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The study’s goal is to study auditory and visual statistical language learning in adult university students. The present work will examine statistical learning using a task developed by Batterink, Reber, Neville, and Paller (2015). This task assesses both implicit learning via a syllable monitoring task, and explicit learning via forced choice post-test. In addition, we will also be using a visual sequence learning task (serial reaction time task) to determine whether participants perform similarly on statistical learning regardless of sensory modality.

Research into second language (L2) pragmatics has addressed a number of learner variables likely to implicate in speech act knowledge. Subscribing to the same line of research, the present study addressed the development and validation of a pragmatic learning strategy inventory (PRALSI), and the relationship between English as a foreign language (EFL) learners' pragmatic learning strategy (PLS) use and their speech act knowledge. A total of 245 Iranian English-major undergraduates, ranging in age from 19 to 31, participated in PRALSI's validation study. Of these, 117 further participated in the second phase of the study to unearth the relationship between PLS use and speech act knowledge, measured through a 24-item written discourse completion test (WDCT). Principal component analysis confirmed the 3-factor structure of PRALSI, comprising implicit, inductive explicit, and deductive explicit strategies. The inventory contains 41 strategies for the learning of three main aspects of pragmatic competence: speech acts, implicature, and conversational routines. Two one-way ANOVAs also showed strategy use, particularly the use of explicit strategies, to be positively correlated with speech act knowledge. The findings reveal the implications of the implicit/explicit learning dichotomy for pragmatic development and strategy use, and the potentially greater advantage explicit strategies offer for pragmatic knowledge.

Research into second language (L2) pragmatics has addressed a number of learner variables likely to implicate in speech act knowledge. Subscribing to the same line of research, the present study addressed the development and validation of a pragmatic learning strategy inventory (PRALSI), and the relationship between English as a foreign language (EFL) learners' pragmatic learning strategy (PLS) use and their speech act knowledge. A total of 245 Iranian English-major undergraduates, ranging in age from 19 to 31, participated in PRALSI's validation study. Of these, 117 further participated in the second phase of the study to unearth the relationship between PLS use and speech act knowledge, measured through a 24-item written discourse completion test (WDCT). Principal component analysis confirmed the 3-factor structure of PRALSI, comprising implicit, inductive explicit, and deductive explicit strategies. The inventory contains 41 strategies for the learning of three main aspects of pragmatic competence: speech acts, implicature, and conversational routines. Two one-way ANOVAs also showed strategy use, particularly the use of explicit strategies, to be positively correlated with speech act knowledge. The findings reveal the implications of the implicit/explicit learning dichotomy for pragmatic development and strategy use, and the potentially greater advantage explicit strategies offer for pragmatic knowledge.

Raw data associated with manuscript "Deferred feedback does not dissociate implicit and explicit category learning systems: Commentary on Smith et al. (2014)"

This paper reports results from two studies conducted to examine word learning among preschool children in group book reading while we developed a scalable method of teaching words during book reading. We sought to identify factors that fostered both depth and breadth of learning by varying the type of information children heard about words while holding exposures constant. We also asked whether prior word knowledge affects children's learning across our different instructional approaches. In Study 1 we evaluated pre-post gains from two types of explicit instruction ("Didactic" and "Conceptual"), an implicit instructional approach ("Review"), and repeated "Exposure." For all three instructed conditions growth in receptive knowledge (our measure of breadth) was statistically equivalent when compared to control (d?=?0.43) and exposure words (d?=?0.41). In Study 2, words were taught using an augmented explicit approach and through repeated exposure. Moderate and statistically significant growth in receptive knowledge was found when comparing instructed to control words (d?=?0.48) and large effects were found with an expressive task measure of depth of knowledge (d?=?1.19). There also was evidence of learning from exposure. Children's vocabulary knowledge moderated learning gains. In Study 1 children with limited knowledge of vocabulary (0.75 SD below the group mean) learned fewer words than others. In Study 2, pre-test vocabulary knowledge moderated gains on the expressive measure for directly taught words and gains on the receptive measure for words taught through exposure. Thus, when words were intentionally taught, all children except those with the weakest initial knowledge acquired the initial lexical representations captured by the receptive measure at a similar rate. Those with stronger vocabulary more quickly acquired initial representations from exposure alone and deeper knowledge when they received intentional instruction. We conclude that teachers can build depth and breadth of vocabulary knowledge by combining intentional instruction of target words with repeated use of varied words by reading books multiple times and instructional comments that include use of novel words.

This paper reports results from two studies conducted to examine word learning among preschool children in group book reading while we developed a scalable method of teaching words during book reading. We sought to identify factors that fostered both depth and breadth of learning by varying the type of information children heard about words while holding exposures constant. We also asked whether prior word knowledge affects children's learning across our different instructional approaches. In Study 1 we evaluated pre-post gains from two types of explicit instruction ("Didactic" and "Conceptual"), an implicit instructional approach ("Review"), and repeated "Exposure." For all three instructed conditions growth in receptive knowledge (our measure of breadth) was statistically equivalent when compared to control (d?=?0.43) and exposure words (d?=?0.41). In Study 2, words were taught using an augmented explicit approach and through repeated exposure. Moderate and statistically significant growth in receptive knowledge was found when comparing instructed to control words (d?=?0.48) and large effects were found with an expressive task measure of depth of knowledge (d?=?1.19). There also was evidence of learning from exposure. Children's vocabulary knowledge moderated learning gains. In Study 1 children with limited knowledge of vocabulary (0.75 SD below the group mean) learned fewer words than others. In Study 2, pre-test vocabulary knowledge moderated gains on the expressive measure for directly taught words and gains on the receptive measure for words taught through exposure. Thus, when words were intentionally taught, all children except those with the weakest initial knowledge acquired the initial lexical representations captured by the receptive measure at a similar rate. Those with stronger vocabulary more quickly acquired initial representations from exposure alone and deeper knowledge when they received intentional instruction. We conclude that teachers can build depth and breadth of vocabulary knowledge by combining intentional instruction of target words with repeated use of varied words by reading books multiple times and instructional comments that include use of novel words.

Learning a language entails the acquisition of a set of structures and the formation of meaningful representations. Although explicit instruction and awareness play an important role in adult non-native (L2) language learning (Goo et al., 2015), empirical research has shown that mere exposure to the L2 is often enough for learners to implicitly pick up the patterns and regularities and to start forming linguistic representations (Williams & Rebuschat, 2022). To notice those patterns and regularities and start speaking a language, the learner must develop a set of perceptual and production abilities. While in child language acquisition, the importance of perception in shaping the ability to produce new sounds is undisputed (Werker & Tees, 2002), in adult L2 acquisition, that connection is not so clear, especially due to a pre-existing underlying system - that of the L1(s) - that may interfere in the learning process. Despite a general agreement that there is a link between perception and production in L2 speech learning, there is conflicting evidence about the nature and directionality of that relationship: On the one hand, studies show that perception improves production (Flege, 1995; Thorin et al., 2018) and, hence, the better a listener perceives distinct sounds in an L2, the better they will produce them. According to this view, it is either assumed that the two speech modalities are related, but their interaction also depends on other factors such as age of acquisition, language use, individual differences or general learning mechanisms (Baker & Trofimovich, 2006), or that they share processes, representations and cognitive resources during an overlapping learning process (Best & Tyler, 2007; Flege, 1995; Flege & Bohn, 2021). On the other hand, empirical evidence suggests that it is not always the case that production and perception have an intertwined relationship: Good production abilities can exist without fine-tuned perception (Darcy & Krüger, 2012) and, conversely, speakers can easily perceive different L2 speech sounds without being able to produce them. A good example is that of native English speakers that can easily discriminate the Spanish contrast /r/-/ɾ/ but have difficulty with its production (Derwing & Munro, 2015). Interestingly, recent research has shown that production may even play an antagonistic role in perception, since the learning performance of participants trained in production and perception was poorer than the performance of participants trained in perception alone (Baese-Berk, 2019). This is due, the authors suggest, to a slower process for production learning and a higher cognitive load implied in the dual task of perceiving and producing speech sounds. Research on L2 speech learning (e.g., Baese-Berk, 2019; Vlahou et al. 2011) suggests that implicit perception training is successful in establishing novel, non-native phonological categories, and that implicit instruction can be just as effective as explicit instruction in L2 segmental acquisition (Valada et al., 2023). However, a previous study conducted with inexperienced native English speakers has shown a null effect of a short implicit perceptual training with Portuguese /e/-/ɛ/ contrasts (Correia et al., 2023). Therefore, more research is necessary to better understand what can and cannot be acquired without more explicit types of intervention. The present study contributes to this important line of enquiry by investigating if (and how) implicit and explicit phonetic training with different modalities is effective in learning novel phonemic contrasts. References: Anderson, J., Mak, L., Keyvani-Chahi, A., Bialystok, E. (2018). Language and Social Background Questionnaire-Revised (LSBQ) [Database record]. APA PsycTests. Anwyl-Irvine, A.L., Massonié J., Flitton, A., Kirkham, N.Z., Evershed, J.K. (2019). Gorilla in our midst: an online behavioural experiment builder. Behavior Research Methods. Baese-Berk, M. M. (2019). Interactions between speech perception and production during learning of novel phonemic categories. Attention, Perception, & Psychophysics, 81(4), 981-1005. Baker, W. & Trofimovich, P. (2006). Perceptual paths to accurate production of L2 vowels: The role of individual differences. International Review of Applied Linguistics in Language Teaching, 44(3), 231-250. Best, C. & Tyler, M. (2007). Nonnative and second-language speech perception: Commonalities and complementarities. In M.J. Munro & O.-S. Bohn (Eds.). Language experience in second language speech learning: In honor of James Emil Flege (pp.13-34). John Benjamins. Correia, S., Rato, A., Fernandes, J. D., Ge, Y., Kachlicka, M., Saito, K, & Rebuschat, P. (2023). Perceptual training in Non-Native/L2 Speech Learning – Evidence from Portuguese. Talk given at the Vienna Workshops on Portuguese Linguistics. Universität Wien. Nov. 16-17. Darcy, I., & Krüger, F. (2012). Vowel perception and production in Turkish children acquiring L2 German. Journal of Phonetics, 40(4), 568-581. Derwing, T. & Munro, M. (2015). Chapter 4 - Pronunciation errors and errors gravity. Pronunciation Fundamentals. Evidence-based Perspectives for L2 Teaching and Research (pp. 55-76). John Benjamins. Flege, E. & Bohn, O.-S. (2021). The Revised Speech-Learning Model (SLM-r). In R. Wayland (Ed.). Second Language Speech Learning (pp. 3-83). Cambridge University Press. Flege, J. E. (1995). Second-language speech learning: Theory, findings, and problems. In W. Strange (Ed.), Speech perception and linguistic experience: Issue in cross-language research (pp. 233–277). York Press. Goo, J., Gisela, G., Yilmaz, Y. & Novella, M. (2015). Implicit and explicit instruction in L2 learning. In P. Rebuschat (Ed.). Implicit and Explicit Learning of Language (pp. 443–482). John Benjamins. Saito, K. & Tierney, A. (2022). Domain-general auditory processing as a conceptual and measurement framework for second language speech learning aptitude: A test-retest reliability study. Studies in Second Language Acquisition. 1-25. Thorin, J., Sadakata, M., Desain, P. & McQueen, J. (2018). Perception and production in interaction during non-native speech category learning. The Journal of the Acoustical Society of America, 144(1), 92-103. Valada, F., De Clerq, B., Correia, S. & Housen, A.(2023). The effects and the effectiveness of different types of instruction on the acquisition of L2 phonology: a meta-analysis. Talk given at EuroSLA32. Birmingham, UK. Aug. 30- Sept 2. Vlahou, E. L., Protopapas, A., Seitz, A. R (2012). Implicit training of nonnative speech stimuli. Journal of Experimental Psychology: General, 141: 1–19.  Werker, J. F., & Tees, R. C. (2002). Cross-language speech perception: Evidence for perceptual reorganization during the first year of life. Infant Behavior & Development, 25(1), 121–133. Williams, J. N. & Rebuschat, P. (2022). Implicit learning and SLA: A cognitive psychology perspective. In A. Godfroid and H. Hopp (Eds), The Routledge Handbook of Second Language Acquisition and Psycholinguistics. Routledge.

Research has shown that teaching second language (L2) learning strategies explicitly promotes an increase in strategy use and in oral proficiency. Consequently, a checklist based on the six types of strategies from Oxford's taxonomy (1990) was created to analyze strategic instruction in the most common textbooks used in the last year of Higher Secondary Education in Spain. The study considered whether there was explicit strategy instruction and its location (within the units [Internal] or in other sections [External]) in course books, and what specific strategies were explicitly taught for the two oral skills, listening and speaking. Results showed, first, that there was explicit internal and external instruction of L2 learning strategies both for listening and speaking, but not in all the books; second, that there was significantly more implicit use than explicit instruction, and less explicit instruction in the units of the textbooks than in specific extra sections in the textbook or in support material; and finally, that internal explicit instruction of strategies remains very limited; and thus, L2 learning strategy instruction, competence and use may not be sufficiently encouraged in those textbooks.

This article is from Frontiers in Computational Neuroscience , volume 7 . Abstract It has been reported recently that while general sequence learning across ages conforms to the typical inverted-U shape pattern, with best performance in early adulthood, surprisingly, the basic ability of picking up in an implicit manner triplets that occur with high vs. low probability in the sequence is best before 12 years of age and it significantly weakens afterwards. Based on these findings, it has been hypothesized that the cognitively controlled processes coming online at around 12 are useful for more targeted explicit learning at the cost of becoming relatively less sensitive to raw probabilities of events. To test this hypothesis, we collected data in a sequence learning task using probabilistic sequences in five age groups from 11 to 39 years of age (N = 288), replicating the original implicit learning paradigm in an explicit task setting where subjects were guided to find repeating sequences. We found that in contrast to the implicit results, performance with the high- vs. low-probability triplets was at the same level in all age groups when subjects sought patterns in the sequence explicitly. Importantly, measurements of explicit knowledge about the identity of the sequences revealed a significant increase in ability to explicitly access the true sequences exactly around the age where the earlier study found the significant drop in ability to learn implicitly raw probabilities. These findings support the conjecture that the gradually increasing involvement of more complex internal models optimizes our skill learning abilities by compensating for the performance loss due to down-weighting the raw probabilities of the sensory input, while expanding our ability to acquire more sophisticated skills.

This article is from Frontiers in Computational Neuroscience , volume 7 . Abstract It has been reported recently that while general sequence learning across ages conforms to the typical inverted-U shape pattern, with best performance in early adulthood, surprisingly, the basic ability of picking up in an implicit manner triplets that occur with high vs. low probability in the sequence is best before 12 years of age and it significantly weakens afterwards. Based on these findings, it has been hypothesized that the cognitively controlled processes coming online at around 12 are useful for more targeted explicit learning at the cost of becoming relatively less sensitive to raw probabilities of events. To test this hypothesis, we collected data in a sequence learning task using probabilistic sequences in five age groups from 11 to 39 years of age (N = 288), replicating the original implicit learning paradigm in an explicit task setting where subjects were guided to find repeating sequences. We found that in contrast to the implicit results, performance with the high- vs. low-probability triplets was at the same level in all age groups when subjects sought patterns in the sequence explicitly. Importantly, measurements of explicit knowledge about the identity of the sequences revealed a significant increase in ability to explicitly access the true sequences exactly around the age where the earlier study found the significant drop in ability to learn implicitly raw probabilities. These findings support the conjecture that the gradually increasing involvement of more complex internal models optimizes our skill learning abilities by compensating for the performance loss due to down-weighting the raw probabilities of the sensory input, while expanding our ability to acquire more sophisticated skills.

This article is from Frontiers in Computational Neuroscience , volume 7 . Abstract It has been reported recently that while general sequence learning across ages conforms to the typical inverted-U shape pattern, with best performance in early adulthood, surprisingly, the basic ability of picking up in an implicit manner triplets that occur with high vs. low probability in the sequence is best before 12 years of age and it significantly weakens afterwards. Based on these findings, it has been hypothesized that the cognitively controlled processes coming online at around 12 are useful for more targeted explicit learning at the cost of becoming relatively less sensitive to raw probabilities of events. To test this hypothesis, we collected data in a sequence learning task using probabilistic sequences in five age groups from 11 to 39 years of age (N = 288), replicating the original implicit learning paradigm in an explicit task setting where subjects were guided to find repeating sequences. We found that in contrast to the implicit results, performance with the high- vs. low-probability triplets was at the same level in all age groups when subjects sought patterns in the sequence explicitly. Importantly, measurements of explicit knowledge about the identity of the sequences revealed a significant increase in ability to explicitly access the true sequences exactly around the age where the earlier study found the significant drop in ability to learn implicitly raw probabilities. These findings support the conjecture that the gradually increasing involvement of more complex internal models optimizes our skill learning abilities by compensating for the performance loss due to down-weighting the raw probabilities of the sensory input, while expanding our ability to acquire more sophisticated skills.

Our project will evaluate the effects of hand dominance and handedness on motor adaptation - the process of reducing motor errors through feedback and practice. The impact of handedness on motor adaptation is poorly understood, as no studies have directly compared left- and right-handed individuals. Moreover, the effect of hand dominance on adaptation remains controversial: some studies report greater adaptation in the dominant hand (Duff and Sainburg 2007), others find no significant difference (Kirby et al. 2019), and still others show the opposite pattern (Carroll, Poh, and de Rugy 2014). We hypothesized that this inconsistent picture can be attributed to at least two factors. First, previous studies investigating the effect of dominance and handedness tend to be severely underpowered. Second, the learning assays used in these experiments tend to reflect, to varying degrees, the operation of multiple learning processes, making it difficult to draw inferences across studies. To address these gaps, we will take a two-pronged approach. First, we will perform a comprehensive meta-analysis of 23 studies, encompassing data from over 200 participants, to assess the impact of handedness and hand dominance on motor adaptation. Second, we will empirically evaluate how hand dominance and handedness influence motor adaptation and interlimb transfer in both left- and right-handers, using psychophysical tasks specifically designed to disentangle explicit and implicit adaptation.

This article is from Advances in Cognitive Psychology , volume 8 . Abstract Accounts of statistical learning, both implicit and explicit, often invoke predictive processes as central to learning, yet practically all experiments employ non-predictive measures during training. We argue that the common theoretical assumption of anticipation and prediction needs clearer, more direct evidence for it during learning. We offer a novel experimental context to explore prediction, and report results from a simple sequential learning task designed to promote predictive behaviors in participants as they responded to a short sequence of simple stimulus events. Predictive tendencies in participants were measured using their computer mouse, the trajectories of which served as a means of tapping into predictive behavior while participants were exposed to very short and simple sequences of events. A total of 143 participants were randomly assigned to stimulus sequences along a continuum of regularity. Analysis of computer-mouse trajectories revealed that (a) participants almost always anticipate events in some manner, (b) participants exhibit two stable patterns of behavior, either reacting to vs. predicting future events, (c) the extent to which participants predict relates to performance on a recall test, and (d) explicit reports of perceiving patterns in the brief sequence correlates with extent of prediction. We end with a discussion of implicit and explicit statistical learning and of the role prediction may play in both kinds of learning.

This article is from PLoS ONE , volume 9 . Abstract Background: Motor learning is central to domains such as sports and rehabilitation; however, often terminologies are insufficiently uniform to allow effective sharing of experience or translation of knowledge. A study using a Delphi technique was conducted to ascertain level of agreement between experts from different motor learning domains (i.e., therapists, coaches, researchers) with respect to definitions and descriptions of a fundamental conceptual distinction within motor learning, namely implicit and explicit motor learning. Methods: A Delphi technique was embedded in multiple rounds of a survey designed to collect and aggregate informed opinions of 49 international respondents with expertise related to motor learning. The survey was administered via an online survey program and accompanied by feedback after each round. Consensus was considered to be reached if ≥70% of the experts agreed on a topic. Results: Consensus was reached with respect to definitions of implicit and explicit motor learning, and seven common primary intervention strategies were identified in the context of implicit and explicit motor learning. Consensus was not reached with respect to whether the strategies promote implicit or explicit forms of learning. Discussion: The definitions and descriptions agreed upon may aid translation and transfer of knowledge between domains in the field of motor learning. Empirical and clinical research is required to confirm the accuracy of the definitions and to explore the feasibility of the strategies that were identified in research, everyday practice and education.

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The focus of the present study was to evaluate aspects of the learning process that aid expertise development for aircraft pilots. Research in learning strategies has recently focused on implicit and explicit learning to determine if it is more important to focus on conscious facts or unconscious procedural performance during the learning process. Of particular concern for the current investigation was to determine if explicit knowledge is necessary for automatic performance of complex cognitive motor skills such as flying. Several recent studies have proposed that explicit knowledge may be detrimental for performance under the cognitive loads of stress. This study therefore examined groups of novice pilots who learned how to fly a flight simulator either implicitly or explicitly to see what effect the learning process had on performance during stress and a subsequent retention test. Participant scanning patterns were also analyzed using an infrared eye tracker to determine which group would exhibit superior attentional control.

Study exploring the impact of different instructional contexts on learning a symbolic math task.

This work advances basic research in the areas of learning and training. One product is a conceptual framework, which addresses the ways explicit and implicit knowledge interact to produce skills. This framework suggests that human performance may be controlled by either a subconceptual knowledge base (the implicit mode) or application of a symbolic conceptual model (the explicit mode). A computational cognitive architecture, CLARION, significantly different from other existing cognitive architectures, is developed in this work to capture a range of data related to the interaction. It helps us to explain (and eventually to predict) training and learning processes. The results of the experiments support the theory of the interactions of implicit and explicit learning processes during skill acquisition. The outcomes (data, models, and theories) provide a more detailed, clearer and more comprehensive perspective on skill learning.

Two universally accepted approaches to grammar instruction are explicit and implicit teaching of the grammar. Both approaches have their own strengths and limitations. Educators may face a dilemma whether to teach grammar explicitly or implicitly. This paper aims to provide insights into the educators' beliefs towards grammar teaching in Malaysian Higher Learning Institutions, and the sources of the held beliefs. Data were generated through semi-structured interviews with five educators from several private colleges located in peninsular Malaysia. Data analysis reveals that a majority of the respondents preferred grammar to be taught explicitly in their ESL classrooms; nevertheless they viewed implicit instruction as necessary when conforming to students' needs. The sources of the held beliefs are educators' experience as well as the institutional requirement. This paper draws our attention to the role of educators as an eclectic teaching practitioner who are able to apply a suitable grammar instruction according to learners' needs. It is hoped that this study will contribute to the growth of literature on grammar teaching and learning especially in Malaysian ESL classrooms.

In most problem-solving activities, feedback is received at the end of an action sequence. This creates a credit-assignment problem where the learner must associate the feedback with earlier actions, and the interdependencies of actions require the learner to either remember past choices of actions (internal state information) or rely on external cues in the environment (external state information) to select the right actions. We investigated the nature of explicit and implicit learning processes in the credit-assignment problem using a probabilistic sequential choice task with and without external state information. We found that when explicit memory encoding was dominant, subjects were faster to select the better option in their first choices than in the last choices; when implicit reinforcement learning was dominant subjects were faster to select the better option in their last choices than in their first choices. However, implicit reinforcement learning was only successful when distinct external state information was available. The results suggest the nature of learning in credit assignment: an explicit memory encoding process that keeps track of internal state information and a reinforcement-learning process that uses state information to propagate reinforcement backwards to previous choices. However, the implicit reinforcement learning process is effective only when the valences can be attributed to the appropriate states in the system either internally generated states in the cognitive system or externally presented stimuli in the environment.