Bridging the trust gap: a mixed-methods study of United Kingdom educators’ perceptions of generative artificial intelligence in higher education assessment

Abstract

Situated against the backdrop of an evolving regulatory landscape, this study investigates the perceptions of United Kingdom university educators regarding the use of generative artificial intelligence in summative assessment. Through a mixed-methods survey of 330 academic staff, the research identifies a significant gap between high levels of digital literacy and low evaluative trust. While respondents report high familiarity with AI tools, confidence in the ability of artificial intelligence to provide fair or nuanced marks remains low. Qualitative analysis of open text questions reveals a nuance crisis, where educators perceive these systems as incapable of comprehending complex student submissions. The findings reveal significant gender disparities in technical proficiency, however, a consistent pattern of low evaluative trust persists across teaching experience levels, with no statistically significant differences detected based on professional seniority, suggesting a potential need to consider alternative pedagogical frameworks, such as performative and synchronous assessments, to safeguard academic integrity.