Â鶹ÒùÔº

Supported by Â鶹ÒùԺ’s 2023/24 Small Grants Fund, this research project aimed to offer timely and novel insights into the educational opportunities and challenges presented by the use of generative artificial intelligence (GenAI) vis-à-vis academic integrity practices in university settings. The project involved interviews and focus groups with educators who were also academic integrity officers (AIOs) across faculties at a Russell Group university in England.

Research participants identified opportunities and challenges of using GenAI in contemporary practices of teaching and learning, with the challenges primarily relating to academic integrity guidance and regulations in a university setting. The report presents the key themes that emerged and offers recommendations for universities, staff and students in harnessing the opportunities identified while simultaneously mitigating the challenges.

Report summary

Our education systems have been acutely shaped by the rapid digitalisation of services (Selwyn, 2016). Recent interventions in the form of artificial intelligence, particularly the rise of language learning models (LLMs) (for example, ChatGPT), have effectively perturbed the teaching and learning industry across educational levels and institutions globally. Despite the plethora of views across sectors, there are relatively fewer empirically charged scholarly discussions on the issue. Redressing this gap, this project explores opportunities and challenges of using generative artificial intelligence (GenAI) vis-à-vis academic integrity in higher education (HE) settings.

Fieldwork for this project was carried out between September and December 2023. It involved semistructured one-to-one formal interviews (n=10) and two focus groups (n=5) with educators who at the time of the fieldwork also played the role of academic integrity officers (AIOs) across faculties at a Russell Group university in England.

Research findings suggest that GenAI as a shadow education (or e-tutoring) tool can be beneficial in terms of expanding access to multiple knowledge bases and digital skills of future graduates. At the same time, its use has the potential to disrupt current quality assurance practices and undermine university principles and values of cultivating critical and creative thinking and learning skills – notably through the homogenisation of learning experiences often based on erroneous (and un-equalising) assumptions. Furthermore, staff views on GenAI vary by discipline due to, for example, their teaching and learning practices, perceived relationship between HE and the relevant industry, and assessment modes and designs. Key recommendations include a clear university-level policy on GenAI use and a revitalisation of academic integrity education and guidelines in partnership with staff and students across and within disciplines.