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 153
... allows the tutor to recognize opportunities to motivate and lead into future instruction using unexpected student questions , or to defer the questions since they will be addressed later in the lesson . Finally , a plan assists in ...
... allows the tutor to recognize opportunities to motivate and lead into future instruction using unexpected student questions , or to defer the questions since they will be addressed later in the lesson . Finally , a plan assists in ...
Page 160
... allows modifiers for both verbs and nouns to occur in plan steps . These allow finer distinctions as shown earlier in Section 5 . The language used in the Blackboard Instructional Planner ( called TUTOR ) is not domain specific . Rather ...
... allows modifiers for both verbs and nouns to occur in plan steps . These allow finer distinctions as shown earlier in Section 5 . The language used in the Blackboard Instructional Planner ( called TUTOR ) is not domain specific . Rather ...
Page 272
... allows the student to pursue any desired strategy . We now describe the tools provided by the tutor for the five problem solving components . Step 1 : Define the problem situation . To represent the situation of the problem , the tutor ...
... allows the student to pursue any desired strategy . We now describe the tools provided by the tutor for the five problem solving components . Step 1 : Define the problem situation . To represent the situation of the problem , the tutor ...
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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