In mathematical learning, it is important to give learners a number of problems that have various features in both of surface problem situations and deep mathematical structures. In this study, we implement a system that generates various word problems by using problem-generation episodes. Each problem-generation episode is knowledge comprising a base example problem and a new analogical instance, which is regarded as a past case where the analogical instance was generated from the example problem. Our system can generate various problems by applying the problem-generation episodes to initial problems stored in the system. In this paper, we describe our approach to generate mathematical word-problems, and perform experimental evaluations to verify whether or not our system can expand the variety of problems. The results of the experiments indicated that our system can appropriately expand the variety. We also found that it needs interactions with a knowledgeable user.
2006 JSAI (The Japanese Society for Artificial Intelligence)