Artificial Intelligence and Education: Proceedings of the 4th International Conference on AI and Education, 24-26 May 1989, Amsterdam, Netherlands, Volume 4Dick Bierman, Joost Breuker, Jacobijn Sandberg IOS, 1989 - 339 pages |
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Page 102
... student model , defines the set of possible rule instantiations . The student model corresponds to the mapping between the set of problems and the set of answers . The assertion that the student's algorithm is sound can be shown to be ...
... student model , defines the set of possible rule instantiations . The student model corresponds to the mapping between the set of problems and the set of answers . The assertion that the student's algorithm is sound can be shown to be ...
Page 177
... Student Model Necessary ? Apprenticeship as a Model for ITS Denis Newman BBN Systems and Technologies Corporation 10 Moulton Street Cambridge , MA 02238 Abstract1 Conventional ... Student Model Necessary? Apprenticeship as a Model for ITS.
... Student Model Necessary ? Apprenticeship as a Model for ITS Denis Newman BBN Systems and Technologies Corporation 10 Moulton Street Cambridge , MA 02238 Abstract1 Conventional ... Student Model Necessary? Apprenticeship as a Model for ITS.
Page 325
... student's behavior . For coaching it will be advantageous to include some knowledge about interconnections between ... model . Ideally , the expert solution is slightly better than the solution the student is expected to submit . The ...
... student's behavior . For coaching it will be advantageous to include some knowledge about interconnections between ... model . Ideally , the expert solution is slightly better than the solution the student is expected to submit . The ...
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Abstract Abstract Interpretation actions algebra algorithm analysis Anderson applied approach architecture Artificial Intelligence behavior Blackboard COACH cognitive Cognitive Science components Computer Science concepts constraints construct correct described diagnosis diagrams dialogue discourse discovery learning discussion level domain knowledge dynamic instructional educational environment equation error evaluation example expert module expert system expertise explanation explicit feedback Figure flag tutor forward chaining function fuzzy goal granularity graphical hierarchy hypothesis Igoals implemented inference input instantiations instructional plan instructional planner Intelligent Tutoring Systems interaction interface interpretation knowledge base knowledge representation language learner lesson LISP programming manipulation mathematical misconceptions monitor node novice objects operators output performance problem solving procedures reasoning recursion represented rules schema selected semantic sequence simulation skills solution specific step structure student model subgoals subjects task teacher teaching troubleshooting tutorial strategy types understanding user model word problem XTRA-TE