Source: Unite.AI
The rise of AI in education has created real excitement around personalized learning, instant feedback, and increased engagement. While the increasing access to information has undeniable value, this factor alone has never been the goal of education.
If learning becomes increasingly frictionless, what will happen to curiosity, persistence, and reflection? Education has always been about more than acquiring knowledge. It helps shape how people think, question, collaborate, and contribute. AI is a powerful tool, but its greatest value may be in strengthening the human experience of learning, not replacing it.
As AI continues to transform education, how do we ensure it helps raise “chalant” learners: people who remain curious, engaged, and willing to care? In this context, being chalant does not mean resisting technology or making learning unnecessarily difficult. It means remaining present in the process: asking questions, noticing what is unclear, and taking responsibility for one’s own understanding. A chalant learner uses tools without surrendering curiosity, judgment, or connection
Learning Is More Than Information Transfer
There is an important difference in learning between receiving information and developing understanding. This theory is called constructivism, where learners construct knowledge through experience versus passively taking in information. Learning has never been only about collecting facts. Learning happens through reflection, experimentation, and application. Learners often build greater confidence when they have the opportunity to discover answers, not simply receive them. This is what being chalant looks like in practice. It is the willingness to stay with a difficult question a little longer, to remain invested when the answer isn’t immediate, and to believe that understanding is something we build rather than simply consume.
Coaching offers an educational approach that prioritizes thinking over telling. A coach does not need to rush in with an answer. Often, the more valuable response is a question that helps the learner reach their own conclusion. Dialogue strengthens critical thinking by exposing learners to multiple perspectives. The mistakes, uncertainty, and moments of reconsideration within these conversations are often where the deepest learning occurs. Coaching invites learners to care about their own thinking. Rather than rewarding speed or certainty, it encourages the kind of attentiveness and curiosity that defines a chalant learner.
At its best, education develops judgment, adaptability, and self-awareness. When learning is centred primarily on knowledge retention, we risk overlooking the deeper capacities education can develop.
Potential Risks With Using AI In Learning
The central concern is not whether learners use AI, but whether AI begins to replace their intellectual engagement. This is where cognitive outsourcing becomes important to consider. When we rely on technology to do the thinking through which our own capabilities are developed, we lose valuable opportunities to practise persistence and problem-solving.
Curiosity often begins with an unanswered question, not immediate certainty. The pause before an answer matters. Remaining chalant means resisting the temptation to rush past that pause. It means staying curious long enough to wrestle with an idea before outsourcing the work of thinking. It gives learners time to form a hypothesis, test an idea, and notice where their thinking changes. When that pause disappears entirely, learners may reach the right answer without developing a clear understanding of how they arrived there.
Learners who rarely have the chance to wrestle with ideas may feel less confident when they encounter ambiguity or unfamiliar challenges. Intellectual ownership comes from constructing, defending, revising, and reflecting upon ideas.
None of this means AI lacks value. It means we need to be more intentional about the role we ask it to play.
Where AI Creates Genuine Value in Education
AI has enormous potential to improve educational experiences. It can provide immediate feedback, help learners address errors before they become habits, and offer language support, differentiated instruction, and additional assistance. AI can also help educators identify patterns and potential learning gaps more quickly. The real promise of these efficiencies is that they could create more room for mentorship, discussion, and creativity, not less.
Another value of AI is how it reduces parts of the administrative load for educators, creating more time for the conversations and relationships that support meaningful learning. AI works best when it supports the human aspects of education instead of competing with them. Used this way, AI doesn’t make learners passive. It creates more space for the conversations, questions, and relationships that help people become more chalant toward their own learning and toward one another.
Why Coaching Becomes Even More Valuable in an AI-First World
Coaching focuses less on delivering answers and more on developing judgment. Coaching conversations create space for confidence, reflection, accountability, and self-awareness to develop. In many cases, the most valuable work is not finding a faster answer, but learning to ask a better question.
Coaches help learners notice blind spots, challenge assumptions, and make meaning from their experiences. Over time, that process can build the trust and psychological safety learners need to understand themselves alongside the content. Much of our growth happens within relationships where we feel seen, supported, and appropriately challenged. AI may respond to what a learner shares, but it cannot enter into a developmental relationship with their emotions, aspirations, and lived experiences.
The more capable AI becomes, the more valuable coaching is.
How Should We Design AI That Encourages Deeper Learning?
AI should function as a thinking partner, not an answer engine. The best educational AI shouldn’t encourage intellectual nonchalance; it should invite learners to participate more fully. We can design prompts that ask learners to explain their reasoning, defend an idea, compare perspectives, and reflect on how their thinking is changing. AI can generate questions instead of only offering answers. It can also support collaborative learning by opening up group discussion rather than replacing it.
Learners should have opportunities to evaluate, critique, and build upon AI-generated ideas rather than treating them as finished answers. The role of reflection must remain part of the learning process, particularly when AI makes arriving at an answer so easy.
Educators can intentionally create moments in which an interaction with AI becomes the beginning of a human conversation, not the end of the learning process. That might mean asking learners to explain what they agree with, identify what feels incomplete, or bring an AI-generated idea into discussion with their peers. We should design learning experiences that make room for curiosity and creativity, rather than rewarding speed alone. This reinforces the idea that technology is most valuable when it expands a learner’s agency rather than creating dependence.
Scaling Learning Without Scaling Disconnection
Technology can dramatically expand educational access and opportunity. We cannot measure success solely through efficiency, completion rates, or the volume of information delivered. Meaningful learning is also reflected in curiosity, confidence, collaboration, critical thinking, and a learner’s willingness to remain engaged. Perhaps that is one way to define the future of education: not simply producing more knowledgeable learners, but raising more chalant ones.
Education should help people become thoughtful, capable contributors to the communities around them. Schools and organizations should evaluate AI not only by what it helps learners complete, but by how it affects their growth, agency, and relationships. The greatest opportunity is not to build AI that thinks for learners, but to build AI that invites them to think more deeply.
The future of education belongs to systems where technology expands human potential while preserving the relationships and curiosity that make learning transformative.