M-Learning platform for assessment and personalized learning of Thai language by primary school children

Abstract

KidLearn is an M-learning platform for primary school children with a personalized learning component for Thai language learning. The purpose of this study is to describe and evaluate the personalization algorithm. By applying item response theory, the algorithm calculates ability in language topics based on responses to test questions and selects new content aimed at maximizing each child’s improvement in ability. An experiment was undertaken in 3 schools with 47 children with low-ability or learning difficulties in Thai language reading. The results show that improvements in the children’s ability in each topic were highly correlated with the ability calculated by the personalization algorithm. Therefore, as well as KidLearn providing an efficient means for boosting a child’s language learning across different topics, it effectively predicts a child’s language ability which provides educators an unobtrusive testing tool for monitoring progress.

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