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    Implicit and Explicit Knowledge in Second Language Learning, Testing and Teaching
    Implicit and Explicit Knowledge in Second Language Learning, Testing and Teaching
    Implicit and Explicit Knowledge in Second Language Learning, Testing and Teaching
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    Implicit and Explicit Knowledge in Second Language Learning, Testing and Teaching

    By Rod Ellis, Shawn Loewen, Catherine Elder and

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    The implicit/ explicit distinction is central to our understanding of the nature of L2 acquisition. This book begins with an account of how this distinction applies to L2 learning, knowledge and instruction. It then reports a series of studies describing the development of a battery of tests providing relatively discrete measurements of L2 explicit/ implicit knowledge. These tests were then utilized to examine a number of key issues in SLA - the learning difficulty of different grammatical structures, the role of L2 implicit/ explicit knowledge in language proficiency, the relationship between learning experiences and learners’ language knowledge profiles, the metalinguistic knowledge of teacher trainees and the effects of different types of form-focused instruction on L2 acquisition. The book concludes with a consideration of how the tests can be further developed and applied in the study of L2 acquisition.

    LanguageEnglish
    PublisherMultilingual Matters
    Release dateJun 19, 2009
    ISBN9781847698858
    Implicit and Explicit Knowledge in Second Language Learning, Testing and Teaching
    Author

    Rod Ellis

    Rod Ellis is an applied linguist who has published widely on second language acquisition and task-based language learning. He is currently a Distinguished Research Professor in the School of Education, Curtin University, Australia and an elected fellow of the Royal Society of New Zealand. He is a past recipient of the Kenneth W. Mildenberger and Duke of Edinburgh prizes.

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      Implicit and Explicit Knowledge in Second Language Learning, Testing and Teaching - Rod Ellis

      Preface

      This book originated in a project funded by the Marsden Fund, a fund administered by the Royal Society of New Zealand to support ideas-driven research. The initial principal investigators were Rod Ellis and Catherine Elder. When Catherine Elder left the project in 2004, her place was taken by Shawn Loewen. Two other researchers at the University of Auckland were also closely involved in the project – Rosemary Erlam and Jenefer Philp – and also, at various times, there were a number of research assistants – in particular, Satomi Mizutani, Keiko Sakui and Thomas Delaney. The successful completion of the project owed much to the combined efforts of all these researchers. The project took place over three years (2002–2005).

      There were three major goals:

      (1) To develop tests to measure second language (L2) implicit and explicit grammatical knowledge.

      (2) To identify the relative contributions of these two types of L2 knowledge to general language proficiency.

      (3) To investigate what effect form-focused instruction has on the acquisition of L2 explicit and implicit grammatical knowledge.

      These three goals are reflected in the structure of this book. Thus, Part 2 reports the results of the research designed to develop tests of implicit and explicit knowledge, Part 3 contains a number of studies that examined the application of the tests in various applied ways, including the role played by implicit and explicit L2 knowledge in language proficiency and Part 4 addresses the effects of instruction on the acquisition of L2 explicit and implicit grammatical knowledge. This book, therefore, is an attempt to bring together the results of the Marsden Fund Project.

      The distinction between implicit and explicit L2 knowledge is fundamental to understanding the nature of L2 acquisition, the role of these two types of knowledge in L2 proficiency and the contribution that various types of instruction can make to L2 acquisition. It is also a distinction that appears to be supported by current neurobiological research, which has shown that the two types of knowledge are neurologically distinct. Because this distinction is central to the whole book, Part 1 (Chapter 1: Introduction) is devoted to its definition and explication.

      The distinction has been incorporated into very different theories of L2 acquisition, including those based on an information-processing model and those derived from sociocultural theory. The research reported in this book was informed by an information-processing model, the model most familiar to the researchers involved. This model views knowledge as related to but independent of language use. It is acquired as a result of learners engaging in active processing of the L2 input they are exposed to and is reflected in the gradual and dynamic way in which learners build their interlanguages. Key processes are those relating to attention to form (i.e. noticing and noticing-the-gap), rehearsal in short-term memory, integration into long-term memory and monitoring (see Ellis, 2008). These are terms that will be used throughout the book. In Part 4 (Chapter 14: Conclusion), an attempt will be made to retrospectively examine the main findings from a different perspective – that afforded by sociocultural theory.

      The contents of the book are, in part, based on a number of previously published papers:

      Elder, C., Erlam, R. and Philp, J. (2007) Explicit language knowledge and focus on form: Options and obstacles for TESOL teacher trainees. In S. Fotos and H. Nassaji (eds) Form Focused Instruction and Teacher Education: Studies in Honour of Rod Ellis. (p. 225–240) Oxford: Oxford University Press (Oxford Applied Linguistics Series).

      Ellis, R. (2004) The definition and measurement of L2 explicit knowledge. Language Learning 54, 227–275.

      Ellis, R. (2004) Measuring implicit and explicit knowledge of a second language: A psychometric study. Studies in Second Language Acquisition 27, 141–172.

      Ellis, R. (2006) Modelling learning difficulty and second language proficiency: The differential contributions of implicit and explicit knowledge. Applied Linguistics 27, 431–63

      Ellis, R., Loewen S. and R. Erlam. (2006) Implicit and explicit corrective feedback and the acquisition of L2 grammar. Studies in Second Language Acquisition 28, 339–68.

      Erlam, R. (2006) Elicited imitation as a measure of L2 implicit knowledge: An empirical validation study. Applied Linguistics 27, 464–491.

      However, none of these papers has been reproduced verbatim. Rather the contents have been modified to avoid repetition and to ensure continuity from one chapter to the next. The book also contains reports of a number of previously unpublished studies that were part of or were closely related to the Marsden Project (see Chapters 4, 7, 8, 10–12). In addition, Chapter 1 (Introduction) and Chapter 14 (Conclusion) have also been specifically written for this book.

      It remains for us to thank the New Zealand Royal Society of Arts for funding the research that led to this book and the University of Auckland’s Research Office for its logistic support. I would also like to thank Katherine Cao for her work on the bibliography of the book and the Center for Applied Linguistics in Washington DC for appointing me as Ferguson Fellow for 2008, which made possible the assembling of the final manuscript.

      Rod Ellis

      University of Auckland

      Part 1

      Introduction

      The chapter in Part 1 introduces the key terms used in this book – implicit/explicit learning, knowledge and instruction. The distinctions between implicit and explicit knowledge and implicit and explicit learning are of central significance in both cognitive psychology and in second language acquisition (SLA) research. The closely related distinction between implicit and explicit instruction is also important for language pedagogy. These distinctions address how we come to know what we know about a second language (L2), how we store that knowledge and the use we make of it. No SLA researcher and no language teacher can afford to ignore these distinctions.

      The chapter begins with an exploration of how these distinctions have been treated in cognitive psychology. It then moves on to examining how they have been addressed in SLA research. Separate sections consider implicit/explicit L2 learning, implicit/explicit L2 knowledge and implicit/explicit language instruction. The issue of whether or not there is an interface between implicit and explicit learning and knowledge is also addressed, as this is of crucial importance when considering the role of instruction in L2 acquisition.

      This chapter aims to provide an introduction to these key constructs together with the theoretical background that informs the empirical studies reported in subsequent parts of the book.

      Chapter 1

      Implicit and Explicit Learning, Knowledge and Instruction

      ROD ELLIS

      Introduction

      The distinctions relating to implicit/explicit learning and knowledge originated in cognitive psychology, so it is appropriate to begin our examination of them with reference to this field of enquiry. Cognitive psychologists distinguish implicit and explicit learning in two principal ways:

      (1) Implicit learning proceeds without making demands on central attentional resources. As N. Ellis (2008: 125) puts it, ‘generalizations arise from conspiracies of memorized utterances collaborating in productive schematic linguistic productions’. Thus, the resulting knowledge is subsymbolic, reflecting statistical sensitivity to the structure of the learned material. In contrast, explicit learning typically involves memorizing a series of successive facts and thus makes heavy demands on working memory. As a result, it takes place consciously and results in knowledge that is symbolic in nature (i.e. it is represented in explicit form).

      (2) In the case of implicit learning, learners remain unaware of the learning that has taken place, although it is evident in the behavioral responses they make. Thus, learners cannot verbalize what they have learned. In the case of explicit learning, learners are aware that they have learned something and can verbalize what they have learned.

      The focus of research in cognitive psychology has been on whether implicit learning can take place, and, if it does, how it can best be explained. However, since Reber’s (1976) seminal study of implicit learning, there has been an ongoing debate about the validity of his ‘multiple learning systems’ view of human cognition. Many researchers dispute the existence of multiple systems and argue in favor of a single system that is capable of achieving different learning outcomes.

      This controversy within cognitive psychology is very clearly evident in a collection of papers addressing the role of consciousness in learning (Jimenez, 2003). In the opening paper, Shanks (2003) critiqued the research that used a technique known as ‘sequential reaction time’ to stake out the claim for multiple, differentiated learning systems. In studies using this technique, the time it takes for people to respond to an array of predictable visual information is compared to the time it takes when this array is suddenly disturbed. The claim here is that a difference in response times demonstrates that some learning must have taken place implicitly prior to the disturbance, even though the participants involved were unable to verbalize what they had learned. Shanks (2003: 38) argued that ‘previous research has failed to demonstrate convincingly that above-chance sequence knowledge can be accompanied by null awareness when the latter is indexed by objective measures such as recognition’. He concluded that there was no convincing evidence that implicit learning is functionally or neurally separate from explicit learning and that it was misguided to look for such dissociation. He advanced the alternative view that there is a single knowledge source that underlies performance and that apparent differences in performance are due to ‘subtle differences between the retrieval processes recruited by the tests’ (p. 36).

      In contrast, other papers in the same collection argued strongly for distinguishing the two types of learning. Wallach and Lebiere (2003), for example, developed a strong argument for a dual learning system based on the central concepts of ACT-R cognitive architecture (Anderson & Lebiere, 1998). This proposes a hybrid learning system consisting of a permanent procedural memory and a permanent declarative memory. The former consists of condition-action rules called ‘productions’ that enable a certain action to be performed provided that specific conditions have been met. Such ‘productions’ operate automatically. Declarative knowledge consists of factual knowledge stored as chunks organized into schemas. It operates in a more controlled fashion and with awareness. Wallach and Lebiere claimed that these two ‘architectural mechanisms’ could account for implicit and explicit learning and, crucially, the interplay between the two systems. They went on to demonstrate how they can account for the findings of a number of previous studies of implicit/explicit learning. The ACT-R model has also proved influential in second language acquisition (SLA) studies (see, e.g. DeKeyser, 2007).

      In the same collection, Hazeltine and Ivry (2003) mustered neuropsychological evidence to support the existence of distinct learning systems. They reviewed studies of the neural activity when people are engaged in sequence learning. They noted that although such activity has been observed in regions across the whole brain, differences in task conditions result in distinct sets of neural regions becoming activated. When the learning task is complex (i.e. involves dual-task conditions) and thus favors implicit learning mechanisms, the medial supplementary motor area, parietal regions and the basal ganglia are involved. In contrast, when the task is simpler (i.e. involving single-task conditions), the prefrontal and premotor cortex are activated.

      The controversy evident in cognitive psychology is mirrored in SLA. The clearest example of this can be found in the critique levelled against Krashen’s (1981) distinction between ‘acquisition’ (the subconscious internalization of grammatical rules that occurs as a result of comprehending input that is slightly beyond the learner’s current knowledge) and ‘learning’ (the conscious formulation of explicit rules of grammar). This was initially subjected to fierce criticism on the grounds that the distinction was not falsifiable. McLaughlin (1978: 21), for example, argued that Krashen failed to provide adequate definitions of what he meant by ‘subconscious’ and ‘conscious’ and ‘provided no way of independently determining whether a given process involves acquisition or learning’. However, McLaughlin’s distaste for the use of ‘conscious’ as a descriptor of the mental activity involved in L2 learning does not reflect mainstream thinking in either cognitive psychology or SLA. Schmidt (1990, 1994, 2001) has shown that consciousness is a useful construct if it can be carefully deconstructed into its several meanings. He distinguished consciousness in terms of intentionality (incidental versus intentional learning), attention (i.e. attended versus unattended learning), awareness (implicit versus explicit learning) and control (automatic versus controlled processing). Schmidt’s work has reinstated the value of ‘consciousness’ for understanding the nature of second language (L2) learning and has had enormous influence on SLA theories and research. It at once acknowledged that Krashen might be right in trying to distinguish implicit and explicit processes and at the same time highlighted the fact that Krashen’s initial distinction was simplistic (e.g. he failed to distinguish consciousness as intentionality, attention, awareness and control).

      The importance of the implicit/explicit distinction for language learning (both first and second) was affirmed in the important collection of papers edited by Nick Ellis (1994). In his introduction, Ellis provided one of the clearest and most convincing statements of the distinction, which I provide in full:

      Some things we just come able to do, like walking, recognizing happiness in others, knowing that th is more common than tg in written English, or making simple utterances in our native language. We have little insight into the nature of the processing involved – we learn to do them implicitly like swallows learn to fly. Other of our abilities depend on knowing how to do them, like multiplication, playing chess, speaking pig Latin, or using a computer programming language. We learn these abilities explicitly like aircraft designers learn aerodynamics. (Ellis, 1994: 1)

      Ellis drew on research in both cognitive psychology and language learning to spell out what he saw as the issues facing researchers. What aspects of an L2 can be learned implicitly? What are the mechanisms of explicit learning available to the learner? How necessary is explicit knowledge for the acquisition of an L2? What is the relationship between explicit and implicit L2 knowledge? How best can instruction aid L2 acquisition? So, rather than dismissing the distinction between implicit and explicit learning/knowledge and taking the lead from Schmidt and Ellis, SLA researchers have focused on trying to identify the processes involved in the two types of learning, how they interact, and how they can be externally manipulated through instruction. Thus, while acknowledging that doubts still remain (especially in cognitive psychology) about the legitimacy of a dual learning system, I am going to assume that a distinction can be made between the implicit and explicit learning of an L2 and between implicit and explicit L2 knowledge.

      Following Schmidt (1994: 20), I will further assume that implicit/explicit learning and implicit/explicit knowledge are ‘related but distinct concepts that need to be separated’. Whereas the former refers to the processes involved in learning, the latter concerns the products of learning. It is possible, for example, that learners will reflect on knowledge that they have acquired implicitly (i.e. without metalinguistic awareness) and thus, subsequently develop an explicit representation of it. Also, it is possible that explicit learning directed at one linguistic feature may result in the incidental implicit learning of some other feature (an issue addressed in Chapter 11). In the case of SLA (less so perhaps in cognitive psychology), implicit and explicit learning have been examined by reference to the kinds of knowledge that result from conditions designed to favor one or other type of learning. That is, there have been relatively few studies that have tried to explore the actual processes involved, although the use of introspective techniques (see, e.g. the account of Leow’s (1997) study below) offers a means of rectifying this gap. In general, studies have sought to infer the kind of learning that has taken place by examining the products of learning. For this reason, this book will focus on ‘knowledge’ rather than ‘learning’.

      Schmidt also argued that learning needs to be distinguished from instruction. It does not follow, for instance, that implicit instruction results in implicit learning or, conversely, that explicit instruction leads to explicit learning. Teachers might hope for such a correlation, but learners have minds of their own and may follow their own inclinations, irrespective of the nature of the instruction they receive (Allwright, 1984). This book is also concerned with the relationship between forms of instruction that can be described as ‘implicit’ or ‘explicit’ and the acquisition of implicit/explicit L2 knowledge.

      In the sections that follow, I will examine how SLA researchers have tackled the three distinctions: (1) implicit/explicit learning, (2) implicit/explicit knowledge and (3) implicit/explicit instruction. This provides a basis for considering the interface position (i.e. the nature of the relationship between implicit and explicit knowledge). Finally, I will provide an overview of the contents of the rest of the book.

      Implicit/Explicit L2 Learning

      As defined above, implicit language learning takes place without either intentionality or awareness. However, there is controversy as to whether any learning is possible without some degree of awareness. This raises the important question of what is meant by ‘awareness’. Schmidt (1994, 2001) distinguished two types of awareness: awareness as noticing (involving perception) and metalinguistic awareness (involving analysis). The former involves conscious attention to ‘surface elements’, whereas the latter involves awareness of the underlying abstract rule that governs particular linguistic phenomena. Schmidt argued that noticing typically involves at least some degree of awareness. Thus, from this perspective, there is no such thing as complete implicit learning and so a better definition of implicit language learning might be ‘learning without any metalinguistic awareness’. That is, the processes responsible for the integration of material into the learner’s interlanguage system and the restructuring this might entail take place autonomously and without conscious control. Other researchers (e.g. Williams, 2005), however, have argued that learning without awareness at the level of noticing is also possible. N. Ellis (2005: 306) has also claimed that ‘the vast majority of our cognitive processing is unconscious’. Thus, there is no consensual definition of implicit learning although all theorists would accept that it excludes metalinguistic awareness.

      Explicit language learning is necessarily a conscious process and is generally intentional as well. It is conscious learning ‘where the individual makes and tests hypotheses in a search for structure’ (N. Ellis, 1994: 1). As Hulstijn (2002: 206) put it, ‘it is a conscious, deliberative process of concept formation and concept linking’.

      The study of implicit and explicit learning in SLA draws heavily on cognitive psychology. The work of Reber (Reber, 1993; Reber et al., 1991) has been seminal in this respect. Reber and colleagues investigated the two types of learning by means of studies involving artificial languages, where groups of participants were either instructed to memorize a set of letter strings generated by the artificial language without the help of any feedback (the implicit learning condition) or to try to figure out the underlying rules of the same letter strings (the explicit learning condition). Following training, both groups completed a judgement test that required them to decide if the strings of letters followed the same rules as the strings they saw during training. They were not forewarned that they would be tested in this way. The main findings of such studies were: (1) there was clear evidence of implicit learning; (2) there was no difference between the test scores of the implicit and explicit learning groups in the case of simple rules, but implicit learning proved more efficient for complex rules; and (3) the test scores of the explicit group demonstrated much greater individual variation than those of the implicit group, reflecting the fact that whereas analytical skills played a role in the former they did not in the latter. However, as we have already seen, the claim that implicit and explicit learning are dissociated has become a matter of controversy among cognitive psychologists. Also, disagreement exists regarding the nature of the knowledge that arises out of implicit learning, with some arguing that it consists of knowledge of fragments or exemplars, and others arguing that it is rule-based.

      Much of the psychological research on implicit learning in language acquisition has followed Reber in employing artificial grammars. Rebuschat (2008), in his review of these studies, suggests that ‘the most important finding to emerge in recent years has been the observation that infants, children and adults can use statistical cues such as transitional probabilities to acquire different aspects of language, including the lexicon, phonology and syntax’. Rebuschat also identifies a number of problems with these studies – many of the studies did not include a measure of awareness, often learners were exposed to the artificial language under conditions that were far from incidental, and the grammars involved were of the phrase-structure rather than fine-state kind.

      In the case of SLA ‘the amount of L2 research narrowly focused on the implicit-explicit distinction is quite limited, not only in the number of studies, but also in duration and in scope of the learning target’ (DeKeyser, 2003: 336). The key issue (as in cognitive psychology) is whether implicit learning of an L2 (i.e. learning without conscious awareness) is possible. A number of studies have addressed this, including several that have examined the effects of enhanced input on language learning. In a series of studies, Williams examined whether learners are able to induce grammatical rules from exposure to input when their attention is focused on meaning (Williams, 1999, 2005; Williams & Lovatt, 2003). The studies showed that learning does take place, that the inductive learning of form (i.e. segmentation) is dissociable from the learning of the functions realized by the forms (i.e. distribution), that learner’ differences in phonological short-term memory influence the extent to which learners are successful in inductive learning, and that language background (i.e. whether learners have prior experience of learning languages) impacts even more strongly on learning. However, Williams’ tests of learning (translation or grammaticality judgement tests) may have favored those learners who attempted to construct explicit rules during the training and thus cannot convincingly demonstrate that implicit learning took place. Indeed, Williams (1999: 38) noted that the learners in this study ‘had high levels of awareness of the product of learning’, although, as he pointed out, awareness of the product of learning does not necessarily imply that conscious analysis occurred while learning. What is needed to resolve this issue are studies that obtain information about the microprocesses involved in the training (learning) phase of such studies.

      One study that has attempted this is Leow (1997). Leow asked beginner learners of L2 Spanish to think aloud as they completed a crossword that exposed them to a number of morphological forms. Learning was measured by means of a multiple choice recognition task and a fill-in-the-blank written production task. The think-aloud protocols were analysed qualitatively to establish to what extent the learners demonstrated meta-awareness in the form of hypothesis-testing and conscious rule-formation. Leow reported that the level of awareness learners demonstrated correlated both with their ability to recognize and produce correct target forms. This study, together with Leow’s (2000) follow-up study, demonstrated that online measures of meta-awareness are related to offline measures of learning, strongly suggesting that the learning that took place in these studies was explicit rather than implicit. DeKeyser (2003: 317), summarizing the results of a number of SLA studies concluded ‘there is very little hard evidence of learning without awareness’. However, N. Ellis (2005) has argued differently on the grounds that studies investigating frequency effects in L2 acquisition have shown that these effects can only be explained if it is assumed that learning without awareness is possible.

      One of the problems of studies that have compared implicit and explicit learning is that the two types of learning have been operationalized and measured in very different ways. A number of studies have shown that learning of some kind, intended by the researcher to be implicit, does take place (Doughty, 1991; Shook, 1994; Gass et al., 2003), but whether or not the learners actually engaged in implicit learning is not demonstrated. Explicit learning is a lot easier to demonstrate – by asking learners to report what they have learned. A number of studies have sought to compare the relative effectiveness of implicit and explicit learning. The general finding is that explicit learning is more effective than implicit learning (N. Ellis, 1993; Rosa & O’Neill, 1999; Gass et al., 2003). No study has shown that implicit learning worked better than explicit learning. However, two studies found no difference between implicit and explicit learning (Doughty, 1991; Shook, 1994). There is also some evidence to suggest that explicit learning is more effective with some linguistic features than others. Robinson (1996) reported that his explicit learners outperformed the implicit learners on a simple structure (subject-verb inversion), but not on a complex structure (pseudo-clefts). Gass et al. (2003) found that their focused condition (which involved explicit attention to form and meaning) proved more effective than the unfocused condition in the case of lexis than it did in the case of morphology or syntax.

      Three studies investigated learners’ awareness of the structures they were learning. Rosa and O’Neill (1999) replicated Leow’s (1997) finding; learners who demonstrated high awareness during learning outperformed those with low awareness. N. Ellis and Robinson both tested the learners’ ability to verbalize the rule they had been learning, but with different results. N. Ellis (1993) found that the most explicit group in his study were able to verbalize the rule, whereas Robinson reported that very few learners in any of his conditions could, although where the simple rule was concerned, the most explicit group (the one receiving an explanation of the rule) outperformed the rest. Finally, Gass et al.’s study raises the possibility that learners’ level of proficiency may mediate the effects of explicit instruction; in this study, the focused condition proved most effective with the low-proficiency learners.

      There is some evidence, therefore, of implicit L2 learning, but much clearer evidence of explicit learning. However, there are two reasons to reserve judgement. First, the treatments in the studies cited above were all of short duration, which arguably creates a bias against implicit learning. Second, the effects of the training were measured by the kinds of tests (e.g. grammaticality judgement tests) that were likely to favor explicit learning.

      Implicit and Explicit L2 Knowledge

      Before we consider the differences between implicit and explicit L2 knowledge, we need to examine what we mean by ‘linguistic knowledge’? There are, broadly speaking, two competing positions. The first, drawing on the work of Chomsky, claims that linguistic knowledge consists of knowledge of the features of a specific language, which are derived from impoverished input (positive evidence) with the help of Universal Grammar (UG). This view of language is innatist and mentalist in orientation, emphasising the contribution of a complex and biologically specified language module in the mind of the learner. The second position, drawing on connectionist theories of language learning, as advanced by cognitive psychologists such as Rumelhart and McClelland (1986), views linguistic knowledge as comprised of an elaborate network of nodes and internode connections of varying strengths that dictate the ease with which specific sequences or ‘rules’ can be accessed. According to this view, then, learning is driven primarily by input and it is necessary to posit only a relatively simple cognitive mechanism (some kind of sensitive pattern detector) that is capable of responding both to positive evidence from the input and to negative evidence available through corrective feedback. These positions are generally presented as oppositional (see Gregg, 2003), but in one important respect, they are in agreement. Both the innatist and connectionist accounts of L2 learning view linguistic competence as consisting primarily of implicit L2 knowledge and see the goal of theory as explaining how this implicit knowledge is acquired. However, they differ in the importance that they attach to explicit knowledge, a point that I will return to later in this chapter.

      In a series of articles (Ellis 1993, 1994, 2004, 2005), I have attempted to identify the criteria that can be used to distinguish implicit and explicit L2 knowledge. I will review these here.

      Implicit knowledge is tacit and intuitive whereas explicit knowledge is conscious

      Thus, it is possible to talk about intuitive and conscious awareness of what is grammatical. For example, faced with a sentence like:

      *The policeman explained Wong the law.

      a learner may know intuitively that there is something ungrammatical and may even be able to identify the part of the sentence where the error occurs, but may have no conscious awareness of the rule that is being broken. Such a learner has implicit but no explicit knowledge of the feature, dative alternation, in question. Another learner, however, may understand that the sentence is ungrammatical because the verb ‘explain’ cannot be followed by an indirect object without ‘to’. A third learner (a linguist perhaps) might know that dative verbs like ‘explain’ that are of Latin origin and verbs like ‘give’ that are of Anglo-Saxon origin perform differently.

      Implicit knowledge is procedural whereas explicit knowledge is declarative

      Implicit knowledge is ‘procedural’ in the sense conferred on this term in the ACT-R cognitive architecture mentioned above. For example, for past tense verbs, learners behave in accordance with a condition-action rule along the lines of ‘if the action to be referred to occurred in the past and is completed, then add -ed to the base form of a verb’. Explicit knowledge is comprised of facts about the L2. This is no different from encyclopedic knowledge of any other kind. I know, declaratively, that the Normans invaded England in 1066. Similarly, I know that verbs like ‘explain’ require an indirect object with ‘to’ and, further, that the indirect object usually follows the direct object. These facts are only loosely connected; they do not constitute a ‘system’ in the same way that the implicit knowledge of proficient L2 users does.

      L2 learners’ procedural rules may or may not be target-like while their declarative rules are often imprecise and inaccurate

      The condition-action rules that learners construct as part of their implicit knowledge may or may not conform to the native speaker’ rules. SLA research has shown that learners typically manifest developmental sequences when they acquire implicit knowledge (see Ellis, 2008). For example, the condition-action rule for the past tense described above would lead to both correct forms (e.g. ‘jumped’) and also overgeneralized forms (e.g. ‘eated’). Such rules are continuously modified during learning. In the case of explicit knowledge, learners’ knowledge is often fuzzy. For example, a learner who responded to the ungrammatical sentence above (*The policeman explained Wong the law) with the comment ‘You can’t use a proper noun after explain’ clearly has some explicit understanding of what makes the sentence ungrammatical, but equally clearly does not have a very accurate notion. Sorace (1985) showed that much of learners’ explicit knowledge is imprecise, but also that it becomes better defined as proficiency increases.

      Implicit knowledge is available through automatic processing whereas explicit knowledge is generally accessible only through controlled processing

      The ‘procedures’ that comprise implicit knowledge can be easily and rapidly accessed in unplanned language use. In contrast, explicit knowledge exists as declarative facts that can only be accessed through the application of attentional processes. One of the widely commented-on uses of explicit knowledge is to edit or monitor production, a process that is only possible in those types of language use that allow learners sufficient time to access the relevant declarative facts. For this reason, explicit knowledge may not be readily available in spontaneous language use where there is little opportunity for careful online planning. It is possible, however, that some learners are able to automatize their explicit knowledge through practice and thus access it for rapid online processing in much the same way as they access implicit knowledge. DeKeyser (2003) suggests that automatized explicit knowledge can be considered ‘functionally equivalent’ to implicit knowledge. Hulstijn (2002: 211), however, is doubtful, arguing that although practice ‘may speed up the execution of algorithmic rules to some extent’, it is still necessary to distinguish the automatization of implicit and explicit knowledge and that what appears to be the automatization of explicit knowledge through practice may in fact entail the separate development of implicit knowledge. N. Ellis (1994) suggests how this might come about; he proposes that sequences produced initially through the application of declarative rules can come to be performed automatically if they are sufficiently practised. That is, it is not the rules themselves that become implicit, but rather the sequences of language that the rules are used to construct.

      Default L2 production relies on implicit knowledge, but difficulty in performing a language task may result in the learner attempting to exploit explicit knowledge

      To borrow terms from sociocultural theory (see Lantolf, 2000), implicit knowledge can be viewed as knowledge that has been fully internalized by the learner (i.e. self-regulation has been achieved). In contrast, explicit knowledge can be viewed as a ‘tool’ that learners use to mediate performance and achieve self-control in linguistically demanding situations. Explicit knowledge manifests itself, for example, through the private speech that learners use to grapple with a problem. When learners are asked to make and justify grammaticality judgements in a think-aloud or dyadic problem-solving task, they typically try to access declarative information to help them do so, if they feel unable or lacking in confidence to make a judgement intuitively (R. Ellis, 1991; Goss et al., 1994).

      Implicit knowledge is only evident in learners’ verbal behavior whereas explicit knowledge is verbalizable

      Implicit knowledge cannot be described as it exists in the form of statistically weighted connections between memory nodes, and its regularities are only manifest in actual language use. This is why learners cannot explain their choice of implicit forms. In contrast, explicit knowledge exists as declarative facts that can be ‘stated’. It is important to recognize, however, that verbalizing a rule or feature need not entail the use of metalanguage. As James and Garrett (1992) pointed out, talking about language can be conducted in a ‘standard received language’ or a ‘nontechnical one’. Thus, the error in the double object sentence above might be explained nontechnically by saying ‘You can’t say explain Wong. You’ve got to say to Wong after explain’. Alternatively, the explanation might call on extensive metalanguage, for example, ‘In the case of dative alternation, there are some verbs like explain that require the indirect object to be realized as a prepositional phrase rather than as a noun phrase’. Although metalanguage is not an essential component of explicit knowledge, it would seem to be closely related.

      There are limits on most learners’ ability to acquire implicit knowledge whereas most explicit knowledge is learnable

      Implicit knowledge is clearly learnable, but there would appear to be age constraints on the ability of learners to fully learn an L2 implicitly given that very few learners achieve native speaker proficiency. There are incremental deficits in our ability to learn implicit knowledge as we age (Birdsong, 2006). In contrast, as Bialystok (1994: 566) pointed out, ‘explicit knowledge can be learned at any age’, and it is not perhaps until old age that learning deficits become apparent. The constraints that exist on learners’ ability to learn explicit facts about a language are of a different order, probably relating to individual differences in the analytical skills needed to memorise, induce or deduce them.

      The learner’s L2 implicit and explicit knowledge systems are distinct

      An issue of considerable importance (and also controversy) is the extent to which a learner’s L2 implicit and L2 explicit systems are distinct. We have already seen that Krashen (1981) viewed the two types of knowledge as entirely separate. Paradis (1994: 397, 2004) also postulated that the two types of knowledge reside in neuranatomically distinct systems. Explicit memory is stored diffusely over large areas of the tertiary cortex and involves the limbic system; implicit memory is ‘linked to the cortical processors through which it was acquired’ and does not involve the limbic system. The two memory systems are also susceptible to selective impairment. Paradis cited evidence to suggest that bilinguals who have learnt the L2 formally (and therefore can be assumed to possess substantial explicit knowledge), may lose the ability to use their L1 in the case of aphasia while maintaining the ability to speak haltingly in the L2.

      Further evidence of the separateness of the two types of knowledge can be found in research based on Ullman’s (2001) dual-mechanism model. Ullman argued that the brain is so organized as to support a mental model consisting of two largely separate systems – the lexicon and the grammar, each with distinct neural bases. He illustrated this model with reference to the processing of morphological forms such as regular and irregular past-tense verb forms. He proposed that procedural memory permits the computation of regular morphological features (e.g. V-ed) by concatenating the phonological forms of the base and an affix (e.g. walk + ed ? walked). In contrast, declarative memory handles irregular forms. Ullman (2001: 39) suggested that ‘for a given morphosyntactic configuration, both systems attempt to compute an appropriately complex form’, but that ‘if a form is found in memory (sang), the rule-based computation is inhibited’.

      Other researchers (e.g. Dienes & Perner, 1999), however, have viewed the distinction between implicit and explicit knowledge as continuous rather than dichotomous. Some evidence for this comes from Ullman himself. Ullman acknowledged that language cannot be so neatly divided into ‘regular’ and ‘irregular’ forms; there are also ‘subregular’ forms (i.e. forms that manifest some degree of regularity without being entirely regular). A good example can be found in the plural forms of German nouns. The default, regular form is -s, but other forms are partially regular (e.g. the -(e)n plural form that occurs predominantly with feminine nouns). Bartke et al. (2005) found that differences in brain responses depended on whether the stimulus was a complete irregular or a subregular form and suggested that the dual-mechanism account proposed by Ullman may need to be modified to incorporate a third processing component to explain how the brain processes subregular forms.

      The view I have advanced in Ellis (2004) is that where representation (but not language use) is concerned we would do better to view the two types of knowledge as dichotomous. Adopting a connectionist account of implicit linguistic knowledge as an elaborate interconnected network, it is not easy to see how knowledge as weighted content (i.e. as a set of neural pathways of greater and lesser strength) can be anything other than separate from knowledge of linguistic facts. This book is predicated on the claim that the two knowledge systems are dissociated.

      L2 performance utilizes a combination of implicit and explicit knowledge

      The problem in determining whether implicit and explicit knowledge stores are separate or linked rests in part, at least, on the problem of determining precisely how learners draw on their linguistic knowledge when performing different language tasks. As Bialystok (1982) pointed out, language use typically involves learners drawing on both systems to construct messages. Furthermore, it is possible that learners will have developed both implicit and explicit knowledge of the same linguistic feature. For example, a learner may have internalized ‘jumped’ as a single item in explicit memory, but may also have developed the procedure for affixing -ed to the base form of the verb in implicit memory – as suggested by Ullman. Thus, the neurological distinctiveness of the two systems will be difficult to detect from simply examining a learner’s linguistic behavior. This is a problem for the measurement of the two types of knowledge that will be considered in Chapter 2. The point at issue now is that irrespective of whether the two systems are psychologically and neurologically distinct, they will never be entirely distinct in performance.

      The following is a summary of the main points that have emerged from this discussion of implicit and explicit L2 knowledge. These points constitute the assumptions that inform the contents of this book.

      (1) Explicit knowledge appears phylogenetically and ontogenetically later than implicit knowledge and it involves different access mechanisms.

      (2) Explicit knowledge is neurologically distinct from implicit knowledge.

      (3) The question of whether the two types of knowledge are to be seen as dichotomous or continuous is a matter of controversy, but neurological evidence and current connectionist models of linguistic knowledge point to a dichotomy.

      (4) The question of the separateness of the representation of the two types of knowledge is independent from the question of whether the processes of implicit and explicit learning are similar or different. This remains a controversial issue. It is likely, however, that learning processes and knowledge types are correlated to some degree at least.

      (5) While there is controversy regarding the interface of explicit and implicit knowledge at the level of learning, there is wide acceptance that they interact at the level of performance.

      A number of studies have examined learners’ implicit and explicit knowledge. These are considered in Chapter 2, where instruments designed to measure the two types of knowledge are described and validated.

      Implicit and Explicit Instruction

      The term

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