What is it about?

Students in computing courses now work in teams where an AI tool, such as ChatGPT or a code copilot, often acts like an extra teammate. This position paper looks at what that means for group work. We describe five changes: students now pair program with AI, teams split tasks in new ways, AI helps teams brainstorm and reflect, AI affects how confident and motivated students feel, and AI is starting to give feedback and even grades. We then propose a practical framework that teachers can use to design teamwork with AI in a responsible way.

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Why is it important?

Teamwork has long been at the heart of computing education because students learn by explaining, debating, and solving problems together. If AI quietly takes over those conversations, students may lose the very skills that group work was meant to build. Our paper gives teachers clear guidance: state which tasks AI may help with, ask students to log and reflect on their AI use, grade reasoning rather than polished output, and keep humans in charge of key decisions. These steps help universities use AI to support collaboration without weakening learning, fairness, or academic integrity.

Perspectives

This paper brought together colleagues from three UAE universities and let me connect my teaching of mathematics and computing with my research on human and AI interaction. As an educator, I wanted to understand what happens to group learning when students can ask an AI before they ask each other. I hope it helps fellow teachers treat AI as a partner that students question and guide, rather than a shortcut that replaces the conversations where real learning happens.

Linda Smail
Zayed University

Read the Original

This page is a summary of: AI-Assisted Collaboration in Computing Education: Rethinking Teamwork Pedagogy, June 2026, Institute of Electrical & Electronics Engineers (IEEE),
DOI: 10.1109/haxd70072.2026.11620836.
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