The double-edged sword: A discussion on the impact of AI implementation in undergraduate education in the field of physical sciences
DOI:
https://doi.org/10.31305/rrijm.2026.v11.n02.038Keywords:
undergraduate education, physical sciences, mathematical derivations, artificial intelligenceAbstract
It is well known that ever since the commencement of open use of artificial intelligence, its impact in every sphere of human life has been profound and academia is no exception. This utilization of AI is poised to fundamentally reshape undergraduate education, and in this paper, we provide a critical analysis of the potential benefits, practical requirements and widespread implications of integrating AI tools into the curriculum. We begin with a brief history of AI in academia, tracing its evolution from expert systems to modern machine learning. The paper then explores concrete applications of AI in problem solving, mathematical derivation and experimental analyses, demonstrating its potential to enhance understanding and efficiency. We also discuss the conflict between AI as a tool for enhancement versus a support that decelerates independent thought and novel ideas. We argue that the uniqueness of future research is not inherently threatened but will depend on how AI is administered – as a collaborator rather a replacement. Finally, the paper examines the ethical considerations, including academic integrity and transparency, concluding that a proactive, pedagogical integration of AI is essential to prepare a new generation of innovative as well as ethically minded scientists who will be all set for cutting edge research.
References
[1] National Research Council. (2012). Discipline Based Education Research: Understanding and improving Learning in Undergraduate Science and Engineering. Washington DC: The National Academies Press.
[2] N. G. Lederman, & F. Abd-El-Khalick, (2000). The changing face of physical science education. Journal of Research in Science Teaching, 37(3), 221-229.
[3] W. Holmes, M. Bialik, & C. Fadel, (2019). Artificial Intelligence in Education: Promises and Implications for Teaching and Learning. Center for Curriculum Redesign.
[4] M. Turing, (1950). Computing machinery and intelligence. Mind, 59(236), 433-460. DOI: https://doi.org/10.1093/mind/LIX.236.433
[5] J. McCarthy, M. L. Minsky, N. Rochester, & C. E. Shannon, (2006). A proposal for the Dartmouth summer research project on artificial intelligence, August 31, 1955. AI Magazine, 27(4), 12-14.
[6] S. Russell, & P. Norvig, (2021). Artificial Intelligence: A Modern Approach (4th ed.). Pearson.
[7] B. G. Buchanan, & E. H. Shortliffe, (1984). Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project. Addison-Wesley.
[8] M. I. Jordan, & T. M. Mitchell, (2015). Machine learning: Trends, perspectives, and prospects. Science, 349(6245), 255-260. DOI: https://doi.org/10.1126/science.aaa8415
[9] G. Carleo,I. Cirac, K. Cranmer, et al. (2019). Machine learning and the physical sciences. Reviews of Modern Physics, 91(4), 045002. DOI: https://doi.org/10.1103/RevModPhys.91.045002
[10] Vaswani, N. Shazeer, N.Parmar, et al. (2017). Attention Is All You Need. Advances in Neural Information Processing Systems, 30.
[11] R. Bommasani, D. A. Hudson, A. Adcock, et al. (2021). On the Opportunities and Risks of Foundation Models. arXiv preprint arXiv:2108.07258.
[12] E. Choi, Z. Xu, Y. Wang, et al. (2023). ChatGPT in Education: Opportunities and Challenges. Computers & Education: Artificial Intelligence, 4, 100128.
[13] National Academies of Sciences, Engineering, and Medicine. (2018). Data Science for Undergraduates: Opportunities and Options. Washington, DC: The National Academies Press.
[14] R. Luckin, W. Holmes, M. Griffiths, & L. B. Forcier (2016). Intelligence Unleashed: An Argument for AI in Education. Pearson.
[15] B. P. Woolf (1992). Artificial Intelligence in Education. Cambridge University Press.
[16] B. D. Nye (2015). Intelligent tutoring systems by the numbers: Thirty years of research and development. International Journal of Artificial Intelligence in Education, 25(2), 198-204. DOI: https://doi.org/10.1007/s40593-014-0028-6
[17] O. Zawacki-Richter, V. I. Marín, M. Bond, & F. Gouverneur (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), 39. DOI: https://doi.org/10.1186/s41239-019-0171-0
[18] UNESCO. (2021). Recommendation on the Ethics of Artificial Intelligence. Paris: UNESCO.
[19] OECD. (2023). AI and the Future of Education: Policy Guidance. OECD Publishing.
