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 48
... considered in this work are concerned with the bottom four levels . An explanatory dialogue is considered to be a type of informing transaction , which includes exchanges of different types . The structure of these exchanges can be ...
... considered in this work are concerned with the bottom four levels . An explanatory dialogue is considered to be a type of informing transaction , which includes exchanges of different types . The structure of these exchanges can be ...
Page 73
... considered as collaborator in learning , rather than offering instruction to the user , considered as pupil . Such IESS offer the prospect that omniscience by the system is not required , and that desirable metalevel skills can be ...
... considered as collaborator in learning , rather than offering instruction to the user , considered as pupil . Such IESS offer the prospect that omniscience by the system is not required , and that desirable metalevel skills can be ...
Page 224
... considered for prediction derivation only when it holds for more than one experiment . This assures that hypotheses containing overly spurious correlations are not considered for prediction making . Similarly , a hypothesis that has ...
... considered for prediction derivation only when it holds for more than one experiment . This assures that hypotheses containing overly spurious correlations are not considered for prediction making . Similarly , a hypothesis that has ...
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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