Generative Artificial Intelligence (GenAI) Utilisation and Academic Integrity among Master's Students in Lagos State University, Nigeria

Abstract

This study examined Generative Artificial Intelligence utilisation and academic integrity among master’s students in Lagos State University, Nigeria. The AI literacy and competence, institutional regulation, and academic ethics awareness as determinants of academic integrity among master's students at Lagos State university, Nigeria. Anchored on Technology Acceptance Model (TAM). The population of the study comprised of 231 master’s students with sample size of 170 determined by Taro Yamane formula and selected through the simple random sampling techniques. The study employed a quantitative, cross-sectional, explanatory (correlational) survey design. Data were collected using a six-section, structured questionnaire on a 5-point Likert scale. Construct validity was established through exploratory factor analysis (KMO = 0.861; Bartlett's test was significant), and reliability was confirmed with Cronbach's alpha coefficients ranging from 0.818 to 0.846. Multiple linear regression results revealed that institutional regulation on AI usage was the strongest positive predictor of academic integrity (β = 0.335, t = 5.061, p < 0.001), followed by academic ethics awareness (β = 0.247, t = 3.747, p < 0.001) and AI literacy and competence (β = 0.191, t = 2.934, p = 0.004). Generative AI utilisation emerged as the only inverse predictor (β = −0.249, t = −3.977, p < 0.001). The four predictors jointly explained 38.5% of the variance in academic integrity (R = 0.621; adjusted R² = 0.370), F(4, 165) = 25.846, p < 0.001. The study concludes that undisclosed AI use, rather than AI itself and erodes integrity. It is therefore recommended that Lagos State University management should develop clear GenAI guidelines by specifying acceptable and unacceptable uses of Generative AI in assignments, examinations, seminars, projects, and dissertations. Keywords: Academic Integrity, Generative Artificial Intelligence, Master’s Student and Utilization.