Modelling second language learners for learning task recommendation
Author(s)
Xie, Haoran
Wang, Philips Fu Lee
Wong, Tak Lam
Author(s)
Zou, D.
Date Issued
2018
Publisher
Inderscience Publishers
Journal
International Journal of Innovation and Learning
Volume
23
Issue
1
Start page
76
End page
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.
SFU Affiliated Publication
Yes
Availability at SFU Library
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