scholarly journals Convergent and Distinct Effects of Multisensory Combination on Statistical Learning Using a Computer Glove

2021 ◽  
Vol 11 ◽  
Author(s):  
Christopher R. Madan ◽  
Anthony Singhal
Keyword(s):  
Statistical Learning ◽  
Visual Cues ◽  
Explicit Knowledge ◽  
Reaction Time Task ◽  
Musical Instrument ◽  
Implicit Knowledge ◽  
Auditory Cues ◽  
Motor Movements ◽  
Explicit And Implicit Knowledge ◽  
Single Modality

Learning to play a musical instrument involves mapping visual + auditory cues to motor movements and anticipating transitions. Inspired by the serial reaction time task and artificial grammar learning, we investigated explicit and implicit knowledge of statistical learning in a sensorimotor task. Using a between-subjects design with four groups, one group of participants were provided with visual cues and followed along by tapping the corresponding fingertip to their thumb, while using a computer glove. Another group additionally received accompanying auditory tones; the final two groups received sensory (visual or visual + auditory) cues but did not provide a motor response—all together following a 2 × 2 design. Implicit knowledge was measured by response time, whereas explicit knowledge was assessed using probe tests. Findings indicate that explicit knowledge was best with only the single modality, but implicit knowledge was best when all three modalities were involved.

scholarly journals Convergent and distinct effects of multisensory combination on statistical learning using a computer glove

2018 ◽  
Author(s):  
Christopher R Madan ◽  
Anthony Singhal
Keyword(s):  
Implicit Learning ◽  
Statistical Learning ◽  
Visual Cues ◽  
Reaction Time Task ◽  
Musical Instrument ◽  
Explicit Learning ◽  
Auditory Cues ◽  
Serial Reaction ◽  
Motor Movements ◽  
Single Modality

Learning to play a musical instrument involves mapping visual+auditory cues to motor movements and anticipating transitions. Inspired by the serial reaction time task and artificial grammar learning, we investigated explicit and implicit statistical learning in a sensorimotor task. Using a between-subjects design with four groups, one group of participants were provided with visual cues and followed along by tapping the corresponding fingertip to their thumb, while using a computer glove. The remaining groups either additionally received accompanying auditory tones or received sensory cues but did not provide a motor response, following a 2×2 design. Implicit learning was measured by response time, whereas explicit learning was assessed using probe tests. Findings indicate that explicit statistical learning was best with only the single modality, but implicit learning was best when all three modalities were involved.

scholarly journals THE CONTRIBUTIONS OF IMPLICIT-STATISTICAL LEARNING APTITUDE TO IMPLICIT SECOND-LANGUAGE KNOWLEDGE

2021 ◽  
pp. 1-29
Author(s):  
Aline Godfroid ◽  
Kathy MinHye Kim
Keyword(s):  
Second Language ◽  
Reaction Time ◽  
Language Learning ◽  
Statistical Learning ◽  
Structural Equation ◽  
Reaction Time Task ◽  
Implicit Knowledge ◽  
Equation Modeling ◽  
Language Tests ◽  
Language Knowledge

Abstract This study addresses the role of domain-general mechanisms in second-language learning and knowledge using an individual differences approach. We examine the predictive validity of implicit-statistical learning aptitude for implicit second-language knowledge. Participants (n = 131) completed a battery of four aptitude measures and nine grammar tests. Structural equation modeling revealed that only the alternating serial reaction time task (a measure of implicit-statistical learning aptitude) significantly predicted learners’ performance on timed, accuracy-based language tests, but not their performance on reaction-time measures. These results inform ongoing debates about the nature of implicit knowledge in SLA: they lend support to the validity of timed, accuracy-based language tests as measures of implicit knowledge. Auditory and visual statistical learning were correlated with medium strength, while the remaining implicit-statistical learning aptitude measures were not correlated, highlighting the multicomponential nature of implicit-statistical learning aptitude and the corresponding need for a multitest approach to assess its different facets.

CONFLICTING EVIDENCE OF EXPLICIT AND IMPLICIT KNOWLEDGE FROM OBJECTIVE AND SUBJECTIVE MEASURES

2019 ◽  
Vol 42 (2) ◽  
pp. 359-382
Author(s):  
Ryo Maie ◽  
Robert M. DeKeyser
Keyword(s):  
Explicit Knowledge ◽  
Implicit Knowledge ◽  
English Speakers ◽  
Subjective Measures ◽  
Full Account ◽  
Monitoring Task ◽  
Grammaticality Judgment ◽  
Conflicting Evidence ◽  
Incidental Exposure ◽  
Explicit And Implicit Knowledge

AbstractThis study is the first to compare objective and subjective measures of explicit and implicit knowledge under learning from incidental exposure. An experiment was conducted, during which L1 English speakers were trained on a semiartificial language, Japlish. A measure of explicit knowledge and a recently proposed measure of implicit knowledge (i.e., an untimed auditory grammaticality judgment and a word-monitoring task) were applied to gauge the two types of knowledge at two testing sessions, and their results were compared with those of subjective measures of awareness. Results revealed clear discrepancies between the two measurement approaches in terms of their sensitivity. In particular, while the subjective measures varied in identifying explicit and implicit knowledge of various Japlish constructions, the objective measures indicated that most of the knowledge was explicit, and development of implicit knowledge (measured by the word-monitoring task) was minimal, only manifested in detecting a case-missing violation at the delayed posttest. The results are discussed with reference to the current literature on explicit and implicit learning and knowledge, and it is concluded that the criterion of (un)awareness might not be by itself sufficient to provide a full account of L2 knowledge developed under incidental conditions.

Temporal Stability of Implicit Sequence Knowledge

2015 ◽  
Vol 62 (4) ◽  
pp. 240-253 ◽  
Author(s):  
Ricardo Tamayo ◽  
Peter A. Frensch
Keyword(s):  
Explicit Knowledge ◽  
Common Knowledge ◽  
Random Noise ◽  
Temporal Stability ◽  
Implicit Knowledge ◽  
Single System ◽  
Artificial Grammars ◽  
Implicit And Explicit ◽  
Explicit And Implicit Knowledge ◽  
Best Fit

Abstract. Previous research has shown that explicit and implicit knowledge of artificial grammars may decay at different rates (e.g., Tamayo & Frensch, 2007 ; Tunney, 2003 ). We extend these findings to sequential regularities embedded in serial reaction time (SRT) tasks. We compared the forgetting patterns of implicit and explicit knowledge after a retention interval of 7 days without rehearsal. Explicit knowledge decayed after 7 days, whereas implicit knowledge was retained. These data were modeled according to the assumptions involved in the single-system model suggested by Shanks, Wilkinson, and Channon (2003) . The best fit for the model was obtained by modifying the parameters related to (a) the common knowledge-strength variable for implicit and explicit knowledge, and (b) reliability of the explicit test. We interpret these dissociations as a boundary condition for single-system models that assume constant random noise to explain dissociations in the forgetting patterns of implicit and explicit sequential knowledge.

The significance of implicit knowledge for learning and teaching chemistry

2014 ◽  
Vol 15 (4) ◽  
pp. 447-461 ◽  
Author(s):  
Keith S. Taber
Keyword(s):  
Education Research ◽  
Physics Education ◽  
Explicit Knowledge ◽  
Good Deal ◽  
Implicit Knowledge ◽  
Student Thinking ◽  
Alternative Conceptions ◽  
Chemistry Learning ◽  
Teaching Research ◽  
Explicit And Implicit Knowledge

This article discusses the nature of implicit knowledge, something which is considered to be highly influential in learning. The notion of implicit knowledge is important in conceptualising studies exploring student thinking and learning in chemistry, and in considering how the results of such studies should be interpreted to inform teaching. Research on cognition suggests that a good deal of the knowledge that people call upon in interpreting their world and making decisions is not accessible to conscious introspection. This has consequences in chemistry education research as individuals are not able to directly report implicit knowledge – so it can only be elicited indirectly. A corollary is that the results of many research studies reporting student conceptions in chemistry need to be understood as reflecting – at least in part – cognition drawing upon implicit knowledge. The distinction between explicit and implicit knowledge is an important one in understanding chemistry learning given that implicit knowledge operates automatically in cognition without deliberation. This suggests that strategies designed to counter students' alternative conceptions may need to be quite different when such ideas derive from the operation of implicit knowledge rather than students' explicit knowledge. The importance of implicit knowledge elements sometimes labelled as p-prims has been widely recognised in physics education research, and it is argued here that research into student thinking and learning in chemistry needs to take more account of the distinction between explicit and implicit knowledge elements if it is to better inform teaching. Research is needed to understand the repertoire and action of implicit knowledge elements active in chemistry learning. This will then facilitate the design of studies to test out teaching approaches that can recruit the most suitable implicit knowledge elements to support learning of canonical chemical ideas.

scholarly journals Development of an explicit and implicit knowledge identification tool for the analysis of the decision-making process of traditional Asian medicine doctors

2021 ◽  
Author(s):  
Musun Park ◽  
Min Hee Kim ◽  
So-young Park ◽  
Minseo Kang ◽  
Inhwa Choi ◽  
...  
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Explicit Knowledge ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Implicit Knowledge ◽  
Decision Making Process ◽  
Analysis Tool ◽  
Asian Medicine ◽  
Explicit And Implicit Knowledge

Background and objectives: While pattern identification (PI) is an essential process for diagnosis and treatment in traditional Asian medicine (TAM), it is difficult to objectify since it relies heavily on implicit knowledge. Here, we propose a machine learning-based analysis tool to objectify and evaluate the clinical decision-making process of PI in terms of explicit and implicit knowledge. Methods: Clinical data for the development of the analysis tool were collected using a questionnaire administered to allergic rhinitis (AR) patients and the diagnosis and prescription results of TAM doctors based on the completed AR questionnaires. Explicit knowledge and implicit knowledge were defined based on the explicit and implicit importance scores of the AR questionnaire, which were obtained through doctors′ explicit scoring and feature evaluations of machine learning models, respectively. The analysis tool consists of eight evaluation indicators used to compare, analyze and visualize the explicit and implicit knowledge of TAM doctors. Results: The analysis results for 8 doctors showed that our tool could successfully identify explicit and implicit knowledge in the PI process. We also conducted a postquestionnaire study with the doctors who participated to evaluate the applicability of our tool. Conclusions: This study proposed a tool to evaluate and compare decision-making processes of TAM doctors in terms of their explicit and implicit knowledge. We identified the differences between doctors′ own explicit and implicit knowledge and the differences among TAM doctors. The proposed tool would be helpful for the clinical standardization of TAM, doctors′ own clinical practice, and intern/resident training.

Verbal working memory as a predictor of explicit and implicit knowledge of English passive voice

2019 ◽  
Vol 2 (2) ◽  
pp. 258-280
Author(s):  
Mirosław Pawlak ◽  
Adriana Biedroń
Keyword(s):  
Working Memory ◽  
Second Language Acquisition ◽  
Explicit Knowledge ◽  
Verbal Working Memory ◽  
Implicit Knowledge ◽  
Target Language ◽  
Passive Voice ◽  
Empirical Inquiry ◽  
Communication Task ◽  
Explicit And Implicit Knowledge

Abstract While there is copious evidence concerning the effectiveness of different instructional options in teaching grammar (e.g., Nassaji, 2017; Pawlak, 2017), less is known about the extent to which the contribution of pedagogical intervention is mediated by individual factors. The same can be said about the product of instructed but also uninstructed second language acquisition, that is the knowledge of target language grammar. The paper attempts to shed light on one such variable, that is working memory, which has recently been an object of intensive empirical inquiry (e.g., Li, 2017; Wen, Biedroń, & Skehan, 2016). It reports the results of a study that investigated the role of verbal working memory in the development of explicit and implicit knowledge of the English passive voice. Participants were 156 Polish university students enrolled in a three-year BA program in English. The data on verbal working memory were collected by means of the Polish Listening Span Test (PLSPAN), developed by Zychowicz, Biedroń and Pawlak (2017). Explicit knowledge was tapped by means of an untimed grammatically judgment test, which focused on reception, and a traditional grammar test, which targeted production. Implicit knowledge was tapped through a timed grammaticality judgment test for reception and a focused communication task (Ellis, 2003) for production. Correlational analysis demonstrated that verbal working memory was a weak predictor of explicit productive and receptive knowledge but not implicit knowledge.

DIFFERENTIAL EFFECTS OF EXPLICIT INSTRUCTION ON SECOND LANGUAGE ACQUISITION.Rick de Graaff. Leiden: Holland Institute of Generative Linguistics, 1997. Pp. 234. NLG 40 paper.

2000 ◽  
Vol 22 (1) ◽  
pp. 117-118
Author(s):  
Irit Kupferberg
Keyword(s):  
Explicit Knowledge ◽  
Native Speakers ◽  
Implicit Knowledge ◽  
L2 Acquisition ◽  
Interface Position ◽  
Generative Linguistics ◽  
Facilitative Role ◽  
Self Instruction ◽  
Explicit And Implicit Knowledge ◽  
Intervening Factors

Is there an interface between explicit and implicit knowledge in L2 acquisition? Rick de Graaff's doctoral dissertation tests this question in an experimental study from a weak interface position. This position indicates that explicit knowledge has a facilitative role in the acquisition of implicit knowledge when it engages the attention of learners and makes them notice input features (Schmidt, 1990). De Graaff studies the effect of explicit computer-aided self-instruction on the acquisition of morphosyntax in Experanto (an artificial language, based on Zamenhoff's Esperanto) and Spanish (as a foreign language) by adult native speakers of Dutch. Acquisition is tested in interaction with five intervening factors that constitute a controlled linguistic, psychological, and pedagogic context (i.e., complexity of structures, rule-based learning in syntax and exemplar-based learning in morphology, familiarity with the structures, availability of explicit knowledge, and learners' aptitude). Experanto is chosen to control for the influence of previous knowledge and contact outside class, and Spanish is chosen to make the results more generalizable.

Implicit Learning–Explicit Knowing: A Role for Sleep in Memory System Interaction

2006 ◽  
Vol 18 (3) ◽  
pp. 311-319 ◽  
Author(s):  
Stefan Fischer ◽  
Spyridon Drosopoulos ◽  
Jim Tsen ◽  
Jan Born
Keyword(s):  
Reaction Time ◽  
Retention Interval ◽  
Explicit Memory ◽  
Explicit Knowledge ◽  
Reaction Times ◽  
Reaction Time Task ◽  
Memory Systems ◽  
Implicit Knowledge ◽  
Generation Task ◽  
Implicit And Explicit Memory

There is evidence that sleep supports the enhancement of implicit as well as explicit memories (i.e., two memory systems that during learning normally appear to act together). Here, employing a serial reaction time task (SRTT) paradigm, we examined the question whether sleep can provide explicit knowledge on an implicitly acquired skill. At learning, young healthy subjects (n = 20) were first trained on the SRTT. Then, implicit knowledge was assessed on two test blocks, in which grammatically incorrect target positions were occasionally interspersed by the difference in reaction times between grammatically correct and incorrect target positions. To assess explicit sequence knowledge, thereafter subjects performed on a generation task in which they were explicitly instructed to predict the sequential target positions. In half the subjects, learning took place before a 9-hour retention interval filled with nocturnal sleep (sleep group), in the other half, the retention interval covered a 9-hour period of daytime wakefulness (wake group). At subsequent retesting, both testing on the generation task and the SRTT test blocks was repeated. At learning before the retention interval, subjects displayed significant implicit sequence knowledge which was comparable for the sleep and wake groups. Moreover, both groups did not display any explicit sequence knowledge as indicated by a prediction performance not differing from chance on the generation task. However, at retesting, there was a distinct gain in explicit knowledge in the subjects who had slept in the retention interval, whereas generation task performance in the wake group remained at chance level. SRTT performance in the test blocks at retesting did not indicate any further gain in skill (i.e., unchanged reaction time differences between grammatically correct and incorrect target positions) independently of whether subjects had slept or remained awake after learning. Our results indicate a selective enhancement of explicit memory formation during sleep. Because before sleep subjects only had implicit knowledge on the sequence of target transitions, these data point to an interaction between implicit and explicit memory systems during sleep-dependent off-line learning.

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