Theoretical Analysis of the Impact of Generative Artificial Intelligence on Computer Science Education
DOI:
https://doi.org/10.71204/wfyysg31Keywords:
Generative AI, Computer Science Education, Theoretical Analysis, Technology AcceptanceAbstract
Generative artificial intelligence (generative AI) has emerged as one of the most transformative technological advancements of the 21st century. In the realm of computer science education, its potential to revolutionize curriculum design, pedagogy, and the overall learning experience has generated considerable interest. This paper offers a comprehensive theoretical analysis of the multifaceted impact of generative AI on computer science education. Distinct from empirical studies, this research exclusively engages in a rigorous discussion anchored in existing theoretical frameworks and scholarly insights. Drawing from constructivist learning theory, technology acceptance models, and ethical considerations, the paper explores how generative AI tools might reshape the roles of educators and learners, transform the delivery of educational content, and stimulate innovation in computer science curricula. Furthermore, the analysis interrogates the potential challenges and risks associated with these technologies, including the dilemmas of academic integrity, algorithmic bias, and a possible overreliance on automation. The discussion concludes with reflections on the future trajectory of AI-enhanced learning environments and recommendations for theoretical development that may guide future empirical inquiries.
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