A student model of katakana reading proficiency for a Japanese language intelligent tutoring system

This work describes the development of a student model that is used in a Japanese language intelligent tutoring system to assess a pupil´s proficiency at reading one of the distinct orthographies of Japanese, known as katakana. While 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 algorithms described here are able to automatically acquire a knowledge base of these phonological transformation rules, use them to assess a student´s proficiency, and then appropriately individualize the student´s instruction