Transforming Translation Education: A Bibliometric Analysis of Artificial Intelligence’s Role in Fostering Sustainable Development

Zhou Bo, Lim Seong Pek, Wang Cong, Lu Tiannan, Hariharan N Krishnasamy, Khairul Firdaus Ne'matullah, Hala Arar

Abstract


This bibliometric analysis focused on the potential and difficulties of implementing artificial intelligence (AI) in translation education. This study aligns with Sustainable Development Goal 4 (Quality Education), whichemphasizes inclusive and equitable learning opportunities. It investigated the effects of AI tools on teaching methods, student engagement, and language skill development,including generative artificial intelligence (generative AI).Through co-citation and co-occurrence analysis of 281 Web of Science articles (2020–2024), this study identified key research trends, gaps, and interdisciplinary linkages. While AI research in education was extensive, its application in translation education remained fragmented and lacked a cohesive theoretical framework. This study extended AI adoption models by incorporating ethical considerations and pedagogical challenges, addressing gaps in prior research. The findings highlighted the need for institutional support, targeted training, and interdisciplinary cooperation to facilitate AI integration. This study identified gaps in AI-driven translation pedagogy and proposed a framework to enhance integration, particularly in teaching methodologies, ethics, and interdisciplinary collaboration. While AI fosters creativity in curriculum design, personalized learning, and multilingual communication, over-reliance on AI tools may weaken language proficiency. To address inequalities in AI access, inclusive and ethical AI integration strategies aligned with Sustainable Development Goal 10 (Reduced Inequalities) are crucial. This study reinforced the importance of institutional support, targeted training, and resource development to ensure sustainable AI adoption in translation education. It calls for informed policies and interdisciplinary cooperation to advance sustainable and equitable education while optimizing AI-driven learning environments.

https://doi.org/10.26803/ijlter.24.3.9


Keywords


artificial intelligence; translation education; ethics; sustainability

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References


Ad?güzel, T., Kaya, M. H., & Cansu, F. K. (2023). Revolutionizing education with AI: Exploring the transformative potential of ChatGPT. Contemporary Educational Technology. https://doi.org/10.30935/cedtech/13152

Akgun, S., & Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI and Ethics, 2(3), 431-440. https://doi.org/10.1007/s43681-021-00096-7

Amaro, V., & João Pires, M. (2024). Found in translation, lost in education: Artificial intelligence’s impacts on translation tertiary education in Macao. Asian Education and Development Studies, 13(4), 269–281. https://doi.org/10.1108/AEDS-01-2024-0012

Almogren, A. S., & Aljammaz, N. A. (2022). The integrated social cognitive theory with the TAM model: The impact of M-learning in King Saud University art education. Frontiers in Psychology, 13, 1050532. http://dx.doi.org/10.3389/fpsyg.2022.1050532

Baidoo-Anu, D., & Ansah, L. O. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 7(1), 52-62. https://doi.org/10.61969/jai.1337500

Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., ... & Amodei, D. (2020). Language models are few-shot learners. Advances in neural information processing systems, 33, 1877-1901. https://proceedings.neurips.cc/paper/2020/hash/1457c0d6bfcb4967418bfb8ac142f64a-Abstract.html

Celik, I., Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The promises and challenges of artificial intelligence for teachers: A systematic review of research. TechTrends, 66(4), 616-630. https://doi.org/10.1007/s11528-022-00715-y

Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1), 43. http://dx.doi.org/10.1186/s41239-023-00411-8

Chan, C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International journal of educational technology in higher education, 20(1), 38. http://dx.doi.org/10.1186/s41239-023-00408-3

Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264-75278. https://doi.org/10.1109/access.2020.2988510

Chiu, T. K. (2023). The impact of Generative AI (GenAI) on practices, policies and research direction in education: A case of ChatGPT and Midjourney. Interactive Learning Environments, 1-17. http://dx.doi.org/10.1080/10494820.2023.2253861

Cooper, G. (2023). Examining science education in ChatGPT: An exploratory study of generative artificial intelligence. Journal of Science Education and Technology, 32(3), 444-452. https://doi.org/10.1007/s10956-023-10039-y

Cotton, D. R., Cotton, P. A., & Shipway, J. R. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in education and teaching international, 61(2), 228-239. https://doi.org/10.1080/14703297.2023.2190148

Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., ... & Wright, R. (2023). Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642

Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019). Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model. Information systems frontiers, 21, 719-734. https://doi.org/10.1007/s10796-017-9774-y

Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2024). A SWOT analysis of ChatGPT: Implications for educational practice and research. Innovations in Education and Teaching International, 61(3), 460-474. https://doi.org/10.1080/14703297.2023.2195846

Gilson, A., Safranek, C. W., Huang, T., Socrates, V., Chi, L., Taylor, R. A., & Chartash, D. (2023). How does ChatGPT perform on the United States Medical Licensing Examination (USMLE)? The implications of large language models for medical education and knowledge assessment. JMIR medical education, 9(1), e45312. https://doi.org/10.2196/45312

Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S. B., ... & Koedinger, K. R. (2022). Ethics of AI in education: Towards a community-wide framework. International Journal of Artificial Intelligence in Education, 1-23. https://doi.org/10.1007/s40593-021-00239-1

Huang, W., Hew, K. F., & Fryer, L. K. (2022). Chatbots for language learning—Are they really useful? A systematic review of chatbot?supported language learning. Journal of Computer Assisted Learning, 38(1), 237-257. https://doi.org/10.1111/jcal.12610

Hwang, G. J., & Chang, C. Y. (2023). A review of opportunities and challenges of chatbots in education. Interactive Learning Environments, 31(7), 4099-4112. https://doi.org/10.1080/10494820.2021.1952615

Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., ... & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and individual differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274

Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). ChatGPT for language teaching and learning. Relc Journal, 54(2), 537-550. https://doi.org/10.1177/00336882231162868

Liu, K., & Afzaal, M. (2021). Artificial intelligence (AI) and translation teaching: A critical perspective on the transformation of education. International Journal of Education and Science, 33(1-3), 64-73. https://doi.org/10.31901/24566322.2021/33.1-3.1159

Lim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I., & Pechenkina, E. (2023). Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators. The international journal of management education, 21(2), 100790. http://dx.doi.org/10.1016/j.ijme.2023.100790

Li, R., Nawi, A. M., & Kang, M. S. (2023). Human-machine Translation Model Evaluation Based on Artificial Intelligence Translation. EMITTER International Journal of Engineering Technology, 11(2), 145-159. https://doi.org/10.24003/emitter.v11i2.812

Lo, C. K. (2023). What is the impact of ChatGPT on education? A rapid review of the literature. Education Sciences, 13(4), 410. https://doi.org/10.3390/educsci13040410

Long, D., & Magerko, B. (2020, April). What is AI literacy? Competencies and design considerations. In Proceedings of the 2020 CHI conference on human factors in computing systems (pp. 1-16). https://doi.org/10.1145/3313831.3376727

Luan, H., Geczy, P., Lai, H., Gobert, J., Yang, S. J., Ogata, H., ... & Tsai, C. C. (2020). Challenges and future directions of big data and artificial intelligence in education. Frontiers in psychology, 11, 580820. https://doi.org/10.3389/fpsyg.2020.580820

Nazaretsky, T., Ariely, M., Cukurova, M., & Alexandron, G. (2022). Teachers' trust in AI?powered educational technology and a professional development program to improve it. British journal of educational technology, 53(4), 914-931. https://doi.org/10.1111/bjet.13232

Ouyang, F., Zheng, L., & Jiao, P. (2022). Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020. Education and Information Technologies, 27(6), 7893-7925. https://doi.org/10.1007/s10639-022-10925-9

Shin, D. (2020). User perceptions of algorithmic decisions in the personalized AI system: Perceptual evaluation of fairness, accountability, transparency, and explainability. Journal of Broadcasting & Electronic Media, 64(4), 541-565. https://doi.org/10.1080/08838151.2020.1843357

Su, J., & Yang, W. (2023). Unlocking the power of ChatGPT: A framework for applying generative AI in education. ECNU Review of Education, 6(3), 355-366. https://doi.org/10.1177/20965311231168423

Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart learning environments, 10(1), 15. https://doi.org/10.1186/s40561-023-00237-x

Wang, Y. (2023). Artificial Intelligence technologies in college English translation teaching. Journal of psycholinguistic research, 52(5), 1525-1544. https://doi.org/10.1007/s10936-023-09960-5

Williamson, B., & Eynon, R. (2020). Historical threads, missing links, and future directions in AI in education. Learning, Media and Technology, 45(3), 223-235. https://doi.org/10.1080/17439884.2020.1798995

Wider, W., Jiang, L., Lin, J., Fauzi, M. A., Li, J., & Chan, C. K. (2024). Metaverse chronicles: a bibliometric analysis of its evolving landscape. International Journal of Human–Computer Interaction, 40(17), 4873-4886. https://doi.org/10.1080/10447318.2023.2227825

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education–where are the educators?. International Journal of Educational Technology in Higher Education, 16(1), 1-27. https://doi.org/10.1186/s41239-019-0171-0

Zhai, X., Chu, X., Chai, C. S., Jong, M. S. Y., Istenic, A., Spector, M., ... & Li, Y. (2021). A Review of Artificial Intelligence (AI) in Education from 2010 to 2020. Complexity, 2021(1), 8812542. https://doi.org/10.1155/2021/8812542


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