Abstract
Word learning is the one of most fundamental steps for English as Second Language (ESL) students. However, it is a challenge to understand each individual student to provide them with personalized learning experience, since it is difficult to identify various variables like learning style, language proficiency, knowledge background for each learner in an e-learning system. To address this issue, we propose an integrated framework to depict the individual vocabulary proficiency by using the implicit and explicit profiles. The explicit user profiling gives the control of users to specify and modify their vocabulary proficiency so that the users will have a sense of ownership of their personalized data, whereas the implicit user profiling is a non-intrusive method which can record and update the proficiency of learners without explicit manually input from users. In this paper, we attempt to integrate these two kinds of profiles to build a powerful learner profile for personalized vocabulary learning. Furthermore, the preliminary empirical results validate the effectiveness of the integrated framework.
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Acknowledgement
The work described in this paper was fully supported by the Start-Up Research Grant (RG 54/2017-2018R) of The Education University of Hong Kong and the Innovation and Technology Fund (Project No. GHP/022/17GD) from the Innovation and Technology Commission of the Government of the Hong Kong Special Administrative Region.
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Wang, F.L., Zou, D., Xie, H. (2018). Personalized Word Learning for ESL Students via Integration of Implicit and Explicit Profiles. In: Cheung, S., Kwok, Lf., Kubota, K., Lee, LK., Tokito, J. (eds) Blended Learning. Enhancing Learning Success. ICBL 2018. Lecture Notes in Computer Science(), vol 10949. Springer, Cham. https://doi.org/10.1007/978-3-319-94505-7_24
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DOI: https://doi.org/10.1007/978-3-319-94505-7_24
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