ISSN: 2222-6990
Open access
In recent years, Mobile Assisted Language Learning (MALL) has emerged as a widespread phenomenon in education as well as in EFL/ESL teaching and learning context with its own set of foundations, techniques, and implications. Among the related studies, a continuous growth in the number of MALL vocabulary studies can be witnessed over the last few decades. To this end, the primary purpose of this study is to identify research hotspots and future trends in the available research literature on vocabulary learning using MALL from 2007 to 2022. A total of 229 articles on this topic were selected from the Scopus database and analysed using Vosviewer software. We used bibliometric methods to reveal document types and yearly distribution of the retrieved articles, the most productive countries and journals, the most used keywords, the most used words in title and abstract area, and the most cited publications and authors (citation & co-citation) in the studies over the 16-year period. Findings showed an increased number of studies from 2007 to 2022 have been published in this field but with a slight fluctuation in between 2012 and 2018. China (24 publications) took the top prominent lead among all countries, whilst the most productive journal in this area was Lecture Notes in Computer Science (11 publications) by Springer Publishing company. In terms of the most frequently used keywords, “Vocabulary Learning” (120 occurrence), “Mobile Assisted Language Learning” (114 occurrence) and “App” (40 occurrence) were the top three ranks, meanwhile “Effect” (62 occurrence), “System” (56 occurrence) and “Foreign Language” (46 occurrence) were the most used words in title and abstract field. Based on the citation and co-citation documents and authors network, the most frequently cited document was Chen & Chung (2008) with 271 citations, while Chen, C. M (citation) with 549 citations and Stockwell, G (co-citation) with 104 citations were the most influential authors. Consequently, this study displays the evolution of the literature and may serve as a guide for future research by comparing existing articles and indicating current research interest as well as future research trends on this topic.
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In-Text Citation: (Chuane & Shukor, 2023)
To Cite this Article: Chuane, Q., & Shukor, S. S. (2023). A Bibliometric Review of Vocabulary Learning via Mobile Assisted Language Learning. International Journal of Academic Research in Business and Social Sciences, 13(1), 513 – 532.
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