Cooperative Learning
Cooperative learning is a structured method of group work where students rely on one another to achieve shared academic goals. It highlights intentional interaction that promotes positive interdependence, mutual support, and genuine collaboration, rather than merely parallel work on the same task (Herrmann, 2013; Davidson & Major, 2014). Each student contributes individually while being accountable to the group, encouraging both academic achievement and the development of social skills through face-to-face interaction and group reflection (Gillies, 2016).
The one that is doing the learning is doing the talking.
CAndy Olandt
Example of Cooperative Learning
Jigsaw Learning: Students are divided into groups, assigned a topic, and learn and teach each other, like the jigsaw activity we did in class with the approaches to learning. It’s also cool how we used Zoom to complete this.
Think-Pair-Share: Students first think about questions individually, then share their thoughts with a partner, and finally, share with the whole class.
Structured heterogeneous grouping: Students are intentionally placed in diverse groups based on their abilities, personalities, and learning styles. Each student has a role, ensuring balanced participation and peer learning.
The Limits of AI in Cooperative Learning
While AI can support learning, it doesn’t always align well with cooperative learning. Cooperative learning relies on peer interaction, shared responsibility, and face-to-face collaboration. Many AI tools are designed for individual use, which can reduce meaningful group dialogue and lead to uneven participation. When students rely on AI for quick answers instead of discussing and solving problems together, it limits critical thinking and weakens social skill development. Without careful guidance, AI use can unintentionally replace rather than support the human connections that make cooperative learning effective.
In the video, “The Pros and Cons of AI in Education: What Every Educator Should Know,” educators emphasise that while AI tools are very effective for personalising learning, they can sometimes hinder collaborative learning. By promoting isolated engagement, AI might reduce meaningful student dialogue and restrict the development of critical thinking and interpersonal skills.
These concerns are growing that when students rely too heavily on automated responses, they miss out on opportunities for peer discussion and shared problem-solving, core components of cooperative learning.
Challenges and Risks of Using AI in the Classroom
- Privacy concerns around student data
- Ethical considerations, including fairness and transparency
- Reduced social adaptability due to less face-to-face interaction
- Overdependence on technology which can weaken problem-solving skills
Educators play a vital role in ensuring that AI is used fairly, transparently, and with student autonomy and dignity in mind. As Gillies (2016) reminds us, cooperative learning thrives on structured, real-world interaction, something AI alone cannot replicate.
Shalan’s Blog Post #2 Reflection
When discussing cooperative learning, I agree that it creates space for students to feel more open and comfortable sharing, especially when the class is divided into smaller groups. It also encourages full participation, and group roles tend to form naturally.
Having a peer who is confident with the topic can be helpful, but I also see it as an opportunity for the group to discover the answer together as a team.
I agree that the best approach depends on the learners, as everyone learns in a unique way. My ongoing challenge has been figuring out how to accommodate all learning styles, but I really like the idea of blending strategies to meet a variety of needs.
For our topic, do you think AI tools in education can support or hinder cooperative learning? In what ways might they enhance collaboration or unintentionally replace it?
