An IB Teacher’s Response to “What’s Really Going On With AI In Schools?”
William Liang’s clarity on AI in schools is a lightning bolt of truth, echoing my 20 years in IB classrooms. He’s right. Most students see assignments not as “voyages of discovery” but as hurdles to clear. And AI is their tool of convenience. But this isn’t laziness. It’s the inevitable result of an education system that prioritizes grades over growth. As an educator who champions a maker mindset, I argue that our focus should shift entirely, starting with William’s bold proposal.
First, let’s flip the script: Banning take-home homework that ChatGPT can do isn’t radical — it’s essential. My IB students enjoy tasks like presentations, Socratic debates, apprenticeship-style projects, and design challenges. These activities show what AI can’t replicate: struggle, iteration, performance and genuine insight. Witnessing a student troubleshoot a harmonic clash in their composition or debug a circuit in an instrument they’ve built? That’s where critical thinking ignites. William nails this: assignments must demand creativity, not just prompts.
Yet fixing assignments alone isn’t enough. We need a mindset revolution. This is not just a suggestion, but a necessity for the future of education. I’ve integrated Carol Dweck’s growth mindset into my pedagogy. This growth mindset shows students must view challenges as opportunities, not threats. Today’s AI “shortcuts” breed “learned helplessness.” A 2025 study by Azeem & Abbas confirms this: over-reliance on AI triggers grade declines and undermines confidence. Instead, AI should act as a wingman, someone who will support, protect, and enhance. Imagine students with Lincoln-esque rhetorical feedback or da Vinci-inspired project critiques. That’s transformative mentorship, not substitution.
Here’s where schools are failing: Most edtech AI platforms promote a consumer mindset. They’re “black boxes”— handing answers while stifling curiosity. I’ve seen teachers drown in “AI slop” from “golden shackle” tools: generating generic lesson plans and auto-graded drivel. As William hints, this wastes potential. True learning demands making.
The solution? Platforms that enable creation, not just consumption. Sage.Education, which I launched as an antidote, lets students build custom AI tools like chatbots. It's a platform that not only teaches students about AI but also allows them to create with it. An integrated block-based coding interface demystifies the “wizard behind the curtain”. This cultivates a maker mindset. When your student designs an essay-feedback bot rather than using one, they’re apprenticing with AI, not cheating it.
History whispers warnings. Like calculators in the 80s, AI exposes flaws in our learning paradigms. But unlike calculators, generative AI acts as both paintbrush and painter. Current “guilty until proven innocent” detection approaches misunderstand why students outsource work. Research shows those with fixed mindsets seek shortcuts to compensate for perceived limitations. This is a symptom our systems create.
The answer isn’t policing shortcuts, but removing their appeal. Like William, I advocate bold classroom redesign. My call to educators:
- Ban replaceable homework as he suggests. Real thinking thrives under facilitated supervision. Redesign assessments to focus on in-class creation and communication.
- Demystify AI. Fostering AI literacy and accountability. Explain and show how AI works, what its strengths and weaknesses are.
- Rewire mindsets using Carol Dweck’s principles. Adopt maker-focused AI platforms like Sage.Education — privacy-friendly, open-ended, and skill-building. Students must see AI as clay, not crutches. My classes now design custom tutors building image classifiers to critique art. And chatbots that debate philosophical texts. This maker mindset transforms users into architects.
- Empower teacher ingenuity. Current “AI-proofing” resembles blocking calculators. It’s better to co-create tools fitting unique classrooms. I customize system prompts to spark discussion, not answers.
- Reward iteration. Grade drafts, version histories, AI chat logs, and reflections—proof of intellectual labor. This is not just about the final product, but about the journey of learning and growing. Focus on the process over output. Making mistakes is essential to learning and growing. Reinforce sharing version histories and showing cookie crumbs of proof of learning.
This shift terrifies institutions built on standardization. But as William rightly observes, students already apprentice with algorithmic “Hemingways.” Our choice is clear: fight their future or equip them to shape it.
The classrooms of tomorrow demand teachers who engineer cognitive challenges, not assignment factories. William’s generation understands this. Do we?
Isabelle Plante is a 20-year IB Music educator. She is also the co-founder of Sage.Education, and advocate for classrooms where students engineer futures, not just essays.