Beyond the Dictionary: EFL Students’ Attitudes and Perceptions Towards Generative AI for Medical Terminology Acquisition
DOI:
https://doi.org/10.55544/ijrah.6.5.2Keywords:
English as a Foreign Language (EFL), Generative Artificial Intelligence (GenAI), Medical TerminologyAbstract
Conventional medical dictionaries often fall short of the learning needs of EFL students seeking to acquire specialised vocabulary. However, Generative Artificial Intelligence (GenAI) offers a faster way to learn new words in this digital era. This preliminary feasibility pilot study investigates the perceptions and attitudes of first-year allied medical sciences students (N=10) towards Generative AI applications for medical vocabulary acquisition. A survey-based approach was used with 10 students, and the data were analysed quantitatively and qualitatively to assess student sentiment, trends in AI tools, and specific vocabulary acquisition practices. GenAI is effective for language acquisition in general, but it is worth exploring how confident students in healthcare disciplines are in using GenAI for medical terms.
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] Al-Obaydi, L. H., Pikhart, M., & Hossain, M. K. (2025). ChatGPT and the development of core language skills: An exploratory study of EFL college students. Contemporary Educational Technology, 17(4), Article ep591. https://doi.org/10.30935/cedtech/17242
Al-Sofi, B. B. M. A. (2024). Artificial intelligence-powered tools and academic writing: to use or not to use ChatGPT. Saudi Journal of Language Studies,4(3),145–161. https://doi.org/10.1108/SJLS-06-2024-0029
Hsu, M. (2023). Mastering medical terminology with ChatGPT and Termbot. Health Education Journal, 83, 352–358. https://doi.org/10.1177/0017896923119737
Li, J., Zong, H., Wu, E., Wu, R., Peng, Z., Zhao, J., Yang, L., Xie, H., & Shen, B. (2024). Exploring the potential of artificial intelligence to enhance the writing of English academic papers by non-native English-speaking medical students - the educational application of ChatGPT. BMC Medical Education, 24(1), 736. https://doi.org/10.1186/s12909-024-05738-y
Omar, A. (2025). Proceedings of the E-Learning and Smart Engineering Systems (ELSES 2025). Atlantis Highlights in Social Sciences, Education and Humanities, 46. https://doi.org/10.2991/978-94-6239-634-0_18
Park, G. E., Kim, H., & Go, U. R. (2024). Generative artificial intelligence in nursing: A scoping review. Collegian, 31. https://doi.org/10.1016/j.colegn.2024.10.004
Sami, A., Tanveer, F., Sajwani, K., Kiran, N., Javed, M. A., Ozsahin, D. U., Muhammad, K., & Waheed, Y. (2025). Medical students’ attitudes toward AI in education: perception, effectiveness, and its credibility. BMC Medical Education, 25(1), Article 82. https://doi.org/10.1186/s12909-025-06704-y
Takai, K. (2025). Exploring AI’s Role in English Education for Medical Students. Vol. 51, pp. 35–44. https://doi.org/10.57457/0002000216
Tran, C., Hryciw, B. N., Moore, S. W., Chaput, A., & Seely, A. J. E. (2025). Perceptions and Use of Generative Artificial Intelligence in Medical Students: A Multicenter Survey. Journal of Medical Education and Curricular Development, 12, 23821205251391969. https://doi.org/10.1177/23821205251391969
Turney, J., Young, T. M., Chauhan, D. R., Beeharry, R., & Mahmud, M. (2026). AI Use for Medical Students: Impact on Clinical Skill Acquisition and Retention. A Systematic Review. Advances in Medical Education and Practice. https://doi.org/10.2147/AMEP.S583763
Wulff H. R. (2004). The language of medicine. Journal of the Royal Society of Medicine, 97(4),187–188. https://doi.org/10.1177/014107680409700412
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