Yi-Chieh Lee, Nattapat Boonprakong, Yugin Tan, Harold Soh et al. — Workshop report from NUS-Google Workshops — cs.CY 📄 Full text (arXiv)
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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Citations
APA: Yi-Chieh Lee, Nattapat Boonprakong, Yugin Tan, Harold Soh et al. (2026). Reshaping Undergraduate Computer Science Education in the Generative AI Era. arXiv:2606.07545. Workshop report from NUS-Google Workshops — cs.CY.