Using AI And Research Methods To Prepare The Next Generation
TL;DR
Data gathered in a focus group of recent Business Management graduates who took a research methods in their final year is used to identify pointers for how use of generative AI can be incorporated into the teaching of research methods and how this can prepare a forthcoming generation of students for the workplace.
Abstract
Generative Artificial Intelligence has had a profound and continuing impact on both research and on higher education in recent years. There are a number of issues arising from this which are particularly relevant to teaching research methods at undergraduate level. Generative AI has considerable potential to facilitate research, notably in reviewing literature, and as such its use should arguably be part of the syllabus for students on a taught degree course. However much of the dialogue, so far, about generative AI in the context of university teaching, particularly at the undergraduate level, has focused on concerns that its use by students weakens established forms of assessment and could inhibit learning through being used as a short cut to obtaining a degree. To complicate the picture further, undergraduates are preparing to enter an uncertain environment for employment, with a concern that generative AI will directly affect many graduate-level jobs and that during their careers it will change the landscape within which they work in ways that cannot possibly be predicted. This paper builds on earlier conceptual work presented at ECRM in 2025 and uses data gathered in a focus group of recent Business Management graduates who took a research methods in their final year. It uses their experience to identify pointers for how use of generative AI can be incorporated into the teaching of research methods and how this can prepare a forthcoming generation of students for the workplace. The recent graduates participated in a focus group in which they reported varying experiences of use of AI whilst they were studying and following university. There were considerable differences between individuals in their propensity to engage with AI and in the resources that they used to support this engagement. However, a common theme highlighted by participants was the scope for universities to provide more thorough guidance about the practicalities of students’ use of AI.