Bai, J., Bai, S., Chu, Y., Cui, Z., Dang, K., Deng, X., ... & Zhu, T. (2023). Qwen technical report. arXiv preprint arXiv:2309.16609. https://arxiv.org/abs/2309.16609
Bender, E. M., Costello, E., Lee, K., Farrow, R., & Ferreira, G. (2025). Unsafe AI for Education: A Conversation on Stochastic Parrots and Other Learning Metaphors. Journal of Interactive Media in Education, 2025(1). https://doi.org/10.5334/jime.1079
Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021, March). On the dangers of stochastic parrots: Can language models be too big?. In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency (pp. 610-623). https://doi.org/10.1145/3442188.3445922
Bulut, O., Beiting-Parrish, M., Casabianca, J. M., Slater, S. C., Jiao, H., Song, D., ... & Morilova, P. (2024). The rise of artificial intelligence in educational measurement: Opportunities and ethical challenges. arXiv preprint arXiv:2406.18900.source - https://www.aera.net
Chui, M., Yee, L., Hall, B., & Singla, A. (2023). The state of AI in 2023: Generative AI’s breakout year. https://www.mckinsey.com
Gao, R., Merzdorf, H. E., Anwar, S., Hipwell, M. C., & Srinivasa, A. (2023). Automatic assessment of text-based responses in post-secondary education: A systematic review https://doi.org/10.48550/arXiv.2308.16151
Guel, Mi & Molina-Espinosa, José-Martín & Ramírez-Montoya, María-Soledad. (2024). Challenges of implementing ChatGPT on education: Systematic literature review. International Journal of Educational Research Open. 8. 10.1016/j.ijedro.2024.100401. http://dx.doi.org/10.1016/j.ijedro.2024.100401
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.12528
Kumar, J. A. (2021). Educational chatbots for project-based learning: investigating learning outcomes for a team-based design course. International journal of educational technology in higher education, 18(1), 65. https://doi.org/10.1186/s41239-021-00302-w
Lee, R. Y., Kross, E. K., Torrence, J., Li, K. S., Sibley, J., Cohen, T., ... & Curtis, J. R. (2023). Assessment of natural language processing of electronic health records to measure goals-of-care discussions as a clinical trial outcome. JAMA Network Open, 6(3), e231204-e231204. doi:10.1001/jamanetworkopen.2023.1204
Luo, Y., Abidian, M. R., Ahn, J. H., Akinwande, D., Andrews, A. M., Antonietti, M., ... & Chen, X. (2023). Technology roadmap for flexible sensors. ACS nano, 17(6), 5211-5295. https://doi.org/10.1021/acsnano.2c12664
NITI Aayog. (2018). National Strategy for Artificial Intelligence—Discussion Paper. NITI Aayog. Source-https://www.niti.gov.in/sites/default/files/2019-01/NationalStrategy-for-AI-Discussion-Paper.pdf
Okonkwo, C. W., & Ade-Ibijola, A. (2021). Chatbots applications in education: A systematic review. Computers and Education: Artificial Intelligence, 2, 100033. https://doi.org/10.1016/j.caeai.2021.100033
Pelletier, K., McCormack, M., Reeves, J., Robert, J., Arbino, N., Dickson-Deane, C., ... & Stine, J. (2022). 2022 educause horizon report teaching and learning edition (pp. 1-58). EDUC22.
Rudolph, J., Tan, S., & Tan, S. (2023). ChatGPT: Bullshit spewer or the end of traditional assessments in higher education?. Journal of applied learning and teaching, 6(1), 342-363. https://doi.org/10.37074/jalt.2023.6.1.9
Sambasivan, N., Arnesen, E., Hutchinson, B., Doshi, T., & Prabhakaran, V. (2021, March). Re-imagining algorithmic fairness in india and beyond. In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency (pp. 315-328). https://doi.org/10.48550/arXiv.2305.16519
Sedrakyan, G., Borsci, S., Machado, M., Rogetzer, P., & Mes, M. (2024, October). Design Implications for Integrating AI Chatbot Technology with Learning Management Systems: A Study-based Analysis on Perceived Benefits and Challenges in Higher Education. In Proceedings of the 2024 International Conference on Artificial Intelligence and Teacher Education (pp. 1-8).https://doi.org/10.1145/3702386.3702405
Shen, X., Chen, Z., Backes, M., & Zhang, Y. (2023). In chatgpt we trust? measuring and characterizing the reliability of chatgpt. arXiv preprint arXiv:2304.08979. https://doi.org/10.48550/arXiv.2304.08979
Thorp, H. H. (2023). ChatGPT is fun, but not an author. Science, 379(6630), 313-313. https://doi.org/10.1126/science.adg7879
Vallerand, R. J. (2000). Deci and Ryan's self-determination theory: A view from the hierarchical model of intrinsic and extrinsic motivation. Psychological inquiry, 11(4), 312-318. https://psycnet.apa.org/doi/10.1037/0003-066X.55.1.68
Wang, R., Zelikman, E., Poesia, G., Pu, Y., Haber, N., & Goodman, N. D. (2023). Hypothesis search: Inductive reasoning with language models. arXiv preprint arXiv:2309.05660. https://doi.org/10.48550/arXiv.2309.05660 https://arxiv.org/abs/2311.07918?utm
Wilkins, D. (2023). Automated title and abstract screening for scoping reviews using the GPT-4 Large Language Model. arXiv preprint arXiv:2311.07918. https://doi.org/10.48550/arXiv.2311.07918
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