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 25
... phases : Requirements collection and analysis , Conceptual design , Logical design and , Implementation design . The ... phase of database design and it is being used in the feasibility demonstration of the ADVISOR project . ADVISOR ...
... phases : Requirements collection and analysis , Conceptual design , Logical design and , Implementation design . The ... phase of database design and it is being used in the feasibility demonstration of the ADVISOR project . ADVISOR ...
Page 124
... phases ( a student may not always go through all four phases ) . The first phase is a general introduction to the concept ( s ) at that level . This is followed by guided exercises ( phase 2 ) to reify the concepts , exercises that ...
... phases ( a student may not always go through all four phases ) . The first phase is a general introduction to the concept ( s ) at that level . This is followed by guided exercises ( phase 2 ) to reify the concepts , exercises that ...
Page 292
... phases associated with each practice problem . During the first phase the student works to identify a failure that has been selected and simulated by the IMTS . In the second phase , following identification of the simulated failure ...
... phases associated with each practice problem . During the first phase the student works to identify a failure that has been selected and simulated by the IMTS . In the second phase , following identification of the simulated failure ...
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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