Finding your position on AI in education

OpenAI has recently produced a course called ‘Chat GPT Foundations for Educators’ which is designed to be a silver bullet to teach educators how to use AI. The course is the product of a partnership with Common Sense Media which is (usually) a reliable source of ‘common sense’ reviews. What they seem to be missing is how teachers can use AI effectively and purposefully. They are not really encouraging teachers to be co-designers, critical evaluators and engineers of content.

It basically falls short of practical (and not contradictory) use case scenarios and has omitted a lot of big picture questioning about the ‘why’ behind the use of AI. The current debate appears to be an assumption that teachers should choose between AI or the highway. But maybe this yes/no binary thinking is the real problem.

AI shouldn’t be an ‘all in’ or ‘all out’ or Yes/No debate. It is much more complicated than that.

If there were a fork in the road that was ‘AI or the highway’, choosing the highway (non AI) is (still) just fine. If you haven’t read about the OpenAI foundation course you can find a useful critique of it here: How does OpenAI Imagine K-12 Education by Erik Salvaggio.

Here are some of the key points of critique:

• it assumes that teachers are passive producers of content

• it posits that productivity is more important than effective pedagogy

• it does not teach critical AI literacy

• it does not target pedagogy

• it is not a best practice example of UDL in action (no closed captioning)

• it assumes that administrative tasks can all be automated

• it does not seem to value the agency of teacher-owned creative processes in course design

• it overstates the predictive capabilities of AI

  and my addition:

• it assumes that teachers need to be ‘all or nothing’ consumers

OpenAI seems to champion itself as a heroic solution to all of the problems that teachers have. It does not really dig into any additional problems that using AI blindly also produce.

If you stand with AI - then you obviously must use it for everything and save so much time and create so many more resources and power up your productivity to the point that even writing your own meeting agenda can be outsourced. But - quantity does not beat quality. And producing does not equate to creating.

When I was at Elam School of Fine Arts, my professor said to me (when I was churning out bad art at a rate of knots): ‘There’s enough sh*t in the world. Why contribute to it?” And I think this is golden advice that can be applied to finding your own position on AI in education.

An easy ‘out’ is to stand on the opposite road with those who say No. You might stand in solidarity with teachers who see AI as a flash in the pan that is best avoided. These teachers might be summed up as the ‘pen and paper warriors’ who want to make sure that text books are used instead of laptops. If you avoid technology, then you also do avoid a lot of the ‘bad’ things - but you also run the risk of stealing learning opportunities away from students who also need to learn critical AI literacy. Teachers have a duty to empower students to understand, question, and navigate AI responsibly. This isn't just about using the tools to enhance their own productivity but helping students to critique and control their own uses to be critical creators of the future.

If you want to start using AI in the classroom it is ok to do so cautiously. In fact, it is best to use any tool with your pedagogue hat on and ask all of the questions like ‘where is the science’, ‘how does this enhance learner experience’, ‘how does this increase critical thinking’, ‘how might this offer more agency’, ‘how might this remove barriers to learning’ etc. And if it doesn’t align to your lens of what education should be and needs to be in the future, then don’t use it. Or more simply put, if you are adding to the sh*t in the world, don’t.

AI, when used purposefully, has the power to enhance, augment and improve learning - but you have to become an active architect of learning and do so.

So what next? Thinking and Linking:

1. Prioritise Critical Literacy: Read up on AI’s limitations, biases, and ethical implications. Foster a culture of inquiry rather than blind adoption. Read widely or at least dip your toes in: 12 Best Blogs on AI

2. Focus on Inclusivity: Accessibility should be a baseline, not an afterthought. All training materials must meet diverse needs to ensure equitable learning and expand rather than restrict learning accessibility. Use AI to expand not restrict.

3. Balance Efficiency with Depth: Productivity should not come at the expense of the thoughtful, creative processes integral to teaching. AI should enhance, not overshadow, pedagogical engagement.

4. Collaborate and Innovate: Join a community of practice to join in the critical conversation (this AI Forum is really worthwhile. It has fortnightly recorded webinars and emailed transcripts for an easy win for those of us who might be time poor). Even if you don’t join a community of practice, you might share innovations, successes, and challenges with AI in education with your colleagues in-house.

5. Critique your Use: Think about process over product, learner agency and the experience for the learners above all. How is augmenting and enhancing learner experience? How is it supporting more critical thinking? Ask ethical questions: How does this tool support diverse learners in my classroom? What biases might the AI outputs carry, and how can I address them? Are the benefits worth the potential trade-offs in creativity or critical thinking? My work-in-progress rubric is below.

6. Become an engineer not a consumer: There are SO MANY new AI tools on the market right now with Chat GPT being just one drop in a vast ocean. Popular educational solutions like MagicSchool.AI can create educational consumables in seconds, but the outputs might not be of true benefit to students’ experience. Consider how you might engineer your own more purposeful solutions rather than accepting ready-made products that might push passivity or feed another tech company’s coffers.

7. Explore Innovation: For some interesting use cases for how to innovate with AI in the classroom check out Harvards’s AI Pedagogy Project (this was also mentioned in the first blog link).

8. Put Pedagogy over Product: AI tools are only as effective as the intentionality behind their use. Targeting strategies like flipped classrooms, differentiation, UDL or gamified learning means that you can apply AI to pedagogical frameworks purposefully.
   

I created this rubric (work in progress) based on the ITL Microsoft Partners in learning rubrics. There are more categories in the rubric - but this is the first page as an example.

AI might not be a silver bullet or a magic solution, but neither is it a storm to be feared.

It’s not really an “AI or the highway” scenario, forcing a binary choice of ‘this or that.’ AI is simply a tool, and like any tool, its value lies entirely in how we use it. By asking critical questions, exploring practical use cases, and fostering collaboration, we can move beyond the ‘yes or no’ debate. Instead, we can become thoughtful, critical users who forge our own purposeful path forward—together.

I added this as a provocation - does the SAMR rubric work when considering AI? SAMR rubric by Puentedura adapted for AI use.

Thoughts? Questions? Leave a comment to share your thoughts.

What is 'make the pie' learning?

Have you ever been to a workshop or presentation and been given a handout while they present a slide show but you’ve spent the time daydreaming about all the things you’d rather be doing? Or have you ever been asked to write something down that was dictated to you only to promptly forget what you had written?

This kind of learning is like being served a pie. The analogy of a ‘pie’ is helpful because pies come in all shapes, sizes, and flavors—sweet and savory—and we can all imagine being handed a pie. In this learning approach, the pie is served to a passive recipient. The recipient of the pie has no active role in making or even cutting the pie. They might eat it, but they don’t gain any understanding of how it was made. Even if it’s delicious, it’s entirely forgettable—it’s not their pie.

Let’s think about what ‘make the pie’ learning might feel like. Traditional learning experiences are more about serving the pie – and handing out the answers – rather than letting learners dig in and make the pie themselves.

In a well-designed learning environment, no two ‘pies’ should be the same and everyone should have their own pie that they have proudly designed and made for themselves.

My ‘make the pie’ philosophy, is encouraging a hands-on and interactive approach to learning. My ‘make the pie’ philosophy is all about getting people to mix, blend and bake the ingredients themselves. In a well-designed learning experience, people should feel like they have been elbow-deep in the recipe of acquiring new skills, feel confident to combine their own ‘ingredients’ of ideas and leave with an experiential understanding of how things come together.

“She really makes us think for ourselves. I am getting more confident at problem-solving and I like how she doesn’t tell us the answers.”

What’s in the Batter?

I’m not making up this whole pie thing. It’s just my way of explaining pedagogy (teaching-science geekery) to people who don’t love jargon as much as me. The ‘make the pie’ philosophy is a way to re-imagine a workshop session as a pie-making extravaganza. Instead of handing everyone a finished pie (complete with crust and all), participants might get a basket of ingredients – flour, butter, fruit, maybe a pinch of sugar. Then it’s their job to mix, knead, and taste-test as they go. This is active learning that fosters trial and error, fast-failing and iteration, collaboration and communication and a lot more too… And the making of the pie is backed up with a solid lineup of learning theories:

• Constructionist Theory: Inspired by Seymour Papert, this approach invites learners to build their own understanding. Just as they’d experiment with different amounts of sugar or spices, they’re encouraged to “construct” knowledge by trying things out and learning from what doesn’t go as planned just as they also learn from what does go as planned. Applying this theory also builds resilience and critical thinking skills.

• Constructivist Theory: Constructivism embraces the idea that learning is a social recipe – we all bring different ingredients, and when we mix with others and talk about what we are doing and why we are doing it, we can create something unique. This means collaboration, discussion, and the freedom to add a little ‘seasoning’ of one’s own ideas on the table is encouraged. This also fosters creativity, community, agency and a sense of ownership of the learning AND encourages people to bring prior knowledge and experience as a valued foundation to any new learning. Key players in constructivist theory are Bruner and Vygotsky.

• Experiential Learning: If you can imagine each step of designing a recipe as a hands-on experience then this is experiential learning. In my ‘make the pie’ learning experiences, learners are constantly doing, making, and problem-solving with me as an expert guide on the side. This isn’t about a teacher telling students what to think or do but about them figuring it out and arriving at a new understanding with expert guidance.

Why Mixing Matters More Than Memorising

In a lot of learning experiences, we’re too focused on presenting the perfect pie – giving answers and ticking boxes – that we skip the mixing stage altogether. But here’s the secret: it’s in the mixing, kneading, and experimenting where the real learning magic happens. Research shows that active learning is what makes concepts stick. When people have a chance to build their understanding, they’re far more likely to remember it. When they make the pie, they’ll talk about what they made AND want to make more pies too.

Letting learners “make the pie” empowers them to feel like they own the final product because, in a very real way, they do. They’ve rolled up their sleeves and tried out the skills in a controlled, playful setting, so they’re prepared to replicate it in real life.

What Does a ‘Make the Pie’ Workshop Look Like?

When you come to one of my sessions, you’re not sitting and waiting for the ‘perfect recipe’ to appear on a slide. You’re gathering ingredients, mixing things up, and working with a team to see how it all comes together. You might start with a challenge and work out how to fix it – just like you would in a real world situation. You’ll leave not only with new knowledge but with the know-how to apply it.

1. Choose Your Ingredients: Participants can select the skills or concepts they want to explore with different options that are differentiated and designed to meet different skill levels.

2. Mix It Up: Everyone has the chance to try new approaches, exchange ideas, and learn by doing in their own time and way – like everyone adding sprinkles and tweaks to a given recipe.

3. Bake Together: There will also be opportunities for collective problem-solving and sparking and capturing ideas.

4. Eat and Reflect Together: While the catering is usually up to you, great learning experiences require some critical reflection. We’ll talk about what was most valuable, most effective, most engaging and most impactful so that we can champion these ingredients again in the next workshop.

Making the Pie means that learning is a process of experimenting, ‘tasting’, mixing up solutions and seeing what works. The ‘Make the Pie’ philosophy promotes a ‘can-do’ mindset – because participants were not handed the answers. The answers were made by them.

Ready to Start Mixing?

So next time you’re looking at a workshop or training session and you see a slide deck and a handout with readymade answers, rethink it and try a ‘make the pie’ recipe for success that’s interactive, memorable, and customised.

Because the best learning isn’t served – it’s stirred, seasoned, and baked with everyone’s minds doing the mixing. Like the sound of this kind of pie? You know where to find me.