AI Playground: How We’re Learning With Machines in the Classroom
- Lidia
- 4 days ago
- 4 min read
If you’ve been following me on Instagram (@the.art.of.inquiry), you already know I’ve been on an AI-in-the-classroom posting spree. Honestly, at this point, my feed is about 40% STEAM lessons, 40% AI experiments, and 20% Jonas Brothers music that I absolutely did not intend use on every single post I make. But hey, the algorithm insists I need it for my well-being.
Anyway 🤭... if you have been following along you already know I’ve been running a mini-series on my current obsession: AI learning experiences that I’ve been trying with students. Not tools… not apps… but little digital playgrounds where curiosity, chaos, and critical thinking collide.
Over the last year or so, the students and I have been diving into these AI experiments, not as magic answer machines that do our work for us, but as places to poke around, ask questions, train models, and see what happens. And let me tell you… when a group of 11-year-olds trains a Teachable Machine model using only doodles from the Notes app, the chaos is AMAZING.
Here’s a quick tour of the AI adventures we’ve been loving in the LLC:
TwinPics.ai: Describe This… Carefully.
If concise writing were a competitive sport, TwinPics would be the championship arena. Students get an image and have to describe it in under 100 characters. Then the generative AI creates a new image based on the description the students have written. They then receive a percentage of accuracy. The goal is to get as close to 100% as possible.
Students learn quickly that adjectives matter, specificity matters, and that “the cat on the left” is not nearly descriptive enough when there are two cats on the left in the image. It’s fast, vocabulary-rich, wonderfully chaotic, and a brilliant way to sharpen language with laughter. OH AND... my high score is 98% accuracy. Not to brag.
Adobe Firefly: Prompt Like an Artist.
Adobe Firefly is where creativity meets precision. Students write prompts to generate images and immediately see what happens when their creative and ridiculous ideas turn a panda into a panda wearing sunglasses on a pizza floatie. This generative AI can be used to create images as well as short videos.
Students revise prompts, test vocabulary, and learn that clear descriptions produce better results. It’s descriptive writing disguised as a digital art class, and honestly, the engagement level is unmatched.
How can you use this? Have students write detailed descriptive prompts in Adobe Firefly to generate images of a story setting they’re creating, then compare how well the AI matched their descriptions and revise their writing for clarity.
Finally, Adobe Firefly is integrated into Book Creator through the “AI Image Generator” feature, which lets students generate images right inside their Book Creator pages without leaving the site. They can write a descriptive prompt, click “Generate,” and instantly add an AI-created illustration directly into their books. Game Changer!
Google Whisk: Idea Remixing at Lightning Speed.
Whisk is pure ideation energy AND I LOVE IT! This is another generative AI image creator with a bit of a twist. Students can drop in text or images and watch the AI remix them into new magical places. No complex prompting required.
Students can upload an image or short description of their favourite book, favourite character, and favourite scene into Whisk and use its quick visual remixes to bring their ideas to life in the art style of their choice.
Just think, you can create Katniss Everdeen in The Hunger Games, hiding in the trees, but make it Sailor Moon. SO COOL! There are many different ways you can use this, your imagination is the limit!
Teachable Machine: Gather it. Train It. Test It.
This one is always a hit. Students build their own mini machine-learning models using photos, drawings, sounds, or poses. They collect data, label categories, train the model, and then test it… which is where the real fun begins!
When the students ask “Why does it think my pencil case is a banana?”, we wonder why the AI misclassifies things, and students investigate. They refine labels, adjust datasets, and learn that the quality and quantity of the data they are inputting really does matter.
It’s hands-on metacognition, a crash course in classification, and a reminder that AI ONLY KNOWS WHAT WE TEACH IT.
Google Quick, Draw!: Sketch Fast, Think Faster.
Quick, Draw! is chaotic good energy and it is by far one of my favourite ways to introduce the idea of datasets and AI. Students have 20 seconds to draw an object while the AI tries to guess what it is. Sometimes it gets it right instantly. Other times, it confidently announces that your jellyfish is actually a chandelier.
Students discuss what features matter most, explore dataset bias, and reflect on how humans and AI interpret symbols differently. It’s silly, fast-paced, and sneaks in some powerful learning about communication and representation. And when you hear the students say, "Do two squiggles make it a snake or a worm?”... all you can do is laugh and think,“Yup, this is exactly the kind of unhinged learning and energy we’re here for.”
Okay, this is all great, but... Why do we need to do this?
No one said you NEED to do this with students, but why not? It is fun, engaging, and there are so many ways we can easily AI into the classroom. AI isn't going anywhere, so we need to harness it for good!
These experiences aren’t about offloading thinking to AI. They’re about building thinking together. Students refine language, test ideas, question assumptions, and explore how humans and machines interpret the same information differently. It’s inquiry. It’s creativity. It’s critical digital literacy. And honestly, it’s right up the alley of any inquiry-driven teacher who lives for those messy, curious, “let’s figure this out together” moments.
If you try any of these with students, TAG ME! I want to see your chaos, your breakthroughs, and your AI generated pandas wearing sunglasses masterpieces.
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send me an email at lidia@theartofinquiry.ca
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