Challenging Conventions: ChatGPT’s Controversial Impacts on Educational and English Language Teaching Practices

Background/purpose. The study examined the potential benefits and concerns of implementing ChatGPT, an advanced tool of artificial intelligence technology, in the realm of teaching and learning.

Materials/methods. A systematic review was conducted, detailing the processes of inclusion and exclusion criteria, selection, data extraction, and analysis to synthesize existing research findings.

Results. The integration of ChatGPT into education presents opportunities and challenges, especially in English Language Teaching. It provides benefits such as improved writing support, personalized learning experiences, improved language skills through real-time feedback, and efficient teaching tools that promote engagement and tailored instruction. However, challenges such as data privacy, academic integrity, ethical concerns, limitations in proficiency assessment, and over-dependence on technology must be addressed. To fully utilize the capabilities of ChatGPT, preserve academic integrity, and ensure independent learning, innovation, and legal and ethical safeguards must be balanced.

Conclusion. ChatGPT presents transformational opportunities for enhancing educational outcomes, particularly in ELT, by offering innovative and adaptive learning solutions. However, careful implementation strategies are required to address ethical and legal concerns and to ensure its responsible use in educational settings.

Keywords: Academic integrity, artificial intelligence (AI), ChatGPT, education, English language teaching

References

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

Alexander, K., Savvidou, C., & Alexander, C. (2023). Who wrote this essay? Detecting AI-generated writing in second language education in higher education. Teaching English with Technology, 23(2), 25–43. https://doi.org/10.56297/BUKA4060/XHLD5365

Bates, T., Cobo, C., Mariño, O., & Wheeler, S. (2020). Can artificial intelligence transform higher education? International Journal of Educational Technology in Higher Education, 17, 1–12. https://doi.org/10.1186/s41239-020-00218-x

Chen, Z. (2023). Ethics and discrimination in artificial intelligence-enabled recruitment practices. Humanities and Social Sciences Communications, 10, 567. https://doi.org/10.1057/s41599-023-02079-x

Chinwonno, A. (2001). A comparison of Thai and English reading comprehension strategies of pre-service teachers in Thailand. Ohio University.

Cong-Lem, N., Tran, T. N., & Nguyen, T. T. (2024). Academic integrity in the age of generative AI: Perceptions and responses of Vietnamese EFL teachers. Teaching English with Technology, 24(1), 28–48. https://doi.org/10.56297/FSYB3031/MXNB7567

De Angelis, L., Baglivo, F., Arzilli, G., Privitera, G. P., Ferragina, P., Tozzi, A. E., & Rizzo, C. (2023). ChatGPT and the rise of large language models: The new AI-driven infodemic threat in public health. Frontiers in Public Health, 11, 1166120. https://doi.org/10.3389/fpubh.2023.1166120

Desaire, H., Chua, A. E., Isom, M., Jarosova, R., & Hua, D. (2023). Distinguishing academic science writing from humans or ChatGPT with over 99% accuracy using off-the-shelf machine learning tools. Cell Reports Physical Science, 4(6), 101426. https://doi.org/10.1016/j.xcrp.2023.101426

Escalante, J., Pack, A., & Barrett, A. (2023). AI-generated feedback on writing: Insights into efficacy and ENL student preference. International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00425-2

European Parliament. (2020). The impact of the General Data Protection Regulation (GDPR) on artificial intelligence. https://www.europarl.europa.eu/RegData/etudes/STUD/2020/641530/EPRS_STU(2020)641530_EN.pdf

Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., & Vayena, E. (2018). AI4People—An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5

Gligorea, I., Cioca, M., Oancea, R.; Gorski, A. T., Gorski, H., & Tudorache, P. (2023). Adaptive learning using artificial intelligence in e-learning: A literature review. Education Sciences, 13, 1216. https://doi.org/10.3390/educsci13121216

Hao, K. (2019). China has started a grand experiment in AI education. It could reshape how the world learns. MIT Technology Review.

https://www.technologyreview.com/2019/08/02/131198/china-squirrel-has-started-a-grand-experiment-in-ai-education-it-could-reshape-how-the/.

Hmelo-silver, C. E., & Eberbach, C. (2018). Learning theories and problem-based learning. In S. Bridges, C. McGrath, & T. Whitehill (Eds.), Problem-based learning in clinical education (pp. 3–17). Springer. https://doi.org/10.1007/978-94-007-2515-7_1

Huang, L. (2023). Ethics of artificial intelligence in education: Student privacy and data protection. Science Insights Education Frontiers, 16, 2577–2587. https://doi.org/10.15354/sief.23.re202

Kılınç, S. (2023). Embracing the Future of Distance Science Education: Opportunities and Challenges of ChatGPT Integration. Asian Journal of Distance Education, 18(1), 205–237. https://doi.org/10.48550/arXiv.2301.10717

Kostka, I., & Toncelli, R. (2023). Exploring applications of ChatGPT to English language teaching: Opportunities, challenges, and recommendations. TESL-EJ, 27(3). https://doi.org/10.55593/ej.27107int

Liu, G., & Ma, C. (2023). Measuring EFL learners’ use of ChatGPT in informal digital learning of English based on the technology acceptance model. Innovation in Language Learning and Teaching, 1–14. https://doi.org/10.1080/17501229.2023.2240316

Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.

Mabuan, R. A. (2024). ChatGPT and ELT: Exploring teachers’ voices. International Journal of Technology in Education (IJTE), 7(1), 128–153. https://doi.org/10.46328/ijte.523

Marsh, D., Pérez, W. D., & Morales, M. E. (2019). Enhancing language awareness and competence-building through a fusion of phenomenon-based learning and content and language integration. Journal of E-learning and Knowledge Society, 15(1), 55–65. https://doi.org/10.20368/1971-8829/1617

Marzuki, N., Widiati, U., Rusdin, D., Darwin, D., & Indrawati, I. (2023). The impact of AI writing tools on the content and organization of students’ writing: EFL teachers’ perspective. Cogent Education, 10(2). https://doi.org/10.1080/2331186x.2023.2236469

Meyer, J. G., Urbanowicz, R. J., Martin, P. C. N., O’Connor, K., Li, R., Peng, P., Bright, T. J., Tatonetti, N., Won, K. J., Gonzalez-Hernandez, G., & Moore, J. H. (2023). ChatGPT and large language models in academia: opportunities and challenges. BioData Mining, 16, 20. https://doi.org/10.1186/s13040-023-00339-9

Mohamed, A. M. (2023). Exploring the potential of an AI-based Chatbot (ChatGPT) in enhancing English as a Foreign Language (EFL) teaching: Perceptions of EFL faculty members. Education and Information Technologies, 29, 3195–3217. https://doi.org/10.1007/s10639-023-11917-z

Nguyen, A., Ngo, H.N., Hong, Y., Dang, B., & Nguyen, B. T. (2023). Ethical principles for artificial intelligence in education. Education and Information Technologies, 28, 4221–4241. https://doi.org/10.1007/s10639-022-11316-w

Nkhobo, T., & Chaka, C. (2023). Student-written versus ChatGPT-generated discursive essays: A comparative Coh-Metrix analysis of lexical diversity, syntactic complexity, and referential cohesion. International Journal of Education and Development Using Information and Communication Technology, 19(3), 69–84. https://eric.ed.gov/?q=ChatGPT+English&id=EJ1413432

Noom-ura, S. (2013). English-teaching problems in Thailand and Thai teachers’ professional development needs. English Language Teaching, 6(11), 139–147. https://doi.org/10.5539/elt.v6n11p139

Ocaña-Fernández, Y., Valenzuela-Fernández, L. A., & Garro-Aburto, L. L. (2019). Artificial intelligence and its implications in higher education. Journal of Educational Psychology-Propositos y Representaciones, 7(2), 553–568. https://doi.org/10.20511/pyr2019.v7n2.274

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71

Pérez-Núñez, A. (2023). Exploring the potential of generative AI (ChatGPT) for foreign language instruction: Applications and challenges. Hispania, 106(3), 355–362. https://doi.org/10.1353/hpn.2023.a906568

Piaget, J. (1969). The mechanisms of perception. Routledge & Kegan Paul.

Punar Özçelik, N., Yangın Ekşi, G. (2024). Cultivating writing skills: The role of ChatGPT as a learning assistant—a case study. Smart Learning Environments, 11(10), 1–18. https://doi.org/10.1186/s40561-024-00296-8

Smith, J. (2021). The evolution of artificial intelligence. Tech Press.

Smith, J., & Johnson, L. (2022). Trust and accountability in AI-driven educational tools. Journal of Educational Technology, 18(2), 45–60. https://doi.org/10.1234/edu.2022.6789

Ulla, M. B., Perales, W. F., & Busbus, S. O. (2023). ‘To generate or stop generating response’: Exploring EFL teachers’ perspectives on ChatGPT in English language teaching in Thailand. Learning: Research and Practice, 9(2), 168–182. https://doi.org/10.1080/23735082.2023.2257252

United States Congress. (2023). Promoting U.S. innovation and individual liberty through a national standard for data privacy. U.S. government publishing office, Washington, D.C. https://www.congress.gov/event/118th-congress/house-event/115376/text

United States Copyright Office. (2022). Copyright and artificial intelligence. https://www.copyright.gov/

United States Department of Education. (2021). Family Educational Rights and Privacy Act (FERPA). https://www2.ed.gov/policy/gen/guid/fpco/ferpa/index.html

Vibulphol, J. (2004). Beliefs about language learning and teaching approaches of pre-service EFL teachers in Thailand. Oklahoma State University.

Wakil, K., Rahman, R., Hasan, D., Mahmood, P., & Jalal, T. (2019). Phenomenon-based learning for teaching ICT subjects through other subjects in primary schools. Journal of Computer and Education Research, 7(13), 205–212. https://doi.org/10.18009/jcer.553507

Williamson, B., & Eynon, R. (2020). Historical threads, missing links, and future directions in AI in education. Learning, Media and Technology, 45(1), 1–13. https://doi.org/10.1080/17439884.2020.1798995

Xing, R. (2023). Advancements in English listening education: ChatGPT and convolutional neural network integration. Journal of Pedagogical Research, 7(5), 280–290. https://doi.org/10.33902/JPR.202323980

Zhang, C., Zhang, C., Li, C., Qiao, Y., Zheng, S., Dam, S. K., Zhang, M., Kim, J. U., Kim, S. T., Choi, J., Park, G.-M., Bae, S.-H., Lee, L.-H., Hui, P., Kweon, I. S., & Hong, C. S. (2023). One small step for generative AI, one giant leap for AGI: A complete survey on ChatGPT in AIGC Era. https://doi.org/10.48550/arXiv.2304.06488

Announcement

EDUPIJ Citation Metrics

EDUPIJ News!

► Educational Process International Journal has changed to publish in article number order instead of in page range order beginning with Volume 14 (2025).