A comparative study on various vocabulary knowledge scales for predicting vocabulary pre-knowledge

Di ZOU, Haoran XIE, Yanghui RAO, Tak Lam WONG, Fu Lee WANG, Qingyuan WU

Research output: Contribution to journalArticles

8 Citations (Scopus)

Abstract

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. Copyright © 2017 IGI Global.
Original languageEnglish
Pages (from-to)69-81
JournalInternational Journal of Distance Education Technologies
Volume15
Issue number1
DOIs
Publication statusPublished - Jan 2017

Citation

Zou, D., Xie, H., Rao, Y., Wong, T.-L., Wang, F. L., & 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.

Keywords

  • Studies
  • Comparative analysis
  • Online instruction
  • Vocabulary development
  • Big data

Fingerprint Dive into the research topics of 'A comparative study on various vocabulary knowledge scales for predicting vocabulary pre-knowledge'. Together they form a unique fingerprint.