I’ve been as educator for a long time. In the 1980’s, the folks who taught me how to do the work connected me with John Dewey. I have continued to read his work over my career and wondered what he would have thought of new technologies and how he would integrate them into his work. This post is my first efforts to think about John Dewey in an educational landscape dominated by algorithms.
We know that artificial intelligence has the potent to reshape the work of education; it can automate assessments, optimize curricula, and generate personalized learning pathways, the question arises: What remains distinctly human about the act of teaching? In an era saturated with algorithms, machine learning models, and predictive analytics, John Dewey’s vision of progressive education offers not a quaint historical footnote—but a timely and enduring framework for re-centering pedagogy around experience, reflection, and democracy.
Dewey’s ideas emerged during a time of profound industrial change. Around the turn of the century (19th to 20th), in the United States, the agrarian culture was shifting to an urban one. Industries were changing, education was changing. Because of this, his insights remain uncannily resonant in today’s digital age, where the mechanization of learning risks outpacing its deeper purposes. AI may efficiently distribute information, but it does not—and cannot—understand what it means to be educated. Dewey reminds us that education is not simply a transmission of content but “a reconstruction of experience.” My early mentors who introduced me to Dewey would appreciate that what has grounded my theory of schooling remains, and Dewey is at the heart of it: learning must be active, social, and rooted in real-world meaning. No chatbot, however articulate, can reconstruct experience on behalf of the learner.
Dewey’s Learning by Doing: A Counterbalance to Passive Automation
One of Dewey’s most foundational principles is experiential learning. He opposed rote memorization and standardized schooling, emphasizing instead that knowledge must grow from active engagement with the environment. In Dewey’s words, “We do not learn from experience… we learn from reflecting on experience.” (These words were used by Dewey several time, I first encountered the in his 1938 Education and Experience.)
In the AI-driven classroom, where intelligent tutoring systems might guide students step-by-step through academic tasks, there is a risk that learners will be over-assisted—shielded from productive struggle. Dewey’s emphasis on inquiry provides a powerful counterbalance. Educators must ask: Are students merely completing tasks provided by machines, or are they formulating questions, testing hypotheses, and discovering patterns? Technology should augment—not replace—students’ opportunities to wrestle with ambiguity.
Productive struggle emerges from problems. When we focus lessons on relevant and interesting (to students) situations, we open the potential for learning that may cause changes in how students perceive the world. It works far better than clear learning objectives that have no meaning to the students.
Experiential learning demands autonomy. Dewey saw the learner as a participant, not a recipient. This view calls into question overly prescriptive AI systems that narrow learning into behaviorist feedback loops. If we lose the messiness of learning, we risk losing creativity, resilience, and ethical reasoning—qualities machines cannot replicate.
The Classroom as a Democratic Microcosm
Dewey famously conceived a as the classroom as a miniature society—a space where democratic habits are formed through collaboration, dialogue, and mutual respect. This dimension of education becomes especially critical in an age when algorithms invisibly structure access to knowledge, sort students, and predict future outcomes.
AI systems are trained on existing data and often reproduce historical biases. Dewey’s philosophy invites educators to interrogate these systems and to foreground ethical discernment. What values are embedded in educational technologies? Who decides which data matter? Dewey’s democratic vision calls for transparency and participation. Students must not only learn with technology—they must learn to question it.
Of the many things Dewey taught us about teaching, this seems the one we have addressed the least. Questioning is not something we are taught to do as students or as educators. We do not question the curriculum, the standards that form it, the data we collect, or the methods used to instruct it. Unless, of course, there is a change in administration.
Furthermore, as classrooms become more connected to global networks and digital tools, Dewey’s commitment to social intelligence becomes a safeguard against alienation. Teaching must intentionally cultivate empathy, shared inquiry, and a sense of belonging. Algorithms may personalize content, but they cannot build community. That task remains in the human domain.
Intelligence as Growth: A Warning Against Static Metrics
Dewey viewed intelligence not as a fixed trait, but as the capacity to grow, adapt, and reconstruct one’s understanding. He rejected standardized testing as reductive and believed learning must emerge through continuous interaction with one’s environment.
Today’s AI systems are often oriented around static metrics—grades, completion rates, engagement scores. These measures may offer snapshots but cannot capture the trajectory of intellectual and personal growth. Dewey’s vision warns educators against mistaking the quantifiable for the meaningful. When teaching is guided solely by algorithmic feedback, we risk collapsing learning into performance, which has little to do with learning.
Instead, educators must reassert the centrality of reflection. Just as Dewey argued for learning journals, project-based assessments, and portfolio evaluations, today’s educators must explore how technology can document not just answers—but thought processes. The future of education lies in integrating data with narrative, metrics with metacognition. AI is good at generating information, including that which we can conflate with the products of learning. This is true regardless of the existence of AI, and it will take a cultural shift before educators truly address this reality.
The Teacher as Facilitator, Not Technician
The rise of AI in education sometimes casts teachers in supporting roles—implementing tech platforms, managing data flows, and responding to automated reports. But Dewey’s conception of the teacher as a guide and co-inquirer remains essential.
Teachers must design contexts for exploration. They must foster classrooms where students debate ideas, examine assumptions, and make connections across disciplines. Dewey would argue that technology is a tool—but the teacher is the architect. In the face of automation, the teacher’s role becomes even more vital: shaping the environment in which meaningful growth can occur.
Educators must resist the reduction of their role to technical facilitation. The true task of teaching, according to Dewey, is ethical and aesthetic—it involves judgment, empathy, and improvisation. No AI can substitute for these forms of responsiveness.
Education for Uncertainty
Perhaps Dewey’s most prescient insight is his embrace of uncertainty. He saw learning as an open-ended journey, where provisional conclusions spur new inquiries. In contrast, many contemporary models of AI-infused learning emphasize prediction and optimization.
Yet, in a world dominated by rapidly evolving technologies, the need to tolerate—and even celebrate—uncertainty is paramount. Students must learn not just what is known, but how to navigate what is unknowable. Dewey’s pedagogy encourages learners to ask not “What is the right answer?” but “How do I approach this problem?” This shift transforms education from content delivery into capacity building.
Teaching in the age of AI must therefore move beyond knowledge acquisition to cultivating flexible thinkers—individuals who can adapt, inquire, and question assumptions. Dewey’s vision offers this scaffolding.
Conclusion: Why Dewey Now?
Artificial intelligence may reshape the mechanics of education, but the deeper questions Dewey raised remain: What kind of society are we preparing students to enter? What kind of individuals are we helping them to become?
In a time when machine-generated content and predictive analytics offer unprecedented tools, John Dewey reminds us that the heart of education lies not in automation—but in reflection, collaboration, and ethical engagement. His theories are not simply relevant—they are vital.
Dewey insisted that education is fundamentally a human endeavor. If we teach with that conviction, then even in a world of AI, we preserve the soul of learning.