Student Perceptions of Generative Artificial Intelligence Regulations: A Mixed-Methods Study of Higher Education in Singapore

Abstract

The rapid adoption of generative artificial intelligence (GenAI) in higher education has raised questions about student use, academic integrity, and institutional regulation. This study examines students' perceptions of and compliance with GenAI regulations in higher education, using a Singaporean university as a case study. Adopting a mixed-methods approach, the research combines thematic analysis of survey responses and quantitative modelling based on the Theory of Planned Behaviour. Qualitative results reveal that students value GenAI for its learning support, time efficiency, and advanced capabilities, yet emphasise the need for clearer guidelines and improved education on appropriate usage. Quantitative analysis highlights the positive influence of guideline understanding on compliance and declaration honesty but notes the negative impacts of perceived restrictiveness and increased GenAI experience. Faculty influence promotes compliance but minimally affects honesty, indicating the need for distinct strategies to address visible and ethical adherence. This research underscores the importance of balanced, flexible regulatory frameworks that integrate educational clarity and faculty engagement, advancing the discourse on GenAI governance in higher education.