Student Modelling: The Key to Individualized Knowledge-Based Instruction

1. Auflage. Softcover version of original hardcover Auflage 1994
ISBN: 978-3-642-08186-6
Verlag: Springer

Buch, Englisch, Band 125, 392 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 610 g

Reihe: NATO ASI Subseries F:

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.

Zielgruppe

Research

Autoren/Hrsg.

McCalla, Gordon I.

Greer, Jim E.

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Mathematik | Informatik EDV | Informatik Professionelle Anwendung Computersimulation & Modelle, 3-D Graphik
• Sozialwissenschaften Psychologie Allgemeine Psychologie Kognitionspsychologie Intelligenz, Denken, Problemlösen
• Sozialwissenschaften Pädagogik Lehrerausbildung, Unterricht & Didaktik E-Learning, Bildungstechnologie
• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein E-Learning

Inhaltsverzeichnis

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.