Teaching Research Methods in a Changing World: Responding to Generative Artificial Intelligence

While the tools associated with Generative Artificial Intelligence have evolved over some years, they have become widely used and entered widespread public consciousness since 2022. Generative AI has an immediate impact on Higher Education because of its effect on many of the skills that students need to acquire. Immediate responses to the availability of Generative AI have focused on concerns about student cheating and about the need to design its inappropriate use out of assessments. While the discussion of how it affects learning and teaching has moved on to recognise that students do need to understand how Generative AI can be used there is still limited appreciation of where it fits into the teaching of research methods. Generative AI, used carefully and appropriately, can be applied as a research tool and as it evolves it is likely that new opportunities for its use will emerge. Research typically entails a measure of independent work and scholarly writing by students. Generative AI can create wording which, at least superficially, can appear to a reader as professional and fluent but which is often generic and superficial. For a student encountering the need to carry out research for the first time, typically as part of a taught degree course, it can be difficult to distinguish between the legitimate use of Generative AI, for example to assist with creating ideas, and its inappropriate use to produce text which does not reflect research which has been carried out. A useful starting point for discussing the application of Generative AI is to compare it with the involvement of another person. For a student to pretend that something is their own work when it is not, constitutes plagiarism whether the work in fact is produced by somebody else or it is produced by an AI engine. Conversely it would be reasonable to discuss concepts with another person and similarly to discuss them with AI. Framing this introduces some challenges around how to build AI into teaching about research.