Perceptions of Generative Artificial Intelligence and Academic Integrity in Higher Education: A Comparative Study of Students and Academic Staff

Abstract The rapid adoption of generative artificial intelligence (AI), particularly large language models such as ChatGPT, is transforming teaching and learning practices in higher education while also raising important concerns about academic integrity, transparency, ethics, and the responsible use of AI. This study examines and compares the perceptions and practices of students and academic staff regarding generative AI, with particular attention to AI use, academic integrity, institutional ambiguity, transparency, and citation practices. The study employed a quantitative, cross-sectional survey design. Data were collected through a structured, paper-based questionnaire administered in person to 202 participants at Kadri Zeka University in Kosovo, including 168 students and 34 academic staff members. The data were analyzed using descriptive statistics and an independent-samples t -test. The findings revealed statistically significant differences between students and academic staff across most of the dimensions examined. Academic staff reported a higher overall frequency of AI use, greater perceived institutional ambiguity, more critical attitudes toward AI use in relation to academic integrity, and stronger support for transparency. In contrast, students reported greater use of AI for academic purposes and more tolerant attitudes toward its use. No statistically significant differences were found between the two groups regarding the perceived importance of academic integrity or citation practices. These findings highlight the need for clearer institutional policies and shared standards for the transparent and responsible use of generative AI in higher education.