Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/61244
Title: Generating incidental word-learning tasks via topic-based and load-based profiles
Authors: Xie, H
Zou, D
Lau, RYK
Wang, FL
Wong, TL
Issue Date: 2016
Source: IEEE multimedia, 2016, v. 23, no. 1, 7325205, p. 60-70
Abstract: Compared to intentional word learning, incidental word learning better motivates learners, integrates development of more language skills, and provides richer contexts. The effectiveness of incidental word learning tasks can also be increased by employing materials that learners are more familiar with or interested in. Here, the authors present a framework to generate incidental word learning tasks via load-based profiles measured through the involvement load hypothesis, and topic-based profiles obtained from social media. They also conduct an experiment on real participants and find that the proposed framework promotes more effective and enjoyable word learning than intentional word learning. This article is part of a special issue on social media for learning.
Keywords: Incidental word learning
Involvement load
Learner profile
Personalization
Social media
Publisher: Institute of Electrical and Electronics Engineers
Journal: IEEE multimedia 
ISSN: 1070-986X
EISSN: 1941-0166
DOI: 10.1109/MMUL.2015.91
Appears in Collections:Journal/Magazine Article

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