The Role of Generative AI in Software Student CollaborAItion

2025-01-23

AI Summary

This study investigates the educational impact of integrating generative AI as a collaborative agent into student software project learning, specifically addressing how AI reconfigures collaborative practices in computer science education. Method: Drawing on the novel “collaborative role delegability” hypothesis, the study systematically defines a full-role embedding paradigm for AI across seven collaborative activities—including pair programming, code review, and requirements clarification—and employs scenario modeling and design fictions to construct four representative pedagogical integration scenarios. Collaborative process analysis and a critical foresight framework are applied to identify core challenges. Results: The research identifies three fundamental challenges: trust establishment, accountability attribution, and competency imbalance. Beyond extending the theoretical boundaries of AI agency in educational technology, it establishes foundational theoretical anchors and methodological pathways for AI-native collaborative pedagogy design.

Technology Category

• Humans and AI: Human-AI Collaboration / Human-AI Teaming
• Multiagent Systems: Teamwork
• Cognitive Modeling & Cognitive Systems: Agent Architectures

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Collaboration is a crucial part of computing education. The increase in AI capabilities over the last couple of years is bound to profoundly affect all aspects of systems and software engineering, including collaboration. In this position paper, we consider a scenario where AI agents would be able to take on any role in collaborative processes in computing education. We outline these roles, the activities and group dynamics that software development currently include, and discuss if and in what way AI could facilitate these roles and activities. The goal of our work is to envision and critically examine potential futures. We present scenarios suggesting how AI can be integrated into existing collaborations. These are contrasted by design fictions that help demonstrate the new possibilities and challenges for computing education in the AI era.

Problem

• Generative AI
• Collaborative Learning
• Software Projects

Innovation

• Generative AI
• Collaborative Learning
• Computer Science Education