A Learning Agreement for Generative AI Use in University Courses: A Pilot Study

Abstract

The rapidly evolving landscape of Generative AI (GenAI) tools necessitate continuous vigilance and adaptation by educators. This dynamism requires stakeholders to stay up to date with developments to address emerging issues effectively, creating complexity in managing the responsible and ethical use of GenAI. This paper presents a pilot study involving the use of student learning agreements for governing GenAI use in a first-year engineering degree course. The learning agreement contains ethical and social considerations students agree to make if they decide to use GenAI in the course. As part of the pilot study, pre-post surveys and student artefacts – a group assignment adapted to accommodate GenAI use – were analysed. Results show that the vast majority of students were in favour of the learning agreement approach both at the start and upon completion of the course. However, 7 of 17 groups did not use GenAI in their assignment. Of the 10 groups that did, only 1 acknowledged GenAI limitations in adherence with the learning agreement. A thematic analysis of student suggestions for improving the learning agreement approach include suggestions for making the agreement easier to understand and adhere to (e.g., providing specific examples, reengaging with the agreement during the course). Overall, findings suggest that learning agreements have the potential to offer an interface through which student decision-making can be supported and interactions among students, educators, researchers, and policy makers related to the ethical and societal challenges of GenAI can take place.