This is the second article in a four-part series exploring how artificial intelligence can be used to strengthen the transferable life skills often referred to as the 4 Cs: Communication, Collaboration, Critical thinking, and Creativity. This article will focus on collaboration.
In a previous article published on AVID Open Access, AI and Collaboration, we explored how AI can be used to enhance and empower student skills in terms of the AVID WICOR® framework. The article outlined ways that educators can use AI to design group experiences, set up group membership, and create assessments. It also reviewed potential student uses, including brainstorming, idea synthesis, critiques, feedback, and identifying blind spots. If you are interested in these strategies, you will want to go back and review that article.
This article will take the conversation in a new direction and explore how students can learn to collaborate directly “with” AI.
Why should students collaborate with a computer program? The answer to this question lies in recent reports and studies that describe how AI is and will continue to be impacting the labor force. Many of those reports predict that AI will significantly disrupt the job market in the near future, and this disruption will look different than past changes.
Unlike robotics and automation, which largely impacted blue-collar jobs, generative AI is poised to disrupt white-collar jobs. The key word here is “disrupt.” While some jobs will likely be entirely replaced by AI technology, and new ones will almost certainly be created, the most likely impact for most workers is disruption. Rather than replace them, AI will force them to learn new skills and change the ways in which they do their jobs.
A popular expression states, “AI probably won’t replace you, but someone who knows how to use AI might.” As with any innovation that we’ve seen, there is probably some truth in this sentiment. In that light, it’s important that we empower our students with AI skills and set them up for future success. If we want them to be college- and career-ready, we will need to help them learn to effectively interact and collaborate with tools that use artificial intelligence.
While there are many tech tools that have AI integrated into them, this article will focus specifically on generative AI chatbots, like OpenAI’s ChatGPT, Google Gemini, Anthropic’s Claude, and Microsoft Copilot.
If you teach students who are too young to create accounts or use these tools themselves, you can lead these activities as a whole class. If your students are allowed to access these tools, you can let them experience these practices firsthand.
Here are three ways that you can teach collaboration skills through AI interactions:
Perhaps the biggest key to successful interaction with AI is knowing how to ask good questions. If you ask bad questions, you’ll probably get poor results. On the other hand, a well-crafted question has the potential to give you a much better response.
In general, questions should be specific and clear, and students need practice with this to become skilled at it. The beauty of asking questions to a chatbot is that you will get an immediate answer, and this answer is great feedback about the quality of the question you asked. If the response is off target, you will need to reconsider how to ask the question.
One good activity is to have each student in a group ask their own version of a shared question and compare results. Once students have identified the best response, they can examine the question or prompt that resulted in this answer. Not only can this be an insightful activity, as they discuss what made the agreed-upon question better than the rest, but it also promotes critical thinking and collaboration amongst peers.
Based on what the students learn, they can work together and collaborate in designing the next prompt or question. By learning to ask better questions of a chatbot, students will improve their questioning skills in general—something that is important in all forms of collaboration.
Asking good follow-up questions is the natural next step to the first strategy. While a well-crafted question or prompt is a great place to start, a single question is seldom enough to generate a complete and useful response. The key to receiving higher-quality responses is in examining the response, reflecting on its strengths and weaknesses, and then asking an effective follow-up question to refine the answer that was provided.
Students should ask themselves such questions as: “What might the chatbot have misunderstood about my question?” “What important information was left out?” and “What follow-up question can I ask to get a better response?”
In addition to these guiding questions, students can directly ask the chatbot for suggestions. Here are some considerations that ChatGPT offers for asking it effective follow-up questions:
- Clarity and Specificity: Ensure that your question is clear and specific to guide the AI toward the kind of response you’re seeking.
- Context: Provide context from previous interactions or the topic at hand to build upon the information already provided.
- Purpose: Be clear about the purpose of your follow-up. What do you want to achieve with the additional information?
- Scope: If the initial response was too broad, narrow the scope of your follow-up question to focus on a particular aspect of the topic.
- Precision in Language: Use precise language to avoid ambiguity, which can lead to more accurate and relevant responses.
- Feedback: Include feedback about what you found useful or not from the previous answers to steer the AI’s next response.
- Sequencing: Sequence your questions logically, building on what has been discussed, to delve deeper into the subject matter.
- Open-Ended Questions: Ask open-ended questions that encourage elaboration, explanation, or analysis, rather than yes-or-no answers.
This would be a good list of suggestions to give to students to help them formulate follow-up questions. Learning to ask quality follow-up questions is a skill that will benefit students in any type of collaboration, including both human-to-AI and human-to-human work.
To build upon the skills of asking quality questions and follow-up inquiries, students need experience in applying those skills to specific tasks.
ChatGPT offers some great suggestions for how to do this.
- Defining Objectives Together: Students start by articulating the goals of their project to the AI, prompting it to ask clarifying questions. This encourages students to think critically about their objectives. A key part of this suggestion is prompting the AI to ask clarifying questions. This sets up the AI to be a thought partner that pushes the students to think more deeply and completely about their ideas.
- Idea Generation: Students can use AI to brainstorm, asking it to provide prompts or questions that stimulate further discussion and exploration of ideas within the group. In this example, the key is that the AI is asking questions, rather than just giving answers. That puts the onus back on the student and requires them to do the critical thinking.
- Debating With AI: Students can present different viewpoints to the AI and use its responses to challenge thinking or validate arguments, fostering a deeper understanding of the subject matter. You might take this one step further and ask the AI to challenge responses that students add to the conversation. This pushes critical thinking to a higher level.
- Iterative Feedback: Students can have the AI review their work at various stages of the creation process and offer feedback, which the group can then discuss and decide whether to incorporate. This will again improve critical thinking and decision-making skills.
- Project Planning: Ask the AI for suggestions on project planning and task delegation but let the students make the final decisions using the AI’s input as one of several considerations.
- Role-Playing Scenarios: Use AI to simulate different stakeholders in a project, allowing students to practice negotiation and perspective-taking as they interact with the AI in various roles.
- Reflective Practice: Have students explain their reasoning about a concept, process, or event to the AI and ask the AI to offer questions or alternatives, thereby encouraging deeper reflection about thought processes and assumptions.
- Simulations and Practice: Students can use AI to simulate social situations where they must collaborate, helping them to develop empathy, communication skills, and emotional intelligence.
- Diverse Perspectives: Encourage students to ask the AI for different cultural or historical perspectives on a topic, which they can then discuss and incorporate into their collaborative work. While this activity isn’t collaboration by itself, it does support the collaboration process and helps students develop important empathy skills.
- Co-Creation: Engage AI in the creation of digital artifacts, such as writing, coding, or design, where AI’s role is to suggest improvements or alternatives that students must evaluate and integrate as appropriate. Again, students should direct the chatbot to restrain from doing the creation itself and instead prompt the students for ideas so that they do the majority of the creating.
The theme to all of these ideas is to structure the interaction with the AI chatbot in such a way that it prompts every student to do the majority of the work and to think more deeply.
This back-and-forth exchange of ideas is the key to collaboration in general, and the chatbot is essentially modeling how to be a good thought partner. Rather than dominating the idea generation, it’s pushing the student to stretch and offer ideas. This set of skills is key in pushing any collaborative group to produce better ideas and greater production.
A Human Layer of Collaboration
These interactions with AI do not need to be done alone; they can be done collaboratively. Students can work together as they collaborate with the chatbot, and this teamwork gives them practice working in partnership as they generate prompts, review responses, and craft follow-up questions together.
Another option is to ask students to interact independently with the AI before comparing and compiling responses with their peers.
Both of these approaches combine human-to-human collaboration practice with skill development in human-to-AI collaboration.
If the predictions of experts are accurate, these are skills that students will need in the workforce of the not-so-distant future.
AVID Connections
This resource connects with the following components of the AVID College and Career Readiness Framework:
- Instruction
- Rigorous Academic Preparedness
- Opportunity Knowledge
- Student Agency
- Break Down Barriers
Extend Your Learning
- Getting Started With Prompts for Text-Based Generative AI Tools (Harvard University Information Technology)
- A Guide to Prompting AI (for What It Is Worth) (One Useful Thing)
- Working With AI: Two Paths to Prompting (One Useful Thing)
- How to Ask AI the Right Questions: Best Practices (Siteefy)