Student modelling : the key to individualized knowledge-based instruction
著者
書誌事項
Student modelling : the key to individualized knowledge-based instruction
（NATO ASI series, Series F . Computer and systems sciences ; v. 125）
Springer-Verlag, c1994
- :Berlin
- :New York
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注記
"Proceedings of the NATO Advanced Research Workshop on 'Student Modelling: the Key to Individualized Knowledge-Based Instruction', held in Ste. Adele, Quebec, Canada, May 4-8, 1991"--T.p. verso
"Published in cooperation with NATO Scientific Affairs Division
Includes bibliographical references and index
内容説明・目次
内容説明
This book is the result of a NATO sponsored workshop entitled "Student Modelling: The Key to Individualized Knowledge-Based Instruction" which was held May 4-8, 1991 at Ste. Adele, Quebec, Canada. The workshop was co-directed by Gordon McCalla and Jim Greer of the ARIES Laboratory at the University of Saskatchewan. The workshop focused on the problem of student modelling in intelligent tutoring systems. An intelligent tutoring system (ITS) is a computer program that is aimed at providing knowledgeable, individualized instruction in a one-on-one interaction with a learner. In order to individualize this interaction, the ITS must keep track of many aspects of the leamer: how much and what he or she has leamed to date; what leaming styles seem to be successful for the student and what seem to be less successful; what deeper mental models the student may have; motivational and affective dimensions impacting the leamer; and so ono Student modelling is the problem of keeping track of alI of these aspects of a leamer's leaming.
目次
1. Background.- 1. The State of Student Modelling.- 2. Artificial Intelligence Techniques for Student Modelling.- 2. Granularity-Based Reasoning and Belief Revision in Student Models.- 3. Student Modelling Through Qualitative Reasoning.- 4. Modeling the Student in Sherlock II.- 5. Using Machine Learning to Advise a Student Model.- 6. Building a Student Model for an Intelligent Tutoring System.- 3. Human Cognition and Student Modelling.- 7. Constraint-Based Student Modeling.- 8. Strengthening the Novice-Expert Shift Using the Self-Explanation Effect.- 9. Diagnosing and Evaluating the Acquisition Process of Problem Solving Schemata in the Domain of Functional Programming.- 4. Formalizing Student Modelling.- 10. Modelling a Student's Inconsistent Beliefs and Attention.- 11. A Formal Approach To ILEs.- 12. Formal Approaches to Student Modelling.- 5. Epilogue.- 13. Re-Writing Cartesian Student Models.
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