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 116
... representation are as important as manipulative activities within that formalism . How subjects construct a solution- enabling representation of an applied problem opens onto deeper questions about representation and problem - solving ...
... representation are as important as manipulative activities within that formalism . How subjects construct a solution- enabling representation of an applied problem opens onto deeper questions about representation and problem - solving ...
Page 119
... representations used in applied problem solving . We interpret these findings as progressive augmentations to the expressiveness of a representation for related linear functions . Distinguished state annotations record values and ...
... representations used in applied problem solving . We interpret these findings as progressive augmentations to the expressiveness of a representation for related linear functions . Distinguished state annotations record values and ...
Page 225
... representation of the objects in REFRACT , and , within the quantitative representation : constraints on the function induction step . The distinction between quantitative and qualitative representation refers to the observation that ...
... representation of the objects in REFRACT , and , within the quantitative representation : constraints on the function induction step . The distinction between quantitative and qualitative representation refers to the observation that ...
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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