Look, I get it. GenAI is exciting. It’s shiny, it talks back, and it even writes your lesson plans while you sip kopi tarik. What’s not to love?
But here’s the thing: can we, as Malaysian academics — especially those of us in universities — take a step back and ask ourselves: Are we really doing enough with this tech? Or are we just scratching the surface and calling it a breakthrough?
Lately, I’ve been seeing an avalanche of GenAI courses, workshops, and webinars popping up like mushrooms after rain. All well-intentioned, of course. But the content? Mostly the same: “How to use ChatGPT to create a worksheet.” “How to ask AI to generate quiz questions.” “How to prompt like a pro.” You know the drill.
Now, don’t get me wrong. There is value in these introductory sessions — especially for teachers in schools who are still new to the tech. I salute the primary and secondary school educators who’ve embraced GenAI and integrated it meaningfully into their classrooms. They’re doing amazing groundwork, often with fewer resources than we have.
But here’s where I start to twitch a little: when we, the folks in tertiary education — the ones with research grants, postgrad students, and entire labs at our disposal — end up doing the exact same thing. Again and again. And again.
I was at a faculty sharing session recently, where a colleague showcased a GenAI “project” — essentially a glorified prompt guide for lesson planning. It was packaged nicely, complete with slick slides and some Canva magic, but I couldn’t help but think: Is this really the best we can do?
We’re supposed to be leading the charge. Not parroting what’s already out there.
Tertiary education should be the space where we push boundaries, not just repurpose tools. Where we break stuff, try wild ideas, build prototypes, write (and debug!) code, experiment with open-source models, develop our own AI tools for education — not just rely on commercial APIs with new labels.
Let’s be honest: ChatGPT is great, but it’s not the innovation. The real innovation comes from how we apply it, adapt it, and build upon it. The real work lies in taking what’s possible and turning it into something purposeful.
I’m not saying everyone needs to be a Python wizard or LLM fine-tuning expert overnight. But if we’re going to stake our claim in the AI-in-education space, we’ve got to aim higher. Otherwise, we risk turning our universities into training centers for skills that are already being taught — and taught well — in schools.
We need to stop being excited just because something looks futuristic. Flashy doesn’t mean forward-thinking. A new font and some AI jargon slapped onto a slide deck isn’t innovation. It’s just marketing.
So here’s a gentle nudge, from one academic to another:
Go deeper. Build. Experiment. Get your hands dirty. Collaborate with people from computing, data science, education tech startups. Take risks. You might fail — and that’s okay. That’s the point.
As for me? I’m trying to practice what I preach. I’m currently in the early stages of building an AI-powered platform for education — something I hope will actually do something new. Not just wrap ChatGPT in a different skin. I’ll be documenting the whole journey here in this blog — the good, the bad, the buggy.
Let’s not just teach about GenAI. Let’s create with it.
The future of education isn’t going to build itself. We’ve got work to do.
Hafiz Hanif, PhDMarch 24, 2025