KESIAPAN GURU DAN ADAPTASI PEDAGOGIS TERHADAP PEMBELAJARAN YANG TERINTEGRASI DENGAN KECERDASAN BUATAN DALAM KURIKULUM MERDEKA
(1) 
(2) UIN Sayyid Ali Rahmatullah Tulungagung
(3) UIN Sayyid Ali Rahmatullah Tulungagung
(*) Corresponding Author
Abstract
Penelitian ini bertujuan untuk mengeksplorasi kesiapan guru dan bentuk adaptasi pedagogis terhadap pembelajaran terintegrasi kecerdasan buatan (AI) dalam konteks implementasi Kurikulum Merdeka di Indonesia. Fenomena ini menjadi relevan mengingat percepatan digitalisasi pendidikan dan tuntutan penguasaan teknologi oleh guru di era pasca-pandemi. Pendekatan yang digunakan adalah kualitatif deskriptif dengan desain fenomenologis, yang berfokus pada pengalaman subjektif guru dalam menghadapi perubahan paradigma pembelajaran berbasis AI. Penelitian dilaksanakan di beberapa sekolah pelaksana Kurikulum Merdeka di Tulungagung pada periode Januari–Juni 2025. Data dikumpulkan melalui wawancara semi-terstruktur, observasi pembelajaran, dan analisis dokumen seperti modul ajar dan rencana pelaksanaan pembelajaran (RPP). Partisipan terdiri atas 10 guru dari jenjang SD, SMP, dan SMA yang dipilih melalui teknik purposive sampling. Analisis data dilakukan menggunakan analisis tematik (Braun & Clarke, 2021), yang menghasilkan tiga tema utama: (1) cognitive readiness — guru memahami dasar konsep AI namun terbatas pada penggunaan aplikasi sederhana; (2) pedagogical adaptation — guru mulai menyesuaikan strategi mengajar menggunakan alat AI seperti ChatGPT dan Quizziz; dan (3) emotional and ethical concerns — guru menunjukkan ambivalensi antara antusiasme dan kecemasan terhadap dominasi teknologi. Temuan ini menunjukkan bahwa kesiapan guru terhadap pembelajaran berbasis AI tidak hanya bersifat teknis, tetapi juga menyentuh dimensi reflektif, etis, dan pedagogis. Penelitian ini berimplikasi pada penguatan kerangka TPACK berbasis AI, serta memberikan dasar bagi perumusan kebijakan dan pelatihan guru di era pembelajaran cerdas.
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Braun, V., & Clarke, V. (2021). Thematic analysis: A practical guide. London, England: SAGE Publications.
Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry and research design: Choosing among five approaches (4th ed.). Thousand Oaks, CA: SAGE Publications.
Denzin, N. K., & Lincoln, Y. S. (2020). The SAGE handbook of qualitative research (5th ed.). Thousand Oaks, CA: SAGE Publications.
Holmes, W., Bialik, M., & Fadel, C. (2022). Artificial Intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
Huda, M., Pratama, R., & Nugroho, E. (2025). Teachers’ pedagogical adaptation in AI-supported classrooms: An Indonesian perspective. Jurnal Teknologi dan Pendidikan Digital, 7(1), 44–59.
Kallio, H., Pietilä, A.-M., Johnson, M., & Kangasniemi, M. (2021). Systematic methodological review: Developing a framework for qualitative semi-structured interview guides. Nurse Education Today, 95, 104601.
Kemendikbudristek. (2022). Panduan implementasi kurikulum merdeka. Jakarta, Indonesia: Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi.
Kim, H., & Reeves, T. (2023). Teachers’ perceptions and readiness for AI-enhanced education. Computers & Education: Artificial Intelligence, 5(1), 100128.
Kumar, A., & Parveen, N. (2022). Teacher readiness for technology integration: Conceptual model and implications. International Journal of Educational Technology in Higher Education, 19(24), 1–15.
Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Beverly Hills, CA: SAGE Publications.
Luckin, R. (2021). Machine learning and human intelligence: The future of education in the 21st century. London, England: UCL Press.
Miles, M. B., Huberman, A. M., & Saldaña, J. (2018). Qualitative data analysis: A methods sourcebook (4th ed.). Thousand Oaks, CA: SAGE Publications.
Mishra, P., & Koehler, M. J. (2006). Technological Pedagogical Content Knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054.
Moustakas, C. (1994). Phenomenological research methods. Thousand Oaks, CA: SAGE Publications.
Nowell, L. S., Norris, J. M., White, D. E., & Moules, N. J. (2017). Thematic analysis: Striving to meet the trustworthiness criteria. International Journal of Qualitative Methods, 16(1), 1–13.
OECD. (2023). AI in education: Policy challenges and opportunities. Paris, France: OECD Publishing.
Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., & Hoagwood, K. (2015). Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Administration and Policy in Mental Health and Mental Health Services Research, 42(5), 533–544.
Parveen, N. (2023). Exploring teacher readiness for AI-based education in developing countries. Asian Journal of Educational Research, 11(4), 233–249.
Rahmawati, L., & Huda, M. (2024). Contextualizing AI pedagogy in Indonesian classrooms: Cultural perspectives and local practices. Jurnal Inovasi Pendidikan Indonesia, 6(2), 75–91.
Rahmawati, L., & Nurhayati, D. (2021). Digital literacy among Indonesian teachers: Challenges and perspectives. Jurnal Cakrawala Pendidikan, 40(3), 561–574.
UNESCO. (2023). Guidelines for Artificial Intelligence and the future of education. Paris, France: UNESCO.
Van Manen, M. (2017). Phenomenology in its original sense. Qualitative Health Research, 27(6), 810–825.
Wibawa, S., & Astuti, P. (2022). Teachers’ pedagogical challenges in implementing technology-based learning. Jurnal Pendidikan dan Kebudayaan, 12(1), 33–47.
Zhang, D., & Aslan, E. (2023). Exploring teachers’ ethical concerns and trust in AI in education. Teaching and Teacher Education, 127, 104017.
DOI: http://dx.doi.org/10.30998/rdje.v11i2.20599
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