Bibliometric mapping of mobile learning
dc.contributor.author | Göksu, İdris | |
dc.date.accessioned | 2021-08-26T14:17:24Z | |
dc.date.available | 2021-08-26T14:17:24Z | |
dc.date.issued | 2021 | en_US |
dc.department | MAÜ, Fakülteler, Edebiyat Fakültesi, Eğitim Bilimleri Bölümü | en_US |
dc.description.abstract | This study aims to reveal the tendency towards research in the field of mobile learning with the analysis of co-authorship, bibliographic coupling, co-occurrence, and citation by taking into consideration of author, publication, keyword, journal, country, university and citation variables. As of September 2019, the meta-data of a total of 5167 studies in the Web of Science database constituted the scope of this study. VOSviewer and sciMAT were used for the bibliometric analysis while Harzing's Publish and Perish software was used for the h-index. As a result of the bibliometric analysis, it was concluded that the most effective countries in mobile learning are Taiwan, USA, China, and England. According to the keyword co-occurrence analysis, mobile devices, higher education, mobile technologies, tablet, and smartphone keywords stand out in the field of mobile learning. Within the period of 2015–2019, trending topics were broadly educational technologies and, more specifically, tablets, mobile phones, MOOCs and learning strategies. It was found that G. J. Hwang is the most influential researcher and National Taiwan University of Science and Technology is the most influential university. It can be concluded that the most effective researches are augmented reality, higher education, and smartphone oriented mobile learning researches. According to the analyses conducted in the context of journals, Computers & Education, British Journal of Educational Technology and Educational Technology & Society were the most contributing journals | en_US |
dc.identifier.scopus | 2-s2.0-85090057508 | en_US |
dc.identifier.scopusquality | N/A | en_US |
dc.identifier.uri | https://www.scopus.com/record/display.uri?eid=2-s2.0-85090057508&doi=10.1016%2fj.tele.2020.101491&origin=inward&txGid=c63cdf6a3b7dc2c2929972d0b36eca44 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12514/2823 | |
dc.identifier.volume | 56 | en_US |
dc.identifier.wos | WOS:000600791800012 | en_US |
dc.identifier.wosquality | Q1 | en_US |
dc.indekslendigikaynak | Web of Science | en_US |
dc.indekslendigikaynak | Scopus | en_US |
dc.language.iso | en | en_US |
dc.publisher | Telematics and Informatics | en_US |
dc.relation.ispartof | Telematics and Informatics | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Bibliometric analysis, Bibliometric mapping, M-learning, Mobile devices, Mobile learning | en_US |
dc.title | Bibliometric mapping of mobile learning | en_US |
dc.type | Article | en_US |
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