Learning Issues for Intelligent Tutoring Systems

1. Front Matter

   Pages i-xix

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2. The Computer as a Tool for Learning Through Reflection

   • Allan Collins, John Seely Brown

   Pages 1-18

3. Toward a Theory of Impasse-Driven Learning

   • Kurt VanLehn

   Pages 19-41

4. Psychological Evaluation of Path Hypotheses in Cognitive Diagnosis

   • Stellan Ohlsson, Pat Langley

   Pages 42-62

5. Modeling the Knowledge Base of Mathematics Learners: Situation-Specific and Situation-Nonspecific Knowledge

   • Ipke Wachsmuth

   Pages 63-79

6. The Knowledge Engineer as Student: Metacognitive Bases for Asking Good Questions

   • William J. Clancey

   Pages 80-113

7. Toward a Theory of Curriculum for Use in Designing Intelligent Instructional Systems

   • Alan Lesgold

   Pages 114-137

8. Enhancing Incremental Learning Processes With Knowledge-Based Systems

   • Gerhard Fischer

   Pages 138-163

9. Mental Models and Metaphors: Implications for the Design of Adaptive User-System Interfaces

   • Norbert A. Streitz

   Pages 164-186

10. Improvement of the Acquisition of Knowledge by Informing Feedback

    • Peter Michael Fischer, Heinz Mandl

    Pages 187-241

11. Socializing the Intelligent Tutor: Bringing Empathy to Computer Tutors

    • Mark R. Lepper, Ruth W. Chabay

    Pages 242-257

12. Cognitive Economy in Physics Reasoning: Implications for Designing Instructional Materials

    • Eileen Scanlon, Tim O’Shea

    Pages 258-277

13. Experimental Data for the Design of a Microworld-Based System for Algebra

    • E. Cauzinille-Marmèche, J. Mathieu

    Pages 278-286

14. Computer-Aided Model Building

    • Joachim Wedekind

    Pages 287-294

15. Back Matter

    Pages 295-307

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Learning Issues for Intelligent Tutoring Systems arrays the most current and exciting research in this dynamic and growing area of cognitive science. The various contributions address the design and use of instructional systems as well as the important theoretical and practical questions involved in implementing knowledge-based systems. This book offers complete and up-to-date reviews of the major research programs in computer-aided instruction and intelligent tutoring systems. Learning Issues for Intelligent Tutoring Systems is an important and useful introduction to this rapidly changing field.

• Evaluation
• curriculum
• intelligent tutoring systems
• knowledge base
• knowledge-based systems
• learning
• mathematics
• modeling

• Deutsches Institut für Fernstudien, Universität Tübingen, Tübingen, Federal Republic of Germany

  Heinz Mandl

• Learning Research and Development Center, University of Pittsburgh, Pittsburgh, USA

  Alan Lesgold

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