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A Bibliometric Review of Pedagogical Innovations and Future Directions for Generative Artificial Intelligence in Computer Science Education
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Author(s): Damola Olugbade (First Technical University, Nigeria), Samson O. Ajao (Bowen University, Nigeria), Hassan Abuhassna (Sunway University, Malaysia), Ifedayo Emmanuel Adu (Bamidele Olumilua University of Education, Science, and Technology, Nigeria)and Owolabi Paul Adelana (The Open University, Milton Keynes, UK)
Copyright: 2026
Pages: 28
Source title:
Pedagogical Innovations in Computer Science Education
Source Author(s)/Editor(s): Manuel B. Garcia (FEU Institute of Technology, Philippines)
DOI: 10.4018/979-8-3373-6546-6.ch014
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Abstract
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.
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