Director of Information and Learning Technology
Byron Public Schools
As the education landscape evolves, artificial intelligence (AI) is becoming a tool that students can access as easily as their pencils. While this brings incredible opportunities, it also raises a critical question: What happens to learning when assignments can be completed by AI?
At Byron Public Schools, we can embrace the challenge of AI by turning to our Profile of a Graduate (PoG). When we developed the PoG six years ago, it was our call to personalize learning by fostering human-centered competencies that would stand the test of time. Looking back now, these skills—creativity, collaboration, communication, critical thinking, citizenship, character, and reflection—are more vital than ever. Over the past six years, we’ve worked to make our assignments and activities more authentic and meaningful by using the Rigor and Relevance Framework to guide our efforts. The emergence of Generative AI has only reinforced the importance of this work—it was the right work then, and it’s even more essential today. When learning goes deep, it creates opportunities for AI to complement the work, enhancing the learning experience rather than replacing it.
A Tale of Two Classrooms
Imagine two classroom scenarios, both tackling the same topic: climate change.
In the first classroom, students are asked to write a three-page research paper on the effects of climate change. Some become genuinely interested in the research, while others may see the task as routine—just another assignment to complete. With tools like ChatGPT offering an easy out, entire essays can be generated in seconds. Although the work is completed, the depth of learning may be limited, particularly when AI tools are relied upon to do the heavy lifting.
Now picture the second classroom. Here, students engage in an interdisciplinary project: designing solutions to help Minnesota farmers adapt to climate change, particularly drought conditions. They integrate science to understand soil health, technology to explore innovative irrigation systems, social studies to evaluate policy implications, and ELA to communicate their findings effectively. Using credible sources—including local farmers, agricultural experts, and AI tools for summarizing local climate data—they analyze the impact of drier summers on crop yields, water usage, and sustainable farming practices. In teams, they brainstorm actionable solutions—like advanced irrigation systems, drought-resistant crops, or policy recommendations. Throughout the process, ELA skills shine as students craft persuasive arguments, compelling narratives, and data-informed presentations. They present their plans to a panel of local stakeholders, blending visuals, data, and storytelling to inspire meaningful action.
In this classroom, AI doesn’t replace learning—it amplifies it using technology as a tool while learning the standards and developing critical human skills like creativity, collaboration, and reflection.
What Makes the Difference?
The second classroom demonstrates a shift from traditional, often cheatable assignments to deeper, AI-proof learning. When assignments align with real-world challenges, students have to think, create, and collaborate in ways that no machine can replicate.
Let’s break it down:
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Creativity: Instead of solely regurgitating facts, students use facts to innovate.
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Critical Thinking: They analyze data, weigh options, and justify decisions.
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Collaboration: Working in teams ensures accountability and shared ownership.
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Communication: Presenting to a real audience demands clarity and persuasion.
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Citizenship: Tackling a community issue connects learning to the world around them.
The Future of Learning in an AI World
The reality is that AI isn’t going anywhere. But the same technology that challenges traditional assignments can also help us create more meaningful ones. It’s not about banning AI—it’s about teaching students to use it responsibly, as a tool that enhances their learning rather than doing it for them.
This is where deeper, project-based learning shines. When students are asked to solve real problems for real world audiences, AI becomes a resource, not a shortcut. And when assignments are designed to reflect the competencies of a Profile of a Graduate, they build the skills students need not just for school, but for life.
Deeper Learning: A Call to Action
Core foundational knowledge remains essential—it’s the cornerstone upon which all learning is built. However, as educational leaders, we have a unique opportunity to rethink what learning outcomes should look like in today’s world. How do we shift assignments that focus primarily on surface-level recall and create more experiences that prepare students for the complexities of the future? How do we design classrooms where students aren’t just completing tasks but are motivated to make meaningful contributions to their local and global communities?
AI isn’t the conclusion of learning—it’s the start of a new era. In this era, human-centered skills like empathy, creativity, and innovation will define success and empower students to navigate a world shaped by both challenges and possibilities.
Realizing this vision requires more than classroom-level innovation. It calls for system-wide supports that ensure all learners can access these richer, more authentic experiences. Policies and professional development should empower educators to design interdisciplinary projects that thoughtfully integrate AI. Resource allocation—such as providing reliable technology access—matters, too. With careful planning and a commitment to equity, deeper learning can ensure that every student, regardless of background or access, is equipped with the tools and transformative experiences they need to succeed in a complex, AI-driven world.
Authors Note: This article was guided by the author’s original vision and developed with the assistance of ChatGPT. The AI tool supported initial idea generation and drafting, while all final decisions on content, tone, and alignment with educational priorities were made by the author.
