A student asks artificial intelligence to write an essay. Moments later, the work is done. The argument is coherent, the grammar is flawless and the conclusion is persuasive. The question, though, is whether the student actually learned anything while it was being written. Did they get anything of value out of the process?
As AI becomes more capable, this question is rapidly becoming one of the most important issues in modern education. If endless answers are available instantly, what becomes the most valuable thing a school can teach? The answer is judgement.
For generations, schools have helped young people acquire knowledge, primarily because knowledge was relatively scarce. Today, information is abundant. Students can access facts, explanations and opinions on almost any subject in a matter of seconds. AI has sped up this shift dramatically – but information alone has never been enough.
Yes, a student can get an answer from a machine. Nevertheless, they still need to decide whether that answer is accurate, relevant, complete or even worth trusting at all. As answers become easier to obtain, the ability to evaluate them becomes more important. In other words, as knowledge becomes more accessible, judgement becomes more valuable. This is where the conversation about education needs to change.
Much of the debate about AI in schools focuses on how students should use the technology. That’s no doubt an important question, but there’s an even more important one: how do we ensure students remain active thinkers rather than passive recipients of machine-generated information?
The answer lies in developing what psychologists and educators call metacognition: the ability to think about one’s own thinking. Metacognition sounds academic, but its application is practical. It’s the habit of asking: How do I know this is true? What evidence supports it? What might I be missing? Have I reached this conclusion too quickly? These are the questions that form the foundation of good judgement.
At Nord Anglia Education, we wanted to understand whether these capabilities could be cultivated deliberately rather than left to chance. Working with Boston College, we conducted a two-year study involving more than 12,000 students across our global family of schools. The findings were significant.
Students who experienced an explicit metacognitive approach demonstrated a 21 per cent increase in critical thinking, a 20 per cent increase in curiosity, and a 15 per cent increase in collaboration, commitment and compassion. These figures naturally invite an important question: how do you measure qualities like curiosity or critical thinking?
The study combined teacher observations, student surveys, classroom evidence and structured reflection. Teachers looked for sustained changes in how students approached learning: whether they asked more thoughtful questions, explored different possibilities before reaching conclusions, reflected more deeply on their work and became increasingly independent learners.
At the same time, students reflected regularly on their own learning, building a picture over time of how their thinking was developing rather than relying on a one-off assessment.
One finding stood out above all others. The greatest improvements came in classrooms where teachers consistently embedded simple “thinking routines” into everyday lessons. These short routines encourage students to explain how they reached a conclusion, consider alternative perspectives, and reflect on the evidence behind their thinking. Rather than an additional subject that needs to be taught, these are habits that can be woven into mathematics, science, languages or the arts, helping students become better thinkers regardless of what they are learning.
The implications of these results extend beyond academic achievement. They suggest that the qualities most needed in an AI-driven world are not fixed traits that some children possess and others don’t. They can be taught, practiced, and strengthened.
Most importantly, perhaps, the research suggests that the same skills that help students learn effectively are also the skills that help them use AI effectively.
A student who possesses strong judgement and clarity of thought won’t simply accept the first answer a machine provides. Instead, they’ll challenge it, test it, compare it with other sources, and recognise its strengths and limitations. It means they remain in charge of their thinking.
It’s clear that the future belongs to students who can combine the power of AI with the discipline of independent thought. So the question facing education is whether we’re teaching them to do exactly that.
It also presents an important challenge for education systems. If judgement, curiosity, and critical thinking are becoming more valuable, they can’t remain mere aspirations that sit alongside the curriculum. They need to become part of how learning is designed.
It’s tempting to reach for the introduction of another subject or another high-stakes examination. Our research suggests something both simpler and more powerful: embedding metacognitive thinking across the curriculum through regular opportunities for students to explain their reasoning, reflect on how they learn and make their thinking visible.
We also found that the quality of reflection mattered more than the quantity. Students made the strongest gains when they reflected on specific learning experiences and the strategies they had used, rather than simply rating their own performance.
As governments around the world, including the UAE’s, continue to invest ambitiously in AI, our education systems must evolve alongside it. That means valuing not only what students know, but also how they think; not only what they produce, but how they arrive there. This is because in an age when answers are everywhere, judgement may become the most valuable thing a school can teach.
