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Student Modelling: The Key to Individualized Knowledge-Based Instruction

  • Conference proceedings
  • © 1994

Overview

Editors:
  1. Jim E. Greer

    1. Department of Computational Science, University of Saskatchewan, Saskatoon, Canada

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  2. Gordon I. McCalla

    1. Department of Computational Science, University of Saskatchewan, Saskatoon, Canada

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: NATO ASI Subseries F: (NATO ASI F, volume 125)

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Table of contents (13 papers)

  1. Front Matter

    Pages I-X
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  2. Background

    1. Front Matter

      Pages 1-1
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    2. The State of Student Modelling

      • Peter Holt, Shelli Dubs, Marlene Jones, Jim Greer
      Pages 3-35

  3. Artificial Intelligence Techniques for Student Modelling

    1. Front Matter

      Pages 37-37
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    2. Granularity-Based Reasoning and Belief Revision in Student Models

      • Gordon I. McCalla, Jim E. Greer
      Pages 39-62

    3. Student Modelling Through Qualitative Reasoning

      • Bert Bredeweg, Radboud Winkels
      Pages 63-97

    4. Modeling the Student in Sherlock II

      • Sandra Katz, Alan Lesgold, Gary Eggan, Maria Gordin
      Pages 99-125

    5. Using Machine Learning to Advise a Student Model

      • Beverly Park Woolf, Tom Murray
      Pages 127-146

    6. Building a Student Model for an Intelligent Tutoring System

      • M. F. Verdejo
      Pages 147-163

  4. Human Cognition and Student Modelling

    1. Front Matter

      Pages 165-165
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    2. Constraint-Based Student Modeling

      • Stellan Ohlsson
      Pages 167-189

    3. Strengthening the Novice-Expert Shift Using the Self-Explanation Effect

      • C. Frasson, M. Kaltenbach
      Pages 191-210

    4. Diagnosing and Evaluating the Acquisition Process of Problem Solving Schemata in the Domain of Functional Programming

      • Claus Möbus, Olaf Schröder, Heinz-Jürgen Thole
      Pages 211-264

  5. Formalizing Student Modelling

    1. Front Matter

      Pages 265-265
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    2. Modelling a Student’s Inconsistent Beliefs and Attention

      • Xueming Huang
      Pages 267-280

    3. A Formal Approach To ILEs

      • Ernesto Costa, Graça Gaspar, Helder Coelho
      Pages 281-294

    4. Formal Approaches to Student Modelling

      • John A. Self
      Pages 295-352

  6. Epilogue

    1. Front Matter

      Pages 353-353
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    2. Re-Writing Cartesian Student Models

      • Warren Sack, Elliot Soloway, Peri Weingrad
      Pages 355-376

  7. Back Matter

    Pages 377-390
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Keywords

About this book

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.

Editors and Affiliations

  • Department of Computational Science, University of Saskatchewan, Saskatoon, Canada

    Jim E. Greer, Gordon I. McCalla

Bibliographic Information

  • Book Title: Student Modelling: The Key to Individualized Knowledge-Based Instruction

  • Editors: Jim E. Greer, Gordon I. McCalla

  • Series Title: NATO ASI Subseries F:

  • DOI: https://doi.org/10.1007/978-3-662-03037-0

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag Berlin Heidelberg 1994

  • Hardcover ISBN: 978-3-540-57510-8Published: 28 March 1994

  • Softcover ISBN: 978-3-642-08186-6Published: 01 December 2010

  • eBook ISBN: 978-3-662-03037-0Published: 29 June 2013

  • Series ISSN: 0258-1248

  • Edition Number: 1

  • Number of Pages: X, 392

  • Topics: Simulation and Modeling, Artificial Intelligence, Cognitive Psychology

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