A Bibliometric Review of Pedagogical Innovations and Future Directions for Generative Artificial Intelligence in Computer Science Education

This chapter provides a bibliometric review of research on Generative Artificial Intelligence (GAI) in Computer Science (CS) education over the past decade. A total of 582 documents been catalogued in Scopus for the period of 2014-2024 was used. The publications were analyzed using Biblioshiny for Bibliometrix and the results were used to identify gaps in the literature and guide future research directions on GAI's impact in education. The findings revealed the surge in publications and citations post 2020 can be attributed to large language models and AI coding assistants. Thematic and keyword analyses show that GAI has been applied primarily in programming education, intelligent tutoring, personalized learning, and assessment. These applications yield outcomes such as enhanced efficiency, student engagement, and scalability, yet also raise concerns about academic integrity, over-reliance, and algorithmic bias. GAI research is spearheaded by developed nations which poses fairness concerns, and simultaneously fosters advancement and moral quandaries in computer science pedagogy.