Impact of AI in teaching and learning of CS in low-resourced schools.

This research investigates the impact of Artificial Intelligence (AI) on the teaching and learning of Computer Science (CS) in low-resourced schools. The study aims to understand how AI is currently being utilized in CS education, assess the benefits it offers, and identify the challenges faced by low-resourced schools in implementing these technologies. Two primary methods were employed: an interview with the founder of Rehan School, a low-resourced school utilizing AI tools like ChatGPT and virtual assistants, and a comparative study analyzing students' performance from low-resourced and well-resourced schools using different learning resources.
Key findings reveal that AI technologies significantly enhance student engagement and learning outcomes in CS education by providing personalized learning experiences and access to advanced educational resources. However, limited infrastructure, funding, and staff training remain significant barriers to widespread adoption. The study concludes that while AI has the potential to bridge educational gaps in low-resourced settings, addressing these challenges is crucial for maximizing its benefits. The findings suggest a need for targeted policies and investments to support the integration of AI in education, particularly in underfunded schools.