An algorithm for domain knowledge base acquisition in an intelligent tutoring system: Japanese transliteration rules

Abstract

This article describes an algorithm for developing a domain knowledge base that is used in a Japanese language intelligent tutoring system. The domain knowledge represents a model of the expertise that a student must acquire in order to be proficient at reading one of the distinct orthographies of Japanese, known as katakana. Whereas the effort required to memorize the relatively few katakana symbols and their associated pronunciations is not prohibitive, a major difficulty in reading katakana is associated with the phonetic modifications which occur when English words which are transliterated into katakana are made to conform to the more restrictive rules of Japanese phonology. The algorithm described here is able to generate a knowledge base of these phonological transformation rules automatically, that is subsequently used to assess a student's proficiency and then appropriately individualize the student's instruction.