Revolusi Penilaian Pembelajaran: Bagaimana AI Mengubah Cara Guru Mengevaluasi Kemajuan Siswa
DOI:
https://doi.org/10.31004/riggs.v4i2.1612Abstract
Penilaian dalam pembelajaran memegang peran strategis sebagai sarana pengukuran capaian belajar sekaligus umpan balik bagi guru dan peserta didik dalam memperbaiki proses pembelajaran secara berkelanjutan. Namun, pendekatan penilaian konvensional yang dominan pada aspek kognitif seringkali mengabaikan dimensi afektif dan psikomotorik sehingga potensi peserta didik belum tergali secara optimal. Pemanfaatan kecerdasan buatan (Artificial Intelligence/AI) dalam penilaian di era Revolusi Industri 4.0 menghadirkan inovasi dalam proses evaluasi, terutama dalam menyediakan analisis data secara cepat, akurat, dan real-time, membantu guru merancang strategi pembelajaran adaptif berbasis capaian belajar individu peserta didik. AI juga membantu penerapan asesmen formatif dan sumatif secara berkelanjutan dengan hasil analisis instan serta memfasilitasi penyusunan laporan perkembangan belajar yang transparan, objektif, dan informatif bagi peserta didik dan orang tua. Studi literatur ini bertujuan menganalisis peran AI dalam transformasi sistem penilaian pembelajaran serta tantangan penerapannya di Indonesia. Hasil kajian menunjukkan bahwa integrasi AI pada sistem penilaian berkontribusi dalam meningkatkan efisiensi, akurasi, dan objektivitas evaluasi, mendukung personalisasi pembelajaran, serta memungkinkan pemetaan potensi peserta didik secara mendalam. Namun, pemanfaatan AI memerlukan dukungan literasi digital guru, infrastruktur teknologi memadai, kebijakan perlindungan data, serta kolaborasi antar pihak terkait agar penerapan AI dalam penilaian dapat berjalan optimal untuk mendukung peningkatan mutu pendidikan yang berkelanjutan.
Downloads
References
Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 5(1), 7–74. https://doi.org/10.1080/0969595980050102
Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications.
Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2019). How to design and evaluate research in education (10th ed.). McGraw-Hill Education.
Gikandi, J. W., Morrow, D., & Davis, N. E. (2011). Online formative assessment in higher education: A review of the literature. Computers & Education, 57(4), 2333–2351. https://doi.org/10.1016/j.compedu.2011.06.004
Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
Ifenthaler, D. (2022). Learning analytics and artificial intelligence in education: Opportunities and challenges for higher education. Computers in Human Behavior, 126, 106976. https://doi.org/10.1016/j.chb.2021.106976
Ifenthaler, D., & Yau, J. Y.-K. (2020). Utilising learning analytics to support study success in higher education: A systematic review. Educational Technology Research and Development, 68, 1961–1990. https://doi.org/10.1007/s11423-020-09788-z
Kitchenham, B., & Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. EBSE Technical Report, EBSE-2007-01.
Luckin, R., Holmes, W., Griffiths, M., & Forcier, L. B. (2016). Intelligence unleashed: An argument for AI in education. Pearson.
Sari, H. P., & Sutapa, Y. (2023). Implementasi kecerdasan buatan dalam penilaian pembelajaran di sekolah menengah: Peluang dan tantangan. Jurnal Teknologi Pendidikan Indonesia, 13(1), 45–56. https://doi.org/10.21009/jtpi.v13i1.3456
Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039
Williamson, B., & Piattoeva, N. (2021). Objectivity as standardization in data-scientific educational governance: Grasping the global through the local. Research in Education, 101(1), 69–91. https://doi.org/10.1177/0034523721992177
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education: From the past to the future. Educational Research Review, 29, 100313. https://doi.org/10.1016/j.edurev.2019.100313
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Hendri A, Ari Isnu, Sularni Sularni, Mini Puspita Sari, Eriyanto Eriyanto, Tomi Hidayat, Rifa’i Rifa’i
This work is licensed under a Creative Commons Attribution 4.0 International License.
