A Comparative Study on Various Vocabulary Knowledge Scales for Predicting Vocabulary Pre-Knowledge
Di Zou, The Hong Kong Polytechnic University, Hung Hom, Hong Kong ; Haoran Xie, The Education University of Hong Kong, Tai Po, Hong Kong ; Yanghui Rao, Sun Yat-sen University, Guangzhou, China ; Tak-Lam Wong, The Education University of Hong Kong, Tai Po, Hong Kong ; Fu Wang, Caritas Institute of Education, Tseung Kwan O, Hong Kong ; Qingyuan Wu, Beijing Normal University Zhuhai Campus, Zhuhai, China
IJDET Volume 15, Number 1, ISSN 1539-3100 Publisher: IGI Global
The world has encountered and witnessed the great popularity of various emerging e-learning resources such as massive open online courses (MOOCs), textbooks and videos with the development of the big data era. It is critical to understand the characteristics of users to assist them to find desired and relevant learning resources in such a large volume of resources. For example, understanding the pre-knowledge on vocabulary of learners is very prominent and useful for language learning systems. The language learning effectiveness can be significantly improved if the pre-knowledge levels of learners on vocabulary can be accurately predicted. In this research, the authors model the vocabulary of learners by extracting their history of learning documents and identify the suitable vocabulary knowledge scales (VKS) for pre-knowledge prediction. The experimental results on real participants verify that the optimal VKS and the proposed predicting model are powerful and effective.
Zou, D., Xie, H., Rao, Y., Wong, T.L., Wang, F. & Wu, Q. (2017). A Comparative Study on Various Vocabulary Knowledge Scales for Predicting Vocabulary Pre-Knowledge. International Journal of Distance Education Technologies, 15(1), 69-81. IGI Global.