Modelling second language learners for learning task recommendation

Haoran Xie, Di Zou, Tak-Lam Wong and Fu Lee Wang

International Journal of Innovation and Learning, 2018, vol. 23, issue 1, 76-92

Abstract: How to recommend appropriate and effective learning tasks based on the characteristics of a second language learner is a vital question in the field of second language acquisition. In this research, we investigate the issue by dividing it into two sub-questions: how to model the characteristics of language learners as different learners may have varied expertise on and subjective preferences of many topics; and how to select learning tasks according to the constructed learner model. Research on the second sub-question has been widely conducted in domains such as recommender systems, and we focus on the first sub-question in this study from the perspective of how to model the preferred learning contexts of a learner in a non-intrusive manner. We conducted an experiment among eighty-two students, and the results showed that our proposed framework outperformed other systems as it provides significantly more effective and enjoyable word learning experience.

Keywords: learner modelling; context familiarity; task recommendation; word learning; e-learning. (search for similar items in EconPapers)
Date: 2018
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