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 22
... objects and circuit concepts representing different kinds of declarative and procedural knowledge utilized by the simulation and expert components . Circuit objects describe the simulation behavior of specific circuits , used by the ...
... objects and circuit concepts representing different kinds of declarative and procedural knowledge utilized by the simulation and expert components . Circuit objects describe the simulation behavior of specific circuits , used by the ...
Page 110
... objects is described more fully below . Each strategy object in the hierarchy is a representation of a technique ... objects are connected by granularity relations of two types . Abstraction granularity is represented with the ...
... objects is described more fully below . Each strategy object in the hierarchy is a representation of a technique ... objects are connected by granularity relations of two types . Abstraction granularity is represented with the ...
Page 112
... object " lisp - program " . All other objects in the hierarchy are attached to this object , either directly , or indirectly through a combination of abstraction and aggregation links . Below " lisp - program " , specialized strategies ...
... object " lisp - program " . All other objects in the hierarchy are attached to this object , either directly , or indirectly through a combination of abstraction and aggregation links . Below " lisp - program " , specialized strategies ...
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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