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 269
... contains the goal variable . Given this equation , subgoals are set to find values for the remaining unknowns . Additional constraints are generated which contain the unknowns and are substituted into the equation containing the goal ...
... contains the goal variable . Given this equation , subgoals are set to find values for the remaining unknowns . Additional constraints are generated which contain the unknowns and are substituted into the equation containing the goal ...
Page 273
... contains the goal variable and the fewest number of unknowns . Once such an equation exists , the tutor recommends that students write additional primitive equations that can be used to replace the remaining unknown variables with ...
... contains the goal variable and the fewest number of unknowns . Once such an equation exists , the tutor recommends that students write additional primitive equations that can be used to replace the remaining unknown variables with ...
Page 331
... contains a goal - cantered history of the user's past actions . We classify the potential questions that can be ... contains a A more detailed discussion can be found in [ Wolz & Kaiser 88 ; Wolz 88 ] plan for the goal . If the User ...
... contains a goal - cantered history of the user's past actions . We classify the potential questions that can be ... contains a A more detailed discussion can be found in [ Wolz & Kaiser 88 ; Wolz 88 ] plan for the goal . If the User ...
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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