An algebraic perspective on implicit and explicit knowledge

2016 ◽  
Vol 3 (1) ◽  
pp. 151-162 ◽  
Author(s):  
Omid Khatin Zadeh ◽  
Sedigheh Vahdat ◽  
Babak Yazdani Fazlabadi
Keyword(s):  
Implicit Learning ◽  
Infinite Number ◽  
Explicit Knowledge ◽  
Algebraic Groups ◽  
The Other ◽  
Explicit Learning ◽  
Abstract Group ◽  
Abstract Structure ◽  
The Mind ◽  
Implicit And Explicit

The isomorphic relationship between an infinite number of concrete algebraic groups and the existence of a single abstract group that underlies all these concrete groups is one of the most fundamental subjects in Abstract Algebra. Looking at the process of explicit learning from a mathematical perspective, this article suggests that explicit knowledge of a certain concrete structure can be viewed as consciousness of an abstract algebraic structure that underlies that structure. On the other hand, implicit knowledge can be regarded as knowing something without being conscious of the abstract structure that underlies that knowledge. Explicit knowledge enables the learner to know what features are shared by these concrete groups or structures. These shared features are the defining elements of underlying abstract structure. The abstract structure is constructed in the mind by the suppression of irrelevant data. Therefore, it is suggested that while implicit learning is a receiving-oriented mode of learning, explicit learning is a suppression-oriented one. The sub-process of suppression enables the cognitive system to focus on abstract structure and its defining features, making the process of explicit learning deeper.

Implicit versus explicit: An act-r learning perspective

1999 ◽  
Vol 22 (5) ◽  
pp. 785-786 ◽  
Author(s):  
Niels A. Taatgen
Keyword(s):  
Implicit Learning ◽  
Explicit Memory ◽  
Explicit Knowledge ◽  
Cognitive Architecture ◽  
Explicit Learning ◽  
Implicit And Explicit Memory ◽  
The Difference ◽  
Implicit And Explicit ◽  
Implicit And Explicit Learning

Dienes & Perner propose a theory of implicit and explicit knowledge that is not entirely complete. It does not address many of the empirical issues, nor does it explain the difference between implicit and explicit learning. It does, however, provide a possible unified explanation, as opposed to the more binary theories like the systems and the processing theories of implicit and explicit memory. Furthermore, it is consistent with a theory in which implicit learning is viewed as based on the mechanisms of the cognitive architecture, and explicit learning as strategies that exploit these mechanisms.

scholarly journals Implicit and Explicit Learning of Temporal Sequences Studied With the Process Dissociation Procedure

2008 ◽  
Vol 100 (2) ◽  
pp. 733-739 ◽  
Author(s):  
Anke Karabanov ◽  
Fredrik Ullén
Keyword(s):  
Implicit Learning ◽  
Serial Recall ◽  
Explicit Knowledge ◽  
Stimulus Presentation ◽  
Explicit Learning ◽  
Process Dissociation ◽  
Process Dissociation Procedure ◽  
Significant Difference ◽  
Implicit And Explicit ◽  
Temporal Sequences

We studied whether temporal sequences can be learned implicitly using a process dissociation procedure (PDP). Participants performed repeated serial recalls of sequential stimuli with a random ordinal structure and fixed temporal structure. Explicit knowledge was evaluated through verbal questions and PDP analysis of two generation tasks (inclusion and exclusion). Participants were divided into two groups: in the Ordinal group, stimulus presentation was visual and the participants were instructed to repeat the ordinal structure; in the Temporal+Ordinal group, stimulus presentation was audio-visual and the participants were instructed to repeat temporal and ordinal structure. We expected predominantly implicit learning in the Ordinal group and explicit learning in the Temporal+Ordinal group. This was supported by two findings. First, a significant difference between inclusion and exclusion performance was seen only in the Temporal+Ordinal group. Second, in both groups, a negative relation was found between the degree of improvement during serial recall and a measure of explicit knowledge in the generation tasks. This relation was independent of the final level of performance during serial recall. These findings suggest that distinct implicit and explicit systems may exist for learning of temporal sequences: implicit learning is gradual and gives rise to knowledge that is inaccessible to conscious control while the explicit system is fast and results in representations that can be used to control performance in inclusion and exclusion tasks.

scholarly journals Effect of coordinate frame compatibility on the transfer of implicit and explicit learning across limbs

2016 ◽  
Vol 116 (3) ◽  
pp. 1239-1249 ◽  
Author(s):  
Eugene Poh ◽  
Timothy J. Carroll ◽  
Jordan A. Taylor
Keyword(s):  
Implicit Learning ◽  
Neural Representation ◽  
Coordinate Frame ◽  
Explicit Learning ◽  
Verbal Reports ◽  
Visuomotor Rotation ◽  
Left And Right ◽  
Task Conditions ◽  
Opposite Limb ◽  
Implicit And Explicit

Insights into the neural representation of motor learning can be obtained by investigating how learning transfers to novel task conditions. We recently demonstrated that visuomotor rotation learning transferred strongly between left and right limbs when the task was performed in a sagittal workspace, which afforded a consistent remapping for the two limbs in both extrinsic and joint-based coordinates. In contrast, transfer was absent when performed in horizontal workspace, where the extrinsically defined perturbation required conflicting joint-based remapping for the left and right limbs. Because visuomotor learning is thought to be supported by both implicit and explicit forms of learning, however, it is unclear to what extent these distinct forms of learning contribute to interlimb transfer. In this study, we assessed the degree to which interlimb transfer, following visuomotor rotation training, reflects explicit vs. implicit learning by obtaining verbal reports of participants' aiming direction before each movement. We also determined the extent to which these distinct components of learning are constrained by the compatibility of coordinate systems by comparing transfer between groups of participants who reached to targets arranged in the horizontal and sagittal planes. Both sagittal and horizontal conditions displayed complete transfer of explicit learning to the untrained limb. In contrast, transfer of implicit learning was incomplete, but the sagittal condition showed greater transfer than the horizontal condition. These findings suggest that explicit strategies developed with one limb can be fully implemented in the opposite limb, whereas implicit transfer depends on the degree to which new sensorimotor maps are spatially compatible for the two limbs.

Re-evaluating Dissociations between Implicit and Explicit Category Learning: An Event-related fMRI Study

2011 ◽  
Vol 23 (7) ◽  
pp. 1697-1709 ◽  
Author(s):  
Todd M. Gureckis ◽  
Thomas W. James ◽  
Robert M. Nosofsky
Keyword(s):  
Implicit Learning ◽  
Category Learning ◽  
Neural Activity ◽  
Incidental Learning ◽  
Brain Activity ◽  
Neural Systems ◽  
Explicit Learning ◽  
Learning Condition ◽  
Perceptual Category Learning ◽  
Implicit And Explicit

Recent fMRI studies have found that distinct neural systems may mediate perceptual category learning under implicit and explicit learning conditions. In these previous studies, however, different stimulus-encoding processes may have been associated with implicit versus explicit learning. The present design was aimed at decoupling the influence of these factors on the recruitment of alternate neural systems. Consistent with previous reports, following incidental learning in a dot-pattern classification task, participants showed decreased neural activity in occipital visual cortex (extrastriate region V3, BA 19) in response to novel exemplars of a studied category compared to members of a foil category, but did not show this decreased neural activity following explicit learning. Crucially, however, our results show that this pattern was primarily modulated by aspects of the stimulus-encoding instructions provided at the time of study. In particular, when participants in an implicit learning condition were encouraged to evaluate the overall shape and configuration of the stimuli during study, we failed to find the pattern of brain activity that has been taken to be a signature of implicit learning, suggesting that activity in this area does not uniquely reflect implicit memory for perceptual categories but instead may reflect aspects of processing or perceptual encoding strategies.

EPILOGUE

2021 ◽  
Vol 43 (3) ◽  
pp. 692-697
Author(s):  
Robert DeKeyser ◽  
Shaofeng Li
Keyword(s):  
Convergent Validity ◽  
Explicit Knowledge ◽  
Outcome Variable ◽  
Future Research ◽  
Explicit Learning ◽  
Language Aptitude ◽  
Language Research ◽  
Instruction Type ◽  
Implicit And Explicit ◽  
Implicit And Explicit Learning

AbstractIn this commentary, we summarize the findings of the seven included studies that examined implicit language aptitude from various perspectives and highlight issues to be resolved in the validation of this new construct in second language research. We start by providing an overview of the contributions of the studies. We then identify the lack of convergent validity of the measures of implicit aptitude reported in the included studies and problematize the equally varied nature of the measurement of implicit knowledge—the outcome variable of aptitude research—and related concepts. In particular, by drawing on empirical evidence and theoretical claims, we attempt to clarify the relationships between implicit and explicit knowledge, implicit and explicit learning, and implicit and explicit instruction. Next, we draw attention to the interactions reported by the included studies between aptitude and outcome measures and between aptitude and instruction type, emphasizing the value and importance of interactional research. We conclude by making recommendations for future research.

Implicit and explicit learning in a hybrid architecture of cognition

1999 ◽  
Vol 22 (5) ◽  
pp. 772-773
Author(s):  
Christian Lebiere ◽  
Dieter Wallach
Keyword(s):  
Implicit Learning ◽  
Conceptual Analysis ◽  
Human Cognition ◽  
Explicit Learning ◽  
Hybrid Architecture ◽  
Integrated Architecture ◽  
The Common ◽  
Implicit And Explicit ◽  
Implicit And Explicit Learning ◽  
Analysis Of Knowledge

We present a theoretical account of implicit and explicit learning in terms of act-r, an integrated architecture of human cognition as a computational supplement to Dienes & Perner's conceptual analysis of knowledge. Explicit learning is explained in act-r by the acquisition of new symbolic knowledge, whereas implicit learning amounts to statistically adjusting subsymbolic quantities associated with that knowledge. We discuss the common foundation of a set of models that are able to explain data gathered in several signature paradigms of implicit learning.

scholarly journals TYPES OF EXPLICIT AND IMPLICIT GRAMMAR INSTRUCTION

2019 ◽  
Vol 34 (6) ◽  
pp. 1645-1650
Author(s):  
Vesna Koceva
Keyword(s):  
Explicit Knowledge ◽  
Relevant Literature ◽  
Theoretical Research ◽  
Explicit Learning ◽  
Grammar Instruction ◽  
Paper Briefly ◽  
Implicit Instruction ◽  
The Difference ◽  
Implicit And Explicit ◽  
Implicit And Explicit Learning

This paper briefly presents a theoretical research conducted by revising an extensive relevant literature on this problematics, by separating, in our opinion, the most important definitions connected with explicit and implicit grammar instruction. The introduction gives a brief explanation of the difference between the implicit and explicit knowledge and learning. The paper further establishes the main differences between the implicit and explicit instruction by citing the positions of Ellis, Housen and Pierrard. A distinction is made between the indirect assistance or intervention i.e. indirect instruction which, in essence, is implicit as well as some implicit instruction. The paper continues with a discussion of Batstone's stance, who believes that the explicit and implicit instructions can only be defined in relation with the teacher or the creator of the teaching material, while the implicit and explicit learning refer to the student and there is no necessary relation between the two pairs of terms. The paper briefly mentions the claims of Norris and Ortega, Doughty and Robinson. The discussion continues with explanation of the types of explicit and implicit instruction, defining the terms reactive, proactive, direct, indirect, deductive, inductive, intensive and extensive grammar instruction. In the end, the paper briefly summarises the main definitions regarding explicit and implicit grammar instruction.

Implicit Learning, Tacit Knowledge, and Implications for Stasis and Change in Cognitive Psychotherapy

1996 ◽  
Vol 10 (3) ◽  
pp. 163-180 ◽  
Author(s):  
E. Thomas Dowd ◽  
Karen E. Courchaine
Keyword(s):  
Cognitive Psychology ◽  
Tacit Knowledge ◽  
Implicit Learning ◽  
Explicit Knowledge ◽  
Learning Processes ◽  
Explicit Learning ◽  
Conscious Awareness ◽  
Cognitive Structures ◽  
Cognitive Psychotherapy

With the evolution of cognitive psychotherapy, there has been an increasing focus on the nature and influence of cognitive structures or schemata. These structures are out of conscious awareness and therefore can be thought of as tacit in nature. As yet, however, there has been little written regarding the implications of the investigations in cognitive psychology of implicit learning and tacit memory for cognitive psychotherapy. This article describes the work of Arthur Reber and other cognitive psychologists on implicit learning and tacit memory and draws tentative implications for the practice of cognitive psychotherapy. Implicit learning processes have been described as robust in nature, holding evolutionary primacy over explicit learning processes, as dissociated from explicit learning, as involving different processes of learning, and as occurring through the tacit detection of covariation. Tacit knowledge precedes and is less available than explicit knowledge.

scholarly journals Acquisition of skilled finger movements is accompanied by reorganization of the corticospinal system

2018 ◽  
Vol 119 (2) ◽  
pp. 573-584 ◽  
Author(s):  
Masato Hirano ◽  
Shinji Kubota ◽  
Shinichi Furuya ◽  
Yoshiki Koizume ◽  
Shinya Tanaka ◽  
...  
Keyword(s):  
Implicit Learning ◽  
Sequence Learning ◽  
Explicit Learning ◽  
Voluntary Movements ◽  
Finger Movements ◽  
Corticospinal System ◽  
Learning Conditions ◽  
Implicit And Explicit ◽  
Implicit And Explicit Learning ◽  
Coordination Patterns

Dexterous finger movements are often characterized by highly coordinated movements. Such coordination might be derived from reorganization of the corticospinal system. In this study, we investigated 1) the manner in which finger movement covariation patterns are acquired, by examining the effects of the implicit and explicit learning of a serial reaction time task (SRTT), and 2) how such changes in finger coordination are represented in the corticospinal system. The subjects learned a button press sequence in both implicit and explicit learning conditions. In the implicit conditions, they were naive about what they were learning, whereas in the explicit conditions the subjects consciously learned the order of the sequence elements. Principal component analysis decomposed both the voluntary movements produced during the SRTT and the passive movements evoked by transcranial magnetic stimulation (TMS) over the primary motor cortex into a set of five finger joint covariation patterns. The structures of the voluntary and passive TMS-evoked movement patterns were reorganized by implicit learning but not explicit learning. Furthermore, in the implicit learning conditions the finger covariation patterns derived from the TMS-evoked and voluntary movements spanned similar movement subspaces. These results provide the first evidence that skilled sequential finger movements are acquired differently through implicit and explicit learning, i.e., the changes in finger coordination patterns induced by implicit learning are accompanied by functional reorganization of the corticospinal system, whereas explicit learning results in faster recruitment of individual finger movements without causing any changes in finger coordination. NEW & NOTEWORTHY Skilled sequential multifinger movements are characterized as highly coordinated movement patterns. These finger coordination patterns are represented in the corticospinal system, yet it still remains unclear how these patterns are acquired through implicit and explicit motor sequence learning. A direct comparison of learning-related changes between actively generated finger movements and passively evoked finger movements by TMS provided evidence that finger coordination patterns represented in the corticospinal system are reorganized through implicit, but not explicit, sequence learning.

Complementary Category Learning Systems Identified Using Event-Related Functional MRI

2000 ◽  
Vol 12 (6) ◽  
pp. 977-987 ◽  
Author(s):  
Howard J. Aizenstein ◽  
Angus W. MacDonald ◽  
V. Andrew Stenger ◽  
Robert D. Nebes ◽  
Jeris K. Larson ◽  
...  
Keyword(s):  
Implicit Learning ◽  
Category Learning ◽  
Medial Temporal Lobe ◽  
Learning Task ◽  
Neural Systems ◽  
Explicit Learning ◽  
Imaging Data ◽  
Activation Patterns ◽  
Implicit And Explicit ◽  
Implicit And Explicit Learning

Event-related fMRI was used to dissociate the neural systems involved in category learning with and without awareness. Ten subjects performed a speeded response category learning task. Functional MR images were acquired during both explicit and implicit learning conditions. Behavioral data showed evidence of learning in both conditions. Functional imaging data showed different activation patterns in implicit and explicit trials. Decreased activation in extrastriate region V3 was found with implicit learning, and increased activation in V3, the medial temporal lobe, and frontal regions were found with explicit learning. These results support the theory that implicit and explicit learning utilize dissociable neural systems. Moreover, in both the implicit and explicit conditions a similar pattern of decreased activation was found in parietal regions. This commonality suggests that these dissociable systems also operate in parallel.

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