AI in the Classroom: What Teachers Are Trying, Learning, and Recommending Right Now

GOA faculty members are exploring ways to use AI to deepen creativity, stimulate inquiry, and build adaptability and student agency. What do these assignments look like? What are teachers finding from these assignments? And what happens when things don’t go exactly as planned?

This is what teachers and students are trying, learning, and recommending right now.

In International Relations, Scott Cotton, who is also faculty at Greenhill School, asks students to use generative AI to create a timeline that illustrates the evolution of feminism in foreign policy over the past 10 years in Germany, Mexico, or India. Students then use AI to propose a few initiatives for the future, considering which countries would be likely or unlikely to implement them. And finally, students submit a reflection on their use of AI in both their timeline and proposals.

“This is an assignment that could have been done without AI,” says Cotton. “Using a chat bot obviously made the research much easier, which the students appreciated.” He found that the timelines “looked rather similar — not a surprise since they were created by similar AI tools.” That lack of variety became part of the lesson: While AI speeds up research and drafting, it can also flatten originality, making the reflection section of the assignment all the more important.

In Capitalism: Past, Present & Future, Mary Anne Christy has students pick Karl Marx, Milton Friedman, or Mao Zedong to learn more about the conflicts between socialism and communism. Students prompt ChatGPT to respond in the historical figure’s voice. “It will be time to challenge these smart, opinionated, prolific men by asking one of them questions,” the assignment reads. “Yes, they are dead. But, we can wrangle AI to fix that.” 

The first run showed areas for improvement. “The assignment was too open-ended and students just pasted in [a transcription of] what the AI told them,” Christy says. “The second time, I got a bit savvier and had them reflect on what they learned.” She then discovered their reflections still didn’t really address errors or hallucinations — another adaptation to make.

Brendan Sarsfield, who teaches Architecture at GOA and is faculty at The American School in Japan, takes a visual approach in his AI assignment. Described as “an exploration-based challenge,” he asks students to use a sketch-to-image AI tool to brainstorm the design visualization stage of their own architectural project. Students input an image of a sketch or model they’ve already created as well as keywords of the project’s design principles and visual expression. They then test additional prompts, choosing different styles, moods, or ambiances.

“The intention [is] to help students quickly ideate where their initial ideas might take them,” Sarsfield says. “AI can produce impressive and visually stunning images that can inspire architects in their design process and journey. These images, however, are far from being taken as a final substitute for an architect's creative design voice. They are used as a stage in the iterative process, an opportunity to quickly render [or] experiment and develop to the next step initial ideas.” In other words, the AI image is not meant to be the final design but a visual brainstorming partner.

Christy hadn’t tried this assignment before AI. “It made what might have been a much longer assignment that wouldn’t fit in the curriculum easier,” she says. Christy’s students also responded positively to the assignment. “I was surprised that students often described this as one of their favorite assignments of the course,” she says. “Especially when they thought they knew the person’s thinking, they seemed to find the conversation illuminating.”

Sarsfield discovered that his students are “wholly valuing the visual thinking they developed individually rather than being reliant on AI.” He continues, “Students approached this challenge as intended — with curiosity and an acceptance that AI was a helpful tool for visual brainstorming but not a solution for their Architectural problem solving. … Most put it aside once completed and used it as a ‘what if’ trigger. Others used the AI outcomes as leaping-off points for further exploration.”

From these experiences, Cotton, Christy, and Sarsfield offer recommendations for educators considering AI in their classrooms:

Reflection matters most. Christy says, “Always ask for reflections from students on how they used the AI and — and this will be new for me this year — on what mistakes they saw the AI make and why they think the AI got it wrong.” Sarsfield adds that reflections need to “evidence students’ rationale for using [AI].”

Maintain clear boundaries. In his course, Sarsfield frames AI use as “purely as an aid to visual thinking” at the front end of the process — never near conclusion — and as a way to “help students to quickly visualise rather than to present as an example of an art/design work.” He also makes sure that the “purpose and process are crystal clear.”

Encourage curiosity. “I've had students engage in a conversation with a chatbot, impersonating a historical figure to review information,” Cotton says. “This has been more for fun and experimentation, rather than an official assessment.” Sarsfield adds that you should prompt AI “not just once, do it many [times] and then evaluate and rationalize how, why, and what in relation to the outcomes.”

Design for student agency. Give students clear parameters and purposeful choices, such as crafting their own prompts and submitting their original work as part of the input stage. Sarsfield says this makes sure AI outputs resonate more closely with their aspirations.

Assess reflection, not outputs. “The assessment of AI use should not be based on the outcome of the AI,” says Sarsfield, “but rather on the metacognitive reflection students engage with in relation to the purpose, efficacy, and intentions of their AI use [with] the AI output being used as a part of the evidence of such an assessment. The emphasis is always on the student's thinking.”

Keep exploring. Christy says, “I would say that, for me, continuing to do professional development on AI every year (or even more frequently!) has been helpful. Seeing how people are changing their lessons and coming up with new ideas has been really helpful.”

AI assignments aren’t just about perfect AI results. They’re about adaptability, with teachers and students learning to ask better questions and reflect on mistakes. Even “failures” spark useful conversations about prompts, scaffolding, and purpose.

AI won’t replace the relationships and judgment at the heart of great teaching. As Adeel Khan, founder and CEO of Magic School AI, reminds us, “AI is not magic. Teachers work unbelievably hard to serve their students and know them and build relationships with them and inspire them to learn, and AI is never going to replace that.” 

But when used with intention, teachers can prepare students for a future where AI is part of the landscape, and where agency, creativity, responsibility, and judgment remain the qualities that matter most.

For more, see:

• What’s shaping the future of learning? Let’s talk about it.
• How AI Supports Better Thinking on School Teams
• Stop Choosing Sides: The False Dichotomies Holding Education Back

This post is part of our Shifts in Practice series, which features educator voices from GOA’s network and seeks to share practical strategies that create shifts in educator practice. Are you an educator interested in submitting an article for potential publication on our Insights blog? If so, please read Contribute Your Voice to Share Shifts in Practice and follow the directions. We look forward to featuring your voice, insights, and ideas.

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