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A strength of this lesson is that pupils compare an AI response with a book, encouraging them to think critically instead of accepting information straight away. This helps them understand that AI can make mistakes and that information should be checked using reliable sources. How will you help pupils understand that books and websites can also contain errors or bias? As a follow-up, ask each group to explain one fact they checked and how they knew it was accurate.
AI Wildlife Challenge
Class Stage:
Stage threeCurriculum Area and Learning Intention: STEM Education.
Technology -build on the process of using, modifying and/or creating algorithms to solve a problem or achieve a desired outcome. Use abstraction [focus on important characteristics and reduce unnecessary detail] and debugging [identify and correct errors] to increase effectiveness or make improvements. AC, DL, M
Science – classify groups of plants and animals according to a range of criteria such as families/ types, habitats, parts/ movement and diet. AL, C, M
AI Concept Being Explored: Machine Learning (Supervised Learning)
Pupils will see that AI learns by finding patterns in the examples it is given. They will also discover that if the training data is limited, the AI is more likely to make mistakes.
Activity Outline
Introduction (5 minutes)
Begin by asking pupils how they think apps like Google Lens or Snapchat filters recognise objects. Explain that AI does not “know” what something is—it learns by looking at lots of examples and spotting patterns.Training the AI (20 minutes)
Using Teachable Machine, pupils work in small groups to train an AI model to recognise two categories: Forest and Beach.They are given a selection of teacher-provided objects, such as leaves, pinecones, shells, pebbles or sticks. Pupils should try taking photos from different angles and distances to help improve the model.
the model has been Once trained, each group tests it with objects it has already seen.
The Mystery Object Challenge (10 minutes)
Next, give each group a few “mystery” objects that were not included in the training data, for example a feather, a flower, a smooth stone or a toy animal.Before testing each object, ask pupils to predict what the AI will decide and explain why. Afterwards, discuss whether the prediction was correct and what may have caused any mistakes.
Critical Question
If the AI got the feather wrong, was the computer making a mistake, or did we not give it enough different examples to learn from? How could this affect AI systems that people use every day?
Responsible-Use Consideration
Remind pupils that they should never use photos of themselves or other people when training AI models. Instead, they should use classroom objects or teacher-approved images to protect everyone’s privacy.
Supporting Critical Thinking
Throughout the lesson, encourage pupils to explain their thinking by asking questions such as:
- Why do you think the AI chose that answer?
- What examples did we give it?
- What could we add to improve the model?
This helps pupils understand that AI depends on the data it is trained on rather than simply “knowing” the correct answer.
Gathering Evidence of Learning
Teacher Observation:
Listen to group discussions and observe whether pupils can explain why the AI made certain predictions and identify ways to improve the training data.Exit Ticket:
Before leaving, pupils complete a short reflection:- One thing I learned about how AI learns.
- One reason AI sometimes gets things wrong.
- One way I could improve my AI model.
This sounds like a great way to introduce the discussion about Cybersafety. I’m sure each time you do this lesson with a different class it would result in different discussion and focus points.
The demo world I chose was Build an Aeroplane in Minecraft Education.
This world is about designing and building an aeroplane while learning about how planes fly. You get to test different ideas, solve problems, and improve your designs. It encourages creativity and teamwork while introducing some basic engineering concepts.
The learning objectives focus on understanding the forces involved in flight, using problem-solving skills, and working together to build and test an aeroplane.
I think this links well with the Curriculum, especially Energy and Forces. Pupils can explore ideas like gravity, lift, and thrust in a practical and engaging way. It also supports STEM learning by encouraging pupils to investigate, create, and learn through trial and error.
Before starting, I would spend a few minutes explaining the basic forces that help an aeroplane fly so pupils have some background knowledge. During the lesson, I would encourage pupils to work in pairs so they can share ideas and help each other. At the end, I would have a short class discussion where everyone could talk about what worked well, what didn’t, and what they would change if they built their plane again. I think this would help pupils make stronger links between the activity and the science behind it.
I really like your game. It was fun to play! I was wondering what they curriculum link was, but when I re-read your post and realised it was digital story telling, it made sense.
I made a game called ‘Recycling Rescue’ https://makecode.com/_R4qcY1aTvgRd
Game Type: Timed Catch/Collect
Game Title: Recycling Rescue
Curriculum Area and Learning Objective: Curriculum Area: SSE
Learning Stand: Environment and sustainable living
Learning Outcome: Geography: examine sustainable practices (social, environmental, economic) in the local community and actions people can take to promote sustainable living. AC, AL, W
Simple Storyboard
Location: A park where recyclable and non-recyclable items are falling from the sky.Player: A recycling bin controlled using the arrow keys.
Relevant Game Elements: Recyclable items (plastic bottles) to collect.
Rubbish items (pizza which should be put into the compost) to avoid. Use this as a discussion about what items should go into the recycling bin, which items can be composted and which items go into the general waste.Score counter and lives displayed on screen.
5. Goal
The player must collect as many plastic bottles as possible before the timer runs out while avoiding food waste. Each bottle collected increases the score. Touching food waste causes the player to lose a life. The player aims to get the highest score before the timer ends or game stops if all lives are lost.6. Computational Thinking
Algorithm DesignI used algorithm design to create the sequence of events that controls the game. First, the recycling bin is moved using the controller buttons. Plastic bottes are generated at random positions and fall down the screen. The game detects when the player collects a bottle or touches food waste, updating the score or lives accordingly. Breaking the game into these logical steps helped me develop and test each part before combining them into the finished game.
This sounds great. I like how you’ve included opportunities for collaboration, testing and improving each other’s code encourages problem-solving and logical thinking.
I used the MakeCode smiley and sad face tutorial: https://makecode.microbit.org/_617XuEe418rh
After learning how to program the micro to display different facial expressions, I would challenge the class to design a “Feelings Check-In” device for the classroom. They could programme the micro to display a happy or sad face and discuss how technology can be used to support wellbeing and communication.
Technology is developed through coding the micro in MakeCode, Engineering through designing and improving the device, Mathematics through using logical sequencing and algorithms, and Science through exploring how inputs and outputs work in digital systems. Pupils would follow the Plan–Do–Review process, working collaboratively to design, test, evaluate and improve their solution before sharing it with the class and reflecting on their computational thinking skills.
I like how you identified developing your use of assistive and accessibility technologies as an area for growth. It shows a clear commitment to creating an inclusive classroom where all pupils can access and participate in learning.
Your action of incorporating one accessibility feature into a literacy lesson each week feels realistic because it is specific, manageable and easy to monitor over time. Introducing one new strategy at a time should help you build confidence while allowing you to see which tools have the greatest impact on pupils’ learning.
I would be interested to know how you might review the impact of these accessibility features on pupil engagement and learning. One way you could gather evidence of progress might be through pupil voice, observations, or samples of pupils’ work before and after introducing the tools.
One of my strengths is that I embrace new technologies and enjoy exploring innovative ways to enhance teaching and learning. I have previously taken part in the FÍS Film Competition with my classes, which provided pupils with meaningful opportunities to collaborate, solve problems, think creatively and communicate their ideas through digital media. Alongside this, we regularly engage in hands-on STEM learning through engineering challenges such as tower and bridge building, encouraging pupils to investigate, design, test and improve their ideas.
This year, I would like to refine my STEM practice by embedding a more consistent engineering design process and using assessment to better support the development of pupils’ computational thinking skills. My aim is to help pupils apply their digital competence and problem-solving skills in increasingly creative and innovative ways.
Design and implement one STEM challenge each half-term using clearly defined design constraints (e.g. a limited number of materials or a set budget) to encourage creative problem-solving and innovation.
Consistently embed the Plan–Do–Review process in every STEM project, enabling pupils to plan their approach, evaluate their solutions and identify improvements through structured reflection.
During each STEM project, focus observations on one computational thinking concept (e.g. decomposition, pattern recognition, abstraction or algorithms) and use these observations to identify pupils who require additional support and those who are ready for further challenge.