GENERATIVE AI AND ITS EFFECT ON ACADEMIC PERFORMANCE IN COMPUTER SCIENCE EDUCATION

Abstract

This study examines the influence of generative artificial intelligence (GenAI) on the academic performance of computer science students. With particular emphasis on coding proficiency, the research explores the ways in which GenAI tools affect student engagement, motivation, and the cultivation of problem-solving competencies. Data were gathered through survey instruments administered to students and teaching assistants within a higher education institution. The results indicate a positive association between the utilization of GenAI tools and enhanced academic performance, most notably in the comprehension of complex programming concepts. Nevertheless, the findings also draw attention to concerns regarding excessive dependence on such tools, as well as potential challenges related to academic integrity. This study underscores the importance of achieving a balanced integration of GenAI within educational frameworks in order to optimize its benefits while minimizing associated risks