Learning Issues for Intelligent Tutoring SystemsLearning 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. |
Contents
Psychological Evaluation of Path Hypotheses | 42 |
Metacognitive Bases | 80 |
Toward a Theory of Curriculum for Use in Designing | 114 |
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ability groups abstract acquisition algebra answer approach arithmetic artificial intelligence AV-only basic behavior Brown Burton Clancey cognitive diagnosis Cognitive Science column component concepts conceptual model correct curriculum developed diagnostic domain equation errors evaluation example expert system explain feedback Figure function given goal graph HERACLES heuristics high-ability Hillsdale human-computer interaction hypothesis impasse inference procedure instruction Intelligent tutoring systems interaction interpretation kinds knowl knowledge base knowledge engineer knowledge representation knowledge-based language Lawrence Erlbaum Assoc learner learning process lesson LISP low-ability machine learning malrule mental model metacognitive metaphor method microworlds mode model of learning NEOMYCIN node object operators particular pattern performance prior knowledge problem solving problem space PROLOGue protocols psychological questions relations repair replay rules sequence situations skills Sleeman solution path specific stable bugs strategies structure student subgoals subjects subprocedure subtraction task teacher teaching theory tion user's VanLehn