Student Dependence on Generative AI and Its Impact on Classroom Learning: A Mixed-Methods Study in Chemistry Education
DOI:
https://doi.org/10.55927/jeda.v5i2.1Keywords:
Generative Artificial Intelligence, AI Dependence, Classroom Learning Engagement, AI Literacy, Chemistry EducationAbstract
This study examines students’ dependence on generative AI and its impact on classroom learning. The research contributes to understanding how AI use, AI literacy, and ethical practices interact to shape learning outcomes in higher education. Using a mixed-methods embedded survey design, data were collected through a questionnaire combining Likert-scale items and open-ended questions from 40 undergraduate students in the Chemistry Education program at Universitas Negeri Makassar during one semester of classroom learning activities. The analysis included descriptive statistics, correlation, regression analysis, and thematic analysis of qualitative responses. The findings show that AI dependence is associated with perceived learning benefits, while AI literacy strongly predicts positive learning outcomes and lower integrity risk. These results highlight the importance of AI literacy and responsible AI use in supporting meaningful classroom learning.
References
Blonder, R., & Feldman-Maggor, Y. (2024). AI for chemistry teaching: Responsible AI and ethical considerations. Chemistry Teacher International. https://doi.org/10.1515/cti-2024-0014
Deng, J. M., Lalani, Z., McDermaid, L. A., & Szozda, A. (2023). Using generative artificial intelligence in chemistry education research: Prioritizing ethical use and accessibility. ChemRxiv. https://doi.org/10.26434/chemrxiv-2023-24zfl
Dos Santos, R. P. (2023). Enhancing chemistry learning with ChatGPT, Bing Chat, Bard, and Claude as agents-to-think-with: A comparative case study. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4629567
El Bahri, N., Itahriouan, Z., & Abtoy, A. (2025). The impact of generative AI on education. In Advances in educational technologies and instructional design (pp. 29–64). IGI Global. https://doi.org/10.4018/979-8-3373-2262-9.ch002
Erümit, A. K., & Sarıalioğlu, R. Ö. (2025). Artificial intelligence in science and chemistry education: A systematic review. Discover Education, 4(1). https://doi.org/10.1007/s44217-025-00622-3
Farrell, H. (2024). Re-imagining student engagement in an AI-enhanced classroom. In AI and education: Teaching in the digital age (pp. 67–73). Routledge. https://doi.org/10.4324/9781003482918-10
Gervacio, A. P. (2024). Exploring how generative AI contributes to the motivated engagement and learning production of science-oriented students. Environment & Social Psychology, 9(11). https://doi.org/10.59429/esp.v9i11.3194
Guo, F., Li, T., & Cunningham, C. J. L. (2025). One year in the classroom with ChatGPT: Empirical insights and transformative impacts. Frontiers in Education, 10. https://doi.org/10.3389/feduc.2025.1574477
Hamerman, E. J., Aggarwal, A., & Martins, C. (2024). An investigation of generative AI in the classroom and its implications for university policy. Quality Assurance in Education. https://doi.org/10.1108/qae-08-2024-0149
He, Y., Xiao, K., Shi, Z., & Zhao, L. (2025). “Dependence” or “critical thinking”? The thinking choices of education doctoral students in generative AI environment: Qualitative research based on interview. In Proceedings of the International Conference on Artificial Intelligence in Education (pp. 498–503). https://doi.org/10.1109/icaie64856.2025.11158573
Huwer, J., Maurer, N., Mundt, P., & Belova, N. (2025). AI in chemistry and chemical education. International Journal of Physics and Chemistry Education, 17(1), 1–4. https://doi.org/10.51724/ijpce.v17i1.403
Irshad, A., Uzair-ul-Hassan, M., & Parveen, I. (2025). Students’ perspectives on generative AI’s role in transforming, challenging, and enhancing higher education learning practices. Indus Journal of Social Sciences, 3(3), 253–268. https://doi.org/10.59075/ijss.v3i3.1897
Jere, S., & Mpeta, M. (2025). Integrating generative artificial intelligence chatbots into chemistry teaching: Impact of affective factors on engagement and conceptual understanding. Eurasia Journal of Mathematics, Science and Technology Education, 21(10), Article em2713. https://doi.org/10.29333/ejmste/17077
Noblecilla Olaya, A. J., & Chéquer Bajaña, D. I. (2025). Transforming critical and creative thinking: The impact of generative artificial intelligence on higher education. Salud, Ciencia y Tecnología, 5, 1763. https://doi.org/10.56294/saludcyt20251763
Priyadi, D., Suyanta, S., Suwardi, S., & Md Isa, I. (2025). Exploring the role of ChatGPT in chemistry learning: A systematic literature review. Jurnal Pendidikan Sains Indonesia, 13(3), 648–662. https://doi.org/10.24815/jpsi.v13i3.45118
Qadir, J. (2025). Generative AI in undergraduate classrooms: Lessons from implementing a customized GPT chatbot for learning enhancement. TechRxiv. https://doi.org/10.36227/techrxiv.173609986.65771022/v1
Saúde, S., Barros, J.-P., & Almeida, I. (2024). Impacts of generative artificial intelligence in higher education: Research trends and students’ perceptions. Social Sciences, 13(8), 410. https://doi.org/10.3390/socsci13080410
Stone, B. W. (2024). Generative AI in higher education: Uncertain students, ambiguous use cases, and mercenary perspectives. Teaching of Psychology. https://doi.org/10.1177/00986283241305398
Watts, F. M., Dood, A. J., Shultz, G. V., & Rodriguez, J.-M. G. (2023). Comparing student and generative artificial intelligence chatbot responses to organic chemistry writing-to-learn assignments. Journal of Chemical Education, 100(10), 3806–3817. https://doi.org/10.1021/acs.jchemed.3c00664
Wood, D., & Moss, S. H. (2024). Evaluating the impact of students’ generative AI use in educational contexts. Journal of Research in Innovative Teaching & Learning. https://doi.org/10.1108/jrit-06-2024-0151
