Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.11861/7167
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Dr. LEE Tin Yun, Philip | en_US |
dc.contributor.author | Lui, Richard Wing Cheung | en_US |
dc.contributor.author | Chau, Michael | en_US |
dc.date.accessioned | 2022-06-20T08:20:04Z | - |
dc.date.available | 2022-06-20T08:20:04Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Journal of Information Systems Education, 2019, vol. 30(3), pp. 167-177. | en_US |
dc.identifier.issn | 2574-3872 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11861/7167 | - |
dc.description.abstract | Serious games, many of which are multi-player games, have been commonly used in information technology education and training. Competition can be intuitively associated with games; however, it is not always considered as a necessary attribute of serious games. Particularly, the learning impact results of competition are mixed. Challenge and control are two game attributes that are highly relevant to competition. With the use of a multi-player serious game, SEO War, this study aims to explore the relationships among competition, perceived control, perceived challenge, and self-efficacy in a game-based learning environment. Particularly, it investigates whether competition leads to self-efficacy. It also examines whether perceived challenge and perceived control mediate the relationship between competition and self-efficacy in serious games. This study contributes to the expanding literature on selecting important attributes for serious games, and it advances our understanding of the mechanism of how competition leads to self-efficacy. Moreover, it will help game designers decide on important game attributes through which games can be enhanced. | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartof | Journal of Information Systems Education | en_US |
dc.title | How does competition help future learning in serious games? An exploratory study in learning search engine optimization | en_US |
dc.type | Peer Reviewed Journal Article | en_US |
item.fulltext | No Fulltext | - |
crisitem.author.dept | Department of Economics and Finance | - |
Appears in Collections: | Applied Data Science - Publication |
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