Generative AI in Computer Science Education : A Study on Academic Performance
Author(s): Mahaini, Dani (2024)
Abstract:
This research investigates the impact of generative artificial intelligence (GenAI) on computer science students’ academic performance. With a focus on coding capabilities, the study explores how GenAI tools influence student engagement, motivation, and the development of problemsolving skills. Data was collected through surveys targeting both students and teaching assistants at the University of Twente. The findings reveal a positive correlation between the use of GenAI tools and improved academic performance, particularly in understanding complex programming concepts. However, the research also highlights concerns about over-reliance on these tools and potential issues of academic integrity. This study underscores the necessity for a balanced integration of GenAI in educational frameworks to maximise benefits while mitigating risks.
Document(s):
Mahaini_BA_EEMCS.pdf