Learning Issues for Intelligent Tutoring Systems

ISBN-13: 9780387966168 / Angielski / Miękka / 1988 / 307 str.

Heinz Mandl; Alan M. Lesgold

Opis

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.

Spis treści

1. The Computer as a Tool for Learning Through Reflection.- 2. Toward a Theory of Impasse-Driven Learning.- 3. Psychological Evaluation of Path Hypotheses in Cognitive Diagnosis.- 4. Modeling the Knowledge Base of Mathematics Learners: Situation-Specific and Situation-Nonspecific Knowledge.- 5. The Knowledge Engineer as Student: Metacognitive Bases for Asking Good Questions.- 6. Toward a Theory of Curriculum for Use in Designing Intelligent Instructional Systems.- 7. Enhancing Incremental Learning Processes with Knowledge-Based Systems.- 8. Mental Models and Metaphors: Implications for the Design of Adaptive User-System Interfaces.- 9. Improvement of the Acquisition of Knowledge by Informing Feedback.- 10. Socializing the Intelligent Tutor: Bringing Empathy to Computer Tutors.- 11. Cognitive Economy in Physics Reasoning: Implications for Designing Instructional Materials.- 12. Experimental Data for the Design of a Microworld-Based System for Algebra.- 13. Computer-Aided Model Building.

O autorze

Heinz Mandl, Diplom-Psychologe, Dr. phil., Professor für Empirische Pädagogik und Pädagogische Psychologie an der Ludwig-Maximilians Universität, Oeuvre Award for Outstanding Contributions to the Science of Learning and Instruction (EARLI, 2003).
Forschungsschwerpunkte: Lehr-Lern Forschung, Wissensmanagement, Netzbasierte Wissenskommunikation, Blended Learning und Bildungscontrolling.