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Reshaping Undergraduate Computer Science Education in the Generative AI Era

● high · 2026-06-10cs-education, generative-ai, curriculum-design, higher-ed, llm, student-experience, ai-literacy, scaffolding, intelligent-tutoring, stem-education

Yi-Chieh Lee, Nattapat Boonprakong, Yugin Tan, Harold Soh et al. — Workshop report from NUS-Google Workshops — cs.CY

This white paper synthesizes findings from two international NUS-Google Workshops in Singapore convening faculty, industry practitioners, and students to reshape undergraduate CS education in response to generative AI. The central argument is that as GenAI automates implementation-level programming, debugging, and testing, CS curricula must shift toward understanding and verifying AI-generated artifacts. Critical skills to preserve include system design, abstraction, and critical evaluation; skills becoming less important include low-level implementation details. The paper proposes prerequisites for reform: fostering AI-native competencies, re-centering fundamental education, enhancing advanced pathways, embracing new pedagogies, and shifting institutional support. This connects to broader debates in CS Education about what constitutes core competence in an era of AI pair programmers, and aligns with AI Literacy frameworks that emphasize evaluation over generation.

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    • Citation

    Lee, Y.-C., Boonprakong, N., Tan, Y., Soh, H., et al. (2026). Reshaping Undergraduate Computer Science Education in the Generative AI Era. arXiv:2606.07545.