Model Pembelajaran Berbasis Artificial Intelligence dan Dampaknya terhadap Pemahaman Perkembangan Peserta Didik pada Mahasiswa
Keywords:
Artificial intelligence, Model pembelajaran, Perkembangan Peserta didik, Pemahaman Mahasiswa, Pendidikan tinggi.Abstract
Perkembangan Artificial Intelligence (AI) telah membuka peluang baru dalam meningkatkan kualitas pembelajaran di perguruan tinggi. Penelitian ini bertujuan menganalisis dampak model pembelajaran berbasis AI terhadap pemahaman perkembangan peserta didik pada mahasiswa. Penelitian menggunakan pendekatan kuantitatif dengan desain one-group pretest-posttest. Subjek penelitian terdiri atas 60 mahasiswa yang menempuh mata kuliah Perkembangan Peserta Didik. Data dikumpulkan melalui tes pemahaman sebelum dan sesudah penerapan model pembelajaran berbasis AI, kemudian dianalisis menggunakan statistik deskriptif dan uji paired sample t-test. Hasil penelitian menunjukkan bahwa penerapan model pembelajaran berbasis AI meningkatkan pemahaman mahasiswa secara signifikan. Rata-rata skor pemahaman meningkat dari 68,25 pada pretest menjadi 84,70 pada posttest (p < 0,05). Selain itu, mahasiswa menunjukkan peningkatan partisipasi, motivasi belajar, dan kemampuan memahami karakteristik serta tahapan perkembangan peserta didik. Fitur AI yang interaktif dan adaptif membantu mahasiswa memperoleh pengalaman belajar yang lebih personal dan efektif. Temuan ini menunjukkan bahwa model pembelajaran berbasis AI dapat menjadi alternatif inovatif untuk meningkatkan pemahaman konseptual mahasiswa pada mata kuliah Perkembangan Peserta Didik. Integrasi AI dalam pembelajaran direkomendasikan untuk mendukung efektivitas proses belajar di perguruan tinggi.
References
Bozkurt, A., Xiao, J., Lambert, S. R., Pazurek, A., Crompton, H., Koseoglu, S., Farrow, R., Bond, M., Nerantzi, C., Honeychurch, S., & Bali, M. (2024). Artificial intelligence and the future of higher education: A global perspective. Educational Technology Research and Development, 72(1), 1–18. https://doi.org/10.1007/s11423-023-10292-0
Chan, C. K. Y., & Hu, W. (2023). Students' voices on generative AI: Perceptions, benefits, and challenges in higher education. Computers and Education: Artificial Intelligence, 4, 100132. https://doi.org/10.1016/j.caeai.2023.100132
Chiu, T. K. F. (2025). The impact of artificial intelligence on student engagement and learning outcomes in higher education. Computers & Education, 216, 105042.
Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. Educational Technology Research and Development, 71(6), 3219–3245. https://doi.org/10.1007/s11423-023-10236-8
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., & Rana, N. P. (2025). So what if ChatGPT wrote it? Multidisciplinary perspectives on opportunities, challenges and implications of generative artificial intelligence for research, practice and education. International Journal of Information Management, 78, 102847.
Holmes, W., & Tuomi, I. (2022). State of the art and practice in AI in education. European Journal of Education, 57(4), 542–570. https://doi.org/10.1111/ejed.12533
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., Pfeiffer, F., 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
Kohnke, L., Moorhouse, B. L., & Zou, D. (2024). Exploring AI-supported adaptive learning in higher education: Opportunities and challenges. Educational Technology & Society, 27(1), 45–58.
Lim, W. M., Gunasekara, A. N., Pallant, J. L., Pallant, J. I., & Pechenkina, E. (2024). Generative AI and the future of education: Current practices and emerging directions. The International Journal of Management Education, 22(1), 100932.
Lo, C. K. (2025). Artificial intelligence-assisted case-based learning and students’ analytical thinking in higher education. Education and Information Technologies, 30(2), 1745–1763.
Luckin, R., & Cukurova, M. (2022). Designing educational technologies in the age of artificial intelligence. British Journal of Educational Technology, 53(5), 1156–1170. https://doi.org/10.1111/bjet.13261
Miller, P. H. (2021). Theories of developmental psychology (7th ed.). Worth Publishers.
Moorhouse, B. L., Yeo, M. A., & Wan, Y. (2024). Generative artificial intelligence in higher education: Pedagogical implications and student learning experiences. Journal of University Teaching & Learning Practice, 21(1), 1–15.
Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2023). AI literacy: Definition, teaching, and learning. Computers and Education: Artificial Intelligence, 4, 100125. https://doi.org/10.1016/j.caeai.2023.100125
Santrock, J. W. (2021). Life-span development (18th ed.). McGraw-Hill Education.
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(1), 15. https://doi.org/10.1186/s40561-023-00237-x
UNESCO. (2023). Guidance for generative AI in education and research. UNESCO Publishing.
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2021). Systematic review of research on artificial intelligence applications in higher education: Where are the educators? International Journal of Educational Technology in Higher Education, 18(1), 39. https://doi.org/10.1186/s41239-021-00261-7
