INCORPORATING AI TUTORS INTO THE COMPUTER SCIENCE CLASSROOM

Abstract

Artificial Intelligence (AI) has emerged as a powerful and transformative force in education, reshaping the way teachers teach and learners learn. Among the various applications of AI in education, AI tutors represent a particularly promising avenue for advancing instructional quality, especially in the computer science classroom. AI tutors offer personalized instruction, adaptive feedback, and real-time assessment that go beyond the capabilities of standard educational tools. Computer science students, who often grapple with abstract concepts and intricate problem-solving tasks, stand to benefit significantly from AI-driven personalized learning pathways. Despite these advantages, questions remain about the practical challenges, ethical considerations, and long-term effectiveness of AI tutors in this domain. This article provides an in-depth look at the integration of AI tutors into the computer science classroom. It reviews relevant literature, discusses key findings regarding the technology’s efficacy, and presents recommendations for achieving optimal results. Although AI tutors appear to be a valuable tool for improving student engagement and performance, educators must address issues such as cost, access, teacher training, and the preservation of critical social and cognitive skills. As the field continues to evolve, ongoing research will be crucial for fine-tuning AI tutors to ensure they complement traditional pedagogy while meeting diverse educational needs.