Towards an Evidence-Based Institutional AI Policy: Phenomenological Insights from English Language Teaching in Indonesian Higher Education
DOI:
https://doi.org/10.26555/vzcm0k60Keywords:
Artificial Intelligence, English language teaching, Higher education, Institutional AI policy, Interpretative phenomenological analysisAbstract
The rapid adoption of artificial intelligence (AI) in higher education has created new opportunities for English Language Teaching (ELT) while simultaneously raising concerns regarding learner autonomy, academic ethics, and institutional governance. Although Indonesia has introduced national guidelines for the responsible use of generative AI in higher education, evidence on how AI is experienced and interpreted within specific educational contexts remains limited. This study explores the lived experiences of AI use among lecturers, students, and institutional leaders in English Language Teaching within Indonesian higher education. Employing an Interpretative Phenomenological Analysis (IPA), the study analyzed data collected from 46 participants across nine English Language Education programs in South Kalimantan through semi-structured interviews, qualitative questionnaires, and institutional document analysis. Three superordinate themes emerged: (1) making sense of AI as an accessible learning partner, (2) negotiating learner autonomy and academic ethics in AI-assisted learning, and (3) translating lived experiences into evidence-based institutional AI policy. The findings indicate that participants perceived AI not merely as a technological tool but as a learning partner whose educational value depends on critical judgment, ethical responsibility, and contextual pedagogical practices. The study contributes to AI and ELT scholarship by providing a phenomenological understanding of AI-assisted learning and demonstrating how lived experiences can inform context-sensitive institutional AI policies that complement broader national policy directions. These findings offer practical insights for higher education institutions seeking to develop responsible, evidence-based AI governance.
References
Al Farhan, M., & Aflahah, N. A. (2026). Self-assessment and critical thinking: An explanatory sequential study of AI implications in English language teaching. Celtic : A Journal of Culture, English Language Teaching, Literature and Linguistics, 13(1), 278–302. https://doi.org/https://doi.org/10.22219/celtic.v13i1.43369
Al Farhan, M., & Istiqamah, I. (2026). AI-Assisted media in language learning: A SWOT analysis from lecturers’ and students’ perspective. GLENS: Global English Insights Journal, 3(2), 104–117. https://doi.org/10.66314/glens.v3i2.553
Almohesh, A. R. I. (2024). AI Application (ChatGPT) and Saudi Arabian Primary School Students’ Autonomy in Online Classes: Exploring Students and Teachers’ Perceptions. The International Review of Research in Open and Distributed Learning, 25(3), 1–18. https://doi.org/10.19173/irrodl.v25i3.7641
Alrayes, A., Henari, T. F., & Ahmed, D. A. (2024). ChatGPT in Education – Understanding the Bahraini Academics Perspective. Electronic Journal of E-Learning, 22(2), 112–134. https://doi.org/10.34190/ejel.22.2.3250
Alshumaimeri, Y. A., & Alshememry, A. K. (2024). The Extent of AI Applications in EFL Learning and Teaching. IEEE Transactions on Learning Technologies, 17, 653–663. https://doi.org/10.1109/TLT.2023.3322128
Al-Smadi, O. A., Rashid, R. A., Saad, H., Zrekat, Y. H., Kamal, S. S. L. A., & Uktamovich, G. I. (2024). Artificial intelligence for English language learning and teaching: Advancing sustainable development goals. Journal of Language Teaching and Research, 15(6), 1835–1844. https://doi.org/10.17507/jltr.1506.09
Bahroun, Z., Anane, C., Ahmed, V., & Zacca, A. (2023). Transforming education: A comprehensive review of generative artificial intelligence in educational settings through bibliometric and content analysis. Sustainability, 15(17), 1–40. https://doi.org/10.3390/su151712983
Black, R. W., & Tomlinson, B. (2025). University students describe how they adopt AI for writing and research in a general education course. Scientific Reports, 15, 1–10. https://doi.org/10.1038/s41598-025-92937-2
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, 1–25. https://doi.org/10.1186/s41239-023-00408-3
Cheong, B. C. (2024). Transparency and accountability in AI systems: Safeguarding wellbeing in the age of algorithmic decision-making. Frontiers in Human Dynamics, 6, 1–11. https://doi.org/10.3389/fhumd.2024.1421273
Dabis, A., & Csáki, C. (2024). AI and ethics: Investigating the first policy responses of higher education institutions to the challenge of generative AI. Humanities and Social Sciences Communications, 11(1), 1–13. https://doi.org/10.1057/s41599-024-03526-z
Dahri, N. A., Yahaya, N., Al-Rahmi, W. M., Aldraiweesh, A., Alturki, U., Almutairy, S., Shutaleva, A., & Soomro, R. B. (2024). Extended TAM based acceptance of AI-Powered ChatGPT for supporting metacognitive self-regulated learning in education: A mixed-methods study. Heliyon, 10(8), 1–21. https://doi.org/10.1016/j.heliyon.2024.e29317
Deci, E. L., & Ryan, R. M. (1985). Intrinsic Motivation and Self-Determination in Human Behavior. Plenum. https://doi.org/10.1007/978-1-4899-2271-7
Direktorat Jenderal Pendidikan Tinggi, R. dan T. (2024). Buku Panduan Penggunaan Generative Artificial Intelligence pada Pembelajaran di Perguruan Tinggi (1st ed.). Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi.
Eke, D. O. (2023). ChatGPT and the rise of generative AI: Threat to academic integrity? Journal of Responsible Technology, 13, 1–4. https://doi.org/10.1016/j.jrt.2023.100060
Francis, N. J., Jones, S., & Smith, D. P. (2025). Generative AI in higher education: Balancing innovation and integrity. British Journal of Biomedical Science, 81, 1–9. https://doi.org/10.3389/bjbs.2024.14048
Giannakos, M., Azevedo, R., Brusilovsky, P., Cukurova, M., Dimitriadis, Y., Hernandez-Leo, D., Järvelä, S., Mavrikis, M., & Rienties, B. (2025). The promise and challenges of generative AI in education. Behaviour & Information Technology, 44(11), 2518–2544. https://doi.org/10.1080/0144929X.2024.2394886
Katsenou, R., Kotsidis, K., Papadopoulou, A., Anastasiadis, P., & Deliyannis, I. (2025). Beyond assistance: Embracing AI as a collaborative co-agent in education. Education Sciences, 15(8), 1–24. https://doi.org/10.3390/educsci15081006
Khasawneh, M. A. S., Aladini, A., Assi, S. A., & Ajanil, B. (2025). Portfolio assessment in AI-enhanced learning environments: A pathway to emotion regulation, mindfulness, and language learning attitudes. Language Testing in Asia, 15(5), 1–18. https://doi.org/10.1186/s40468-025-00345-0
Kim, J., Lee, H., & Cho, Y. H. (2022). Learning design to support student-AI collaboration: Perspectives of leading teachers for AI in education. Education and Information Technologies, 27(5), 6069–6104. https://doi.org/10.1007/s10639-021-10831-6
Lan, M., & Zhou, X. (2025). A qualitative systematic review on AI empowered self-regulated learning in higher education. NPJ Science of Learning, 10(1), 1–16. https://doi.org/10.1038/s41539-025-00319-0
Limiya, A., & Kumar, P. (2025). Generative artificial intelligence in enhancing English language skills: A systematic review. Studies in Media and Communication, 13(4), 256–267. https://doi.org/10.11114/smc.v13i4.7763
MacIntyre, G., Cogan, N., Stewart, A., Quinn, N., O’Connell, M., & Rowe, M. (2022). Citizens defining citizenship: A model grounded in lived experience and its implications for research, policy and practice. Health & Social Care in the Community, 30(3), 695–705. https://doi.org/10.1111/hsc.13440
Mohammed, S. J., & Khalid, M. W. (2025). Under the world of AI-generated feedback on writing: mirroring motivation, foreign language peace of mind, trait emotional intelligence, and writing development. Language Testing in Asia, 15(7), 1–26. https://doi.org/10.1186/s40468-025-00343-2
Naz, I., & Robertson, R. (2024). Exploring the Feasibility and Efficacy of ChatGPT3 for Personalized Feedback in Teaching. Electronic Journal of E-Learning, 22(2), 98–111. https://doi.org/10.34190/ejel.22.2.3345
Perkins, M., Furze, L., Roe, J., & MacVaugh, J. (2024). The Artificial Intelligence Assessment Scale (AIAS): A framework for ethical integration of generative AI in educational assessment. Journal of University Teaching and Learning Practice, 21(06), 1–18. https://doi.org/10.53761/q3azde36
Prosek, E. A., & Gibson, D. M. (2021). Promoting Rigorous Research by Examining Lived Experiences: A Review of Four Qualitative Traditions. Journal of Counseling & Development, 99(2), 167–177. https://doi.org/10.1002/jcad.12364
Radanliev, P. (2025). AI ethics: Integrating transparency, fairness, and privacy in AI development. Applied Artificial Intelligence, 39(1), 1–42. https://doi.org/10.1080/08839514.2025.2463722
Satiti, L. H., Fauziati, E., & Seytaningsih, E. (2024). AI Chatbot as an Effective English Teaching Partner for University Students. International Journal of Educational Research & Social Sciences, 5(3), 463–469. https://doi.org/10.51601/ijersc.v5i3.820
Schaeffer, D., Coombs, L., Luckett, J., Marin, M., & Olson, P. (2024). Risks of AI Applications Used in Higher Education. Electronic Journal of E-Learning, 22(6), 60–65. https://doi.org/10.34190/ejel.22.6.3457
Shukla, S. (2024). Principles Governing Ethical Development and Deployment of AI. International Journal of Engineering, Business and Management, 8(2), 26–46. https://doi.org/10.22161/ijebm.8.2.5
Smith, J. A., Flowers, P., & Larkin, M. (2009). Interpretative phenomenological analysis: Theory, method, and research. SAGE Publications.
Song, N. (2024). Higher education crisis: Academic misconduct with generative AI. Journal of Contingencies and Crisis Management, 32(1), e12532. https://doi.org/10.1111/1468-5973.12532
Suchithra, V. G., & Arya, C. S. (2025). The Study on Ethics and Biases in AI-Powered Education. European Journal of Contemporary Education and E-Learning, 3(2), 37–43. https://doi.org/10.59324/ejceel.2025.3(2).04
Utami, S. P. T., Andayani, A., Winarni, R., & Sumarwati, S. (2023). Utilization of artificial intelligence technology in an academic writing class: How do Indonesian students perceive? Contemporary Educational Technology, 15(4), 1–13. https://doi.org/10.30935/cedtech/13419
Wei, L. (2023). Artificial intelligence in language instruction: Impact on English learning achievement, L2 motivation, and self-regulated learning. Frontiers in Psychology, 14, 1–14. https://doi.org/10.3389/fpsyg.2023.1261955
Yan, L., Pammer‐Schindler, V., Mills, C., Nguyen, A., & Gašević, D. (2025). Beyond efficiency: Empirical insights on generative AI’s impact on cognition, metacognition and epistemic agency in learning. British Journal of Educational Technology, 56(5), 1675–1685. https://doi.org/10.1111/bjet.70000
Yusuf, A., Pervin, N., & Román-González, M. (2024). Generative AI and the future of higher education: A threat to academic integrity or reformation? Evidence from multicultural perspectives. International Journal of Educational Technology in Higher Education, 21(1), 1–29. https://doi.org/10.1186/s41239-024-00453-6
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Miftah Al Farhan, Soraya Djamilah, Vira Wulandari
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish in Ahmad Dahlan Journal of English Studies (ADJES) agree to the following terms:
- Authors retain copyright and grant the Ahmad Dahlan Journal of English Studies (ADJES) right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share (copy and redistribute the material in any medium or format) and adapt (remix, transform, and build upon the material) the work for any purpose, even commercially with an acknowledgment of the work's authorship and initial publication in Ahmad Dahlan Journal of English Studies (ADJES).
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in Ahmad Dahlan Journal of English Studies (ADJES).
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
