Pergeseran Otoritas Pedagogis Guru di Era AI Generatif: Sistematis Literatur Review dalam Perspektif Manajemen Mutu Pendidikan

Masduki Ahmad; Dailami Firdaus; Heni Rochimah; Wulandari Wulandari

doi:10.71094/vkj.v3i4.251

Authors

Masduki Ahmad Program Studi Manajemen Pendidikan, Universitas Negeri Jakarta, Indonesia
Dailami Firdaus Program Studi Teknologi Pendidikan, Universitas Islam As-Syafiiyah, Indonesia
Heni Rochimah Program Studi Teknologi Pendidikan, Universitas Islam As-Syafiiyah, Indonesia
Wulandari Program Studi Manajemen Pendidikan, Universitas Negeri Jakarta, Indonesia

DOI:

https://doi.org/10.71094/vkj.v3i4.251

Keywords:

Generative AI, Teacher Pedagogical Authority, Educational Quality Management

Abstract

This study examined the shift in teachers' pedagogical authority in the era of generative artificial intelligence (AI) from the perspective of educational quality management. The research was motivated by the increasing use of generative AI by students in learning activities, which not only supports academic tasks but also challenges teachers’ roles, academic integrity, and learning quality. A systematic literature review was conducted using a structured article selection process. Data were collected from 13 reputable scientific articles published between 2023 and 2025 and analyzed through thematic coding. The findings indicate that students primarily use generative AI for academic writing, information retrieval, content comprehension, problem-solving, coding, and multimodal content production. Teachers’ pedagogical authority has shifted from being the main knowledge source to roles including ethical guidance, AI literacy mentorship, information validation, authentic assessment design, collaboration facilitation, and risk management in digital learning. The implications suggest that educational quality in the AI era heavily depends on teachers and institutions managing AI use critically and responsibly. Generative AI can enhance personalized learning, access to information, learning effectiveness, and collaboration; however, without pedagogical oversight, it may increase dependency, weaken cognitive processes, and threaten academic integrity.

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References

Abbas, M., Jam, F. A., & Khan, T. I. (2024). Is it harmful or helpful? Examining the causes and consequences of generative AI usage among university students. International Journal of Educational Technology in Higher Education, 21(1). https://doi.org/10.1186/s41239-024-00444-7

Al-Abdullatif, A. M. (2024). Modeling Teachers’ Acceptance of Generative Artificial Intelligence Use in Higher Education: The Role of AI Literacy, Intelligent TPACK, and Perceived Trust. Education Sciences, 14(11). https://doi.org/10.3390/educsci14111209

Alfiras, M. I. I., Emran, A. Q., & Mohamed, A. M. (2025). Ethics and governance of generative AI in education: a systematic review on responsible adoption. Discover Education, 5(1), 37. https://doi.org/10.1007/s44217-025-01051-y

Almashour, M., Aldamen, H. A. K., & Jarrah, M. (2025). “They know AI, but they also know us”: student perceptions of EFL teacher identity in AI-enhanced classrooms in Jordan. Frontiers in Education, Volume 10. https://doi.org/10.3389/feduc.2025.1611147

Ambady, A., & K V, T. (2025). Persona pedagogica in crisis: are educators becoming data custodians in the age of AI? Frontiers in Artificial Intelligence, 8, 1743016. https://doi.org/10.3389/frai.2025.1743016

Atchley, P., Pannell, H., Wofford, K., Hopkins, M., & Atchley, R. A. (2024). Human and AI collaboration in the higher education environment: opportunities and concerns. Cognitive Research: Principles and Implications, 9(1), 20. https://doi.org/10.1186/s41235-024-00547-9

Barrett, A., & Pack, A. (2023). Not quite eye to A.I.: student and teacher perspectives on the use of generative artificial intelligence in the writing process. International Journal of Educational Technology in Higher Education, 20(1), 59. https://doi.org/10.1186/s41239-023-00427-0

Barus, O. P., Hidayanto, A. N., Handri, E. Y., Sensuse, D. I., & Yaiprasert, C. (2025). Shaping generative AI governance in higher education: Insights from student perception. International Journal of Educational Research Open, 8(December 2024), 100452. https://doi.org/10.1016/j.ijedro.2025.100452

Bearman, M., & Ajjawi, R. (2023). Learning to work with the black box: Pedagogy for a world with artificial intelligence. British Journal of Educational Technology, 54(5), 1160–1173. https://doi.org/https://doi.org/10.1111/bjet.13337

Bearman, M., Ryan, J., & Ajjawi, R. (2023). Discourses of artificial intelligence in higher education: a critical literature review. Higher Education, 86(2), 369–385. https://doi.org/10.1007/s10734-022-00937-2

Celik, I., Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The Promises and Challenges of Artificial Intelligence for Teachers: a Systematic Review of Research. TechTrends, 66(4), 616–630. https://doi.org/10.1007/s11528-022-00715-y

Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00411-8

Chan, C. K. Y., & Tsi, L. H. Y. (2024). Will generative AI replace teachers in higher education? A study of teacher and student perceptions. Studies in Educational Evaluation, 83, 101395. https://doi.org/https://doi.org/10.1016/j.stueduc.2024.101395

Cheah, Y. H., Lu, J., & Kim, J. (2025). Integrating generative artificial intelligence in K-12 education: Examining teachers’ preparedness, practices, and barriers. Computers and Education: Artificial Intelligence, 8(January), 100363. https://doi.org/10.1016/j.caeai.2025.100363

Chouksey, N., Mishra, G. C., & Chouksey, R. (2020). Path Analysis in Rice Yield and Yield Attributing Characters by Structural Equation Model. International Journal of Current Microbiology and Applied Sciences, 9(5), 3098–3103. https://doi.org/10.20546/ijcmas.2020.905.367

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), 28–47. https://doi.org/10.56297/FSYB3031/MXNB7567

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

Creely, E., & Janssen, K. (2025). Onto-epistemological Understandings of Generative Artificial Intelligence in Education. International Journal of Changes in Education, 2(2), 55–65. https://doi.org/10.47852/bonviewijce52024380

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), 1006. https://doi.org/10.1057/s41599-024-03526-z

Dimitriadou, E., & Lanitis, A. (2023). A critical evaluation, challenges, and future perspectives of using artificial intelligence and emerging technologies in smart classrooms. Smart Learning Environments, 10(1), 12. https://doi.org/10.1186/s40561-023-00231-3

Du, H., Sun, Y., Jiang, H., Islam, A. Y. M. A., & Gu, X. (2024). Exploring the effects of AI literacy in teacher learning: an empirical study. Humanities and Social Sciences Communications, 11(1), 1–10. https://doi.org/10.1057/s41599-024-03101-6

Farhi, F., Jeljeli, R., Aburezeq, I., Dweikat, F. F., Al-shami, S. A., & Slamene, R. (2023). Analyzing the students’ views, concerns, and perceived ethics about chat GPT usage. Computers and Education: Artificial Intelligence, 5(June). https://doi.org/10.1016/j.caeai.2023.100180

Gamlem, S. M., Johnston, S.-K., Moltudal, S., McGrane, J., & Hopfenbeck, T. N. (2026). Generative AI in initial teacher education: Exploring the alignment of perceptions and experiences of pre-service teachers and their teacher educators. Teaching and Teacher Education, 172, 105382. https://doi.org/https://doi.org/10.1016/j.tate.2026.105382

Gesser-Edelsburg, A., Hijazi, R., Eliyahu, E., & Tal, A. (2024). Bridging the Divide: An Empirical Investigation of Artificial Intelligence and Generative Artificial Intelligence Integration Across Genders, Disciplines and Academic Roles. European Journal of Open, Distance and E-Learning, 26(S1), 51–69. https://doi.org/10.2478/eurodl-2024-0008

Gruenhagen, J. H., Sinclair, P. M., Carroll, J.-A., Baker, P. R. A., Wilson, A., & Demant, D. (2024). The rapid rise of generative AI and its implications for academic integrity: Students’ perceptions and use of chatbots for assistance with assessments. Computers and Education: Artificial Intelligence, 7, 100273. https://doi.org/https://doi.org/10.1016/j.caeai.2024.100273

Gustilo, L., Ong, E., & Lapinid, M. R. (2024). Algorithmically-driven writing and academic integrity: exploring educators’ practices, perceptions, and policies in AI era. International Journal for Educational Integrity, 20(1), 3. https://doi.org/10.1007/s40979-024-00153-8

Henderson, M., Bearman, M., Chung, J., Fawns, T., Buckingham Shum, S., Matthews, K. E., & de Mello Heredia, J. (2025). Comparing Generative AI and teacher feedback: student perceptions of usefulness and trustworthiness. Assessment & Evaluation in Higher Education, 1–16. https://doi.org/10.1080/02602938.2025.2502582

Karimi, M. N., & Keshvari, Z. (2026). Learner autonomy driven by (generative) artificial intelligence as a source of emotional vulnerability and identity tensions in mid-career tertiary-level language teachers. Teaching and Teacher Education, 176, 105507. https://doi.org/https://doi.org/10.1016/j.tate.2026.105507

Kim, I., Yi, S., & Kim, K. (2024). A Study on the Development and Validation of Generative AI Literacy Measurement Tool for Elementary and Secondary Teachers. The Journal of Learner-Centered Curriculum and Instruction, 24(22), 697–708. https://doi.org/ART003141368

Li, J., & Zhang, Q. (2026). Teacher identity negotiation in AI-enhanced higher education and its implications for professional development. Teaching and Teacher Education, 176, 105499. https://doi.org/https://doi.org/10.1016/j.tate.2026.105499

Mah, C., Walker, H., Phalen, L., Levine, S., Beck, S. W., & Pittman, J. (2024). Beyond CheatBots: Examining Tensions in Teachers’ and Students’ Perceptions of Cheating and Learning with ChatGPT. Education Sciences, 14(5). https://doi.org/10.3390/educsci14050500

Maphosa, V., & Maphosa, M. (2023). Artificial intelligence in higher education: a bibliometric analysis and topic modeling approach. Applied Artificial Intelligence, 37(1), 2261730. https://doi.org/10.1080/08839514.2023.2261730

Martin, A. J., Collie, R. J., Kennett, R., Liu, D., Ginns, P., Sudimantara, L. B., Dewi, E. W., & Rüschenpöhler, L. G. (2025). Integrating generative AI and load reduction instruction to individualize and optimize students’ learning. Learning and Individual Differences, 121(December 2024). https://doi.org/10.1016/j.lindif.2025.102723

Mortlock, R., & Lucas, C. (2024). Generative artificial intelligence (Gen-AI) in pharmacy education: Utilization and implications for academic integrity: A scoping review. Exploratory Research in Clinical and Social Pharmacy, 15, 100481. https://doi.org/10.1016/j.rcsop.2024.100481

Nam, B. H., & Bai, Q. (2023). ChatGPT and its ethical implications for STEM research and higher education: a media discourse analysis. International Journal of STEM Education, 10(1). https://doi.org/10.1186/s40594-023-00452-5

Otto, S., Ejsing-Duun, S., & Lindsay, E. (2025). Disruptive tensions and emerging practices: an exploratory inquiry into student perspectives on generative Artificial Intelligence in a problem-based learning environment. Education and Information Technologies, 30(13), 19111–19140. https://doi.org/10.1007/s10639-025-13533-5

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Bmj, 372. https://doi.org/10.1136/bmj.n71

Qadhi, S. M., Alduais, A., Chaaban, Y., & Khraisheh, M. (2024). Generative AI, Research Ethics, and Higher Education Research: Insights from a Scientometric Analysis. Information (Switzerland), 15(6), 1–22. https://doi.org/10.3390/info15060325

Rahimi, M., Fathi, J., & Zou, D. (2025). Exploring the impact of automated written corrective feedback on the academic writing skills of EFL learners: An activity theory perspective. Education and Information Technologies, 30(3), 2691–2735. https://doi.org/10.1007/s10639-024-12896-5

Shen, W., Chai, C., Chiu, T. K. F., Yau, K. W., Meng, H., King, I., Wong, S., & Yam, Y. (2026). Pedagogy first, technology second: Cross-level relationships between teacher professional knowledge and student learning in artificial intelligence (AI) education. Computers and Education: Artificial Intelligence, 10, 100564. https://doi.org/https://doi.org/10.1016/j.caeai.2026.100564

Shi, H., & Aryadoust, V. (2024). A systematic review of AI-based automated written feedback research. ReCALL, 36(2), 187–209. https://doi.org/DOI: 10.1017/S0958344023000265

Sousa, A. E., & Cardoso, P. (2025). Use of Generative AI by Higher Education Students. Electronics (Switzerland), 14(7), 1–20. https://doi.org/10.3390/electronics14071258

Susnjak, T. (2023). PRISMA-DFLLM: An Extension of PRISMA for Systematic Literature Reviews using Domain-specific Finetuned Large Language Models. 1–20.

Vetter, M. A., Lucia, B., Jiang, J., & Othman, M. (2024). Towards a framework for local interrogation of AI ethics: A case study on text generators, academic integrity, and composing with ChatGPT. Computers and Composition, 71, 102831. https://doi.org/https://doi.org/10.1016/j.compcom.2024.102831

Wang, L., & Ren, B. (2024). Enhancing Academic Writing in a Linguistics Course with Generative AI: An Empirical Study in a Higher Education Institution in Hong Kong. Education Sciences, 14(12). https://doi.org/10.3390/educsci14121329

Wang, S., & Zhang, H. (2026). Digital mentor paradox: Transforming algorithmic anxiety into professional growth through AI-scaffolded pedagogical reasoning and identity. Teaching and Teacher Education, 176, 105526. https://doi.org/https://doi.org/10.1016/j.tate.2026.105526

Williamson, B., Macgilchrist, F., & Potter, J. (2023). Re-examining AI, automation and datafication in education. Learning, Media and Technology, 48(1), 1–5. https://doi.org/10.1080/17439884.2023.2167830

Wu, C., Zhang, H., & Carroll, J. M. (2024). AI Governance in Higher Education: Case Studies of Guidance at Big Ten Universities. Future Internet, 16(10). https://doi.org/10.3390/fi16100354

Yan, W., Nakajima, T., & Sawada, R. (2024). Benefits and Challenges of Collaboration between Students and Conversational Generative Artificial Intelligence in Programming Learning: An Empirical Case Study. Education Sciences, 14(4). https://doi.org/10.3390/educsci14040433

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. https://doi.org/10.1186/s40561-024-00316-7