ENGLISH VOCABULARY LEARNING SUPPORT SYSTEM BASED ON STOCHASTIC WORD PROFICIENCY MODEL ESTIMATING ELUSIVE WORDS FOR STUDENTS

This research focuses on a learning environment for teenage Japanese students to improve their English vocabulary. We propose a system that helps learners (students) improve their English vocabulary by intensively memorizing words by means of a Word Proficiency Model (WPM) represented by a Bayesian network, which is known as one of the stochastic models. A student’s WPM can reflect relationships between features of English words (e.g., part of speech, word length, and so on) and the learner’s ease in learning the words. The proposed system generates a word list arranged in order of difficulty for respective students to learn based on the result of probabilistic inference using the WPM. Intensive learning of the words by means of the list generated by the proposed system improves the acquisition of English vocabulary by helping learners unconsciously memorize words they find difficult.