DISTRIBUSI KENDALI PEDAGOGIS ANTARA GURU DAN KECERDASAN BUATAN GENERATIF: KAJIAN INTEGRATIF-KRITIS ATAS PERENCANAAN, PELAKSANAAN, DAN ASESMEN PEMBELAJARAN
Keywords:
teacher agency, learning assessment, generative artificial intelligence, pedagogical control, lesson planning
Abstract
Generative artificial intelligence is increasingly being used to design learning plans, generate learning materials, support learning interactions, and provide feedback. These developments not only raise questions regarding the effectiveness of the technology, but also alter the distribution of authority in pedagogical decision-making. This article aims to analyse how pedagogical control is distributed between teachers and generative artificial intelligence during the planning, implementation, and assessment stages of learning. The research employs a critical-integrative literature review of 28 substantive publications from the period 2023–2026. Two methodological frameworks were used to guide the synthesis process, whilst one policy document was utilised to strengthen the analysis of teachers’ agency. The literature data were analysed through thematic coding, cross-source comparison, and critical interpretation of the technology’s functions, teachers’ authority, and the risks of delegating decision-making. The findings indicate that generative artificial intelligence is best suited to carrying out limited and revisable operational control, such as generating design alternatives, modifying materials, simulating interactions, and compiling initial feedback. Conversely, teachers must retain control over strategic, contextual, relational, evaluative and ethical aspects. Uncontrolled delegation may result in curricular misalignment, factual errors, homogenisation of learning, a reduction in pedagogical relationships and a blurring of accountability. This article proposes the concept of ‘asymmetric distribution of pedagogical control’, namely a division of functions that utilises the generative capacity of AI without equating the machine’s authority with the teacher’s professional responsibility. The findings confirm that the quality of AI integration is not determined by the extent of automation, but rather by the clarity of delegation boundaries, validation mechanisms, and the sustainability of teacher agency.
References
DAFTAR PUSTAKA
Alghamdi, L. H., & Alghizzi, T. M. (2025). Educators’ reflections on AI-automated feedback in higher education: A structured integrative review of potentials, pitfalls, and ethical dimensions. *Frontiers in Education, 10*, Article 1704820. https://doi.org/10.3389/feduc.2025.1704820
Braun, V., & Clarke, V. (2021). *Thematic analysis: A practical guide*. SAGE.
Cai, H., Han, B., Sun, J., Li, X., & Wong, L. H. (2025). Harnessing AI for teacher education to promote inclusive education: Investigating the effects of ChatGPT-supported lesson plan critiques on the development of pre-service teachers’ lesson planning skills. *The Internet and Higher Education, 67*, Article 101022. https://doi.org/10.1016/j.iheduc.2025.101022
Celik, I., Kontkanen, S., Laru, J., & Dalyanci, A. A. (2026). Co-constructing adaptive lesson plans with GenAI: Pre-service teachers’ Intelligent-TPACK and prompt engineering strategies. *Computers & Education, 241*, Article 105485. https://doi.org/10.1016/j.compedu.2025.105485
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*, Article 100363. https://doi.org/10.1016/j.caeai.2025.100363
Chua, K. H., Sathasivam, R. V., Mafarja, N., & Abdul Rahim, S. S. (2026). Exploring the benefits and challenges of AI-driven lesson planning among preservice science teachers. *STEM Education, 6*(1), 1–20. https://doi.org/10.3934/steme.2026001
Crompton, H., & Burke, D. (2024). The educational affordances and challenges of ChatGPT: State of the field. *TechTrends, 68*(2), 380–392. https://doi.org/10.1007/s11528-024-00939-0
Cukurova, M. (2025). *Promoting and protecting teacher agency in the age of artificial intelligence: Position paper*. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000396540
Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2024). A SWOT analysis of ChatGPT: Implications for educational practice and research. *Innovations in Education and Teaching International, 61*(3), 460–474. https://doi.org/10.1080/14703297.2023.2195846
Gamlem, S. M., McGrane, J., Brandmo, C., Moltudal, S., Sun, S. Z., & Hopfenbeck, T. N. (2026). Exploring pre-service teachers’ attitudes and experiences with generative AI: A mixed methods study in Norwegian teacher education. *Educational Psychology, 46*(1), 27–51. https://doi.org/10.1080/01443410.2025.2528663
Gurl, T. J., Markinson, M. P., & Artzt, A. F. (2025). Using ChatGPT as a lesson planning assistant with preservice secondary mathematics teachers. *Digital Experiences in Mathematics Education, 11*(1), 114–139. https://doi.org/10.1007/s40751-024-00162-9
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*. Advance online publication. https://doi.org/10.1080/02602938.2025.2502582
Jeon, J., & Lee, S. (2023). Large language models in education: A focus on the complementary relationship between human teachers and ChatGPT. *Education and Information Technologies, 28*(12), 15873–15892. https://doi.org/10.1007/s10639-023-11834-1
Kahn, P., Carrigan, M., Smith, P., Murtagh, L., Liu, R., & Song, F. (2025). Teacher agency and generative artificial intelligence: Teaching in higher education as a responsive, cultural activity. *Learning, Media and Technology*. Advance online publication. https://doi.org/10.1080/17439884.2025.2575993
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*, Article 102274. https://doi.org/10.1016/j.lindif.2023.102274
Krushinskaia, K., Elen, J., & Raes, A. (2026). Pre-service teachers’ agency during their interactions with generative AI while designing for learning—A process view on Intelligent-TPACK. *Computers and Education Open, 10*, Article 100325. https://doi.org/10.1016/j.caeo.2025.100325
Lee, S. S., & Moore, R. L. (2024). Harnessing generative AI (GenAI) for automated feedback in higher education: A systematic review. *Online Learning, 28*(3), 82–106. https://doi.org/10.24059/olj.v28i3.4593
Li, B., Lowell, V. L., Wang, C., & Li, X. (2024). A systematic review of the first year of publications on ChatGPT and language education: Examining research on ChatGPT’s use in language learning and teaching. *Computers and Education: Artificial Intelligence, 7*, Article 100266. https://doi.org/10.1016/j.caeai.2024.100266
Lo, C. K., Yu, P. L. H., Xu, S., Ng, T. K., & Jong, M. S.-Y. (2024). Exploring the application of ChatGPT in ESL/EFL education and related research issues: A systematic review of empirical studies. *Smart Learning Environments, 11*, Article 50. https://doi.org/10.1186/s40561-024-00342-5
Mai, D. T. T., Da, C. V., & Hanh, N. V. (2024). The use of ChatGPT in teaching and learning: A systematic review through SWOT analysis approach. *Frontiers in Education, 9*, Article 1328769. https://doi.org/10.3389/feduc.2024.1328769
Moundridou, M., Matzakos, N., & Doukakis, S. (2024). Generative AI tools as educators’ assistants: Designing and implementing inquiry-based lesson plans. *Computers and Education: Artificial Intelligence, 7*, Article 100277. https://doi.org/10.1016/j.caeai.2024.100277
Qian, Y. (2025). Pedagogical applications of generative AI in higher education: A systematic review of the field. *TechTrends, 69*(5), 1105–1120. https://doi.org/10.1007/s11528-025-01100-1
Sharples, M. (2023). Towards social generative AI for education: Theory, practices and ethics. *Learning: Research and Practice, 9*(2), 159–167. https://doi.org/10.1080/23735082.2023.2261131
Su, J., & Yang, W. (2023). Unlocking the power of ChatGPT: A framework for applying generative AI in education. *ECNU Review of Education, 6*(3), 355–366. https://doi.org/10.1177/20965311231168423
Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. *Smart Learning Environments, 10*, Article 15. https://doi.org/10.1186/s40561-023-00237-x
van den Berg, G., & du Plessis, E. (2023). ChatGPT and generative AI: Possibilities for its contribution to lesson planning, critical thinking and openness in teacher education. *Education Sciences, 13*(10), Article 998. https://doi.org/10.3390/educsci13100998
Wang, L., Chen, X., Wang, C., Xu, L., Shadiev, R., & Li, Y. (2024). ChatGPT’s capabilities in providing feedback on undergraduate students’ argumentation: A case study. *Thinking Skills and Creativity, 51*, Article 101440. https://doi.org/10.1016/j.tsc.2023.101440
Whittemore, R., & Knafl, K. (2005). The integrative review: Updated methodology. *Journal of Advanced Nursing, 52*(5), 546–553. https://doi.org/10.1111/j.1365-2648.2005.03621.x
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
Zhang, L., Deng, X., & Shadiev, R. (2026). A meta-review of generative AI in education: Synthesizing findings from systematic reviews. *Journal of Educational Computing Research, 64*(4), 1068–1092. https://doi.org/10.1177/07356331261419689
Zhao, J., Chapman, E., & Ghassemi Pour Sabet, P. (2024). Generative AI and educational assessments: A systematic review. *Education Research & Perspectives, 51*, 124–155. https://doi.org/10.70953/ERPv51.2412006
Alghamdi, L. H., & Alghizzi, T. M. (2025). Educators’ reflections on AI-automated feedback in higher education: A structured integrative review of potentials, pitfalls, and ethical dimensions. *Frontiers in Education, 10*, Article 1704820. https://doi.org/10.3389/feduc.2025.1704820
Braun, V., & Clarke, V. (2021). *Thematic analysis: A practical guide*. SAGE.
Cai, H., Han, B., Sun, J., Li, X., & Wong, L. H. (2025). Harnessing AI for teacher education to promote inclusive education: Investigating the effects of ChatGPT-supported lesson plan critiques on the development of pre-service teachers’ lesson planning skills. *The Internet and Higher Education, 67*, Article 101022. https://doi.org/10.1016/j.iheduc.2025.101022
Celik, I., Kontkanen, S., Laru, J., & Dalyanci, A. A. (2026). Co-constructing adaptive lesson plans with GenAI: Pre-service teachers’ Intelligent-TPACK and prompt engineering strategies. *Computers & Education, 241*, Article 105485. https://doi.org/10.1016/j.compedu.2025.105485
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*, Article 100363. https://doi.org/10.1016/j.caeai.2025.100363
Chua, K. H., Sathasivam, R. V., Mafarja, N., & Abdul Rahim, S. S. (2026). Exploring the benefits and challenges of AI-driven lesson planning among preservice science teachers. *STEM Education, 6*(1), 1–20. https://doi.org/10.3934/steme.2026001
Crompton, H., & Burke, D. (2024). The educational affordances and challenges of ChatGPT: State of the field. *TechTrends, 68*(2), 380–392. https://doi.org/10.1007/s11528-024-00939-0
Cukurova, M. (2025). *Promoting and protecting teacher agency in the age of artificial intelligence: Position paper*. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000396540
Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2024). A SWOT analysis of ChatGPT: Implications for educational practice and research. *Innovations in Education and Teaching International, 61*(3), 460–474. https://doi.org/10.1080/14703297.2023.2195846
Gamlem, S. M., McGrane, J., Brandmo, C., Moltudal, S., Sun, S. Z., & Hopfenbeck, T. N. (2026). Exploring pre-service teachers’ attitudes and experiences with generative AI: A mixed methods study in Norwegian teacher education. *Educational Psychology, 46*(1), 27–51. https://doi.org/10.1080/01443410.2025.2528663
Gurl, T. J., Markinson, M. P., & Artzt, A. F. (2025). Using ChatGPT as a lesson planning assistant with preservice secondary mathematics teachers. *Digital Experiences in Mathematics Education, 11*(1), 114–139. https://doi.org/10.1007/s40751-024-00162-9
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*. Advance online publication. https://doi.org/10.1080/02602938.2025.2502582
Jeon, J., & Lee, S. (2023). Large language models in education: A focus on the complementary relationship between human teachers and ChatGPT. *Education and Information Technologies, 28*(12), 15873–15892. https://doi.org/10.1007/s10639-023-11834-1
Kahn, P., Carrigan, M., Smith, P., Murtagh, L., Liu, R., & Song, F. (2025). Teacher agency and generative artificial intelligence: Teaching in higher education as a responsive, cultural activity. *Learning, Media and Technology*. Advance online publication. https://doi.org/10.1080/17439884.2025.2575993
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*, Article 102274. https://doi.org/10.1016/j.lindif.2023.102274
Krushinskaia, K., Elen, J., & Raes, A. (2026). Pre-service teachers’ agency during their interactions with generative AI while designing for learning—A process view on Intelligent-TPACK. *Computers and Education Open, 10*, Article 100325. https://doi.org/10.1016/j.caeo.2025.100325
Lee, S. S., & Moore, R. L. (2024). Harnessing generative AI (GenAI) for automated feedback in higher education: A systematic review. *Online Learning, 28*(3), 82–106. https://doi.org/10.24059/olj.v28i3.4593
Li, B., Lowell, V. L., Wang, C., & Li, X. (2024). A systematic review of the first year of publications on ChatGPT and language education: Examining research on ChatGPT’s use in language learning and teaching. *Computers and Education: Artificial Intelligence, 7*, Article 100266. https://doi.org/10.1016/j.caeai.2024.100266
Lo, C. K., Yu, P. L. H., Xu, S., Ng, T. K., & Jong, M. S.-Y. (2024). Exploring the application of ChatGPT in ESL/EFL education and related research issues: A systematic review of empirical studies. *Smart Learning Environments, 11*, Article 50. https://doi.org/10.1186/s40561-024-00342-5
Mai, D. T. T., Da, C. V., & Hanh, N. V. (2024). The use of ChatGPT in teaching and learning: A systematic review through SWOT analysis approach. *Frontiers in Education, 9*, Article 1328769. https://doi.org/10.3389/feduc.2024.1328769
Moundridou, M., Matzakos, N., & Doukakis, S. (2024). Generative AI tools as educators’ assistants: Designing and implementing inquiry-based lesson plans. *Computers and Education: Artificial Intelligence, 7*, Article 100277. https://doi.org/10.1016/j.caeai.2024.100277
Qian, Y. (2025). Pedagogical applications of generative AI in higher education: A systematic review of the field. *TechTrends, 69*(5), 1105–1120. https://doi.org/10.1007/s11528-025-01100-1
Sharples, M. (2023). Towards social generative AI for education: Theory, practices and ethics. *Learning: Research and Practice, 9*(2), 159–167. https://doi.org/10.1080/23735082.2023.2261131
Su, J., & Yang, W. (2023). Unlocking the power of ChatGPT: A framework for applying generative AI in education. *ECNU Review of Education, 6*(3), 355–366. https://doi.org/10.1177/20965311231168423
Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. *Smart Learning Environments, 10*, Article 15. https://doi.org/10.1186/s40561-023-00237-x
van den Berg, G., & du Plessis, E. (2023). ChatGPT and generative AI: Possibilities for its contribution to lesson planning, critical thinking and openness in teacher education. *Education Sciences, 13*(10), Article 998. https://doi.org/10.3390/educsci13100998
Wang, L., Chen, X., Wang, C., Xu, L., Shadiev, R., & Li, Y. (2024). ChatGPT’s capabilities in providing feedback on undergraduate students’ argumentation: A case study. *Thinking Skills and Creativity, 51*, Article 101440. https://doi.org/10.1016/j.tsc.2023.101440
Whittemore, R., & Knafl, K. (2005). The integrative review: Updated methodology. *Journal of Advanced Nursing, 52*(5), 546–553. https://doi.org/10.1111/j.1365-2648.2005.03621.x
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
Zhang, L., Deng, X., & Shadiev, R. (2026). A meta-review of generative AI in education: Synthesizing findings from systematic reviews. *Journal of Educational Computing Research, 64*(4), 1068–1092. https://doi.org/10.1177/07356331261419689
Zhao, J., Chapman, E., & Ghassemi Pour Sabet, P. (2024). Generative AI and educational assessments: A systematic review. *Education Research & Perspectives, 51*, 124–155. https://doi.org/10.70953/ERPv51.2412006
Published
2026-08-24
How to Cite
Indriani, Agustang, A. D. M. P., Massuanna, M. W., Muh. Rijal, & Hudayah Sulaiman. (2026). DISTRIBUSI KENDALI PEDAGOGIS ANTARA GURU DAN KECERDASAN BUATAN GENERATIF: KAJIAN INTEGRATIF-KRITIS ATAS PERENCANAAN, PELAKSANAAN, DAN ASESMEN PEMBELAJARAN. Didaktik : Jurnal Ilmiah PGSD STKIP Subang, 12(03), 349 - 371. https://doi.org/10.36989/didaktik.v12i03.18350
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Articles
