November 4, 2026Learning in the Age of AI: Part 1 | What We Don't Know About AI (and What We Know About Learning)

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Learning in the Age of AI: A Series

In this series Mr. Derek Cutler, our Director of Innovation, takes a deeper look into AI in education: exploring the science of learning, rethinking assessment, and nurturing the human connections that matter most.

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For all the excitement surrounding artificial intelligence, there is still an extraordinary amount we don't know about it.

We don't know which of today's leading AI companies or language models will survive or dominate five years from now. Billions of dollars are being invested in developing increasingly powerful systems and building the infrastructure needed to support them, yet significant questions remain about how those investments will generate sustainable returns.

Even the technology itself holds some mysteries. Researchers understand how large language models are designed and trained, but they still cannot fully explain many of the internal processes that allow these systems to demonstrate such remarkable capabilities.

And perhaps most importantly for those of us in education, we don't yet know what the widespread use of AI will mean for how humans will learn and develop.

What we do know is that even in its current form, AI has remarkable potential. It can explain difficult concepts, provide personalized feedback, adapt to different learning needs, and help us accomplish tasks in just seconds that previously took hours.

Efficiency vs. Depth

Some schools are already building entirely new educational models around these possibilities. You may have heard of Alpha Schools rapidly expanding schools throughout the United States. The premise of these schools is that students interact with adaptive AI to deliver core academic instruction in just two hours each day. Alpha reports impressive academic outcomes, with students achieving 99th-percentile results on national standardized assessments in many grade levels and subjects.

While these possibilities are exciting and deserve attention, they also raise important questions. Education researchers have expressed concerns about the potential for 'brittle knowledge,' a phenomenon where students perform exceptionally well in familiar, structured learning or testing environments but struggle to apply that understanding to new or unfamiliar situations.

Read the article: Alpha School wants AI to teach a billion kids. Should it?

None of this is to suggest that Alpha School's approach is necessarily wrong, or that AI cannot dramatically improve education. But promising results are not the same as sufficient evidence to fundamentally redesign how children learn.

Fortunately, while AI is new, we have decades of educational research, along with the experience and expertise of our teachers, to help us understand what meaningful learning looks like.

So What Does Meaningful Learning Look Like?

A few weeks ago, I was walking through the hallways when I came across our Grade 7 students preparing for a project in Ms. St. Jean's English Language Arts class. The students had been researching intergenerational relationships. They were working in groups to design carnival games they would eventually host for residents at Aspira Retirement Living in order to connect with seniors in our community.

What caught my attention wasn't simply what they were creating. It was the conversations happening as they worked. Students were trying out their games, discussing the rules, and debating different approaches. Would this version work better? Was the game too difficult? How could they make it more engaging?

There were competing ideas, disagreements, compromises, and plenty of problem-solving. Moving between groups was Ms. St. Jean, asking questions, offering guidance, and helping students work through challenges without simply providing the answers.

Watching this unfold, I couldn't help but think about the learning happening in those moments. The students were learning how to listen, evaluate different perspectives, navigate disagreements, anticipate problems, and adapt their thinking. Putting those skills into practice with real people, in a situation where things might not go exactly as planned, ensured this learning experience was anything but ‘brittle’.

I could have generated the ideas for carnival games, written the instructions, or developed an entire plan in seconds. I'd even bet that some of the games it came up with might have been better, with more polished designs and clearer instructions. But would that have been a better learning experience?

And this is where efficiency in education can be a double-edged sword. AI might help us complete tasks faster, or even produce better results, but that doesn't necessarily mean students are learning more. Sometimes, in making things easier, we risk removing the very experiences that help students learn.

The Art of Teaching

This is the distinction I keep coming back to when considering the potential of AI in education. Students need to acquire foundational knowledge, certainly. They still need to know their times tables and be able to write a well-constructed paragraph. But they also need opportunities to apply that knowledge, test their ideas, work through uncertainty, and discover what happens when their first approach doesn't work.

Educators have a term for this: productive struggle. It’s the kind of challenge that helps students learn by working things out for themselves. Of course, there's a difference between productive struggle and unnecessary frustration. Good teaching is about knowing when to provide support and when to let students work through a challenge themselves. AI introduces another tool into that process but it doesn’t intuitively know when struggle is productive and when it's time to step in. That's where the art of teaching, and truly knowing your students, remains irreplaceable.

At Aberdeen Hall, we're continuing to explore the possibilities AI offers while grounding our approach in what we know about how children learn. We don't have all the answers, and our practices will undoubtedly evolve as the technology and research develop. But whatever AI looks like in five years, we know that children will still need opportunities to think, collaborate, and make sense of the world for themselves.

Whatever AI makes possible, those are experiences worth preserving.