From Automation to Cognition: Redefining the Roles of Educators and Generative AI in Computing Education
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Abstract (arXiv)
Generative Artificial Intelligence (GenAI) offers numerous opportunities to revolutionise teaching and learning in Computing Education (CE). However, educators have expressed concerns that students may over-rely on GenAI and use these tools to generate solutions without engaging in the learning process. While substantial research has explored GenAI use in CE, and many Computer Science (CS) educators have expressed their opinions and suggestions on the subject, there remains little consensus on implementing curricula and assessment changes. In this paper, we describe our experiences with using GenAI in CS-focused educational settings and the changes we have implemented accordingly in our teaching in recent years since the popularisation of GenAI. From our experiences, we propose two primary actions for the CE community: 1) redesign take-home assignments to incorporate GenAI use and assess students on their process of using GenAI to solve a task rather than simply on the final product; 2) redefine the role of educators to emphasise metacognitive aspects of learning, such as critical thinking and self-evaluation. This paper presents and discusses these stances and outlines several practical methods to implement these strategies in CS classrooms. Then, we advocate for more research addressing the concrete impacts of GenAI on CE, especially those evaluating the validity and effectiveness of new teaching practices.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 16 Dec 2024.
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Citing papers per year: 2025: 1; 2026: 3.
4 papers.
- 2025Evaluating the Effectiveness of Large Language Models in Solving Simple Programming Tasks: A User-Centered Studycited by 1
- 2026Ensuring Computer Science Learning in the AI Era: Open Generative AI Policies and Assignment-Driven Written Quizzescited by 0
- 2026Using AI in engineering education: a balancing act, driven by clear purposecited by 0
- 2026Patterns of Learner-AI Interaction and Academic Performance in an Object-Oriented Programming Coursecited by 0
- 2026Using AI in engineering education: a balancing act, driven by clear purpose15 Jun 2026
- 2026Patterns of Learner-AI Interaction and Academic Performance in an Object-Oriented Programming Course26 May 2026
- 2026Ensuring Computer Science Learning in the AI Era: Open Generative AI Policies and Assignment-Driven Written Quizzes16 Jan 2026
- 2025Evaluating the Effectiveness of Large Language Models in Solving Simple Programming Tasks: A User-Centered Study5 Jul 2025