Date
Publisher
arXiv
The increasing integration of artificial intelligence (AI) in higher education has raised important questions regarding students' transparency in reporting AI-assisted work. This study investigates the psychological mechanisms underlying university students' willingness to disclose AI use by applying the Cognition--Affect--Conation (CAC) framework. A sequential explanatory mixed-methods design was employed. In the quantitative phase, survey data were collected from 546 university students and analysed using structural equation modelling to examine the relationships among cognitive perceptions, affective responses, and disclosure intention. In the qualitative phase, semi-structured interviews with 22 students were conducted to further interpret the quantitative findings. The results indicate that psychological safety significantly increases students' willingness to disclose AI use and is positively shaped by perceived fairness, perceived teacher support, and perceived organisational support. Conversely, evaluation apprehension reduces disclosure intention and psychological safety, and is strengthened by perceived stigma, perceived uncertainty, and privacy concern. Qualitative findings further reveal that institutional clarity and supportive instructional practices encourage openness, whereas policy ambiguity and fear of negative evaluation often lead students to adopt cautious or strategic disclosure practices. Overall, the study highlights the dual role of enabling and inhibitory psychological mechanisms in shaping AI-use disclosure and underscores the importance of supportive institutional environments and clear guidance for promoting responsible AI transparency in higher education.
Study at a glance
- Question: What psychological factors encourage or discourage university students from disclosing their use of artificial intelligence in coursework?
- Setting and data: Universities across China; survey of 546 undergraduate and postgraduate students, followed by semi-structured interviews with 22 students.
- Method: Sequential explanatory mixed-methods design using structural equation modeling and deductive-inductive thematic analysis.
Why it matters
As generative artificial intelligence becomes common in coursework, universities face questions about academic integrity. Little empirical research examines the psychological reasons why students choose to voluntarily disclose or conceal their use of these tools.
Key findings
- Psychological safety significantly increased students' willingness to disclose AI use, supported by perceived teacher support, perceived fairness, and perceived organizational support.
- Evaluation apprehension reduced students' willingness to disclose AI use and lowered psychological safety, driven by perceived stigma, perceived uncertainty, and privacy concerns.
- Interviews revealed that students adopted cautious, conditional, or strategic disclosure practices, especially when faced with conflicting instructor expectations or risks of negative academic evaluation.
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