Exploring Omani EFL Student Teachers’ Perceptions on Fostering Critical Thinking Through Ethical Use of AI

Background/purpose. This study explores the perceptions of Omani pre-service EFL teachers on promoting critical thinking through the ethical use of AI. The rationale of this study is to better understand the perceived strengths and training needs of pre-service teachers regarding the use of AI, which can improve future educational policy and practice.

Materials/methods. A mixed methods approach is employed in this research, which combines a quantitative analysis of survey data with qualitative insights from focus group discussions to examine how AI ethics affect critical thinking and teaching practices. Data was collected from 83 EFL pre-service teachers at the University of Technology and Applied Sciences, Rustaq College, Oman.

Results. The most notable finding to emerge from the analysis is a strong awareness of AI ethics among EFL pre-service teachers, with a particular emphasis on data protection, academic integrity, and the balanced use of AI to enhance critical thinking. However, challenges like integrating AI ethics into curricula, a lack of sufficient resources, and limited expertise were identified.

Conclusion. This study underlines the importance of institutional support when integrating AI ethics into education and fostering critical thinking skills, ensuring AI acts as an enabler rather than a hindrance to the educational experience.

Keywords: AI, EFL students’ teachers, AI ethics, critical thinking

References

Alasadi, E. A. & Baiz, C. R. (2023). Generative AI in education and research: Opportunities, concerns, and solutions. Journal of Chemical Education, 100(8), 2965–2971.‏ https://pubs.acs.org/doi/abs/10.1021/acs.jchemed.3c00323

Alshamy, A., Al-Harthi, A. S. A., & Abdullah, S. (2025). Perceptions of Generative AI Tools in Higher Education: Insights from Students and Academics at Sultan Qaboos University. Education Sciences, 15(4), 501. https://doi.org/10.3390/educsci15040501

Alhalangy, A., & AbdAlgane, M. (2023). Exploring the Impact of AI on The EFL Context: A Case Study of Saudi Universities. Journal of Intercultural Communication, 23(2), 41–49. https://doi.org/10.36923/jicc.v23i2.125

Alhudithi, E. (2021). Review of Voyant tools: See through your text. Language Learning and Technology, 25(3), 43–50. https://scholarspace.manoa.hawaii.edu/server/api/core/bitstreams/05516ef7-dd9e-4461-a1c7-14eb895d740e/content

Allahrakha, N. (2024). UNESCO's AI Ethics Principles: Challenges and Opportunities. International Journal of Law and Policy, 2, 24–36. http://dx.doi.org/10.59022/ijlp.225

Alwaqdani, M. (2025) Investigating teachers’ perceptions of artificial intelligence tools in education: potential and difficulties. Education and Information Technologies, 30, 2737–2755. https://doi.org/10.1007/s10639-024-12903-9

Bélisle Pipon, J.C. & Victor, G. (2024). Ethics dumping in artificial intelligence. Frontiers in artificial intelligence, 7, 1426761. http://dx.doi.org/10.3389/frai.2024.1426761

Bin-Nashwan, S. A., Sadallah, M. & Bouteraa, M. (2023). Use of ChatGPT in academia: Academic integrity hangs in the balance. Technology in Society, 75, 102370.‏ https://doi.org/10.1016/j.techsoc.2023.102370

Börekci, C. & Çelik, Ö. (2024). Exploring The Role of Digital Literacy in University Students' Engagement with AI through the Technology Acceptance Model. Sakarya University Journal of Education, 14. http://dx.doi.org/10.19126/suje.1468866

Bu, Q. (2022). Ethical Risks in Integrating Artificial Intelligence into Education and Potential Countermeasures. Science Insights, 41. 561–566. https://doi.org/10.15354/si.22.re067

Campbell, M., Ferguson, E., Herzinger, V., Jackson, N., & Marino, A. (2004). Combined descriptive and explanatory information improves peers’ perceptions of autism. Research in Developmental Disabilities, 25(4), 321–339. https://doi.org/https://doi.org/10.1016/j.ridd.2004.01.005

Celik, I. (2023). Exploring the determinants of artificial intelligence (AI) literacy: Digital divide, computational thinking, cognitive absorption. Telematics and Informatics, 83, 102026.‏ https://doi.org/10.1016/j.tele.2023.102026

Cerný, M. (2024). University Students’ Conceptualisation of AI Literacy: Theory and Empirical Evidence. Social Sciences, 13(129), 1–26. https://doi.org/https://doi.org/ 10.3390/socsci13030129

Chaaban, Y., Qadhi, S., Chen, J., & Du, X. (2024). Understanding Researchers’ AI Readiness in a Higher Education Context: Q Methodology Research. Education Sciences, 14(709), 1–19. https://doi.org/10.3390/educsci14070709

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. https://link.springer.com/article/10.1186/s41239-023-00408-3‏

Chen, H. (2024). The Ethical Challenges of Educational Artificial Intelligence and Coping Measures: A Discussion in the Context of the 2024 World Digital Education Conference. Science Insights Education Frontiers, 2(20) 3263–3281. https://doi.org/10.15354/sief.24.re339

Chisega-Negrilǎ, A. (2024). Teaching and Learning in an AI-powered world. Bulletin of Carol I National Defence University, 13(3), 105–116. https://doi.org/10.53477/2284-9378-24-33

Choi, J., Yang, E. & Goo, E. (2024). The Effects of an Ethics Education Program on Artificial Intelligence among Middle School Students: Analysis of Perception and Attitude Changes. Applied Sciences, 14(4), 1588. https://doi.org/10.3390/app14041588

Ciampa, K., Wolfe, Z. M. & Bronstein, B. (2023). ChatGPT in education: Transforming digital literacy practices. Journal of Adolescent & Adult Literacy, 67(3), 186–195.‏ https://doi.org/10.1002/jaal.1310

Creswell, J. W. & Creswell, J. D. (2023). Research design: Qualitative, quantitative and mixed-methods approaches (6th Ed.). SAGE Publications Inc.

Creswell, J. W., & Plano Clark, V. L. (2018). Designing and Conducting Mixed Methods Research (3rd ed.). Thousand Oaks, CA: SAGE.

Dakakni, D. & Safa, N. (2023). Artificial intelligence in the L2 classroom: Implications and challenges on ethics and equity in higher education: A 21st century Pandora's box. Computers and Education. Artificial Intelligence, 5, 100179. https://doi.org/10.1016/j.caeai.2023.100179

Diyenti Rusdin, D., Mukminatien, N., Suryati, N., Laksmi, E. D., & Marzuki. (2024). Critical thinking in the AI era: An exploration of EFL students’ perceptions, benefits, and limitations. Cogent Education, 11(1), 2290342. http://doi.org/10.1080/2331186X.2023.2290342

Ditta, A. & Aslam, M., (2025). Education in the AI Age: Navigating Challenges of Generative AI Integration. LatIA, 3, 327 http://dx.doi.org/10.13140/RG.2.2.21078.05445

Fadlelmula, F. & Qadhi, S. (2024). A systematic review of research on artificial intelligence in higher education: Practice, gaps, and future directions in the GCC. Journal of University Teaching and Learning Practice, 21(6), 1–28. https://doi.org/10.53761/pswgbw82

Ferrara, E. (2024). The butterfly effect in artificial intelligence systems: Implications for AI bias and fairness. Machine Learning with Applications, 15, 100525.‏ https://doi.org/10.1016/j.mlwa.2024.100525

Habib, S., Vogel, T., Anli, X., & Thorne, E. (2024). How does generative artificial intelligence impact student creativity? Journal of Creativity, 34(1), 100072.‏ https://doi.org/10.1016/j.yjoc.2023.100072

Hassan, B. (2024). AI in Higher Education: Balancing Pedagogical Benefits and Ethical Challenges. Science Step Journal II, 5, 302-322.

Henriksen, D., Creely, E., Gruber, N., & Leahy, S. (2025). Social-Emotional Learning and Generative AI: A Critical Literature Review and Framework for Teacher Education. Journal of Teacher Education. 1–17. https://doi.org/10.1177/00224871251325058

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, 32(3), 504–526. https://doi.org/10.1007/s40593-021-00239-1

Huang, L. (2023). Ethics of Artificial Intelligence in Education: Student Privacy and Data Protection. Science Insights Education Frontiers. 16(2). 2–577-2587. https://doi.org/10.15354/sief.23.re202

Hysaj, A., Freeman, M. & Hamam, D. (2024). Using AI Tools to Enhance Academic Writing and Maintain Academic Integrity. In Proceedings of International Conference on Human-Computer Interaction (pp. 57–66). Cham: Springer Nature Switzerland.‏

Ifenthaler, D., Majumdar, R., Gorissen, P., Judge, M., Mishra, S., Raffaghelli, J., & Shimada, A. (2024). Artificial Intelligence in Education: Implications for Policymakers, Researchers, and Practitioners. Technology, Knowledge and Learning, 29, 1693–1710. https://doi.org/10.1007/s10758-024-09747-0

Khreisat, M. N., Khilani, D., Rusho, M. A., Karkkulainen, E. A., Tabuena, A. C. & Uberas, A. D. (2024). Ethical Implications of AI Integration in Educational Decision Making: Systematic Review. Educational Administration: Theory and Practice, 30(5), 8521–8527.‏ https://doi.org/10.53555/kuey.v30i5.4406

Kong, S., Cheung, W. & Zhang, G. (2022). Evaluating an Artificial Intelligence Literacy Programme for Developing University Students’ Conceptual Understanding, Literacy, Empowerment and Ethical Awareness. Educational Technology & Society, 26(1), 16–30. https://www.jstor.org/stable/48707964

Kwak, Y., Ahn, J., & Seo, Y. (2022). Influence of AI ethics awareness, attitude, anxiety, and self-efficacy on nursing students’ behavioral intentions. BMC Nursing, 21(267), 1–8. https://doi.org/10.1186/s12912-022-01048-0

Li, L., Sha, L., Li, Y., Raković, M., Rong, J., Joksimovic, S., & Chen, G. (2023). Moral machines or tyranny of the majority? A systematic review on predictive bias in education. In Proceedings of the 13th International Learning Analytics and Knowledge Conference (LAK23) (pp. 499–508).‏ https://doi.org/10.1145/3576050.3576119

Liang, Yi. (2023). Balancing: The Effects of AI Tools in Educational Context. Frontiers in Humanities and Social Sciences, 3, 7–10. http://doi.org/10.54691/fhss.v3i8.5531.

Mackey, A. & Gass, S. (2005). Second language research: Methodology and design. Lawrence Erlbaum Associates: Mahawah, New Jersey.

Masum, M. R., & Training, T. (2024). AI Ethics Certification Course Online by Tonex – CAEGP. http://doi.org/10.13140/RG.2.2.14141.06883.

Miao, J., Thongprayoon, C., Suppadungsuk, S., Valencia, O., Qureshi, F., & Cheungpasitporn, W. (2024). Ethical Dilemmas in Using AI for Academic Writing and an Example Framework for Peer Review in Nephrology Academia: A Narrative Review. Clinic & Practice, 14(1), 89–105. https://doi.org/10.3390/clinpract14010008

Murat, T. Ç. (2024). AI Pair Programming Acceptance: A Value-Based Approach with AHP Analysis. In Proceedings of 2024 10th International Conference on Control, Decision and Information Technologies (CoDIT), pp.556–561.

Nguye, A., Ngo, H., Ngo, Y., Dang, B. & Nguyen, B. (2023). Ethical principles for artificial intelligence in education. Education and Information Technologies, 1(28), 4221–4242. https://doi.org/10.1007/s10639-022-11316-w

OpenAI (2023, November 6). Introducing GPTs. https://openai.com/index/introducing-gpts/

Özkan, Y. & Samur, M. (2025). The Use of Artificial Intelligence in History Education. In Proceedings of Virtual Technology Innovations in Education (pp. 329-352). IGI Global Scientific Publishing. http://dx.doi.org/10.4018/979-8-3693-6030-9.ch012

Pallant, J. (2010). SPSS survival manual: A step-by-step guide to data analysis using SPSS. New York, NY: McGraw-Hill International.

Palmquist, A., Sigurdardottir, H.D.I., & Myhre, H. (2025). Exploring interfaces and implications for integrating social-emotional competencies into AI literacy for education: a narrative review. Journal of Computer Education, 1, 1-37. https://doi.org/10.1007/s40692-025-00354-1

Pant, A., Hoda, R., Spiegler, S. V., Tantithamthavorn, C., & Turhan, B. (2024). Ethics in the age of AI: an analysis of ai practitioners’ awareness and challenges. ACM Transactions on Software Engineering and Methodology, 33(3), 1-35. https://doi.org/10.1145/3635715‏

Prakesh, A. & Nair, V. (2024). Integrating Generative AI into Legal Education: From Casebooks to Code, Opportunities and Challenges. Law, Technology and Humans, 6. 60–79. http://dx.doi.org/10.5204/lthj.3640

Qadhi, S., Alduais, A., Chaaban, Y., & Majeda, K. (2024). Generative AI, Research Ethics, and Higher Education Research: Insights from a Scientometric Analysis. Information, 15(325), 1–22. https://doi.org/10.3390/info15060325

Qian, W. (2024). Goal Progression, Trait Changes, and Practice Paths of Artificial Intelligence Ethics Education of Professional Courses in Higher Education. Journal of Electrical Systems, 20(2). 2151-2160. http://dx.doi.org/10.52783/jes.1665

Qiao, H., & Zhao, A. (2023). Artificial intelligence-based language learning: illuminating the impact on speaking skills and self-regulation in Chinese EFL context. Frontiers in Psychology, 14, 1255594, 1–15. https://doi.org/10.3389/fpsyg.2023.1255594

Roshanaei, M. (2024). Towards best practices for mitigating artificial intelligence implicit bias in shaping diversity, inclusion and equity in higher education. Education and Information Technologies, 1-26.‏ http://doi.org/10.1007/s10639-024-12605-2

Rossii, V. (2024). Ethics and AI-Plagiarism in an Academic Environment: Students’ Understanding of Compliance with Author’s Ethics and the Problem of Plagiarism in the Process of Interaction with Generative Artificial Intelligence. Higher Education in Russia, 33(2), 31–53. https://doi.org/10.3389/fpsyg.2023.1255594

Salles, A. & Farisco, M. (2024). Neuroethics and AI ethics: a proposal for collaboration. BMC Neuroscience, 25. http://dx.doi.org/10.1186/s12868-024-00888-7

Slimi, Z., & Carballido, B. (23AD). Navigating the Ethical Challenges of Artificial Intelligence in Higher Education: An Analysis of Seven Global AI Ethics Policies. TEM Journal, 12(2), 590–602. https://doi.org/10.18421/TEM122-02

Stoesz, B. M. (2024). Academic Integrity Through Ethical Teaching and Assessment: Overview and Current Trends. In: S.E (eds) Second Handbook of Academic Integrity. Springer International Handbooks of Education. Springer, Cham. https://doi.org/10.1007/978-3-031-54144-5_89

Tan, M. J. & Maravilla, N. (2024). Shaping integrity: why generative artificial intelligence does not have to undermine education. Frontiers in Artificial Intelligence, 7. https://doi.org/10.3389/frai.2024.1471224

Tholander, J., & Jonsson, M. (2023, July July 10–14). Design ideation with AI-sketching, thinking and talking with generative machine learning models. In Proceedings of the 2023 ACM designing interactive systems conference (pp. 1930–1940).‏

Tossell, C., Tenhundfeld, N., Momen, A., Cooley, K., & de Visser, E. (2024). Student Perceptions of ChatGPT Use in a College Essay Assignment: Implications for Learning, Grading, and Trust in Artificial Intelligence. IEEE Transactions on Learning Technologies, 17(1), 1–15. https://doi.org/10.1109/TLT.2024.3355015

Tummalapenta, S. R., Pasupuleti, R. S., Chebolu, R. M., Banala, T. V., & Thiyyagura, D. (2024). Factors driving ChatGPT continuance intention among higher education students: integrating motivation, social dynamics, and technology adoption. Journal of Computers in Education, 1–24. https://doi.org/10.1007/s40692-024-00343-w

Tung, A. Y. Z., & Dong, L. W. (2023). Malaysian Medical Students’ Attitudes and Readiness Toward AI (Artificial Intelligence): A Cross-Sectional Study. Journal of Medical Education and Curricular Development, 10. https://doi.org/10.1177/23821205231201164

Walter, Y. (2024). Embracing the future of Artificial Intelligence in the classroom: the relevance of AI literacy, prompt engineering, and critical thinking in modern education. International Journal of Educational Technology in Higher Education, 21(15), 1–29. https://doi.org/10.1186/s41239-024-00448-3

Walter, Y. (2024). Embracing the future of Artificial Intelligence in the classroom: the relevance of AI literacy, prompt engineering, and critical thinking in modern education. International Journal of Educational Technology in Higher Education, 21(1), 15.‏ http://doi.org/10.1186/s41239-024-00448-3

Weber, A. (2020). Ethics concerns in artificial intelligence use in education. In Proceedings of INTED2020, 4539–4544. http://doi.org/10.21125/inted.2020.1262

Wei, L. (2023). Artificial intelligence in language instruction: impact on English learning achievement, L2 motivation, and self-regulated learning. Frontiers in Psychology, 14(1261955.), 1–14. https://doi.org/10.3389/fpsyg.2023.1261955

Yu, L., & Yu, Z. (2023). Qualitative and quantitative analyses of artificial intelligence ethics in education using VOSviewer and CitNetExplorer. Frontiers in Psychology, 14, 1–14. https://doi.org/10.3389/fpsyg.2023.1061778

Zhai, C., Wibowo, S., & Li, L. D. (2024). The effects of over-reliance on AI dialogue systems on students' cognitive abilities: a systematic review. Smart Learning Environments, 11(1), 28. http://doi.org/10.1186/s40561-024-00316-7‏

Zhang, H., Lee, I., DiPaola, D., Cheng, Y., & Breazeal, C. (2023). Integrating Ethics and Career Futures with Technical Learning to Promote AI Literacy for Middle School Students: An Exploratory Study. International Journal of Artificial Intelligence in Education, 33(1), 290–324. https://doi.org/10.1007/s40593-022-00293-3

Zhu, Y. (2024). The Impact of AI-Assisted Teaching on Students' Learning and Psychology. Journal of Education, Humanities and Social Sciences, 38, 111–116. http://dx.doi.org/10.54097/k7a37d11

Announcement

EDUPIJ Citation Metrics

EDUPIJ News!