Mobile-Assisted Language Learning (mall) Research Trends and Patterns Through Bibliometric Analysis: Empowering Language Learners Through Ubiquitous Educational Technologies

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Date

2022

Journal Title

Journal ISSN

Volume Title

Publisher

Elsevier

Abstract

Mobile devices and technologies have proliferated extensively and become an integral part of lifeand learning. Mobile-assisted language learning (MALL) has progressed as an emerging area ofresearch corresponding to recent advances in mobile technologies and the proliferation ofsmartphones and tablet computers. Accordingly, this study examined MALL research between2008 and 2020 through a bibliometric analysis using social network analysis (SNA) and textmining techniques. The SNA and text mining analysis suggest five broad research themes: (1) self-regulated language learning by defining one’s own learning objectives, (2) providing learneragency and motivation by empowering autonomy, (3) personalizing learning through artificialintelligence (AI)-supported mobile learning (m-learning), (4) MALL for learning in the wild, and(5) MALL to support higher education. The findings show that while MALL research has beenconsiderably operationalized around linguistic factors, nonlinguistic factors relating to learners’interactions with mobile devices or applications have been largely overlooked. It was found thatMALL scholarship has recently tended to incorporate the use of mobile devices in informallearning contexts and outside the classroom due to the flexibility and anytime anywhere func-tionality of m-learning. The study concludes with several suggestions and highlights the areas thatneed more attention in MALL research.

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Keywords

Mobile-assisted language learning, Informal learning, Mobile learning smartphones, Bibliometric analysis

Turkish CoHE Thesis Center URL

Citation

Karakaya, K., & Bozkurt, A. (2022). Mobile-assisted language learning (MALL) research trends and patterns through bibliometric analysis: Empowering language learners through ubiquitous educational technologies. System, 110, pp.1-11. https://doi.org/10.1016/j.system.2022.102925 ‌

WoS Q

Q1

Scopus Q

Q1

Source

Volume

110

Issue

Start Page

1

End Page

11