Teaching with AI: A Systematic Review of Chatbots, Generative Tools, and Tutoring Systems in Programming Education
Said Elnaffar, Farzad Rashidi, Abedallah Zaid Abualkishik
Abstract
This review examines the role of artificial intelligence (AI) agents in programming education, focusing on how these tools are being integrated into educational practice and their impact on student learning outcomes. An analysis of 58 peer-reviewed studies published between 2022 and 2025 identified three primary categories of AI agents: chatbots, generative AI (GenAI), and intelligent tutoring systems (ITS), with GenAI being the most frequently studied. The studies report that the primary instructional objectives include providing enhanced programming support 94.83% of studies, delivering motivational and emotional benefits 18.96%, and increasing efficiency for educators 6.90%. Reported benefits include personalized feedback, improved learning outcomes, and time savings. The review also highlights challenges, such as implementation barriers documented in 93.10% of studies, overreliance resulting in superficial learning in 65.52%, and concerns regarding AI errors and academic integrity. These findings suggest the need for instructional frameworks that prioritize the development of prompt engineering skills and human oversight to address these issues. This review provides educators and curriculum designers with an evidence-based foundation for the practical and ethical integration of AI in programming education.