Merancang Asesmen PAI di Era Generative AI: Pergeseran dari Penilaian Produk menuju Penilaian Proses, Reasoning, dan Authenticity Siswa
DOI:
https://doi.org/10.69896/modeling.v13i1.3215Keywords:
asesmen PAI, generative AI, reasoning, authentic assessment, academic integrityAbstract
Kemunculan generative artificial intelligence (GenAI) seperti ChatGPT, Gemini, dan berbagai large language models (LLM) telah mengubah lanskap pembelajaran dan asesmen pendidikan. Dalam Pendidikan Agama Islam (PAI), perubahan tersebut menghadirkan persoalan yang lebih kompleks karena asesmen tidak hanya ditujukan untuk mengukur penguasaan pengetahuan, tetapi juga kemampuan bernalar, penghayatan nilai, sikap, dan kemampuan menerapkan ajaran Islam dalam konteks kehidupan nyata. Penelitian ini bertujuan menganalisis kebutuhan transformasi asesmen PAI pada era GenAI dan merumuskan model asesmen yang lebih berorientasi pada proses, reasoning, dan authenticity peserta didik. Penelitian menggunakan pendekatan kualitatif dengan metode studi kepustakaan. Data diperoleh melalui analisis artikel jurnal ilmiah, buku akademik, dokumen kebijakan pendidikan, dan literatur tentang asesmen autentik serta GenAI dalam pendidikan. Data dianalisis secara tematik melalui tahap identifikasi, kategorisasi, komparasi, interpretasi, dan sintesis. Hasil kajian menunjukkan bahwa asesmen berbasis produk tunggal semakin rentan kehilangan validitas sebagai bukti kemampuan individual ketika proses pengerjaannya dapat dialihkan kepada GenAI. Oleh karena itu, asesmen PAI perlu menggabungkan bukti proses, argumentasi atau reasoning, refleksi personal, performa autentik, dialog lisan, dan transparansi penggunaan AI. Artikel ini menawarkan model Process–Reasoning–Authenticity (PRA) yang menempatkan produk sebagai salah satu bukti, bukan satu-satunya dasar penilaian. Model tersebut dapat menjadi kerangka praktis bagi guru PAI untuk merancang asesmen yang tetap valid, adil, reflektif, dan berorientasi pada pembentukan karakter.
Downloads
References
Ananda, L. J., Fahrurrozi, & Febrian, D. (2020). Penguatan kompetensi guru dalam penilaian autentik berbasis higher order thinking skills. School Education Journal PGSD FIP Unimed, 9(3), 263–270. https://doi.org/10.24114/sejpgsd.v9i3.16155
Aria, D., Sukyadi, D., & Kurniawan, E. (2021). Teacher assessment literacy: Indonesian EFL secondary teachers’ self-perceived on classroom-based assessment practice. English Review: Journal of English Education, 10(1), 15–26. https://doi.org/10.25134/erjee.v10i1.5349
Black, P., & Wiliam, D. (2009). Developing the theory of formative assessment. Educational Assessment, Evaluation and Accountability, 21(1), 5–31. https://doi.org/10.1007/s11092-008-9068-5
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
Eke, D. O. (2023). ChatGPT and the rise of generative AI: Threat to academic integrity? Journal of Responsible Technology, 13, 100060. https://doi.org/10.1016/j.jrt.2023.100060
Faizin, N., Alfan, M., Basid, A., Ramadhan, M. R., Panatik, S. A., & Kawakip, A. N. (2025). Muslim students’ acceptance of artificial intelligence in Islamic religious education: An extended TAM approach. Discover Education, 4, 304. https://doi.org/10.1007/s44217-025-00767-1
Fischer, I., Sweeney, S., Lucas, M., & Gupta, N. (2024). Making sense of generative AI for assessments: Contrasting student claims and assessor evaluations. The International Journal of Management Education, 22(3), 101081. https://doi.org/10.1016/j.ijme.2024.101081
Hao, L., von Davier, M., & Harris, D. J. (2024). Transforming assessment: The impacts and implications of large language models and generative AI. Educational Measurement: Issues and Practice, 43(2), 5–15. https://doi.org/10.1111/emip.12602
Latif, M. W. (2021). Exploring tertiary EFL practitioners’ knowledge base component of assessment literacy: Implications for teacher professional development. Language Testing in Asia, 11, 19. https://doi.org/10.1186/s40468-021-00130-9
Lin, T. J., & Chiu, T. K. F. (2024). A scoping review on how generative artificial intelligence transforms assessment in higher education. International Journal of Educational Technology in Higher Education, 21, 40. https://doi.org/10.1186/s41239-024-00468-z
Miao, F., & Holmes, W. (2023). Guidance for generative AI in education and research. UNESCO.
Muthohharoh, S. R., Bharati, D. A. L., & Rozi, F. (2020). The implementation of authentic assessment to assess students’ higher order thinking skills in writing at MAN 2 Tulungagung. English Education Journal, 10(3), 374–386. https://doi.org/10.15294/eej.v10i1.36590
Nicol, D. J., & Macfarlane-Dick, D. (2006). Formative assessment and self-regulated learning: A model and seven principles of good feedback practice. Studies in Higher Education, 31(2), 199–218. https://doi.org/10.1080/03075070600572090
Ogunleye, B., Zakariyyah, K. I., Ajao, O., Olayinka, O., & Sharma, H. (2024). Higher education assessment practice in the era of generative AI tools. Journal of Applied Learning and Teaching, 7(1), 46–56. https://doi.org/10.37074/jalt.2024.7.1.28
Panadero, E., & Jonsson, A. (2013). The use of scoring rubrics for formative assessment purposes revisited: A review. Educational Research Review, 9, 129–144. https://doi.org/10.1016/j.edurev.2013.01.002
Panadero, E., Jonsson, A., & Strijbos, J.-W. (2016). Scaffolding self-regulated learning through self-assessment and peer assessment: Guidelines for classroom implementation. In D. Laveault & L. Allal (Eds.), Assessment for learning: Meeting the challenge of implementation (pp. 311–326). Springer. https://doi.org/10.1007/978-3-319-39211-0_18
Rahmawati, A. R., Wulandari, R., Sadaruddin, M. A. S., Mustofa, T. A., & Chedimae, H. (2025). Optimization of artificial intelligence in Islamic Religious Education: Opportunities and challenges in learning evaluation. Suhuf: International Journal of Islamic Studies, 37(2), 274–287. https://doi.org/10.23917/suhuf.v37i2.11015
Sadler, D. R. (1989). Formative assessment and the design of instructional systems. Instructional Science, 18, 119–144. https://doi.org/10.1007/BF00117714
Sari, N. I. P., Thohir, M., & Al Fath, M. G. F. (2025). Between humans and religious values: Collaboration in AI-based Islamic Religious Education learning. el-Tarbawi, 18(2). https://doi.org/10.20885/tarbawi.vol18.iss2.art5
Sofyan, A., & Salito. (2024). Pengembangan penilaian pembelajaran PAI berbasis kecerdasan buatan: Peluang dan tantangan di MTs Durul Jazil. Al-Qalam: Jurnal Kajian Islam dan Pendidikan, 16(2). https://doi.org/10.47435/al-qalam.v16i2.3290
Sullivan, M., Kelly, A., & McLaughlan, P. (2023). ChatGPT in higher education: Considerations for academic integrity and student learning. Journal of Applied Learning and Teaching, 6(1), 31–40. https://doi.org/10.37074/jalt.2023.6.1.17
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, 15.
Weng, X., Xia, Q., Gu, M., Rajaram, K., & Chiu, T. K. F. (2024). Assessment and learning outcomes for generative AI in higher education: A scoping review on current research status and trends. Australasian Journal of Educational Technology, 40(6), 37–55. https://doi.org/10.14742/ajet.9540
Wiggins, G. (1998). Educative assessment: Designing assessments to inform and improve student performance. Jossey-Bass.
Xia, Q., Weng, X., Ouyang, F., Lin, T. J., & Chiu, T. K. F. (2024). A scoping review on how generative artificial intelligence transforms assessment in higher education. International Journal of Educational Technology in Higher Education, 21, 40. https://doi.org/10.1186/s41239-024-00468-z
Zulaiha, S., Mulyono, H., & Ambarsari, L. (2020). An investigation into EFL teachers’ assessment literacy: Indonesian teachers’ perceptions and classroom practice. European Journal of Contemporary Education, 9(1), 189–201. https://doi.org/10.13187/ejced.2020.1.189
Abdilah, Y. A. (2023). Tinjauan sistematis etika penggunaan ChatGPT di perguruan tinggi. Integralistik, 34(2). https://doi.org/10.15294/integralistik.v34i2.50278
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
Sullivan, M., Kelly, A., & McLaughlan, P. (2023). ChatGPT in higher education: Considerations for academic integrity and student learning. Journal of Applied Learning and Teaching, 6(1), 31–40. https://doi.org/10.37074/jalt.2023.6.1.17
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
Ogunleye, B., Zakariyyah, K. I., Ajao, O., Olayinka, O., & Sharma, H. (2024). Higher education assessment practice in the era of generative AI tools. Journal of Applied Learning and Teaching, 7(1), 46–56. https://doi.org/10.37074/jalt.2024.7.1.28
Weng, X., Xia, Q., Gu, M., Rajaram, K., & Chiu, T. K. F. (2024). Assessment and learning outcomes for generative AI in higher education: A scoping review on current research status and trends. Australasian Journal of Educational Technology, 40(6), 37–55. https://doi.org/10.14742/ajet.9540
Rahmawati, A. R., Wulandari, R., Sadaruddin, M. A. S., Mustofa, T. A., & Chedimae, H. (2025). Optimization of artificial intelligence in Islamic Religious Education: Opportunities and challenges in learning evaluation. Suhuf: International Journal of Islamic Studies, 37(2), 274–287. https://doi.org/10.23917/suhuf.v37i2.11015
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Abdul Hakim

This work is licensed under a Creative Commons Attribution 4.0 International License.







