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 61
... overall reaction from the students is that the system is very helpful and friendly . The diagnosis of subject - verb agreement and pronominal errors ( which are the only ones being tested so far ) is 100 % accurate . Type 1 subjects ...
... overall reaction from the students is that the system is very helpful and friendly . The diagnosis of subject - verb agreement and pronominal errors ( which are the only ones being tested so far ) is 100 % accurate . Type 1 subjects ...
Page 107
... overall diagnosis . The design of the system guarantees that full recognition will occur at some grain size and that partial recognition at finer grain sizes is probable . The combination of these two types of recognition provides a ...
... overall diagnosis . The design of the system guarantees that full recognition will occur at some grain size and that partial recognition at finer grain sizes is probable . The combination of these two types of recognition provides a ...
Page 287
... overall mean score was 45.5 percent correct , and the Logo / discovery learning condition whose overall mean score was 47.1 percent correct . The experiment also examined four interaction effects . significant test by group ( F2 97 ...
... overall mean score was 45.5 percent correct , and the Logo / discovery learning condition whose overall mean score was 47.1 percent correct . The experiment also examined four interaction effects . significant test by group ( F2 97 ...
Common terms and phrases
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