Why Collaboration Matters
Collaboration has long been central to teaching and learning. Through group work, discussion, and shared inquiry, students learn to articulate ideas, consider alternative perspectives, and build knowledge together. These processes support not only content understanding but also communication, critical thinking, and interpersonal skills.
Generative AI introduces a new dimension to collaboration. Students can now use AI to brainstorm ideas, draft responses, or explore alternative approaches independently. While these tools can support learning, they also raise important questions. If students turn first to AI rather than to one another, how does that shift the role of peer interaction? And how can educators design collaborative experiences that continue to prioritize human engagement and shared learning?
Collaboration as a Learning Process
Effective collaboration is not simply dividing tasks among group members. It is a process of shared thinking, negotiation, and reflection. Students benefit from opportunities to explain their reasoning, question assumptions, and build on one another’s ideas. Research on collaborative learning shows that collaboration itself is essential for deeper understanding and knowledge construction (Bach & Thiel, 2024).
In the age of AI, maintaining this process is essential. AI can contribute ideas quickly, but it does not replace the learning that occurs when students grapple with uncertainty together. Educators play a key role in designing collaborative activities that require interaction, dialogue, and decision-making, which are elements that cannot be fully outsourced to AI.
Collaborative Learning with AI
When used thoughtfully, AI can support collaboration rather than replace it. For example, students might use AI as a starting point for discussion, generating initial ideas that they then evaluate, refine, or challenge as a group. In this way, AI becomes one voice among many, rather than the dominant source of input.
At the same time, collaboration in the age of AI requires clear expectations. Students benefit from understanding when AI use is appropriate, how it should be documented, and how it fits within collaborative work. Framing AI as a tool to support group thinking, not as a substitute for it, helps maintain the integrity of collaborative learning.
Examples of Collaboration in the Age of AI
Across these examples, the goal is not to prevent AI use, but to design collaboration in ways that keep students interacting with one another. AI can support the process, but it should not replace the dialogue that makes collaboration meaningful.
AI-Supported Brainstorming:
Groups may use AI to generate initial ideas or perspectives on a topic, then evaluate those ideas together. Students can discuss which suggestions are useful, which are incomplete, and how they might build on them. This encourages critical thinking and shared decision-making.
Collaborative Problem-Solving:
In problem-based tasks, students can compare their own approaches with AI-generated solutions. The group can analyze differences, identify strengths and limitations, and justify their chosen approach. This shifts the focus from finding an answer to understanding the reasoning behind it.
Group Reflection and Synthesis:
After completing a collaborative task, students can use AI to summarize key points or identify themes, then refine or challenge that summary as a group. This reinforces collective understanding while ensuring that students remain actively engaged in shaping the outcome.
Collaboration, Accountability, and Transparency
One of the challenges of collaboration, especially in group work, is ensuring accountability. Generative AI adds another layer to this challenge, as it can be difficult to distinguish between individual and shared contributions.
Clear expectations help address this. Educators can ask students to document their process, describe how AI was used, or reflect on their contributions to group work. Studies of AI use in education highlight the importance of transparency and clear guidelines in maintaining trust and accountability (Kasneci et al., 2023).
Transparency also supports trust. When students understand how AI fits into collaborative tasks, they are more likely to use it responsibly and thoughtfully.
Collaboration, Pedagogy, and Purpose
In the age of AI, collaboration remains a powerful way to support learning, but its purpose must be clear. When collaborative activities are designed with intention, they encourage students to engage with one another, develop shared understanding, and practice skills that extend beyond individual performance.
Generative AI can be part of this process, but it should be guided by pedagogy. By designing collaborative experiences that emphasize dialogue, reasoning, and reflection, educators can ensure that collaboration continues to support meaningful learning.
Looking Ahead
Collaboration and creativity are closely connected. Collaborative environments often provide the space for new ideas to emerge, develop, and take shape. In the next article, Creativity in the Age of AI, we will explore how generative AI influences creative thinking and how educators can support originality and expression when AI tools are part of the learning process.
References
Bach, A., & Thiel, F. (2024). Collaborative online learning in higher education—quality of digital interaction and associations with individual and group-related factors. Frontiers in Education, 9, 1356271. https://doi.org/10.3389/feduc.2024.1356271
Kasneci, E., et al. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, Article 102274. https://doi.org/10.1016/j.lindif.2023.102274
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Washington, G. (2026, April 30). Feedback in the Age of AI [Blog post].
Retrieved from https://pedagogybeforetechnology.blogspot.com/
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