ANCORing Generative AI within the Computing Curriculum

Generative AI and Large Language Models have become ubiquitous across education and within higher education institutions. Emerging challenges include potential over-reliance on Generative AI, risks to academic integrity, and inequitable access: there is an urgent need for students to develop ethical, self-regulated and grounded learning practices in its use. This paper presents insights distilled from a survey of 14 computer science educators in the UK, and identifies the overarching importance of teaching responsibility and ethical implications of the use of AI to students. The ANCOR framework is presented as a method for teaching responsible Generative AI use, integrating ethical reasoning, real-world examples, and curriculum-wide approaches. It offers a novel contribution by providing both actionable teaching techniques and a conceptual approach for embedding ethical and responsible use of Generative AI tools across computing curricula, including guidance on ethics integration, contextualising relevant policies, developing ethical decision-making skills, addressing anthropomorphism, and using illustrative real-world cases.

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Publication Details

Journal
Open Access Institutional Repository at Robert Gordon University (Robert Gordon University)
Published
2026-04-02
DOI
https://doi.org/10.56433/vmnhhk83
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00

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article

ANCORing Generative AI within the Computing Curriculum

Martin Goodfellow, Mark Zarb
Open Access Institutional Repository at Robert Gordon University (Robert Gordon University)
Ethics and Social Impacts of AI
article

ANCORing Generative AI within the Computing Curriculum

Martin Goodfellow, Mark Zarb
article en

Abstract

Generative AI and Large Language Models have become ubiquitous across education and within higher education institutions. Emerging challenges include potential over-reliance on Generative AI, risks to academic integrity, and inequitable access: there is an urgent need for students to develop ethical, self-regulated and grounded learning practices in its use. This paper presents insights distilled from a survey of 14 computer science educators in the UK, and identifies the overarching importance of teaching responsibility and ethical implications of the use of AI to students. The ANCOR framework is presented as a method for teaching responsible Generative AI use, integrating ethical reasoning, real-world examples, and curriculum-wide approaches. It offers a novel contribution by providing both actionable teaching techniques and a conceptual approach for embedding ethical and responsible use of Generative AI tools across computing curricula, including guidance on ethics integration, contextualising relevant policies, developing ethical decision-making skills, addressing anthropomorphism, and using illustrative real-world cases.

Open Access Institutional Repository at Robert Gordon University (Robert Gordon University)
University of Strathclyde (GB)
University of Strathclyde
Peace, Justice and strong institutions
Openalex Percentile: Top 21%
Ethics and Social Impacts of AI
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ANCORing Generative AI within the Computing Curriculum — Martin Goodfellow, Mark Zarb · Open Access Institutional Repository at Robert Gordon University (Robert Gordon University) (2026) | TGRS Research Map | TGRS