Evaluating the Impact of AI Copilots on Framework Usage and Professional Development of Student Developers: A Case Study of Africa University CEAS Students.

Abstract

The rapid integration of AI Copilots into software development has reshaped how student developers interact with frameworks, make project decisions, and prepare for professional roles. This study investigates the impact of AI Copilots on framework adoption and professional development among student developers at Africa University. Using a quantitative research approach, data was collected through structured surveys from a sample of 80 students. The study examines how AI Copilots influence students' efficiency, learning curves, and project selection, as well as their role preferences within software development. Findings indicate that AI Copilots significantly affect framework selection by reducing learning barriers, leading students to favour more complex but efficient technologies. Additionally, AI assistance influences decision-making in project scope and specialization, with many students shifting toward roles emphasizing AI integration. However, concerns over dependency on AI and diminished problem-solving skills were noted. The study concludes that while AI Copilots enhances productivity and exposure to diverse frameworks, there is a need for a balanced approach to ensure skill development and independent thinking. Recommendations include curriculum updates to incorporate AI literacy and industry partnerships to align AI-assisted learning with professional expectations.