The importance of artificial intelligence and intelligent generators in English language teaching in Law programs
Keywords:
artificial intelligence; legal English; legal education; feedback; AI literacyAbstract
Introduction: English education for Law students requires linguistic competence, professional communication, critical reading, and source verification. The spread of generative artificial intelligence provides tools capable of producing explanations, simulations, translations, feedback, and legal texts, but it also introduces plausible errors, nonexistent references, bias, and confidentiality risks. Materials and methods: A structured narrative review examined academic literature and institutional documents published between 2020 and September 2026, focusing on artificial intelligence in higher education, English as a foreign language, and legal education; findings were organized through thematic analysis. Results: The reviewed evidence indicates that these technologies can expand communicative practice, provide initial feedback, adapt activities, and facilitate simulations of client interviews, negotiation, legal argumentation, and oral advocacy. Discussion: Their educational value depends on instructional design that requires students to compare outputs with authentic legal sources, explain their revisions, and retain intellectual authorship; therefore, the PIVER pedagogical cycle is proposed: purpose, interaction, verification, revision, and use record. Conclusions: Artificial intelligence can strengthen legal English when it serves as a supervised formative aid rather than a substitute for reading, writing, legal reasoning, or professional responsibility.
References
American Bar Association. (2024). Formal opinion 512: Generative artificial intelligence tools. https://www.americanbar.org/content/dam/aba/administrative/professional_responsibility/ethics-opinions/aba-formal-opinion-512.pdf
Cotton, D. R. E., 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
Council of Europe. (2020). Common European Framework of Reference for Languages: Learning, teaching, assessment - Companion volume. Council of Europe Publishing. https://rm.coe.int/common-european-framework-of-reference-for-languages-learning-teaching/16809ea0d4
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., ... Wright, R. (2023). 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
European Commission. (2022). Ethical guidelines on the use of artificial intelligence and data in teaching and learning for educators. Publications Office of the European Union. https://op.europa.eu/en/publication-detail/-/publication/d81a0d54-5348-11ed-92ed-01aa75ed71a1
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., ... 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
Li, B., Lowell, V. L., Wang, C., & Li, X. (2025). A systematic review of empirical research on generative AI in language learning and teaching. System, 128, 103542. https://doi.org/10.1016/j.system.2024.103542
Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000386693
Munir, B. (2025). Integrating generative AI in legal pedagogy: A case study. International Journal of Legal Information, 53(1), 36-48. https://doi.org/10.1017/jli.2025.4
OECD. (2023). OECD Digital Education Outlook 2023: Towards an effective digital education ecosystem. OECD Publishing. https://doi.org/10.1787/c74f03de-en
OECD. (2026). OECD Digital Education Outlook 2026: Exploring effective uses of generative AI in education. OECD Publishing. https://doi.org/10.1787/062a7394-en
Teng, M. F. (2024). A systematic review of ChatGPT for English as a foreign language writing: Opportunities, challenges, and recommendations. International Journal of TESOL Studies, 6(3), 36-57. https://doi.org/10.58304/ijts.20240304
Yan, L., Sha, L., Zhao, L., Li, Y., Martinez-Maldonado, R., Chen, G., Li, X., Jin, Y., & Gašević, D. (2024). Practical and ethical challenges of large language models in education: A systematic scoping review. British Journal of Educational Technology, 55(1), 90-112. https://doi.org/10.1111/bjet.13370
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