Learning Issues for Intelligent Tutoring Systems
Heinz Mandl, Alan Lesgold
Springer Science & Business Media, Dec 6, 2012 - Computers - 307 pages
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.
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abstract acquisition active algebra analysis answer approach arithmetic artificial intelligence basic behavior Brown Burton Clancey cognitive diagnosis column component concepts correct curriculum described developed dialogue domain equation errors evaluation example expert system explain feedback Figure function given goal graph HERACLES heuristics high-ability human–computer interaction hypothesis impasse implemented incorrect incremental learning inference procedure instruction Intelligent tutoring systems interaction kinds knowl knowledge base knowledge engineer knowledge representation knowledge-based Lawrence Erlbaum Assoc learner learning process lesson LISP low-ability machine learning malrule mental model metacognitive metaknowledge metaphor method microworlds mode model of learning NEOMYCIN Newell node object operators particular pattern performance prerequisite problem solving problem space procedural knowledge PROLOGue protocols psychological questions relations repair rules sequence situations skills Sleeman solution path specific strategies structure student subgoals subjects subtraction task taught teacher teaching theory tion types user's VanLehn