The Hidden Cost of Disclosure: A Multi-Institutional Study on Undergraduate Students’ Generative AI Usage and Faculty Accusations
Matthew A. Vetter, Islam Farag, Jialei Jiang, Brent Lucia, John J. SilvestroA current challenge in higher education policy is creating a transparent learning environment where students can disclose their use of GenAI to their faculty without any repercussions. This quantitative study investigates how self-reported GenAI usage patterns, course policies, and wrongful accusations shape student disclosure behaviors. Analyzing survey data from 560 students at four Northeastern U.S. institutions, the research explores disclosure through a trust-distrust lens. Results indicate that frequent GenAI users were significantly more likely to rarely disclose usage. Furthermore, participants who “always” disclosed their AI use faced over three times the odds of being accused by instructors than those who “never” disclosed. These findings highlight the hidden costs of transparency and underscore the need for equitable GenAI policies and trust-sensitive pedagogical practices. Ultimately, the study offers timely implications for developing supportive, AI-integrated learning environments that encourage transparency without the risk of repercussions