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 18
... involved : knowledge about the application domain , e.g .. specific four - poles , and Jknowledge about how to operate a simulated laboratory , e.g. , how to set up and run meaningful simulations . To overcome some of the problems ...
... involved : knowledge about the application domain , e.g .. specific four - poles , and Jknowledge about how to operate a simulated laboratory , e.g. , how to set up and run meaningful simulations . To overcome some of the problems ...
Page 27
... involved consultation of specialised manuals , analysis of case studies and , analysis of the tasks and knowledge involved in the design of a conceptual data model . Development of the knowledge base also requires identification of ...
... involved consultation of specialised manuals , analysis of case studies and , analysis of the tasks and knowledge involved in the design of a conceptual data model . Development of the knowledge base also requires identification of ...
Page 141
... involved , a " control " knowledge " which allows decisions to be made about when and how each mode of analysis is to be used . The viewpoints described in the previous paragraph may be characterized in two ways . Firstly , they are ...
... involved , a " control " knowledge " which allows decisions to be made about when and how each mode of analysis is to be used . The viewpoints described in the previous paragraph may be characterized in two ways . Firstly , they are ...
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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