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Autor/inn/enTang, Kai-Yu; Chen, Chao-Chen; Hwang, Gwo-Jen; Tu, Yun-Fang
TitelDid Library Learners Benefit from M-Learning Strategies? Research-Based Evidence from a Co-Citation Network Analysis of the Literature
QuelleIn: Educational Technology Research and Development, 70 (2022) 5, S.1719-1753 (35 Seiten)Infoseite zur Zeitschrift
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ZusatzinformationORCID (Tang, Kai-Yu)
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN1042-1629
DOI10.1007/s11423-022-10136-6
SchlagwörterLearning Strategies; Handheld Devices; Educational Technology; Computer Oriented Programs; Libraries; Museums; Independent Study; Inquiry; Learner Engagement; Performance; Social Networks; Network Analysis
AbstractMobile learning strategies have been employed for social learning activities, including library- and museum-supported learning. Previous studies have reviewed the literature from the technological aspect. However, a retrospective study from the perspective of bibliometric and network structure has not yet been provided. The aim of this study was therefore to systematically review journal papers on library-supported mobile learning (LibML). A coding framework including library types, mobile learning strategies, and research issues was adopted based on the literature and was used to screen and categorize the research papers. A co-citation network analysis was then adopted to analyze and visualize the structural relationships among the papers. A total of 53 eligible articles with 1370 citations in follow-up studies were collected from the Scopus database. The results showed that two main research streams of LibML were identified from the overall network structure, including library- and museum-supported mobile learning. In terms of the mobile learning strategy, library-supported research mainly focused on self-directed learning, whereas museum-supported research emphasized inquiry-based learning. In terms of research issues, most library-supported research focused on patrons' affective engagement, whereas museum-supported research emphasized learning performance. This study provides a citation-based approach to reveal the research trends and mainstream LibML research. The main contribution of combining co-citation and social network analysis is to provide a visualized network diagram of LibML research. Limitations of the methodological approach are noted. Discussion and future directions from the follow-up study are provided. (As Provided).
AnmerkungenSpringer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2024/1/01
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