Y. Mormul, J. Przybyszewski, A. Nakoud and P. Cuffe, “Reliance on Artificial Intelligence Tools May Displace Research Skills Acquisition Within Engineering Doctoral Programmes: Examples and Implications”, presented at IEEE International Conference on IT in Higher Education and Training, Paris, France, November 2024

The escalation in capabilities of Large Language Models has triggered urgent discussions about their implications for tertiary education, particularly regarding how they might facilitate academic misconduct in graded engineering coursework. However, graduate research education — where a student works closely with a supervisor over years to develop both implicit and explicit research skills — has received comparatively less attention in this discussion. This paper seeks to develop this discourse by presenting targeted case studies that explore the opportunities and threats posed by artificial intelligence to engineering doctoral education. For instance, using a specimen exercise from a PhD-level research skills module, we demonstrate how artificial intelligence tools can now deeply penetrate research workflows in technical computing and scripting. We likewise investigate the capabilities of chatbot tools to assist engineering PhD candidates with the broader research skills central to their training and development. These include writing and proofreading theses and research papers, producing data visualizations, simulating peer review processes, and preparing scientific diagrams. By evaluating the capabilities and limitations of extant artificial intelligence in these areas, we can discuss both the potential benefits and ethical concerns of doctoral students engaging with such assistance.