Explainable English Material Recommendation Using an Information Retrieval Technique for EFL Learning

Abstract

Learning material recommendation has been a common field in the recommendation in e-learning due to the difficulty the learners experience in choosing appropriate learning materials among many resources. However, few traditional recommendation methods can be applied to e-learning as they are because they do not consider the learners’ characteristics. Such methods may not be persuasive enough for the learners and make them less motivated. In this study, we propose an explainable English material recommendation that can adapt to the changes of learners’ learning state and can explain the basis of the recommendation by using an information retrieval technique. This aims to address learners’ trust and motivation issues. The algorithm estimates the difficulty of materials and learners’ English skills and makes material recommendations that fit their skill levels. A case study in the setting of extensive reading is also described. Lastly, this paper introduces plans for implementation using an e-learning system with this recommendation. In the future, we will conduct an experiment and improve the recommendation algorithms.