Artificial Intelligence Chatbots and Independent Learning among University Students
DOI:
https://doi.org/10.63345/Keywords:
Artificial intelligence chatbots, independent learning, generative AI, self-regulated learning, cognitive offloading, university studentsAbstract
Artificial intelligence chatbots have rapidly become embedded in university learning, offering conversational explanations, personalized feedback, idea generation, and on-demand academic assistance.
Despite growing evidence of their educational utility, it remains unclear whether sustained chatbot use develops students’ independent learning capacity or gradually transfers essential cognitive and metacognitive activities from learners to automated systems.
This study addresses this gap by conceptualizing chatbot-supported learning as a dynamic continuum between strategic cognitive scaffolding and AI-dependent cognitive offloading. A learning-analytics framework is proposed to examine how prompt refinement, answer verification, self-explanation, independent task completion, and reliance on direct AI-generated solutions relate to self-regulated learning among university students.
Rather than evaluating chatbot adoption through usage frequency alone, the study introduces a behavioural perspective in which the quality and sequence of human–AI interactions are treated as indicators of developing or diminishing learner autonomy. The proposed investigation combines self-regulated-learning constructs with interaction-level AI analytics to distinguish productive assistance seeking from excessive computational dependency.
References
1. 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., Stadler, M., & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
2. Guan, R., Raković, M., Chen, G., & Gašević, D. (2025). How educational chatbots support self-regulated learning? A systematic review of the literature. Education and Information Technologies, 30, 4493–4518. https://doi.org/10.1007/s10639-024-12881-y
3. Zhai, C., Wibowo, S., & Li, L. D. (2024). The effects of over-reliance on AI dialogue systems on students' cognitive abilities: A systematic review. Smart Learning Environments, 11, 28. https://doi.org/10.1186/s40561-024-00316-7
4. Deng, R., Jiang, M., Yu, X., Lu, Y., & Liu, S. (2024). Does ChatGPT enhance student learning? A systematic review and meta-analysis of experimental studies. Computers & Education, 214, 105224. https://doi.org/10.1016/j.compedu.2024.105224
5. 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. https://doi.org/10.1186/s40561-023-00237-x
6. Lo, C. K. (2023). What is the impact of ChatGPT on education? A rapid review of the literature. Education Sciences, 13(4), 410. https://doi.org/10.3390/educsci13040410
7. Albadarin, Y., Saqr, M., Pope, N., & Tukiainen, M. (2024). A systematic literature review of empirical research on ChatGPT in education. Discover Education, 3, 60. https://doi.org/10.1007/s44217-024-00138-2
8. Baig, M. I., & Yadegaridehkordi, E. (2024). ChatGPT in higher education: A systematic literature review and research challenges. International Journal of Educational Research, 127, 102411. https://doi.org/10.1016/j.ijer.2024.102411
9. Lo, C. K., Hew, K. F., & Jong, M. S. Y. (2024). The influence of ChatGPT on student engagement: A systematic review and future research agenda. Computers & Education, 219, 105100. https://doi.org/10.1016/j.compedu.2024.105100
10. An, Q., Koh, J. H. L., & Liu, Q. (2026). Generative artificial intelligence in higher education: A systematic review of student use and learning outcomes. Australasian Journal of Educational Technology. https://doi.org/10.14742/ajet.10561
