Keywords
Mobile-Assisted Language Learning
Bibliometric Data
Citation Network
Bibliometric Analysis
How to Cite
Abstract
The development of Computer- and Mobile-Assisted Language Learning (CMALL) has significantly transformed language education by enhancing learning methodologies. This study employed bibliometric analysis to examine CMALL- related publications from 2004 to 2024 using the Scopus database, which includes 5,287 publications (4,542 focusing on CALL and 745 on MALL). The aim is to map publication trends, identify influential authors and institutions, analyze collaboration patterns, and explore thematic developments in the field. Using Boolean search techniques and filters to ensure relevance and quality, the analysis employs VOS viewer software to visualize co-authorship, citation, and keyword co-occurrence networks. The research findings are organized into three essential domains: publication trends, co-author collaboration, and citation networks. According to the analysis findings, the growing international research interest in CMALL has led to the USA and China emerging as primary contributors. Key thematic clusters include AI integration, mobile app-based instruction, cognitive approaches, and digital sustainability. A data-based assessment of CMALL’s development extensively examines its broad academic framework and worldwide significance. It also identifies research gaps and proposes directions for future studies at the intersection of language learning and educational technology.
References
Ahsan, K., Akbar, S., Kam, B., & Abdulrahman, M. D. (2023). Implementation of micro-credentials in higher education: A systematic literature review. Education and Information Technologies, 28(10), 13505–13540. https://doi.org/10.1007/s10639-023-11739-z
Al Hebshi, A. A., & Gamlo, N. (2022). The effects of mobile game-based learning on Saudi EFL foundation year students’ vocabulary acquisition. Arab World English Journal, 13(1), 408- 425. https://doi.org/10.24093/awej/vol13no1.27
Bakan, U., & Han, T. (2019). Research and trends in the field of social media from 2012 to 2016: A content analysis of studies in selected journals. Estudios Sobre el Mensaje Periodístico, 25(1), 13–31. https://doi.org/10.5209/esmp.63713
Biscaro, C., & Giupponi, C. (2014). Co-authorship and bibliographic coupling network effects on citations. PLOS ONE, 9(6), e99502. https://doi.org/10.1371/journal.pone.0099502
Boţa-Avram, C. (2022). Bibliometric analysis of sustainable business performance: Where are we going? A science map of the field. Economic Research-Ekonomska Istraživanja, 36(1), 2137–2176. https://doi.org/10.1080/1331677x.2022.2096094
Chen, J., Yuan, D., Dong, R., Cai, J., Ai, Z., & Zhou, S. (2024). Artificial intelligence significantly facilitates development in the mental health of college students: A bibliometric analysis. Frontiers in Psychology, 15, 1375294. https://doi.org/10.3389/fpsyg.2024.1375294
Chen, X., Zou, D., Cheng, G., & Xie, H. (2021). Artificial intelligence-assisted personalized language learning: Systematic review and co-citation analysis. In Proceedings of the 2021 IEEE 21st International Conference on Advanced Learning Technologies (ICALT) (pp. 137–141). IEEE. https://doi.org/10.1109/ICALT52272.2021.00079
Cornillie, F., Thorne, S. L., & Desmet, P. (2012). Digital games for language learning: Challenges and opportunities. ReCALL, 24(3), 243–256. https://doi.org/10.1017/S0958344012000134
Dizon, G., & Gayed, J. M. (2021). Examining the impact of Grammarly on the quality of mobile L2 writing. JALT CALL Journal, 17(2), 74–92. https://doi.org/10.29140/jaltcall.v17n2.336
Drigas, A., & Charami, F. (2014). ICTs in English learning and teaching. International Journal of Emerging Technologies in Learning, 2(4), 4–8. https://doi.org/10.3991/ijes.v2i4.4016
Gupta, N., Ali, K., Jiang, D., Fink, T., & Du, X. (2024). Beyond autonomy: Unpacking self-regulated and self-directed learning through the lens of learner agency- A scoping review. BMC Medical Education, 24, Article 1519. https://doi.org/10.1186/s12909-024-06476-x
Fu, Q. (2018). Impacts of mobile technologies, systems, and resources on language learning: A systematic review of selected journal publications from 2007–2016. Knowledge Management & E-Learning, 10(4), 375–388. https://doi.org/10.34105/j.kmel.2018.10.023
Hariharasudan, A., & Kot, S. (2024). Research trends in green human resource management: A comprehensive review of bibliometric data. In Green Human Resource Management, Springer. https://doi.org/10.1007/978-981-99-7104-6_19
Han, Y. (2020). Connecting the past to the future of computer-assisted language learning: Theory, practice, and research. Issues and Trends in Learning Technologies, 8(1), https://doi.org/10.2458/azu_itlt_v8i1_han
Han, R., Lam, H. K., Zhan, Y., Wang, Y., Dwivedi, Y. K., & Tan, K. H. (2021). Artificial intelligence in business-to-business marketing: A bibliometric analysis of current research status, development, and future directions. Industrial Management & Data Systems, 121(12), 2467–2497. https://doi.org/10.1108/imds-05-2021-0300
Herring, S. C., Stein, D., & Virtanen, T. (2013). Pragmatics of computer-mediated Communication. De Gruyter. https://doi.org/10.1515/9783110214468
Hinkelman, D. (2018). Evolution of blended learning. In Blended Learning in English Language Teaching (pp. 1–21). Palgrave Macmillan. https://doi.org/10.1057/978-1-137-53686-0_1
Iftikhar, A., Ali, I., Arslan, A., & Tarba, S. Y. (2022). Digital innovation, data analytics, and supply chain resiliency: A bibliometric-based systematic literature review. Annals of Operations Research, 333(2–3), 825–848. https://doi.org/10.1007/s10479-022-04765-6
Intellectsoft. (2025). How AI improves the language learning experience. Intellectsoft Blog. https://www.intellectsoft.net/blog/how-ai-improves-the-language-learning-experience/
Kannan, J., & Munday, P. (2018). New trends in second language learning and teaching through the lens of ICT, networked learning, and artificial intelligence. Círculo de Lingüística Aplicada a la Comunicación, 76, 13–30. https://doi.org/10.5209/clac.62495
Li, Banban. (2023). Individual differences in computer-assisted language learning research [Review of the book Individual differences in computer-assisted language learning research]. Studies in Second Language Learning and Teaching, 13(3). https://doi.org/10.14746/ssllt.38970
Liu, K. (2020). The trend of mobile-assisted language learning from 2014 to 2018. In Proceedings of the 2020 International Conference on Education, Culture and Management Innovation (ECEMI). Destech Publications. https://doi.org/10.12783/dtssehs/ecemi2020/34701
Martín-Martín, A., Orduna-Malea, E., Thelwall, M., & Delgado López-Cózar, E. (2018). Google Scholar, Web of Science, and Scopus: A systematic comparison of citations in 252 subject categories. Journal of Informetrics, 12(4), 1160–1177. https://doi.org/10.1016/j.joi.2018.09.002
Mongeon, P., & Paul-Hus, A. (2016). The journal coverage of Web of Science and Scopus: a comparative analysis. Scientometrics, 106(1), 213-228. https://doi.org/10.1007/s11192-015-1765-5
Mulyani, Y. P. (2021). The forty-year history of revenue management: Bibliometric analysis. OPSI, 14(1), 38. https://doi.org/10.31315/opsi.v14i1.4677
Podsakoff, P. M., MacKenzie, S. B., Podsakoff, N. P., & Bachrach, D. G. (2008). Scholarly influence in the field of management: A bibliometric analysis of the determinants of university and author impact in the management literature in the past quarter century. Journal of Management, 34(4), 641–720. https://doi.org/10.1177/0149206308319533
Qian, K., & Tang, J. (2018). Researching mobile-assisted English language learning among adult distance learners in China. International Journal of Computer-Assisted Language Learning and Teaching, 8(3), 1–28. https://doi.org/10.4018/ijcallt.2018070101
Schwienhorst, K. (2002). Why virtual, why environments? Implementing virtual reality concepts in computer-assisted language learning. Simulation & Gaming, 33(2), 196–209. https://doi.org/10.1177/1046878102332008
Shrestha, P. (2014). Innovations in learning technologies for English language teaching. System, 42, 474–475. https://doi.org/10.1016/j.system.2013.12.016
Su, F., & Zou, D. (2020). Technology-enhanced collaborative language learning: Theoretical foundations, technologies, and implications. Computer Assisted Language Learning, 35(8), 1754–1788. https://doi.org/10.1080/09588221.2020.1831545
Tamilmani, K. T., & Nagalakshmi, R. (2019). Embedding technology in curriculum design and development. International Journal of Innovative Technology and Exploring Engineering, 8(7C2), 252–256. http://dx.doi.org/10.2139/ssrn.3557543
Woo, J. H., & Choi, H. (2021). Systematic review for AI-based language learning tools. arXiv. https://doi.org/10.48550/arxiv.2111.04455
Xi, H. (2018). Improving communicative competence through synchronous communication
in computer-supported collaborative learning environments: A systematic review. Education Sciences, 8(1), 15. https://doi.org/10.3390/educsci8010015
Xue, H., Dai, F., Liu, G., Cao, P., & Huang, B. (2021). Edge computing: A systematic Mapping study. In Proceedings of the 2021 IEEE International Conferences. IEEE. https://doi.org/10.1109/dasc-picom-cbdcom-cyberscitech52372.2021.00090
Yang, F., Wen, J., & Qi, L. (2020). Information and communication technology in English language education: A review and future research directions. In Proceedings of the 5th International Conference on Education and Multimedia Technology (ICEMT). https://doi.org/10.2991/assehr.k.200306.134
Yazdi, A., Ramachandran, S., Mohsenifard, H., Nawaser, K., Sasani, F., & Gharleghi, B. (2024). The ebb and flow of brand loyalty: A 28-year bibliometric and content analysis. arXiv. https://doi.org/10.48550/arxiv.2402.13177
Yang, J. (2013). Mobile-assisted language learning: Review of the recent applications of emerging mobile technologies. English Language Teaching, 6(7), 19–25. https://doi.org/10.5539/elt.v6n7p19
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