Why the Next Revolution in Education Begins with Understanding the Learner
Education has spent centuries asking an important question:
“How can we teach better?”
Today, with artificial intelligence entering education, that question is being asked again with new urgency. AI can generate lesson plans, activities, assessments and resources in seconds.
Yet I believe the next revolution in education begins with an even more fundamental question: “How do people actually learn?”
I began thinking seriously about this through my work as an educator in Japan, where I have taught learners ranging from infants to adults over 75.
One experience with a class of young children became particularly important.
Several children repeatedly left their places to play with the classroom light switches. It was easy to see this as a behaviour problem: they were distracted and needed to sit down.
But when I observed more carefully, I noticed something else. Some could not properly see the storybook. Others struggled to engage with activities that offered them little meaningful participation. The light switches, meanwhile, offered something immediate: press the switch and something happens.
The behaviour was telling me something about the lesson.
When I later became responsible for the class, I changed the environment. I adjusted the seating so everyone could see. Songs were sometimes heard first, then repeated with movements or picture cards. Instead of constantly preventing the children from exploring, I incorporated their curiosity into English: lights on, lights off; open the door, close the door. I also gave them meaningful classroom responsibilities.
The disruptive behaviour almost disappeared.
Not because the children had changed, but because the learning experience had changed. Another experience took this idea further.
In an after-school programme, one child had been struggling with his maths homework for around an hour. Everyone else had finished. Some of the other children had tried to help him, but addition and subtraction still did not seem to make sense. By then, the others were playing around him while he was still stuck.
Grégory Charles | LET Global Voices | 3 October 2026 1
I was his English teacher, not his maths teacher, but I wondered whether another perspective might help.
So I closed the book.
We moved away from the distractions and simply talked. I deliberately wanted to distance us from the mathematics for a moment. He had already spent around an hour struggling with it, and continuing to focus on the same problem was unlikely to change how he was experiencing it.
I wanted to give him some distance from that frustration, but I also wanted to understand him a little better. If I could find something that resonated with him—something already familiar and meaningful in his world—perhaps it could offer another pathway back into the mathematics.
Eventually, we started talking about food.
He liked pizza.
So pizza became our mathematics.
I drew a pepperoni pizza with five pieces and asked how many he could see. “Five.”
“You really like pepperoni. How many would you want?”
“Ten.”
I gave him another colour and asked him to add pepperoni until he reached ten. He drew five more. We now had five in one colour and five in another.
“So we started with five. How many did you add?”
“Five.”
Five plus five is ten.
For subtraction, I drew several pizzas.
“Now we eat two. How many are left?”
I crossed out two pizzas while making the gesture of eating them, and he counted what remained.
Gradually, we moved from drawings and gestures to fingers, and then from fingers to imagining the quantities without drawing them.
In less than twenty minutes, he returned to his homework and was able to finish what he had previously been struggling with.
The mathematics had not changed. But his state of mind, the representation and the pathway to understanding had.
That experience made me think differently about a well-known educational metaphor in which different animals are given the same test, such as climbing a tree. The monkey succeeds while the fish inevitably fails.
But what if the goal still matters?
Grégory Charles | LET Global Voices | 3 October 2026 2
Imagine the goal is retrieving an apple from a tree. A monkey can climb toward it. A bird can fly to it. An elephant might reach it with its trunk.
The fish cannot do any of those things.
If those are the only pathways the system recognises, the fish fails.
But what if we ask a different question?
What can the fish already do that the system has not considered?
The fish can use water. Perhaps it experiments, tries, fails and adapts until it discovers that it can project a stream of water toward the apple and knock it down.
Climbing, flying, reaching and projecting water are completely different pathways—but they can lead to the same goal.
The goal may be shared. The pathway does not have to be.
Only later did I recognise that experiences like these shared a recurring pattern. I would observe something unexpected, question my first interpretation, try to understand what was happening, adapt my response, and reflect on what changed.
Observe. Question. Understand. Adapt. Reflect.
I eventually formalised this process as OQUAR, a practice-derived reflective framework for educational inquiry and decision-making.
As I explored AI more seriously, another question followed:
Could technology support this process without taking the decision away from the teacher?
Teachers do not simply need more content. They need time and support to preserve observations, identify patterns, question assumptions and reflect on previous decisions.
AI should not replace professional judgement. It should expand the teacher's capacity to exercise it.
This thinking contributed to Lumina EDSS, an Educational Decision Support System I am developing to help teachers preserve classroom observations and records, identify patterns, reflect on previous decisions and consider possible adaptations while keeping professional judgement at the centre.
But the questions did not stop at the classroom.
If understanding learners can inform educational decisions, could the same habit of questioning be applied to education itself?
Why does education exist? How did it develop? Why does it change? What should AI's role be? What can today's educational systems teach us about what education might become?
Those questions eventually grew into Educational Evolution, an independent interdisciplinary research programme through which I am investigating education across its origins, historical development, contemporary systems and possible futures.
Grégory Charles | LET Global Voices | 3 October 2026 3
But education is not limited to schools, classrooms or people who hold the professional title of teacher. Parents teach children. Mentors and coaches guide others. Colleagues share knowledge and skills. People teach and learn from one another formally and informally throughout their lives. Educational Evolution is therefore intended for anyone interested in understanding how people learn, how understanding the person in front of us can help us explain or guide more effectively, and how one person can help another to learn—whether or not they consider themselves an educator.
Understanding education also means questioning the ideas that shaped it. What problems were earlier thinkers trying to solve? What remains valuable today? What may need to adapt as our societies, technologies and understanding of learning change?
Educational Evolution asks those questions—but it must also be willing to ask them about itself.
New ideas are not automatically better because they are new, just as technological change is not automatically educational progress. What matters is understanding the evidence, the context and the problem we are trying to solve.
Perhaps the principle of the apple applies not only to learners, but to education itself. The challenge is to understand what should change, what should remain, and why. And perhaps this brings us back to the role AI might play.
I sometimes think of it like a game of chess. When you are deeply focused on the position in front of you, it can be difficult to see what the next move should be. Yet someone looking at the same board from another perspective may notice a possibility that becomes obvious once it is pointed out.
Perhaps AI can help give us some of that distance—not by making the move for us, but by helping us see the board from another perspective.
The decision still belongs to us.
And that leaves perhaps the most important question:
If we could see education from another perspective, what might we notice that we cannot see from where we are standing now?