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Autor/inn/enZou, Di; Xie, Haoran; Rao, Yanghui; Wong, Tak-Lam; Wang, Fu Lee; Wu, Qingyuan
TitelA Comparative Study on Various Vocabulary Knowledge Scales for Predicting Vocabulary Pre- Knowledge
QuelleIn: International Journal of Distance Education Technologies, 15 (2017) 1, S.69-81 (13 Seiten)Infoseite zur Zeitschrift
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Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN1539-3100
DOI10.4018/IJDET.2017010105
SchlagwörterComparative Analysis; Vocabulary Development; Predictor Variables; Prior Learning; Models; Knowledge Level; Writing Assignments; Essays; Accuracy; Rating Scales
AbstractThe 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. (As Provided).
AnmerkungenIGI Global. 701 East Chocolate Avenue, Hershey, PA 17033. Tel: 866-342-6657; Tel: 717-533-8845; Fax: 717-533-8661; Fax: 717-533-7115; e-mail: journals@igi-global.com; Web site: http://www.igi-global.com/journals
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2020/1/01
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