Generative AI’s Influence in Computer Science Classrooms: A Rapid Review Methodology

Abstract

Generative AI tools such as ChatGPT are rapidly being adopted in Computer Science Education (CSE), offering novel ways to support student learning, particularly in programming, computational thinking, and foundational mathematics. Despite growing interest in these tools, empirical evidence examining their educational impact remains limited. This rapid review synthesizes current research to explore (1) how generative AI tools are being used in CSE classrooms, (2) how students, educators, and professionals perceive their use, and (3) what challenges and opportunities exist for their future integration. Using PRISMA guidelines adapted for rapid review methodology, we conducted a comprehensive search in June 2024 through EBSCO databases, focusing on peer-reviewed empirical studies published since 2022. Of the 64 identified studies, only three met the inclusion criteria, reflecting the emerging nature of this research area. The selected studies show that ChatGPT is primarily used to provide immediate feedback during coding exercises, support debugging processes, and facilitate iterative learning. Students report positive experiences, citing AI’s usefulness in clarifying complex tasks, improving efficiency, and offering 24/7 assistance. However, educators and professionals raise concerns about potential over-reliance on AI, diminished critical thinking, and the erosion of academic integrity. These concerns show the importance of developing pedagogical strategies that balance AI support with human cognitive engagement. Frameworks such as CHAT-ACTS encourage students to self-regulate their interactions with AI tools, while instructional designs like Harvard’s CS50 Duck demonstrate how AI can be integrated to support learning without providing direct answers. Although this review is based on a limited sample, it provides early insights into the affordances and risks of generative AI in CSE. It calls for future research on instructional design, ethical policy development, and longitudinal studies that examine how AI tools shape learning behaviours, skill acquisition, and disciplinary practices over time. Responsible integration of AI in CSE will require thoughtful alignment with educational goals that prioritize higher-order thinking and learner agency.

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