https://orcid.org/0000-0002-1764-158X
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Abstract
This study sought to examine research trends in computer-assisted language learning (CALL) using a retrospective scientometric approach. Scopus was used to search for relevant publications on the topic and generate a dataset consisting of 3,697 studies published in 11 journals between 1977 and 2020. A document co-citation analysis method was adopted to identify the main research clusters in the dataset. The impact of each publication on the field was measured by using the burst index and the betweenness centrality and the content of influential publications was closely analysed to determine the focus of each cluster and the key themes of the studies in focus. Overall, we identified seven major clusters. We further found that leveraging synchronous computer-mediated communication and negotiated interaction, multimedia, telecollaboration or e-mail exchanges, blogs, digital games, Wikis and podcasts to support language learning was probably beneficial for language learning. Varying degrees of support were found in various studies for each of these technologies. Stronger support was found for synchronous computer-mediated communication and negotiated interaction, multimedia, telecollaboration or e-mail exchanges and digital games and weaker support was found for blogs, Wikis, and podcasts. The limitations the supporting studies listed were also considered inconsequential. On the other hand, while there was strong support for blogs, Wikis and podcasts, some major drawbacks were observed. The findings of the study would be helpful for teachers and instructors who want to decide whether to use technology in the classroom for instructional purposes. Additionally, researchers and graduate students who need to identify a research topic for their thesis or dissertation may find the results of the study useful for them, too.
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No potential conflict of interest was reported by the authors.
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Mei Hui Lim
Lim Mei Hui is a student at Nanyang Technological University, Singapore. Her research interests include computer-assisted language learning, meta-analyses, and Scientometrics. She is in the Undergraduate Research Experience on CAmpus (URECA) programme, which is an 11-month research programme which aims to equip students with research skills related to their field of study or research interests. She has presented the result of her research in multiple academic events.
Vahid Aryadoust
Vahid Aryadoust is an Assistant Professor of language assessment literacy at the National Institute of Education of Nanyang Technological University, Singapore. He has led a number of language assessment research projects funded by, for example, the Ministry of Education (Singapore), Michigan Language Assessment (USA), Pearson Education (UK), and Paragon Testing Enterprises (Canada), and published his research in, for example, Computer Assisted Language Learning, Language Testing, System, Language Assessment Quarterly, Assessing Writing, Educational Assessment, Educational Psychology, etc. He has also (co)authored a number of book chapters and books published by Routledge, Cambridge University Press, Springer, Cambridge Scholar Publishing, Wiley Blackwell, etc. He is a member of the Advisory Board of multiple international journals and has been awarded the Intercontinental Academia Fellowship (2018–2019). His most recent book on quantitative methods in language assessment was published by Routledge (https://www.routledge.com/products/search?author=Vahid%20Aryadoust). His YouTube channel has been awarded the John Cheung Social Media Award, 2020, which recognizes exemplary and innovative use of social media. The channel is available from: https://www.youtube.com/user/vahidaryadoust