Artificial Intelligence in Language Education: A Bibliometric Analysis

Author:

Jaleniauskienė Evelina1,Lisaitė Donata2,Daniusevičiūtė-Brazaitė Laura3

Affiliation:

1. 1 Kaunas University of Technology , Lithuania

2. 2 University of Antwerp , Belgium , Kaunas University of Technology , Lithuania

3. 3 Kaunas University of Technology , Lithuania

Abstract

Abstract Artificial Intelligence (AI) occupies a transforming role in education, including language teaching and learning. Using bibliometric analysis, this study aims to overview the most recent research related to the use of AI in language education. Specifically, it reviews the existing body of research, productivity in this field in terms of authors and countries, co-authorship, most cited references and most popular journals that publish on this topic. Furthermore, the study also analyses the most common keywords and extracts relevant terms that reveal trending topics. For the period between 2018 and 2022, 2,609 documents were retrieved from the Web of Science database. The results showed that each year a consistent number of publications on the application of AI in language education appears. Scholars from China and the USA have been revealed to be most productive. Computer Assisted Language Learning contains the highest number of publications. Within the research on the use of AI in language education, the most targeted language-learning aspects were acquisition, motivation, performance, vocabulary, instruction, feedback, and impact. The analysis of the most common keywords related to AI-based solutions showed that mobile-assisted language learning, virtual reality, augmented reality, elements of gamification, games, social robots, machine translation, intelligent tutoring systems, chatbots, machine learning, neural networks, automatic speech recognition, big data, and deep learning were most popular.

Publisher

Walter de Gruyter GmbH

Subject

Linguistics and Language,Language and Linguistics

Reference31 articles.

1. Aoun, J. E. (2017). Robot-Proof: Higher Education in the Age of Artificial Intelligence. MIT Tab

2. Becker, S. A., Brown, M., Dahlstrom, E., Davis, A., DePaul, K., Diaz, V., & Pomerantz, J. (2018). NMC Horizon Report: 2018 Higher Education Edition. Louisville, CO: EDUCAUSE, 2018. https://library.educause.edu/~/media/files/library/2018/8/2018horizonreport.pdf

3. Chen, X., Zou, D., Cheng, G., & Xie, H. (2021, July). Artificial intelligence-assisted personalized language learning: systematic review and co-citation analysis. 2021 International Conference on Advanced Learning Technologies (ICALT) (pp. 241–245). IEEE. https://doi.org/10.1109/icalt52272.2021.00079

4. Chen, X., Zou, D., Xie, H., Cheng, G., & Liu, C. (2022). Two Decades of Artificial Intelligence in Education: Contributors, Collaborations, Research Topics, Challenges, and Future Directions. Educational Technology & Society, 25(1), 28–47. https://www.jstor.org/stable/48647028

5. Chu, H.-C., Hwang, G.-H., Tu, Y.-F., & Yang, K.-H. (2022). Roles and research trends of artificial intelligence in higher education: A systematic review of the top 50 most-cited articles. Australasian Journal of Educational Technology, 15–35. https://doi.org/10.14742/ajet.7526

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