TRANSFORMASI BELAJAR BIOLOGI MELALUI MODUL DIGITAL INTERAKTIF BERBASIS AI: EKSPLORASI PERSEPSI SISWA KELAS XI SMA
Keywords:
AI, Modul Digital, Persepsi Siswa, Pembelajaran Biologi, Sistem KoordinasiAbstract
Kemajuan teknologi digital seharusnya mampu menjawab tantangan pembelajaran abad ke-21, khususnya dalam bidang Biologi yang kompleks dan sering kali dianggap sulit oleh siswa. Namun, pada kenyataannya, masih banyak siswa yang mengalami kesulitan memahami materi karena keterbatasan media pembelajaran yang interaktif dan adaptif. Penelitian ini bertujuan untuk mengeksplorasi persepsi siswa kelas XI SMA terhadap penggunaan modul digital interaktif berbasis kecerdasan buatan (AI) dalam pembelajaran Biologi. Penelitian ini menggunakan pendekatan pendekatan kuantitatif dan kualitatif (mix-methods explanatory sequential design dengan teknik survei. Hasil penelitian menunjukkan bahwa persepsi siswa terhadap modul digital berbasis AI berada pada kategori sangat baik, terutama dalam aspek kebermanfaatan materi. Temuan ini mengindikasikan bahwa integrasi AI dalam modul digital berpotensi memberikan transformasi positif dalam pengalaman belajar Biologi di tingkat sekolah menengah. Temuan ini mengindikasikan bahwa integrasi AI dalam pembelajaran Biologi melalui modul digital memiliki potensi besar dalam mendukung transformasi pembelajaran yang lebih inovatif dan personalisasi
References
Akour, M., & Alenezi, M. (2022). Higher Education Future in the Era of Digital Transformation. Education Sciences. https://doi.org/10.3390/educsci12110784.
Alammary, A. (2021). Blended learning models for introductory programming courses: A systematic review. PLOS ONE, 16(1), e0244640. https://doi.org/10.1371/journal.pone.0244640
Alneyadi, R., & Wardat, Y. (2023). Exploring the impact of artificial intelligence in teaching and learning of science: A systematic review of empirical research. Research in Science Education. https://doi.org/10.1007/s11165-024-10176-3
Alasadi, E., & Baiz, C. (2023). Generative AI in Education and Research: Opportunities, Concerns, and Solutions. Journal of Chemical Education. https://doi.org/10.1021/acs.jchemed.3c00323.
Almasri, F. (2024). Exploring the impact of artificial intelligence in teaching and learning of science: A systematic review of empirical research. Research in Science Education, 54(5), 977-997.https://doi.org/10.1007/s11165-024-10176-3
Anghel, G. A., Zanfir, C. M., Matei, F. L., Voicu, C. D., & Neacșa, R. A. (2025). The Integration of Artificial Intelligence in Academic Learning Practices: A Comprehensive Approach. Education Sciences, 15(5), 616. https://doi.org/10.3390/educsci15050616
Bandura, A. (1997). Self-efficacy: The exercise of control (Vol. 11). Freeman.
Chairad, M., Damanik, S., Hasibuan, B., & Lubis, A. (2025). The Importance of Adaptive E-Modules in 21st Century Education. Proceedings of the 6th International Conference on Innovation in Education, Science, and Culture, ICIESC 2024, 17 September 2024, Medan, Indonesia. https://doi.org/10.4108/eai.17-9-2024.2352962.
Code, A., Pisica, I., Pacheco Mendoza, E., Stenalt, M., & Hachmann, K. (2024). The integration of artificial intelligence in academic learning practices: A comprehensive approach. Education Sciences, 15(5), 616. https://doi.org/10.3390/educsci15050616
Consoli, T., Schmitz, M., Antonietti, C., Gonon, P., Cattaneo, A., & Petko, D. (2024). Quality of technology integration matters: Positive associations with students’ behavioral engagement and digital competencies for learning. Education and Information Technologies, 30, 7719 - 7752. https://doi.org/10.1007/s10639-024-13118-8.
Dawson, S., Joksimovic, S., Poquet, O., & Siemens, G. (2019, March). Increasing the impact of learning analytics. In Proceedings of the 9th international conference on learning analytics & knowledge (pp. 446-455).
Hanatan, R., Yuniastuti, E., & Prayitno, B. (2023). Developing Interactive Digital Modules on Discovery Learning to Improve Students Learning Interest. Jurnal Teknodik. https://doi.org/10.32550/teknodik.vi.862.
Huang, R. H., Liu, D. J., Tlili, A., Yang, J., Wang, H., & Zhang, M. (2020). Handbook on facilitating flexible learning during educational disruption: The Chinese experience in maintaining undisrupted learning in COVID-19 outbreak. Beijing: Smart Learning Institute of Beijing Normal University, 46.
Ismaniati, C., Iskhamdhanah, B., & , V. (2023). Development of Interactive E-Modules to Increase Learning Motivation and Science Literacy in Elementary School Students. Jurnal Iqra' : Kajian Ilmu Pendidikan. https://doi.org/10.25217/ji.v8i1.2699.
Mukul, E., & Büyüközkan, G. (2023). Digital transformation in education: A systematic review of education 4.0. Technological Forecasting and Social Change. https://doi.org/10.1016/j.techfore.2023.122664.
Riyanto, F., Miranto, S., & Noor, M. F. (2024). The development of an interactive biology e module based on Articulate Storyline for Class XI digestive system concepts. International Journal of Learning Media on Natural Science (IJLENS), 1(1), 14–19. https://doi.org/10.60005/ijlens.v1i1.20
Strielkowski, W., et al. (2024). AI driven adaptive learning for sustainable educational transformation. Sustainable Development. https://doi.org/10.1002/sd.3221
Syahfitri, J., & Safitri, D. (2024). The effect of digital based interactive modules to improve student’s critical thinking skills and learning motivation on biology learning. Jurnal Penelitian Pendidikan IPA, 10(5), 2495–2502. https://doi.org/10.29303/jppipa.v10i5.3878
Tarigan, W., Sipahutar, H., & Harahap, F. (2021). The Effect of Interactive Digital Learning Module on Student’s Learning Activity and Autonomy. Bioedukasi: Jurnal Pendidikan Biologi. https://doi.org/10.20961/bioedukasi-uns.v14i2.49366.
Tsai, C., Ku, H., & Campbell, A. (2021). Impacts of course activities on student perceptions of engagement and learning online. Distance Education, 42, 106 - 125. https://doi.org/10.1080/01587919.2020.1869525.
Walter, Y. (2024). Embracing the future of Artificial Intelligence in the classroom: the relevance of AI literacy, prompt engineering, and critical thinking in modern education. International Journal of Educational Technology in Higher Education, 21, 1-29. https://doi.org/10.1186/s41239-024-00448-3.
Wang, S., Wang, F., Zhu, Z., Wang, J., Tran, T., & Du, Z. (2024). Artificial intelligence in education: A systematic literature review. Expert Syst. Appl., 252, 124167. https://doi.org/10.1016/j.eswa.2024.124167.
Yaseen, H., Mohammad, A. S., Ashal, N., Abusaimeh, H., Ali, A., & Sharabati, A. A. A. (2025). The impact of adaptive learning technologies, personalized feedback, and interactive AI tools on student engagement: The moderating role of digital literacy. Sustainability, 17(3), 1133. https://doi.org/10.3390/su17031133
Yin, J., Xu, H., Pan, Y., & Hu, Y. (2025). Effects of different AI-driven Chatbot feedback on learning outcomes and brain activity. NPJ Science of Learning, 10. https://doi.org/10.1038/s41539-025-00311-8
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education–where are the educators?. International journal of educational technology in higher education, 16(1), 1-27. https://doi.org/10.1186/s41239-019-0171-0
