“Is this a trap?”: Student teachers’ perceptions and adoption of GenAI in assessments in three teacher education courses

Abstract

Generative artificial intelligence (GenAI) poses unprecedented challenges and opportunities for assessment in universities. Existing studies that explore students’ adoption of GenAI in assessment show mixed and, to some extent, contradictory findings. Some studies have found optimistic views on GenAI, while others have highlighted significant concerns among students. This study aimed to explore students’ interactions with GenAI in completing non-exam assessments using a socio-technical view that recognises the sociocultural and technological factors influencing students’ behaviours. We sampled three teacher education courses that sought to embed the use of GenAI in the assessment. A mixed-methods approach was adopted, which involved data collected from a survey (N = 85), student interviews (N = 11), course materials and a declaration of GenAI use in students’ submitted assignments (N = 158). Our findings indicate that approximately two-thirds of the students decided not to adopt GenAI when allowed, and that the assessment design, the perceived value of the assessment, students’ self-confidence and concerns about being wrongly accused of plagiarism were the most frequently cited reasons. This study shows the importance of consistent assessment policies and effective communication. Moreover, it is important for instructors to have a programme-level view when designing GenAI-related assessment policies.

Implications for practice or policy:

• Effective communication with students about what GenAI usage is or is not allowed in assessment is critical to avoid misunderstanding.
• Personalising and/or contextualising assessments helps reduce students’ reliance on GenAI.
• Course leaders should consider the overall policy and context for using GenAI in assessment beyond their own courses.