Current - Issue
Year 2026 · Volume 6 · Issue 5
Original Article
AI Agent-Based Intelligent Learning System for Personalize Education, Student Performance Prediction and Adaptive Content Generation
Suman Rani1
1 Research Scholar, Department of Computer Science and Engineering, Indira Gandhi University, Meerpur, Haryana, India.
Published Online: September-October 2026
Pages: 311-316
Cite this article
↗ https://www.doi.org/10.59256/ijrtmr.20260605034References
[1] O. Zawacki-Richter, V. I. Marín, M. Bond, and F. Gouverneur, “Systematic review of research on artificial intelligence applications in higher education - where are the educators?,” International Journal of Educational Technology in Higher Education, vol. 16, Art. no. 39, 2019, doi:10.1186/s41239-019-0171-0.
[2] E. Kasneci et al., “ChatGPT for good? On opportunities and challenges of large language models for education,” Learning and Individual Differences, vol. 103, Art. no. 102274, 2023, doi:10.1016/j.lindif.2023.102274.
[3] J. Kuzilek, M. Hlosta, and Z. Zdrahal, “Open University Learning Analytics dataset,” Scientific Data, vol. 4, Art. no. 170171, 2017, doi:10.1038/sdata.2017.171.
[4] C. Piech et al., “Deep knowledge tracing,” in Advances in Neural Information Processing Systems, vol. 28, 2015. [Online]. Available: https://arxiv.org/abs/1506.05908
[5] P. Lewis et al., “Retrieval-augmented generation for knowledge-intensive NLP tasks,” in Advances in Neural Information Processing Systems, vol. 33, pp. 9459-9474, 2020. [Online]. Available: https://arxiv.org/abs/2005.11401
[6] S. Yao et al., “ReAct: Synergizing reasoning and acting in language models,” in Proc. International Conference on Learning Representations, 2023. [Online]. Available: https://arxiv.org/abs/2210.03629
[7] R. E. Wang, A. T. Ribeiro, C. D. Robinson, S. Loeb, and D. Demszky,
“Tutor CoPilot: A human-AI approach for scaling real-time expertise,” arXiv preprint, arXiv:2410.03017, 2024, doi:10.48550/arXiv.2410.03017.
[8] S.M. Lundberg and S.-I. Lee,“A unified approach to interpreting model predictions,” in Advances in Neural Information Processing Systems, vol. 30, 2017. [Online]. Available:
https://arxiv.org/abs/1705.07874
[9] C. Guo, G. Pleiss, Y. Sun, and K. Q. Weinberger, “On calibration of modern neural networks,” in Proc. 34th International Conference on Machine Learning, vol. 70, pp. 1321-1330, 2017. [Online]. Available: https://proceedings.mlr.press/v70/guo17a.html
[10] L. Yan et al., “Practical and ethical challenges of large language models in education: A systematic scoping review,” arXiv preprint, arXiv:2303.13379, 2023, doi: 10.48550/arXiv.2303.13379.
[2] E. Kasneci et al., “ChatGPT for good? On opportunities and challenges of large language models for education,” Learning and Individual Differences, vol. 103, Art. no. 102274, 2023, doi:10.1016/j.lindif.2023.102274.
[3] J. Kuzilek, M. Hlosta, and Z. Zdrahal, “Open University Learning Analytics dataset,” Scientific Data, vol. 4, Art. no. 170171, 2017, doi:10.1038/sdata.2017.171.
[4] C. Piech et al., “Deep knowledge tracing,” in Advances in Neural Information Processing Systems, vol. 28, 2015. [Online]. Available: https://arxiv.org/abs/1506.05908
[5] P. Lewis et al., “Retrieval-augmented generation for knowledge-intensive NLP tasks,” in Advances in Neural Information Processing Systems, vol. 33, pp. 9459-9474, 2020. [Online]. Available: https://arxiv.org/abs/2005.11401
[6] S. Yao et al., “ReAct: Synergizing reasoning and acting in language models,” in Proc. International Conference on Learning Representations, 2023. [Online]. Available: https://arxiv.org/abs/2210.03629
[7] R. E. Wang, A. T. Ribeiro, C. D. Robinson, S. Loeb, and D. Demszky,
“Tutor CoPilot: A human-AI approach for scaling real-time expertise,” arXiv preprint, arXiv:2410.03017, 2024, doi:10.48550/arXiv.2410.03017.
[8] S.M. Lundberg and S.-I. Lee,“A unified approach to interpreting model predictions,” in Advances in Neural Information Processing Systems, vol. 30, 2017. [Online]. Available:
https://arxiv.org/abs/1705.07874
[9] C. Guo, G. Pleiss, Y. Sun, and K. Q. Weinberger, “On calibration of modern neural networks,” in Proc. 34th International Conference on Machine Learning, vol. 70, pp. 1321-1330, 2017. [Online]. Available: https://proceedings.mlr.press/v70/guo17a.html
[10] L. Yan et al., “Practical and ethical challenges of large language models in education: A systematic scoping review,” arXiv preprint, arXiv:2303.13379, 2023, doi: 10.48550/arXiv.2303.13379.
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