Automatic Vocabulary Study Map Generation by Semantic Context and Learning Material Analysis

Abstract

Learning English as a foreign language is a core part of K-12 education for many countries in which English is not the main spoken language, and especially in Asia. One of the fundamental tasks that students encounter is to learn vocabulary that is a part of the assigned curriculum. These are often sourced from reference materials or assigned vocabulary lists and may not consider the learner’s current proficiency or the semantic context of words that were recently learnt. By suggesting vocabulary that have similar proficiency or semantic contexts to what a student has recently studied could improve and support vocabulary learning. In this paper, we propose a method for recommending words that have similar difficulty and semantic context with previous words learnt based on the analysis of prescribed textbooks for Japanese junior high school students. This research could be used to guide a student learning English by helping them select a sequence of vocabulary that is appropriate.