This Teacher’s Journal: Blog Post 10 | March 22, 2025
Introduction: Beyond the Hype of Influencers
In recent weeks there’s been a lot of chatter on social media about the importance of teachers sharing their voice. (See posts by Bronwyn Ryrie Jones and Michelle Michael) so this post is not a theoretical reflection. It is drawn from the real-world work of teaching in a secondary school classroom in a dynamic and human way.
So here are six things I’ve learned – informed by research and theory, shaped by nearly 40 years of teaching practice, and distilled through reflection – about what it means to teach with AI in a real secondary school classroom. They are in no particular order or hierarchy. They truly overlap and blend into each other. I offer them for your critique and reflection.
1. Pedagogy matters!
If there is one thing teaching with technology has taught me over the years, it is this: the technology always matters less than what we choose to do with it. We need to use technology – all technology – with a purpose in the classroom.
In classrooms shaped by accelerating technological change, it can be easy to get caught up in the noise around generative AI. There’s a temptation to talk about AI like it’s a shiny new toy with so many affordances. We’ve seen this hub bub around tech before. AI is truly different to what has come before yet what matters is not the AI itself, but the learning. AI has an impact on the why, the how, and the what of learning in our subjects.
Further, using AI in the classroom is less about the tool itself and more about what it invites us to become – as teachers, as learners, as a community of inquiry. To me, my experience of AI in the classroom suggests that this is a technology challenges us to be more human, not less. It challenges us to find our purpose and the purpose of in our subject area disciplines for the future.
At the heart of this first reflection is my deep belief that we must prepare learners for a VUCA world – a world that is increasingly volatile, uncertain, complex, ambiguous. One that is being shaped by AI. AI is already forcing us to our current assumptions about how schools, classrooms, and assessments work. I anticipate that this VUCA future will increasingly challenge communities to reconsider what they hope for from schools. I suspect they will expect schools to be places that create learners who are much more than knowledge consumers – learners who are connected members of communities, learners who are knowledge makers, co-creators, collaborators, and critical citizens.
It’s time for us to reflect on our pedagogical assumptions. For such the world of the future we need pedagogies that are future-oriented, human-centred, and ethically grounded. We need pedagogies that help our classrooms to be more human in a world where powerful technologies take leaps and bounds forward in capability every day. We need ways of teaching that do more than play with new technologies as if they are toys, use technologies in a misguided attempt to prop up a current raft of failing industrial models of practice, or use those technologies to replace the important humanity at the heart of teaching.
It’s time to reflect on your pedagogy, to reinvent it, to reimagine your why.
Our why matters. Our values matter. Our commitment to the full development of the learner – intellectual, emotional, ethical – matters.
2. Learning First. Always.
The first and most important lesson is deceptively simple: AI works best when we centre learning, not the tool. That sounds obvious, but it’s easy to forget. The flash and fluency of large language models can distract. But in my classroom, I’ve learned to ground it all in the learner. This principle is foundational. The classroom is not an edtech showroom or a stand at a conference or open day. It’s a place where human beings wrestle with ideas, identities, histories, and possibilities.
That means teaching students to actually use the tool: how to prompt well, how to work iteratively in multi-turn chat conversations with the AI, how to bring their own insights and experiences into the interaction. It means embedding AI in the flow of meaningful, context-rich learning – not tacking it on.
And it also means building a culture of trust, transparency, and connection. I need to know how my students learn. I need to connect with them – not just as students, but as people. AI works best in a classroom where people feel safe to be seen, to think, explore, make mistakes, and try again.
3. Move from Differentiation – Design for All, Not Just Some
For years, I’ve thought mainly in terms of differentiation. Flipped learning and AI mixed together create something beyond differentiation – they allow for a truly universal design. Together, I believe an AI-infused flipped learning approach supports me to teach in a way that accommodates the needs of every student. Using flipped learning and AI together, I believe I can provide multiple supported entry points to learning for every student. While I still have a lot to learn and to get better at, I believe a flipped-AI-UDL approach provides me with an effective and practical means of supporting all of my students.
By flipping the classroom, I give students early, flexible access to content – on their terms. The asynchronous and flexible content delivery is supported with AI and underpins the development of skills. I scaffold student use of AI, not just as a productivity tool.
My goal is to allow every student to use AI as their personal tutor, study partner, and thought partner. My goal is to give every student the skills to interact with the platforms that mediate their interactions with LLMs. I’m platform agnostic, every student is expected to have the skills to develop an ability to work with ChatGPT, Copilot, and Gemini – the interfaces that are powered by LLMs. The interfaces may change but I aim to ensure that my students can all use these tools in increasingly sophisticated ways. In my classroom, it’s not about students doing more faster or easier. It’s all students becoming more independent in their ability to solve problems. It’s about helping every student to go deeper into learning, with support, autonomy, and adaptability built in.
Students aren’t just using AI to finish tasks. They’re using it to build confidence, to stretch their thinking, and to craft learning pathways that make sense for them. That’s what liberation in learning looks like.
With the right scaffolds, AI enables students to work at their own pace, in their own way, and with tools tailored to their needs. UDL asks us to design learning experiences that are accessible, meaningful, and empowering for all students from the start of a learning episode. AI makes this goal not only possible but practical.
Students should be given permission to use AI as their 24/7 study buddy, mentor, and guide—within a safe, supported framework. Teaching students to work reflectively and responsibly with LLMs in a “HI + AI hybrid mode” increases their confidence, accelerates their growth, and gives them powerful tools for life beyond school. The flipped classroom provides an early grounding in content that prepares them to engage more deeply and creatively with ideas in class.
4. Teaching Is Still a (very) Human Job
Here’s the paradox: the more AI shows up in my classroom, the more human I need to be. If you like, the irony of teaching with AI is that it has compelled me to prioritise teaching in ways more human.
When the machines can draft, summarise, translate, and explain – what’s left for the teacher? Everything that matters.
I no longer have to be the expert who delivers all the content, answers every question, models every skill. I can delegate a lot of that to AI.
What I must be is truly present.
Being present.
Asking the right questions. Modelling curiosity. Sitting with them in the complexity and the ambiguous.
Making space for emotion, for ethics, for identity.
Knowing why we learn what we do. Knowing why and how I teach what I do. Knowing what matters and when it matters.
Teaching has always been about people. Now it’s about that even more. When so many aspects of content delivery and even skill development can be enhanced or simulated by AI, the human, moral, and relational dimensions of education become even more critical.
AI allows me step back from being a content deliverer and lean into what I believe really counts: values, relationships, and vision. Now, more than ever, we need to embrace the soul of teaching – the presence, the values, the vision.
We need to help our students to understand that learning is not preparation for life – it is life itself. We need to help our students to understand that learning is to affirm – to say yes to life, to justice, to becoming.
Learning must be rooted in hope, purpose, and humanity. Our why matters. Our values matter. Our commitment to the full development of the learner—intellectual, emotional, ethical—matters. Teaching with AI can liberate us to focus more fully on these human aspects, to respond to complexity with care, and to guide students with clarity and compassion.
AI has allowed me more space to connect my classes’ learning experiences to hope, purpose, and humanity.
5. Students Need to Be Shown, Not Just Told: Teach the Tool
There’s a myth that young people just “get” technology. They don’t. They know what they’ve used. And most haven’t been shown how to use AI effectively, safely, or ethically.
I’ve learned that teaching with AI means teaching the tool explicitly. Not just how to prompt, but how to think with it. How to critique it. How to recognise when it’s being helpful – and when it’s not.
I provide structure: thinking routines, templates, examples. I coach. I check in. I model. I challenge. Because they need it. Because they deserve it. And because without it, we risk handing them powerful tools they don’t know how to wield.
Privacy, data, digital habits – these all matter. It’s our job to help them build good ones.
Using AI in the classroom doesn’t work without explicit instruction. I certainly ‘teach the tool’ through what I call hard scaffolding, but this must be paired with soft scaffolding – regular meaningful check-ins, one-on-one coaching, detailed actionable and timely feedback, and plenty of reassurance and affirmation.
Students are not digital natives in the way many assume. They only know what they’ve been shown and what they’re currently using. AI is a new skillset – and, like adults, students benefit from expert guidance. Some still struggle to search the internet effectively, let alone use an LLM responsibly.
The “just do it” ethos that often surrounds digital tools is seductive but insufficient. Students need support. They need to be taught how to avoid common AI pitfalls and how to work safely, ethically, and effectively. Privacy, data security, and digital discernment remain critical. Our job is to guide, coach, and protect.
6. Amplify Student Voice: Help Students Speak – and Help Them Mean It
AI can do a lot. But it can’t be the human.
One of the biggest risks I’ve seen is students outsourcing their voice. Letting AI do the heavy lifting, then submitting what’s basically a machine-generated answer. Not because they’re lazy – but because they’re unsure, overwhelmed, or disconnected. The risk is not that students lose their voice entirely, but that they become ventriloquist’s dummies – passively echoing machine-generated ideas instead of expressing their own.
That’s why I work to amplify student voice – not just protect it. I aim to build tasks that require connection and reflection. I work to build a classroom culture that celebrates identity, culture, human insights.
I make it clear to students:
AI can support your thinking, but your thinking still matters.
AI can support you finding your words, but your words still matter.
You matter.
Used well, AI isn’t a substitute. It’s a springboard. It gives students the confidence and capacity to explore, express, and extend their learning. That’s the kind of voice that lasts. That’s the kind of voice that leads to action.
We must design learning experiences that promote reflection, voice, and agency. AI is not just a scaffold – it’s a tool that can allow students to do more and be more with their knowledge, skills, and creativity. But we must be intentional.
It’s about recognising that authentic voice, supported by the right tools, is core to developing confident, capable learners. AI, used well, can boost expression, accelerate drafting, support argument construction – but it should never speak in place of the student. The student must still do the thinking, still own the ideas.
Amplifying voice in this way is a form of empowerment. It contributes to a safe, inclusive, and agentic learning environment where students see themselves as thinkers, contributors, and changemakers.
Conclusion: A Call to Do More and Be More
Teaching with AI is not a shortcut. It’s not a gimmick. It’s a challenge. It’s an opportunity.
It’s an invitation.
To reimagine what teaching is.
To rethink what learning can be.
To reconnect with the human heart of education.
Teaching with AI is not about making things easier. It’s about making things matter. It is a call to go beyond the minimal, beyond compliance, beyond coverage. It is a call to rethink what it means to teach – and what it means to be human – in an age of intelligent machines.
My ideas here are not a finished product. They are an evolving praxis. But they point to a future where my teaching area, history, is not just a subject to be learned but a medium through which students imagine new worlds.
In this future, teaching with AI is not just a skill. It is a moral, pedagogical, and civic responsibility.
If we use AI well, we can help our students do more, be more, and imagine better worlds. And isn’t that why we teach?
Disrupted History 