Writing
Featured · Medium · January 2026
Moving from fear to inquiry in AI classrooms.
A year of embedded observation in secondary classrooms. Argues that a teacher's emotional stance toward AI shapes whether students treat it as a thinking partner or a shortcut. Introduces VERIFY and EPFL as frameworks for moving from banning to teaching. References Hasan (2024), Porayska-Pomsta et al. (2024), and UNESCO (2021).
Classrooms reveal their mood before anyone speaks.
Many students have learned to treat curiosity like it carries a risk.
Misuse stems from disconnection, not deception.
Teaching in the age of AI is often defined by control. It does not have to be.
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Cornerstone reads
Not the full archive. The arguments that hold the rest together. Some are v1 thinking that has since iterated. The complete list lives on LinkedIn.
Aug 2025 · v1 article
The standalone articulation of VERIFY as a six-step thinking cycle. Argues the real risk isn't AI misuse, it's intellectual surrender. Maps onto the Australian Framework for Generative AI in Schools. The framework on the current Work page has continued to iterate since.
Read on LinkedInJun 2025 · v1 article
The original six-step EPFL: Feeling, Intent, Prompt, Output, Consequence, Reflection. Argues the real issue is the invisible emotional and ethical dynamics in every AI interaction. The current v2.0 form on the Work page is the iteration that came out of using v1 in real classrooms.
Read on LinkedInJun 2025
The piece where VERIFY first appeared (before becoming a standalone article). Argues that "ethics" gets used as a reason to pause progress instead of shape it. Ethics aren't delivered through policies; they are stood for through how you show up.
Read on LinkedInv1 article · RePrompted
Argues we shouldn't start AI education with chatbots but with thinking. Challenges the cheating frame, makes the case for play-based learning that builds critical thinking before tool access. Introduces RePrompted, the card-based classroom tool.
Read on LinkedInEthics of literacy
Argues that treating literacy as reading and writing is not just outdated but ethically harmful. Meaning is already multimodal. Connects multimodal literacy to AI ethics: ethical agency begins with recognising how meaning is designed across text, image, sound, data, and interface.
Read on LinkedInDigital literacy
Challenges the myth that technology is "just a tool." Argues students need to understand how their digital footprints are shaped, how data flows invisibly, and how AI systems influence their worldview. From digital users to digital shapers.
Read on LinkedInResearch practice
Observes how students freeze when research hits obstacles. Paywalled articles, broken links, dead ends. Argues the key is teaching students to shift, not stop: use AI as a sounding board, work backward through reference lists, make research their own.
What readers wrote back
This is exactly the adoption mistake many institutions make: they treat access as literacy. Giving students a chatbot is not the same as teaching them how systems frame, distort, compress, and reward certain kinds of thinking.
Ethical AI use in education isn't just policy, it's daily practice. The conversation about ethics needs to happen before the tech is even turned on.