Please use this identifier to cite or link to this item: https://repository.cihe.edu.hk/jspui/handle/cihe/536
DC FieldValueLanguage
dc.contributor.authorXie, Haoran-
dc.contributor.authorWang, Philips Fu Lee-
dc.contributor.authorWong, Tak Lam-
dc.contributor.otherZou, D.-
dc.contributor.otherLau, R. Y. K.-
dc.date.accessioned2021-04-14T02:18:39Z-
dc.date.available2021-04-14T02:18:39Z-
dc.date.issued2016-
dc.identifier.urihttps://repository.cihe.edu.hk/jspui/handle/cihe/536-
dc.description.abstractCompared 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.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofIEEE MultiMediaen_US
dc.titleGenerating incidental word-learning tasks via topic-based and load-based profilesen_US
dc.typejournal articleen_US
dc.identifier.doi10.1109/MMUL.2015.91-
dc.contributor.affiliationSchool of Computing and Information Sciences-
dc.relation.issn1941-0166en_US
dc.description.volume23en_US
dc.description.issue1en_US
dc.description.startpage60en_US
dc.description.endpage70en_US
dc.cihe.affiliatedYes-
item.languageiso639-1en-
item.openairetypejournal article-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.cerifentitytypePublications-
crisitem.author.deptSchool of Computing and Information Sciences-
crisitem.author.deptRita Tong Liu School of Business and Hospitality Management-
crisitem.author.deptSchool of Computing and Information Sciences-
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