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 125
... answer ( T ) . The term answer ( T ) identifies the desired property of the variable T. The preconditions give constraints on this variable . The answer to the problem is the number of different possibilities for the variable T. The ...
... answer ( T ) . The term answer ( T ) identifies the desired property of the variable T. The preconditions give constraints on this variable . The answer to the problem is the number of different possibilities for the variable T. The ...
Page 126
... Answer : 100 3. How many two digit numbers are there where the first digit is greater than or equal to the second digit ? Answer : A4 + A5 1. How many two digit numbers are there where the first digit is less than the second digit ? Answer ...
... Answer : 100 3. How many two digit numbers are there where the first digit is greater than or equal to the second digit ? Answer : A4 + A5 1. How many two digit numbers are there where the first digit is less than the second digit ? Answer ...
Page 310
... answer ( the amount of detail required and in what area ) and where the tool can elaborate on the answers that it gives in a variety of ways which depend on the knowledge that it has , the type of question asked , and the answer to that ...
... answer ( the amount of detail required and in what area ) and where the tool can elaborate on the answers that it gives in a variety of ways which depend on the knowledge that it has , the type of question asked , and the answer to 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