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Title: Modelling second language learners for learning task recommendation
Author(s): Xie, Haoran 
Wang, Philips Fu Lee 
Wong, Tak Lam 
Author(s): Zou, D.
Issue Date: 2018
Publisher: Inderscience Publishers
Journal: International Journal of Innovation and Learning 
Volume: 23
Issue: 1
Start page: 76
End page: 92
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.
DOI: 10.1504/IJIL.2018.088779
CIHE Affiliated Publication: Yes
Appears in Collections:CIS Publication

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