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Cognitive Mechanisms of Learning presents experimental research works on the issue of knowledge acquisition in Cognitive Psychology. These research works – initiated by groups of researchers with academic backgrounds in Philosophy, Psychology, Linguistics and Artificial Intelligence – explore learning mechanisms by viewing humans as information processing systems. Although the book is centered on research studies conducted in a laboratory, one chapter is dedicated to applied research studies, derived directly from the fundamental research works. Computer modeling of learning mechanisms is presented, based on the concept of “cognitive architecture”. Three important issues – “the methodology”, “the achievements” and “the evolution” – in the field of learning research are also examined.

Table of Contents

  1. Cover
  2. Foreword
  3. Acknowledgments
  4. Introduction
  5. 1 Useful Concepts and Representation Formalisms
    1. 1.1. Useful concepts
    2. 1.2. Some formalisms used in cognitive psychology to represent knowledge stored in the LTM
  6. 2 Definition and Historical Overview
    1. 2.1. Definition
    2. 2.2. Conceptual frameworks
    3. 2.3. Principal concepts of problem-solving
    4. 2.4. Formal models
  7. 3 Learning to Solve a Problem
    1. 3.1. Breaking down a complex problem into sub-problems
    2. 3.2. The four stages of problem-solving
    3. 3.3. The three stages of learning by problem-solving
  8. 4 Learning a Concept from Examples of Concepts: Induction
    1. 4.1. Rule-based category learning
    2. 4.2. The question of “confirmation bias”
    3. 4.3. The duality between rule-based concept identification and similarity-based concept identification
    4. 4.4. Concluding remarks
  9. 5 Implicit Learning
    1. 5.1. Presentation
    2. 5.2. What have learners learned, and are they aware of the knowledge which they acquire?
    3. 5.3. Fragment status and the question of “abstract” or “concrete” acquired knowledge
    4. 5.4. Conclusion on implicit learning
  10. 6 The Role of Prior Knowledge in Constructing a Representation of a Problem
    1. 6.1. Experimental method based on comparing group results
    2. 6.2. Experimental method based on multiple trials of the same problem with vocal description of actions by the subject: individual protocol and modeling
    3. 6.3. Experimental method using learning transfer to study the effect of problem presentation in the choice of prior knowledge
    4. 6.4. Conclusion: the role of prior knowledge in the construction of problem representations
  11. 7 Acquiring Knowledge in a Specific Domain
    1. 7.1. Learning through (self-)explanation
    2. 7.2. Problem-based learning
    3. 7.3. Appendix: some notes on cognitive load theory
  12. 8 Causal Learning
    1. 8.1. Historical overview
    2. 8.2. Conceptual framework
    3. 8.3. Formalization and experimental research on adults
    4. 8.4. Experimental research on children
  13. 9 Symbolic Processing System Models in Cognitive Psychology
    1. 9.1. Why formalize?
    2. 9.2. Modeling complex skill acquisition using ACT-R: Taatgen and Lee (2003)
    3. 9.3. Modeling a two-player game
    4. 9.4. A model of learning through multiple analogies
    5. 9.5. Robert Siegler’s two models for learning arithmetic calculation
    6. 9.6. Links between SPS models in cognitive psychology and learning models in AI
  14. Conclusion
  15. References
  16. Index
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