Transactions of the Japanese Society for Artificial Intelligence
Online ISSN : 1346-8030
Print ISSN : 1346-0714
ISSN-L : 1346-0714
Original Paper
Development of Automatic Generation Function of Derivative Problems and Its Experimental Evaluation
Yusuke OokawachiTakuya UenoTsukasa Hirashima
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2012 Volume 27 Issue 6 Pages 391-400

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Abstract

This paper describes a function of automatic problem generation of high school level mechanics problems for adaptive exercises. We have defined derivative problems from view point of specialization-generalization or partialization-expansion of solution structure of the original problem. In this framework, first, a problem is characterized by a situation model the problem belongs to and solution structure that describes the way to solve it. Specialization or generalization is applied for a situation model. Relation between situation models from view point of specialization or generalization are described as a microworld graph, and by following the connections, a problem can be specialized or generalized. Partialization or expansion is applied for solution structure. By partializing or expending solution structure of the original problem, partialized or expand problems are generated. We call these generated problems ``derivative problems'' for the original one. We have already implemented the automatic generation function of these derivative problems. Two experimental evaluations of the function and generated problems were carried out. This paper described the results of the experiments.

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© 2012 JSAI (The Japanese Society for Artificial Intelligence)
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