The Thinking Classroom Goes Global: What International Schools Are Teaching Us About AI
By David Jacobson | AP World History, Shanghai American School
A few weeks ago I was reading about a teaching forum at the Suzhou Experimental Primary School, where six teachers gathered to share how they’d been using AI in their classrooms. One of them — an art teacher named Ms. Wang — said something that I haven’t been able to shake: “AI is a museum that helps us find inspiration, not a print shop.”
That phrase landed hard. Because the print shop problem is real, and it’s what I spend a lot of my energy fighting against. When a student uses AI to generate an essay response to the causes of World War I, they’ve visited the print shop. When they use AI to pull together a dozen primary sources, identify the gaps, and then argue — in their own voice, with their own reasoning — about what those gaps mean, they’ve wandered through the museum. The difference is everything.
What the Suzhou forum reminded me is that the conversations I’m having in Shanghai aren’t happening in a vacuum. Teachers all over the world — and especially across China and the wider Asia-Pacific — are working through the exact same tensions. And some of what they’re figuring out is genuinely worth paying attention to.
China Is Moving Fast, and Not Just on Technology
China’s approach to AI in education tends to get covered through a geopolitical lens — who’s winning the AI race, who’s building the next generation of tech workers. But that framing misses what’s actually interesting about what’s happening inside classrooms.
Thomas Hatch, who documented the Suzhou forum for International Education News, captured a moment that felt more philosophical than technical. Ms. Huang, a Chinese language teacher, offered this: “Every good question is a seed of creation.” Ms. Wang, the art teacher, pushed back against the idea that AI could fully enter creative space: “AI can create beautiful paintings, but it can’t read the crooked little happiness” — meaning the particular, idiosyncratic way a child experiences joy that only a teacher who knows that child can recognize.
These aren’t the kinds of things you hear when people are just trying to automate education. These are teachers wrestling with what it actually means to know a student.
That wrestling is happening at international schools throughout China too. A recent AmCham China feature surveyed educators at schools including Wellington College Tianjin, the Western Academy of Beijing, ISA Wuhan, and Chengdu International School. The picture that emerged wasn’t of schools rushing to embrace AI or refusing to touch it — it was of institutions genuinely trying to figure out what responsible integration looks like.
Stephen Taylor, Director of Innovation at the Western Academy of Beijing, put the central principle simply: AI should “enhance — never replace — critical thinking, interaction, and overall learning quality.” Mahesh Selvaraj, Deputy Head at ISA Wuhan International School, echoed it with a different emphasis: “Keep the ‘human touch’ at the heart of pedagogy; technology must be supplementary, not replacement.”
These aren’t controversial positions. But they require genuine follow-through, which is where the work actually lives.
The Metacognitive Laziness Problem
Robert Christensen, Principal at Optics Valley International School, named something I’ve been observing in my own students for a while now. He called it “metacognitive laziness” — the tendency to offload the cognitive work of thinking to AI, rather than using AI to extend or challenge your thinking.
I see this most clearly when I assign DBQ (Document-Based Question) essays, which are central to AP World History. The documents are right there. The students’ job is to read them, analyze them, connect them to the historical argument, and write. What I’ve noticed is that some students will paste the documents into an AI tool and ask it to summarize before they’ve even read the original. They’re not thinking with the documents — they’re outsourcing the first encounter with them.
The fix isn’t to ban AI from the classroom. The fix is to be deliberate about when AI enters the process. I’ve started building assignments where students have to annotate documents by hand before they’re allowed to use any AI tools. The annotation has to show up in what they submit. That small structural choice has changed what’s happening in class — students come in having actually grappled with the text, and the conversations get better.
Olivia Xu, a Grade 12 student at Tianjin International School, described it well: AI “excels for conceptual reminders but requires caution for creative tasks requiring logical reasoning.” That’s a student naming the same line I’m trying to hold as a teacher.
What Colleen Kenny Gets Right About Media Literacy
Colleen Kenny, writing for LinkedIn from her perch at NYU Tisch School of the Arts, has been making a case that media literacy is now “education’s most urgent democratic task.” Her central argument is about what she calls “content chaos” — the AI-accelerated fragmentation of shared information environments that makes it harder for citizens to agree on basic facts, let alone interpretations.
She’s talking about something that’s directly relevant to what I do in a history classroom. History is fundamentally an argument about how we interpret evidence. If my students can’t tell the difference between a real primary source and a fabricated one, or between a credible historical analysis and a confident-sounding AI hallucination, I haven’t taught them history. I’ve given them a feeling of history.
Kenny noted, with welcome transparency, that she used AI tools including Gemini, Claude, and Perplexity to refine her article — while keeping “human judgment primacy” throughout. That’s the modeling I try to do with students too. The point isn’t to pretend AI doesn’t exist. The point is to show how a thinking person uses it without being used by it.
The Asia-Pacific View: Infrastructure, Ethics, and the Gap Between Countries
Dr. Libing Wang, Chief of Education at UNESCO’s Regional Office in Bangkok, has offered a useful check on the international schools conversation. It’s easy, from inside a well-resourced school in Shanghai or Beijing, to imagine that the AI-in-education story is everywhere about fine-tuning pedagogy and getting the philosophy right. But Dr. Wang points out that across the Asia-Pacific region, many schools are still working on reliable internet access. The meaningful question about AI equity isn’t just “how should students use it” — it’s “which students get to use it at all.”
That’s worth sitting with. The international school world I work in is a particular bubble. The teachers I’m in conversation with at Wellington College Tianjin or WAB are working through challenges that are genuinely different from what teachers face in rural provinces across China, let alone in smaller economies across the region.
UNESCO’s framework for AI in education keeps returning to the ethical core: students should learn to evaluate AI-generated content critically, to understand algorithmic bias, to protect their own data, and to develop what UNESCO calls “human-centered” AI use. Singapore has moved aggressively on this, launching a national initiative to build AI literacy among both students and teachers. South Korea and Japan have integrated AI components into teacher education programs. China’s timeline calls for AI to be integral to textbooks and exams at all levels by 2035 — an ambition that puts the policy infrastructure ahead of most of the world.
What Teachers Can Actually Do: The Pedagogical Spectrum
One thing I’ve been thinking about is that AI doesn’t sit in one place on the pedagogical spectrum — it shows up differently depending on what kind of learning you’re trying to support.
At the lower end of Bloom’s taxonomy — recalling facts, summarizing content, identifying basic patterns — AI is frankly very good. A student who needs to understand the timeline of the Opium Wars can get solid scaffolding from an AI tool quickly. That’s not cheating; that’s efficiency. The problem is when we stop there.
At the upper end — analyzing evidence, evaluating competing interpretations, creating original arguments — AI starts to break down in instructive ways. It tends toward confident consensus and away from genuine ambiguity. It can’t hold the productive uncertainty that real historical thinking requires. When I ask my students to use AI to construct an argument and then challenge it, the challenge part is almost always where the real learning happens. The AI gives you a plausible position. The student has to figure out where it’s wrong, incomplete, or culturally blinkered.
Ryan Witt, Head of Tianjin International School, made a point that I think applies here: “Schools must invest in professional development for staff to model appropriate usage.” The teacher’s job isn’t just to set the assignment — it’s to show students, explicitly, what thoughtful AI use looks like at different stages of learning. That means being visible about our own process. When I use AI to help me draft a lesson outline, I tell my students. I show them the output and then show them what I changed and why. That transparency is part of the curriculum now.
The Question Worth Asking
Professor Wu Kangning, quoted in the Suzhou forum coverage, asked the question I think every educator needs to sit with: “Should we embrace AI or wait and see? Should we lead or follow?”
There’s no comfortable answer. Waiting and seeing means students are navigating these tools without guidance, which is its own risk. Leading means being willing to experiment in public, make mistakes in front of students, and revise your thinking openly — which is uncomfortable, but also, honestly, exactly what we’re asking students to do.
The international schools I’ve been reading about are leading. Not perfectly, not without stumbling, but genuinely. And the thing that most strikes me about the teachers I’ve been reading — from Suzhou to Wuhan to Beijing to Tianjin — is that they’re not asking whether AI belongs in education. They’ve settled that. They’re asking the harder question: What kind of education do we want AI to serve?
That’s the right question. I’m still working on the answer. But I’m grateful I’m not working on it alone.
David Jacobson teaches AP World History, Modern World History, and Asian History at Shanghai American School. He writes about AI, pedagogy, and what it actually looks like to teach in a world that’s changing faster than curriculum cycles.
Sources:
– Thomas Hatch, “Can AI ‘Ignite the Mind and Heart’?” — International Education News, March 4, 2026
– AmCham China, “Learning in the Age of AI: How China’s International Schools Are Adapting” — AmCham China
– Colleen Kenny, “Content Chaos: Why AI Makes Media Literacy Education’s Most Urgent Democratic Task” — LinkedIn
– Dr. Libing Wang, UNESCO Regional Office Bangkok — UNESCO, “How Generative AI is Reshaping Education in Asia-Pacific”
– Professor Wu Kangning, quoted in International Education News, March 2026
