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 35
... types of Igoals , such as domain specific Igoals ( e.g. a programming Igoal such as " have the student learn car / cdr recursion without composition " ) , language specific Igoals ( " have the student learn append " ) or cognitive ...
... types of Igoals , such as domain specific Igoals ( e.g. a programming Igoal such as " have the student learn car / cdr recursion without composition " ) , language specific Igoals ( " have the student learn append " ) or cognitive ...
Page 88
... types of deviation errors were observed , accounting for 98 % of all errors in this sample . To further enhance diagnostic specificity , these thirteen error types were further subdivided into a total of 34 more specific subcategories ...
... types of deviation errors were observed , accounting for 98 % of all errors in this sample . To further enhance diagnostic specificity , these thirteen error types were further subdivided into a total of 34 more specific subcategories ...
Page 246
... type for the user ; it does not lock the keyboard ; it never types where a user could type ; help information is provided in a separate window pane . The COACH Interaction Paradigm ; How users learn The COACH interaction paradigm ...
... type for the user ; it does not lock the keyboard ; it never types where a user could type ; help information is provided in a separate window pane . The COACH Interaction Paradigm ; How users learn The COACH interaction paradigm ...
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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