Generative AI in Higher Education: Graduate Teaching Assistants’ Practice and Reflection on ChatGPT for Module Assessment

Abstract

The rapid evolvement of Artificial Intelligence (AI) and the launch of ChatGPT and other Generative AI tools have concerned Higher Education Institutions (HEIs), which now need to develop comprehensive pedagogical guidelines and frameworks in this emerging AI era. These advancements have sparked discussions and research on their implications on assessment design and student assessment, with multiple opposing perspectives emerging. Whilst ChatGPT is perceived as an important opportunity for enhancing student learning, it is considered as a significant threat to academic integrity and student skills development. These differing perspectives create the need for teaching staff to reflect on their pedagogical practices on ChatGPT and Generative AI and propose potential paths forward for HEIs. Although research on Generative AI and assessment design is rapidly growing, the perspective of Graduate Teaching Assistants (GTAs) as teaching staff uniquely positioned to bridge the gap between faculty and students, is under-represented. To this end, in this practice paper, GTAs reflect on their dual identities as student and tutor to evaluate differing positions to the role of ChatGPT to support or hinder assessment. By being involved in a ChatGPT project for student assessment for MSc students in Engineering degrees, the authors present their reflections on the impact that ChatGPT and Generative AI technologies may have on HEIs, with a focus on assessment design, as well as on potential paths forward for the sector. This practice paper contributes to the ongoing discussions and research on the development of pedagogical guidelines and frameworks in the Generative AI era.