 6,32 5,17

TIME 1 TIME 2

Written TR Direct WCF Indirect WCF Self-correection

Figure 9. Means for fluency (syllables/minute) across writing groups (Low proficiency participants).

the most interesting results are those of the interaction repetition*proficiency*group, which resulted significant in only one of the measures, syllables/minute, (F (3, 44) = 9.01, MSe = 9.01, η2 = .17, p = .04), as shown in Figures 9 (above) and 10 (below). This increased performance must be linked to the results of the no feedback group (mere task repetition in writing) in both

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CHAPTER VII. DISCUSSION. proficiency levels and to the self-correction group of low proficiency participants. More specifically, this result can be interpreted as suggesting that mere task repetition of a writing task without the availability of WCF (and regardless of whether or not writers are asked to self- reflect on their own texts before revising them) does lead to writing a longer text, which does not mean that these texts are more accurate or complex, as we will discuss in the following sections. This result goes in line with previous research which has reported significant fluency increases for task repetition in writing in the short term (Amiryousefi, 2016; Baba & Nita, 2014; Nitta & Baba, 2014; 2015; in press) and provides new empirical evidence with respect to the beneficial effects of task repetition on written fluency in an under-researched population such as low-proficiency learners.

Fluency: syllables/minute (High proficiency)

24,21

15,66 15,68 16,1 14,16 13,45 13,04 13,34

TIME 1 TIME 2

Written TR Direct WCF Indirect WCF Self-correction

Figure 10. Means for fluency (syllables/minute) across writing groups (High proficiency participants).

It may be the case that, as in oral task repetition, participants in these groups drew on meaning-form mappings that they had used in their first performance and they could access their syntactic and lexical stores faster during the repetition of the task. On the contrary, participants in the groups receiving and processing WCF, whether direct or indirect, irrespective of proficiency level, did not increase their fluency from T1 to T2 significantly, as in the case of the self-correction group of high proficiency learners. This tendency in our data needs to be linked to the fact that writing is a problem-solving, goal-oriented communicative act and L2 writers show variation in what problems they tackle and what goals they pursue when, how and

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CHAPTER VII. DISCUSSION. why (cf. Manchón & Roca de Larios, 2007). Our findings can therefore be interpreted from this goal perspective. It could be suggested that being asked to reflect on one’s own writing (with and without the availability the feedback) before engaging in the kind of task repetition that revising a text entails prompted some of our participants (and especially the most proficient groups) to prioritise a focus on form. Directing learners´ attention to form seemed to have had a detrimental effect on fluency for these groups. Possibly, learners were reflecting on the explicit knowledge gained from direct WCF or reflecting on their L2 repertoire, as induced by the previous focus on form stage (processing of indirect WCF or self-correcting errors) when repeating the task. The resulting attention to form slowed down their process of converting ideas into language with the result that their writing fluency did not increase significantly as compared to the other groups. Strikingly, the self-correction group of low proficiency learners did increase their fluency. It may be the case that encouraging low proficiency leaners to self- correct their errors has a very restricted focus-on-form effect. Their rather limited L2 knowledge may be insufficient to provide corrections for their error or even to recognise them. As a consequence, when asked to repeat the task after self-correcting their errors, they simply do not pay greater attention to form in the repeat performance and do the task a second time in a very similar way as they did the first time, but more fluently. In this way, the self-correction group of low proficiency learners behaved in an analogous manner to the written task repetition group, who did not seem to engage in any focus on form stage. Therefore, we could argue that asking low proficiency learners to self-correct their errors has a rather limited language learning potential, a finding that could have several implications for the teaching of writing and the treatment of errors in the language classroom and for the learning which derives from these practices.

The results regarding the mediating role of proficiency appear to be different depending on the group. Participants in the task repetition group were able to increase fluency irrespective of proficiency level while those in the self-correction group behaved differently depending on their proficiency level. Low proficiency participants were able to increase their fluency rate significantly while high proficiency participants were not. In a similar fashion to the task repetition group, groups receiving WCF, behaved in the same way disregarding their proficiency level. In this case, the mediating role for proficiency cannot be clearly stated. Future research should look into trade-off effects (Skehan, 1998; 2009) between the dimensions of fluency and accuracy and the potential mediating roles of WCF.

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Complexity and accuracy.

Task repetition in writing did not lead to statistically significant more complex performance in terms of syntactic and lexical complexity and this applied across proficiency levels. In a similar way, Amiryousefi (2016) did not report gains in these two areas of performance either. However, this result contradicts findings in previous studies (Nitta & Baba, 2014; 2015; in press) which reported increases in lexical and syntactic complexity, albeit in the long term. Therefore, it is likely that for task repetition in writing to yield positive results in the dimension of complexity massed repetition over a period of time, longer than six weeks, (see Amiryousefi, 2016) is needed. As suggested earlier, the off-line nature of writing may also have had an impact on these results and do so in the way previously discussed at several points. Another possible mediating variable for the lack of positive results in complexity is that learners may have decided to face the task in a different way. Again, this is related to goal setting in written practices (Manchón & Roca de Larios, 2007). Writing is a problem-solving, goal-oriented communicative meaning-making act and L2 writers may vary in how they approach the task as well as how they decide to engage in the problem-solving activity and how they orient it to achieve their goal(s). Similarly, the nature of the task may have had an effect on these results. Task repetition in writing has only been studied through narrative tasks. It is possible that other types of task, decision-making tasks for example, as in our study, may prompt different effects related to the different characteristics each task type may bring into play when performing task repetition in the written mode. However, due to the lack of research conducted with different task types, its effects on task repetition cannot be clearly stated.

With regard to accuracy, only low proficiency learners who were provided with and processed direct or indirect WCF were able to take advantage of task repetition in writing. Low proficiency learners in the WCF groups were able to decrease their lexical and morphosyntactic errors significantly due to the combined effect of WCF and task repetition. Significant results were found in the factor repetition*group in the measure of LEXE/100w (F (3, 44) = 3.27, MSe = 3.06, η2 = .18, p= .03); LEXE/T (F (3, 44) = 4.21, MSe = .06, η2 =.22, p= .01); MSE/T (F (3, 44) = 3.33, MSe = .16, η2 = .19, p= .03); and TOTALE/T (F (3, 44) = 4.01, MSe = .27, η2 = .22, p= .01), while significant results were also found in the factor repetition*proficiency*group in the measure of lexical errors per 100 words, LEXE/100w (F (3, 44) = 3.27, MSe = 3.06, η2 = .18). More specifically, effects for lexical errors were found for the direct and indirect WCF groups of low proficiency participants while only those in the indirect WCF condition were also able to decrease the number of morpho-syntactic and total errors as shown in Figures 11 and 12 below.

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Lexical errors

7,2 6,64 6,6

5,5 5,07 4,38 4,36

1,94

0,61 0,76 0,93 0,87 0,9 0,24 0,55 0,54

LEXE/100W T1 LEXE/100W T2 LEXE/T T1 LEXE/T T2

Written TR Direct WCF Indirect WCF Self-correction

Figure 11. Means lexical errors per 100 words and per T-unit across writing groups. Low proficiency participants.

Morpho-syntactic - Total errors per T-unit.

2,89 2,74 2,49 2,37 2,29 2,05 1,87 1,92 1,76 1,76 1,64 1,72 1,45 1,33 1,16 0,95

MSE/T TIME1 MSE/T TIME 2 TOTALE/T TIME1 TOTALE/T TIME 2

Written TR Direct WCF Indirect WCF Self-correction

Figure 12. Means for morpho-syntactic and total errors per T-unit across writing groups. Low proficiency participants.

The results obtained are in line with those reported in previous research regarding the beneficial effects of WCF (see Bitchener, 2012; Bitchener & Ferris, 2012 and Bitchener & Storch, 2016 for recent reviews). More specifically, they echo the findings in Storch and Wigglesworth (2010), who suggested an advantage of indirect over direct WCF, and those in Sánchez and

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Manchón (2014) regarding the differential effects of different types of WCF on different dimensions of accuracy. WCF seems to have beneficial effects on language development and, as a result of engaging learners in focus on form processes, leads to increased accuracy. However, as stated before, this greater engagement in focus on form processes may have been the cause for the lack of positive results for the direct and indirect WCF groups in the area fluency, thus providing evidence of the purported trade-off effects among the 3 dimensions of CAF (Skehan, 1998, 2009) in our case in written performance: learners whose attention was explicitly directed to form seemed to have been paying more attention to the accuracy of their performance than to the speed with which they produced their texts in the second encounter with the task. In contrast, those who did not engage in focus on form stages between performances still focused on meaning instead of form in the repeat performance leading to higher fluency.

The participants in the direct WCF group seemed to have benefited from the explicitness of direct error correction and, as a consequence, they increased their lexical accuracy. The fact that they were provided with the correct form of their erroneous production led them to easily turn input (WCF) into intake in the form of incorporation of the correct form into their revised texts. This was also the case for low proficiency participants in the indirect WCF group. However, these participants did not receive the correct form of their errors. Therefore, it is possible that they erroneously used linguistic forms that they knew, but had not fully acquired yet. It could be suggested that providing them with indirect WCF in this case encouraged them to reflect on language and this produced a more accurate performance. This group was also able to decrease their error rate of morpho-syntactic and total number of errors. As suggested by Storch and Wigglesworth (2010), indirect WCF may have fostered deeper linguistic processing and reflection than direct WCF resulting in higher accuracy in morpho-syntactic forms. Participants who received direct WCF may have not engaged in linguistic processing and reflection as much as those under the indirect WCF condition, which may have prompted noticing at the level of understanding (implying processing and analysis (Schmidt, 1990), while learners in the direct WCF group only compared their errors with the WCF received and seemed not to go further than noticing at the level of detection (without processing and analysis of input). Therefore, their accuracy of morpho-syntactic forms did not improve from time 1 to time 2 despite receiving direct WCF and being asked to analyse it. The nature of the task may have also influenced the results obtained. In a recent meta-analysis of WCF studies, Kang and Han´s (2015) found that the learning effect derived from the provision and processing of WCF are mediated by task type. Furthermore, the unconstrained nature of the task used which may have led learners to conceptualise the task in a different way, resulting in a new version of the task. In this new

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CHAPTER VII. DISCUSSION. version of the task, learners may have explored new ways to complete it and it is likely that they made new errors different from those targeted in the WCF processing session where they were provided with WCF and, therefore, limited WCF effects. The fact that learners may have made new errors is also related to the fact that task repetition does not entail verbatim repetition per se. Probably, the erroneous forms on which WCF was provided may be repeated in the second encounter with the task although the opposite scenario is also possible. Erroneous forms may be (un)intentionally omitted in the repetition of the task when completing it a second time, not because of the fact that these represent problematic forms for learners but simply because they used different language. This may impede assessing if input has been converted into uptake. As a consequence, the effects of WCF while engaged in task repetition in the written modality have to be carefully considered when analysed in terms of CAF measures. Cerezo, Manchón and Nicolás-Conesa (in press) also adduce other reasons why learners may fail to take advantage of WCF: i) all the feedback which is provided may not be processed and/or understood even if learners are encouraged to process and reflect on it in a feedback processing session and ii) WCF provision, whether direct or indirect, is unlikely to become uptake unless learners understand both errors and corrections.

Although the results may appear to be mediated by proficiency, this may not be the case since the lack of positive effects for task repetition as mediated by direct and indirect WCF for high proficiency participants may be attributed to the very low inaccuracy these participants exhibited in time 1. Having made such a low amount of errors the first time they did the task, they were not able to decrease their error rate significantly at time 2. However, as reported in the Results section, they did decrease the number of errors from time 1 to time 2, although this reduction was not significant.

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VIII. CONCLUSION.

This concluding chapter is structured as follows. First of all, a summary of the rationale of our research will be presented followed by a synthesis of the main findings. Next, the contribution and pedagogical implications of our study will be outlined, and we will finish acknowledging the limitations to our study and suggesting possible avenues for future research agendas.

VIII.1. SUMMARY OF THE RATIONALY OF THE STUDY. The present PhD dissertation was undertaken with the ultimate aim of advancing and contributing to previous research in three main areas: i) the modality-related effects of TR, ii) the effects of TR in the writing mode as a function of the feedback provided, whether direct or indirect and iii) the mediating role that proficiency may play in bringing about language learning gains via TR.

The effects of task repetition were initially hypothesised by Bygate (1996) in and for the oral modality in mind. TR repetition was claimed to lead to increased performance and engage learners in focus on form processes. In the first iteration of the task, learners are likely to prioritise meaning over form while they may shift their attention from meaning to formal aspects of language in the repeated performance. These purported benefits relied on the assumption that speech production processing poses certain constrains on the allocation of attentional resources (Manchón, 2014c). However, these predictions are called into question when we consider that task repetition may not function in the written mode as it does in speaking. Byrnes and Manchón (2014b) stressed the need to problematise TBLT tenets when applied to writing since assumptions held for oral language may well not apply to writing. As compared to the nature of oral communication and of spoken language, this potential differential nature of task repetition in writing is mainly related to the temporal dimension of written practice, its problem-solving nature and the greater permanence and visibility of both the written product and the WCF provided on it (Manchón, 2014c). As discussed in our literature review, these characteristics of writing have been claimed to facilitate learners´ focus on form and greater control of their attentional resources, these being the reason why learners may be more willing to pay attention to formal aspects of language and engage in processes potentially leading to language development. Whether this potential greater attention to language fits the

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CHAPTER VIII. CONCLUSION. predictions of TR in speaking (i.e. TR would foster greater attention to language during the second iteration of the task) was the empirical question that in great part guided our PhD.

Secondly, written corrective feedback is considered a crucial element when implementing TR in writing (Manchón, 2014b). Re-writing a text with the help and availability of WCF should be considered as a further form of task repetition since it directs learners´ attention to form, which is the ultimate aim for implementing task repetition in speaking. Furthermore, WCF is considered an inherent part of written practice and is considered as a further subprocess in writing (Manchón & Williams, 2016). Also, the literature on WCF has consistently showed the beneficial effects of the provision and processing of WCF (see Bitchener & Storch, 2016 for a recent review), which explains why some scholars have claimed that the inclusion of WCF stages is beneficial when engaging in task repetition (Ellis, 2009a; Manchón, 2014b). The mediating effects of different types of WCF and whether certain types (direct or indirect) lead to greater processing/uptake are empirical questions that also guided our research and justify some of the research questions guiding it, namely those in which we investigated the potential mediation of different WCF types i.e. direct/indirect, on task repetition.

Finally, the need to study the mediating role proficiency may play in task repetition became evident when considering findings in previous research (Mojavezi, 2013). Mojavezi found that TR was mediated by learner proficiency and, more precisely, that higher proficiency learners are able to take greater advantage of task repetition. However, Bygate (in press) recently argued that TR is likely to function in the same way across proficiency levels. These contradictory views and the lack of research in this direction provide the rationale for the inclusion of L2 proficiency as one of the independent variables in our study.

VIII.2. SYNTHESIS OF MAIN FINDINGS. We conducted our research with the intention of shedding light on the areas of research outlined above. We next provide a synthesis of our main findings regarding i) task repetition across modalities; ii) task repetition in writing as mediated by different types of WCF; and (iii) the overarching mediating role of proficiency over these two.

VIII.2.1. TASK REPETITION ACROSS MODALITIES (SPEAKING/WRITING). Regarding task repetition in speaking and writing, significant results were found in the dimension of fluency. This result indicated that task repetition prompts significantly more fluent

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CHAPTER VIII. CONCLUSION. performance, but only in the oral mode (regardless of proficiency level). That is, both high and low proficiency learners were able to take advantage of task repetition in terms of fluency. Additionally, significant differences were also found in the area of syntactic complexity. However, this significant result points to the significant decrease in the measure for subordination across groups from time 1 to time 2. This reduction was much more marked in the writing groups, which therefore contributed to a higher extent to this significant decrease. No other significant results were found for the rest of dimensions i.e. lexical complexity and accuracy.

Our results partially confirm Bygate´s predictions (1996, 2001) with regard to the beneficial effects of task repetition in terms of fluency and do so in an under-researched population i.e. low-proficiency learners. However, the evident lack of positive results in the written mode as compared to speaking confirm Manchón´s prediction regarding the mediation of modality regarding the effects of TR (2014c).

Also, Bygate´s (1996, 2001) claims regarding the lack of a role for proficiency in TR were confirmed. Participants behaved very much alike across proficiency levels in the two modes. Thus, high and low proficiency participants were able to increase their performance in the oral mode in the area of fluency, while high and low proficiency participants in the written modality seemed not to have taken advantage of task repetition, in contrast to Mojavezi´s findings (2013).

With respect to modality-related effects, significant results were found in the areas of syntactic and lexical complexity. These results indicate that the written mode elicits more complex language in terms of lexical diversity and lexical richness by high-proficiency learners and more complex language in terms of subclausal complexity in both high and low proficiency levels. These results echo those in previous research (see, for example, Kormos, 2014; Vasylets et al., 2017) and have been interpreted from the perspective of the differential nature of production in both modalities, mainly, the greater availability of time during writing, the problem-solving and goal-oriented nature of composing (Manchón & Roca de Larios, 2007) and the greater visual saliency of the written product (Manchón, 2011a; 2013).

VIII.2.2. TASK REPETITION IN WRITING. Significant results were found for task repetition in writing as mediated by different types of WCF. In the dimension of accuracy, significant results were found for low proficiency learners. Low proficiency participants in the direct and indirect WCF groups reduced their lexical errors in both measures (LEXE/100w and LEXE/T) due to the combined effect of TR and WCF

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CHAPTER VIII. CONCLUSION. processing. Moreover, learners in the indirect WCF group were also able to reduce their morpho-syntactic errors (MSE/100w and MSE/T) and total errors (TOTALE/100w and TOTALE/T). from T1 to T2. In contrast, no significant effects were found for high proficiency participants in terms of accuracy as a result of TR, regardless of WCF condition. Finally, with respect to fluency, significant results were found. More specifically, participants in the writing group were able to increase their fluency (words/minute and syllables/minute) from T1 to T2 regardless of proficiency level while only low proficiency learners in the self-correction group were able to do so. This apparent tension between CAF dimensions has been explained in terms of trade-off effects (Skehan, 1998, 2009) and learners´ limited attentional capacity (Skehan, 1998). Learners in our study seemed to have paid attention either to accuracy or fluency and this behaviour was favoured by the provision (or lack of provision) of different types of WCF. No other significant results were found for task repetition in the written modality in terms of either syntactic and lexical complexity regardless of proficiency or WCF condition.

A role for proficiency is somewhat more evident in this respect. While being a fact that learners in the writing groups performed in the same way across proficiency levels, the results concerning the effects of WCF were only found to be significant for low proficiency learners. In a similar way, low proficiency learners in the self-correction condition were able to increase in fluency while high proficiency participants in the same group did not increase significantly their performance in the area of fluency.

VIII.3. CONTRIBUTION OF OUR RESEARCH. The research conducted and reported in this PhD can be taken as contribution to previous research on task repetition and to the cognitively-oriented strand of L2 writing.

In the area of task repetition, the main contribution derives from the light our research sheds on the predicted modality-related effects of task repetition, as suggested in Manchón (2014c). The assumption that task repetition is beneficial to allow learners to engage in focus on form processes does not seem to apply boldly to the written mode, at least with the type of tasks used in our study and the L2 users investigated. The theoretical claims regarding the beneficial effects of task repetition were hypothesised due to the time constrains that characterise oral language. However, our study confirms that the temporal dimension of L2 writing and the greater availability of time on task for task completion in writing allow learners to focus on meaning and form at the same time, making use of their full linguistic resources in the first iteration of the task. Thus, having the opportunity to repeat the task does not lead

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CHAPTER VIII. CONCLUSION. learners to engage in successive focus on form processes and therefore does not result in increased performance beyond being able to write more in less time.

Furthermore, task repetition in writing seems to be mediated by proficiency when a WCF processing stage is implemented in the task repetition cycle. High and low proficiency participants who did not engage in WCF processing were able to increase in fluency as a result of task repetition. In contrast, only low proficiency learners who were provided with and processed WCF, either direct or indirect, were able to increase in accuracy as a consequence of the combined effect of WCF processing and task repetition. However, high proficiency participants in these groups i.e. direct or indirect WCF groups, did not show any evidence of significant increased performance in any dimension due to engaging in task repetition as mediated by direct or indirect WCF.

In a similar fashion, part of the results concerning modality differences in speaking and writing when studying task repetition appear to be mediated by proficiency. More precisely, two different modality related effects were found in the areas of lexical and syntactic complexity. It is the former, lexical complexity, which seems to be proficiency-mediated. Only high proficiency writers were able to outperform high proficiency speakers in terms of lexical variety and richness. On the other hand, low proficiency learners behaved in a similar way across modalities in these areas. Regarding syntactic complexity, writing groups across proficiency levels outperformed oral groups. This purported greater language learning potential of L2 writing can be explained in connection to the characteristics of written language. Firstly, the greater availability of time imposes on learners lower demands of attentional resources, who may be able to focus on meaning and form at the same time and make full use of their linguistic resources during the first iteration with the task (as evident in the lack of positive effects of task repetition in writing). This self-paced timed nature of writing is also likely to foster deeper linguistic processing. Learners are able to access their knowledge stores and analyse their explicit knowledge in search for potential solutions to problems. It may be even the case that they access and analyse implicit knowledge, making it explicit and available for subsequent use (Manchón & Williams, 2016). Secondly, the permanence and visibility of the compositions is also likely to lead learners to reflect on language and revise the text already written (Manchón, 2013). Additionally, it has also been claimed that the visual saliency of written output may lead to produce “pushed output” (Swain, 1985) with potential benefits for language learning and that these characteristics may also prompt learners to set up higher goals (Leki, 2001; Manchón 2013). Finally, in connection to this last claim concerning goal setting during writing, the act of composing is a problem-solving, goal-oriented activity. Learners need to make strategic decision

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CHAPTER VIII. CONCLUSION. regarding what attentional resources to devote to each aspect of the task demanding attention and this has been claimed to engage learners in focus on form processes and lead to language development. Therefore, theoretical predictions (see Manchón, 2011a; 2013; Manchón & Williams, 2016; Williams, 2012) which pointed writing as a site with greater language potential were in the right direction and these predictions have been confirmed by research findings (see for example Vasylets et al., 2017).

Finally, our research has also confirmed previous predictions suggested in Skehan´s Limited Attentional Capacity Model (1998) regarding the tension between different areas of linguistic performance i.e. fluency and accuracy. These competitive relation among dimensions suggests that learners are not able to pay to different aspects of language performance at the same time.

VIII. 4. PEDAGOGICAL IMPLICATIONS. The pedagogical implications which have arisen from the findings in the present research can be synthesized in two main areas: i) the affordances of each modality and ii) the importance of WCF when implementing task repetition in the written mode.

From the light shed by the results of this study, oral and written modes are presented as different contexts which may create distinctive environments for language development and learning and it is so due to their differentiating characteristics. Although it was found that task repetition in the oral mode fostered more fluent performance than writing, modality-related effects indicate that writing may trigger the deployment of more complex language in terms of lexical and syntactic complexity. This greater use of complex language is related to processes of attention to formal aspects of language which are potentially conducive to language learning and are facilitated by the characteristics of writing, namely the greater availability of time, the permanence and visibility of both the written text and the WCF provided on it (see below) and its problem-solving nature (Manchón, 2011a; 2013). We have already argued how these characteristics may model language learning through writing and the language opportunities that may derive from engaging in meaningful, goal-oriented, cognitively-demanding writing tasks. Therefore, writing should be made more central in the L2 classroom as a potential site for L2 development and learning where learners are able to work at their own pace (Williams, 2012).

The importance of WCF while engaged in the task repetition cycle can be regarded from two different perspectives. Firstly, from the scope of low proficiency learners, WCF represents a valuable tool for language instructors to promote accuracy gains. The greater explicitness of

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CHAPTER VIII. CONCLUSION. direct WCF forms and the greater depth of processing associated with the provision of indirect WCF prompted higher lexical (direct and indirect WCF) and higher morpho-syntactic accuracy (indirect WCF) as well as overall accuracy (indirect WCF) supporting findings in previous research (Bitchener & Ferris, 2012; Bitchener & Storch, 2016). Furthermore, low-proficiency learners in the self-correction group did not seem to have engaged in focus on form processes induced by WCF provision as evident in their very similar behaviour to low-proficiency participants in the writing group. Therefore, implementing self-correction stages in the L2 writing classroom should be considered as having scarce pedagogical value and rather limited language learning potential. Secondly, with respect to high proficiency learners, there seems to be a limited effect for WCF to promote significant accuracy gains. At the same time, the associated focus on form related to WCF processing may have hindered fluent performance in the subsequent written production, as it was the case for high proficiency participants in the written task repetition group who did not receive or process WCF. Following from this, language instructors need to adjust the type of intervention to learners´ proficiency when implementing task repetition in the L2 writing classroom depending on the desired learning outcomes.

Finally, in earlier sections we made reference to the mediating role which different types of task may have on TR and WCF processing and the language learning outcomes that may derive from task variation when implanting TR and WCF stages during the TR cycle. Therefore, a wide variety of tasks should be explored in order to expand learning opportunities in the L2 writing classroom.

VIII.5. LIMITATIONS TO OUR STUDY AND FUTURE RESEARCH. A number of limitations to our study should be acknowledged. First of all, the reduced number of participants in our study (n= 66) makes it difficult to draw conclusive implications from our results. Therefore, studies with a higher number of participants need to be conducted to shed further light on the results of the present research.

Another limitation relates to the fact that we only investigated the effects of one type of task and this may be the reason why a certain disparity in findings compared to previous research was found. Generally, TR has yielded positive results in the area of fluency and some other dimensions of performance i.e. accuracy and/or complexity. However, our findings relate to the area of fluency and only to the area of accuracy when a form of WCF is present in task repetition conditions in writing. The nature of the decision-making task in our study may have prompted these different effects as compared to the narrative tasks mostly used to assess the

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CHAPTER VIII. CONCLUSION. effects of task repetition both orally (Bygate, 2001) and in writing (Nitta & Baba, 2014). Some scholars have already suggested (Manchón, 2014b) that learning outcomes may be mediated by task-type. Furthermore, the effects of WCF have also been found to be mediated by the type of task studied in a recent meta-analysis of empirical research in the field of WCF (Kan & Han, 2015). Along with the results in our study and those in previous research, task-type effects in task repetition, but also in other areas (e.g. task-modality or WCF), represent an emergent area of research in need of further empirical studies.

Another empirical question we did not investigate in our study is whether the same effects for task repetition would be found if task complexity were involved. Vasylets et al., (2017) predicted that task complexity may play a role since L2 writers might not be able to achieve all the goals set while performing the task the first time and may need to engage in task repetition to do so. Therefore, an empirical question for further research would be to look into the mediating role of task complexity on the modality-dependency of task repetition effects.

Similarly, the nature of the trade-off effects suggested in the Limited Attentional Capacity Model (Skehan, 1998) need to be investigated more in depth. The results in the present study did support Skehan´s claims (1998, 2009) regarding tension between the areas of fluency and accuracy and suggests that learners are not able to pay attention to different aspects of language performance at the same time in contrast to Robinson´s Cognition Hypothesis (2001) which claims that manipulating task conditions actually leads to greater accuracy and complexity. However, there is generalised lack of consensus in research testing both models, issue which future studies have to examine.

Our study investigated TR in the short term and, as many other studies (see Ahmadian & Tavakoli, 2011; Fukuta, 2015; Hu, 2018 for similar time lapses across iterations) we found beneficial effects. Some other studies have addressed the long-term effects of task repetition both orally (Ahmadian, 2011; Bygate, 2001) and in writing (Nitta & Baba, 2014) on L2 acquisition. These studies did report significant effects for TR, but the scarcity of research on the long-term effects of TR both orally and in writing calls for further empirical validation. More specifically, TR in writing has reported positive results both in the area of accuracy (Amiryousefi, 2016) and complexity (see Nitta & Baba, 2014) in periods of time comprehending six weeks to forty weeks respectively. Therefore, empirical research is needed to shed light on the mediating role that the number of repetitions of a task plays so as to lead learners to shift their attention from one dimension of performance to another. Additionally in writing, the mediating role of WCF on task repetition in the longer-term has not received due research attention (but see Amelohina,

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Manchón & Nicolás-Conesa, 2017 for a notable exception). We anticipate this line of research to result in welcome synergies not only for WCF and TR agendas but it will also be beneficial for the fields of SLA and L2 writing in relation to the insights this strand of research may bring about concerning language development, learning and acquisition. Related to this, the question regarding whether different types of WCF result in different learning outcomes still remains unanswered. Some studies have lent support to these purported differential effects (Sánchez & Manchón, 2014; Storch and Wigglesworth, 2010) although more research is needed.

Finally, the proficiency-dependency of task repetition effects need to be further investigated. Theoretical predictions regarding the lack of a role for proficiency in task repetition (Bygate, in press) contradict the available empirical findings (Mojavezi, 2013) while our study seemed to point in both directions (lack of a role for task repetition orally and in writing and certain role for proficiency for task repetition in writing in combination with the availability and processing of WCF). Similarly, other areas within learners´ individual differences, such as motivation or working memory capacity (WMC) (Ahmadian, 2012) would also enrich previously held assumptions and theoretical predictions regarding the potential benefits of task repetition in the oral and written modes.

Despite these limitations, we would like to think that the research reported in this PhD represents a further step in current efforts to make cognitively-oriented L2 writing much more central in Second Language Acquisition. Our study provides empirical evidence of the importance of problematising theoretical tenets thought in and for the oral mode before making them apply to all language modalities. Additionally, it offers new empirical evidence of the language learning potential of written practices and of the provision and processing of written corrective feedback within a Task-Based Language and Teaching framework.

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RESUMEN EN ESPAÑOL

RESUMEN

OBJETIVOS, HIPÓTESIS Y PREGUNTAS DE INVESTIGACIÓN La repetición de la tarea (RT) ha recibido mucha atención de la investigación reciente en modalidad oral (lingüísticos (Ahmadian & Tavakoli, 2010; Bygate, 1996, 2001, 2006; Bygate & Samuda, 2005; Gass et al., 1999; Hawkes, 2010; Kim, 2013; Lynch & Maclean, 2000; 2001). Se afirma que esta variable de implementación de la tarea libera en parte recursos atencionales de los aprendices de leguas reduce la carga cognitiva de los aprendices de lenguas y les lleva a involucrarse en procesos de atención a la lengua, lo que a su vez conlleva una mejora en la actuación en términos lingüísticos (Ahmadian & Tavakoli, 2010; Bygate, 1996, 2001, 2006; Bygate & Samuda, 2005; Gass et al., 1999; Hawkes, 2010; Kim, 2013; Lynch & Maclean, 2000; 2001). No obstante, RT se ha investigado en mucha menor medida en la modalidad escrita (Baba & Nitta, 2014; Nitta & Baba, 2014, 2015, 2018; Amiryousefi, 2016) aún a pesar de que se ha dado cuenta de los efectos diferenciadores de la RT en las distintas modalidades (Manchón, 2014) y del papel que la respuesta al escrito (RE) en la modalidad escrita. Asimismo, los efectos mediadores de la competencia lingüística en la RT continúan necesitando comprobación empírica (Mojavezi, 2013). Más concretamente, las áreas de investigación a las que esta tesis doctoral pretende contribuir son las siguientes: 1. Los efectos mediadores de la modalidad sobre la RT. El objetivo de este estudio es analizar los efectos de la modalidad (oral/escrita) sobre la actuación lingüística en términos de medidas CAF (complejidad, corrección y fluidez, en sus siglas en inglés). 2.Los efectos de la repetición de la tarea en función del tipo de RE, siendo ésta un elemento crucial en la implementación de la repetición externa de la tarea en la modalidad escrita. 3. El papel mediador de la competencia lingüística sobre la repetición de la tarea habiendo sido afirmado el papel moderador de la competencia lingüística en los efectos de la RT (Mojavezi, 2013).

Basándonos en nuestros objetivos y en las predicciones teóricas mencionadas, las siguientes hipótesis de investigación guiaron nuestro estudio: H1. La modalidad tendrá un papel mediador en la implementación de la repetición de la tarea y se encontrarán efectos diferentes en modalidad escrita a aquellos que se dan en la modalidad oral. La dirección de estas potenciales diferencias no se ha establecido dada el escaso

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RESUMEN EN ESPAÑOL número de estudios de investigación comparando modalidades de producción lingüística en la repetición de la tarea. H2. Proporcionar respuesta al escrito (RE) y el procesamiento de dicha RE por parte del aprendiz durante el ciclo de repetición de la tarea en modalidad escrita conllevará una mayor actuación que la mera repetición de la tarea o la autocorrección. H3. La naturaleza de la respuesta al escrito, directa o indirecta, tendrá efectos diferenciales sobre la actuación lingüística al implementar la repetición de la tarea en modalidad escrita y las diferencias observadas estarán mediadas por el nivel de competencia lingüística de los aprendices. No se establece la influencia de estos efectos dado que los resultados de la investigación previa no son concluyentes. H4. El nivel de competencia lingüística tendrá un papel mediador al implementar la repetición de la tarea. Los aprendices de nivel más elevado se beneficiarán en mayor medida de la repetición de la tarea.

Con la finalidad de confirmar o refutar nuestras hipótesis, las siguientes preguntas de investigación guiaron nuestro estudio:

RQ1. ¿Resulta la repetición de la tarea en distintas modalidades de producción lingüística (oral/escrita) en diferencias cuantitativas en la actuación lingüística de los aprendices cuantificada en diferentes medidas de complejidad, corrección y fluidez (CAF – en sus siglas en inglés)? ¿Tiene un papel mediador la competencia lingüística sobre los efectos observados?

RQ2. ¿Resulta la repetición de la tarea modalidad escrita en función de la respuesta al escrito en efectos sobre la actuación lingüística de los aprendices cuantificada en diferentes medidas de complejidad, corrección y fluidez (CAF – en sus siglas en inglés) cuando repiten la misma tarea? ¿Tiene un papel mediador la competencia lingüística sobre los efectos observados?

RQ3. ¿Resulta la repetición de la tarea en modalidad escrtia en función del tipo de respuesta al escrito (directa/indirecta) en efectos sobre la actuación lingüística de los aprendices cuantificada en diferentes medidas de complejidad, corrección y fluidez (CAF – en sus siglas en inglés) cuando repiten la misma tarea?

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RECOGIDA DE DATOS Y METODOLOGÍA

Sesenta y seis participantes (varones n=29, mujeres n=37) en diferentes niveles de competencia lingüística (Alto n= 31; Bajo n= 35), medida a través de un test estandarizado “Oxford Placement”, y fueron distribuidos en uno de cinco grupos en cinco condiciones experimentales diferentes: oral (G1: A n= 6; B n= 8) escrito (G2: A n= 7; L= 8), RE directa (G3: A n= 6; B n= 7), RE indirecta (G4 A n= 6; B n= 7) y autocorrección (G5: A n= 6; B n= 5). Previamente a la recogida de datos, todos los participantes completaron un formulario de consentimiento de participación en el estudio y un cuestionario demográfico que incluía preguntas sobre sus experiencias de aprendizaje de idiomas pasadas y sus preferencias con respecto al aprendizaje de idiomas. La información obtenida a través de las preguntas de este cuestionario se utilizó para distribuir a los participantes en los distintos grupos experimentales y conseguir la más alta homogeneidad posible entre todos los grupos. Todos los grupos realizaron una tarea de toma de decisiones (Gilabert, 2005; 2007) (día 1) de manera oral o escrita y repitieron la tarea una semana después (día 8) en la misma modalidad en la que lo había hecho previamente (día 1). La tarea de toma de decisiones, “Firechief Task” dispone de dos versiones, simple y compleja. Con anterioridad a la recogida de datos del presente estudio, ambas versionas se pilotaron con una población similar a la de nuestro estudio para decidir qué versión usar. La versión compleja resultó en una mayor producción en términos de palabras, siendo ésta, pues, la versión escogida para nuestro estudio. Antes de comenzar la tarea, los participantes dispusieron de 30 segundos para leer las instrucciones y familiarizarse con la tarea, acorde con las instrucciones originales en Gilabert (2005, 2007). Transcurrido este tiempo, se les invitó a comenzar la producción. Los grupos G3, G4 y G5 asistieron a una sesión adicional (día 4) en la que se les pidió que analizaran la RE directa o indirecta (G3 y G4, respectivamente) en los errores cometidos en sus composiciones escritas o bien que autocorrigieran sus escritos (G5). Para este fin, se les proporcionó una tabla de procesamiento de RE que debían completar no sólo con el/los error/es cometido/s, si no también con una explicación sobre el porqué del error. Este procedimiento se siguió con el fin de incentivar un procesamiento más profundo de la RE, que a su vez está asociado con un mayor incorporación inmediata y una mayor retención a largo plazo de ítems lingüísticos (Qi & Lapkin, 2001, Santos, López-Serrano & Manchón, 2010).

Tanto la primera realización de la tarea, así como la repetición de la misma y la sesión de procesamiento de la RE se realizaron en condiciones de tiempo ilimitado, lo que permitió a los participantes acceder a todos sus recursos lingüísticos disponibles. De esta manera, se intentó equilibrar la carga cognitiva de los participantes al realizar la tarea.

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Para analizar las diferencias entre T1 y T2, se analizó la producción de los participantes en medidas CAF, en sus siglas en inglés – complejidad, corrección y fluidez. Siguiendo el modelo taxonómico de complejidad de Bulté y Housen (2012), decidimos estudiar las dimensiones de complejidad léxica y sintáctica. Estas dos dimensiones se componen de diferentes sub- constructos y se eligieron diferentes medidas para abarcar todas estas subdimensiones. En cuanto a la complejidad léxica, se estudió la variedad (valor D), la riqueza, (índice de Guiraud) y la sofisticación (índice avanzado de Guiraud). La complejidad sintáctica se estudió a través de diferentes medidas: complejidad general (MLT), subordinación (DC/T), coordinación (T/S), complejidad clausal (NPC) y variedad sintáctica (STRUTt). Para medir la corrección, se prefirieron medidas que contabilizaron el número total de errores dada la sensibilidad de otro tipo de medidas para participantes de bajos niveles de competencia lingüística. Las medidas seleccionadas fueron las siguientes: número de errores totales por cada 100 palabras y por T- unit, número de errores léxicos por cada 100 palabras y por T-unit y número de errores morfosintácticos por cada 100 palabras y por T-unit. Adicionalmente para la modalidad escrita, se computaron de la misma manera el número de errores de deletreo por cada 100 palabras y por T-unit. Por último, las medidas de fluidez incluyeron el número de palabras por minuto y el número de sílabas por minuto.

Con la finalidad averiguar diferencias significativas, se llevaron a cabo dos análisis de varianza (ANOVA). El primero de estos análisis comparó la actuación de los grupos 1 (oral) y 2 (escrito) en la repetición con un diseño factorial 2x2x2. El segundo comparó la repetición de la tarea en la modalidad escrita en diferentes condiciones comparando los grupos 2 (escrito), 3 (RE directa), 4 (RE indirecta) y 5 (autocorrección) con un diseño factorial 2x4x2.

RESULTADOS Y DISCUSIÓN

En cuanto al primero de los análisis (RT en modalidades oral y escrita), no se encontraron resultados significativos en las dimensiones de complejidad léxica o corrección. Sí se encontraron resultados significativos en el área de complejidad sintáctica. Más concretamente, se encontró un resultado significativo que evidencia una reducción en la ratio de subordinación de T1 a T2 para todos los grupos, siendo esta mucho más marcada para los grupos en modalidad escrita. Con respecto a la fluidez, se encontraron resultados significativos que señalan que RT incrementa la fluidez en modalidad oral independientemente del nivel de competencia lingüística. Estos resultados apoyan parcialmente las predicciones sobre los efectos de RT en modalidad oral sobre la fluidez (Bygate, 1996; 2001) y muestran evidencia de efectos positivos

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RESUMEN EN ESPAÑOL en una población con nivel de competencia bajo, una población poco investigada hasta la fecha. No obstante, la evidente falta de resultados positivos en la modalidad escrita indica que, para encontrar resultados positivos en modalidad escrita debido a la RT, posiblemente sea necesario RT continuada (Nitta & Baba, 2014), actuación externa en forma de RE (Manchón 2014b) o incluso ambas. De la misma manera, se encontraron resultados significativos en relación a la modalidad con respecto al uso de lenguaje más complejo en modalidad escrita que en modalidad oral, acorde a resultados de investigación previa (Vasylets, Gilabert & Manchón, 2017). La modalidad escrita emerge pues como un contexto que puede promover mayores oportunidades de aprendizaje debido a las características diferenciadoras de la escritura en segundas lenguas, especialmente, la mayor disponibilidad de tiempo.

Con respecto a RT en modalidad escrita en diferentes condiciones de escritura, no se encontraron resultados significativos en la dimensión de complejidad léxica o sintáctica en línea con resultados de investigación previa (Amiryousefi, 2016). Se encontraron resultados significativos en el área de fluidez en los grupos que no recibieron ni procesaron respuesta al escrito, esto es, participantes de nivel de competencia bajo en los grupos G1 y G5 y participantes de nivel de competencia alto en el grupo G1 (Nitta & Baba, 2014). Por el contrario, los participantes de nivel de competencia bajo en los grupos de RE directa y RE indirecta incrementaron significativamente su corrección, apoyando las conclusiones respectivas a los efectos beneficiosos del procesamiento de la RE (Bitchener & Storch, 2016). Es probable que los participantes cuya atención fue dirigida a aspectos formales de la lengua debido al procesamiento de la RE prestaran más atención a la corrección que a la fluidez en la repetición de la tarea. Por el contrario, los participantes que no procesaron RE entre T1 y T2 continuaron prestando atención al significado en la repetición de la tarea, con el consiguiente aumento en fluidez. Por lo tanto, puede haber existido tensión entre las dimensiones de corrección y fluidez como algunos autores han señalado (Skehan, 1998, 2009).

Ciertas limitaciones de nuestro estudio deben ser reconocidas. En primer lugar, el limitado número de participantes no permite establecer implicaciones concluyentes. Además, solo se estudió un tipo de tarea. Diferentes tipos de tarea pueden mediar los resultados de aprendizaje, así como los efectos de RE, por lo que la investigación futura debe abordar los efectos de distintos tipos de tarea. De igual manera, la investigación futura debe investigar los efectos longitudinales de RT en modalidad escrita y el efecto mediador de distintos tipos de RE, así como explorar el papel de la motivación y de diferencias individuales al implementar RT en la clase de lengua.

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