What happens when you put 5th graders in charge of training an AI model? At Kent City Elementary, the result isn’t just a technology lesson. It’s empowerment. As part of Michigan’s Hour of AI, a statewide initiative designed to introduce students to how artificial intelligence works and its real-world impact, local classrooms became spaces for hands-on exploration of AI.

What matters here isn’t just the technology. It’s how naturally this work aligns with the five Engagement Accelerators. Here’s what that looked like in practice, and what educators at any level can take away.

This post draws on reporting and photos by School News Network. Quotes from students, educators, and policymakers are attributed to their original source.

Relationships: Building Positive Connections Between Students and Staff

The heart of technology is people. Superintendent Bill Crane emphasizes that AI should “enhance, not replace, the human connections” that drive teaching. This vision is supported by a strong partnership between the Kent ISD EdTech team and Kent City’s AI Steering Committee.

In practice, this means classrooms where teachers circulate, ask questions, and learn alongside students as they troubleshoot AI models. What could easily become solo screen time instead turns into real conversation, with students talking through problems, asking each other for help, and working out loud. When that kind of trust is present, students feel safe enough to take risks, make mistakes, and try again, all of which matter when the technology is new and unfamiliar.

Student-Centered Learning: When Student Interest and Needs Drive the Experience

In this STEM classroom, learners move beyond simply using apps. They become AI trainers. Using the AI for Oceans curriculum, students teach models to distinguish between fish and trash. When the AI makes a mistake, fifth-grader Aiden Austin quickly realizes, “I have to keep training.”

This shift changes the power dynamic. Students are no longer just clicking through a program or following along with the teacher. They are the ones making decisions, testing outcomes, and figuring out what went wrong when the AI doesn’t get it right. That is student-driven learning in action: students have agency over the AI model and ownership of its outcomes.

Climate and Environment: The Learning Environment That Makes It Possible

Technology is most powerful when connected to real-world problems, and the right classroom environment makes that connection possible. Through AI for Oceans, students explore how machine learning can support environmental responsibility, such as cleaning waterways.

The work wasn’t always easy. When students had to sort fish by feelings like “happy” or “scary,” fifth-grader Addison Nouser said, “It was hard to tell if a fish that had a smile was happy, because its eyes could appear like it was not.” But the room wasn’t quiet or frustrated. Students were asking questions, debating their choices, and teachers were right there with them, figuring it out together. That kind of productive struggle, where students sit with something difficult and work through it rather than give up, is exactly what this accelerator describes. And when teachers are learning alongside students instead of standing at the front with all the answers, the whole room feels more like a partnership. Students were discovering firsthand that biased or careless data leads to flawed outcomes, a lesson that extends far beyond the ocean and into everyday decision-making.

Instructional Moves: The Teaching Choices That Make It Click

How do you explain how AI works to a ten-year-old? Nicole Andreas started with something her students already knew. She asked the class to define an artificial tree. “A fake tree,” a student answered. From there, she made the connection: artificial intelligence is “fake knowledge.”

That one question opened the door. Students started with something they could picture, a fake tree, and used that to make sense of something they couldn’t see, artificial intelligence. From there, Andreas walked students through the AI for Oceans lesson in four parts, each section building on what students had already taught the computer. The work was process-focused. There wasn’t always one right answer, and students talked through their choices as they went. By the time they reached conversations about bias, students had enough hands-on experience to understand what bias actually looks like in a system they had trained themselves.

Asset-Driven Teaching: Leveraging Students’ Backgrounds and Strengths

An asset-driven approach recognizes students’ perspectives and reasoning as strengths. When Aiden decided that a blue fin counts as a “blue fish,” he explained, “I decided that the fins are part of the fish’s body. If they have a blue fin, then I am counting them as a blue fish.” That moment shows a student applying his own logic to a system and seeing how his choices shaped the AI’s behavior. Rather than being corrected, his reasoning was valued.

This kind of thinking matters well beyond the classroom. State Rep. Carol Glanville, who visited the classroom during the Hour of AI event, stressed that AI education is essential. “AI is here, and we can’t avoid it,” she said. She noted that programs like this one help students not only navigate AI today but also prepare for careers that will depend on it. By teaching students to think critically and question what AI produces, educators are giving them skills they will carry forward.

The Shift That Matters

When students understand that AI systems reflect the decisions of the people who build and train them, they begin to see technology differently. They stop asking only what a tool can do and start asking why it behaves the way it does. That shift, from passive use to critical awareness, is what prepares students for the future.

For educators exploring AI in their classrooms, this example shows that strong engagement practices are not separate from technology integration. They are the foundation of it.

Try This in Your Classroom

Want to explore AI with your students? Check out the AI for Oceans curriculum to get started. To learn more about the Engagement Accelerators and how they can frame meaningful learning experiences, view the framework here.

Ready to Go Deeper? Join Us at the AI Summit

The classrooms in this story show what’s possible when educators approach AI with curiosity and intentionality. If you’re ready to take the next step, Kent ISD’s third annual AI Summit is the place to do it.

This year’s summit moves beyond tool tutorials and into what matters most: practical ways to use AI in your teaching and how to confidently bring AI learning into your classroom alongside students.

Featuring keynote speaker Alana Winnick, author of The Generative Age and founder of Students for Innovation, the evening will include focused breakout sessions led by local educators doing this work right here in Kent County. Whether you’re just getting started or already exploring AI in your classroom, you’ll leave with shared language, practical frameworks, and connections to colleagues across the region.

Date: April 27, 2026, 4:30 – 7:30 PM | 3 SCECHs | Dinner provided

Location: Kent ISD, Main Campus, MySchool@Kent (Parking Lot 3), 1655 E Beltline Ave NE, Grand Rapids, MI 49525

Cost: $30 early bird pricing for Kent ISD service area educators through April 3. $50 after April 3 and for all participants.

Register for the 2026 Kent ISD AI Summit

Written by Katherine Fredrickson, Education Technology Consultant for Kent ISD. Edited by Amanda Walma, T&L Marketing and Communications Specialist for Kent ISD. With contributions from Lindsay Lane, Innovative Teaching and Learning Consultant, and review by Sarah Wood, Education Technology Consultant. AI tools were used to support the drafting and editing process. Photos courtesy of School News Network.