A child leaving 6th Class this year began primary school in a very different world. During their eight years in school, technology has changed rapidly, artificial intelligence has become part of everyday life, and new careers have emerged that would have been difficult to imagine when they first entered Junior Infants.
We cannot know exactly what technologies our pupils will use or what jobs they will do in the future. What we can do is help them develop transferable thinking skills: breaking problems into manageable parts, recognising patterns, making predictions, testing ideas, learning from mistakes and improving solutions.
These are central to computational thinking, and they are also central to mathematical thinking.
| Computational Thinking | Mathematical Thinking |
| Decomposition | Breaking problems into smaller parts |
| Pattern recognition | Identifying relationships and structures |
| Abstraction | Deciding which information matters |
| Algorithms | Developing and communicating a method |
| Debugging | Checking, revising and improving a solution |
The technology itself is not the learning. A child using a Bee-Bot, ScratchJr, a micro:bit or LEGO robotics is only developing these skills if the task requires them to reason, predict, test, justify and refine.
Across our school, we try to build this progressively through each stage.
Stage 1: Bee-Bots
Bee-Bots are one of my favourite tools because they are so simple to use, but the learning can be huge.
Moving a Bee-Bot across a grid can easily become an exercise in pressing buttons. The challenge is what makes it powerful.
Instead of asking pupils simply to reach the finish, we can ask:
- Can you predict how many moves it will take?
- Can you find two different routes?
- Which route is shorter?
- Can you avoid an obstacle?
- Where did the instructions go wrong?
Suddenly, pupils are working with sequencing, direction, counting, spatial reasoning, comparison and debugging.
The simplicity of the technology allows the thinking to take centre stage.
Stage 2: ScratchJr
At Stage 2, we introduce ScratchJr. The first few lessons are necessarily about learning how the technology works, but the real learning begins when pupils move beyond copying a set of instructions.
Open-ended tasks are key.
When pupils are challenged to create an animation or solve a problem in their own way, collaboration and creativity become central. They have to agree on a plan, sequence actions, estimate movement, test ideas and make changes when something does not work.
The shift is from:
Can I copy the correct blocks?
to:
How can we solve this problem?
That is where mathematical thinking begins to deepen.
Stage 3: Connecting Coding to Real-World Problems
At Stage 3, pupils begin using the micro:bit and MakeCode Arcade.
Our school has been fortunate to take part in the Coding for the Sustainable Development Goals project with the Technological University of the Shannon. Pupils received visits from experts and also had the opportunity to visit the university campus.
We are very grateful to the TUS team for these opportunities and for helping both pupils and teachers see how technology can be used to support the Sustainable Development Goals.
The mathematical relevance is important. A sustainability challenge might require pupils to collect data, compare results, identify patterns, use variables, make predictions or decide what information is important.
The technology becomes a tool for asking better questions:
What do we need to measure? What does the data tell us? What patterns can we see? What happens if we change this value?
Coding begins to move from an isolated activity to a way of exploring real-world problems mathematically.
Stage 4: Designing and Refining Solutions
At Stage 4, pupils begin applying what they have learned to more complex challenges.
Through Microsoft DreamSpace, our pupils used micro:bits to develop solutions linked to the Sustainable Development Goals. One group designed a system to count plastic bottles being placed into a recycling bin.
A micro:bit was attached inside the bin and used its accelerometer to detect when the lid opened. Each movement increased a count. When a set number was reached, a message was sent to a second micro:bit being used as a simple smartwatch.
The mathematical thinking was embedded throughout: counting, thresholds, variables, data, testing accuracy and deciding how to deal with false readings.
Our work with FIRST LEGO League, supported by University College Dublin, offered another powerful example.
The biggest learning was not the finished robot. It was the process of creating it.
Pupils had to measure distances, estimate turns, work with angles, test routes, compare solutions and repeatedly refine their ideas.
The cycle became:
That is computational thinking and mathematical problem solving working side by side.
We are very grateful to the UCD team for giving our pupils this experience and helping us see the potential of LEGO robotics for developing deep mathematical thinking
Tips and Pitfalls
A few lessons from our experience stand out.
Look for opportunities to work with experts. Universities, industry partners and external programmes can open doors for pupils, but they also give teachers opportunities to learn.
Do not focus on the technology. LEGO kits, micro:bits and robots are fantastic, but if every pupil is simply following instructions to create the same finished product, much of the problem solving disappears.
Invest in teacher confidence and CPD. Teachers do not need to become expert programmers, but they do need enough confidence to recognise the thinking behind an activity and ask the questions that deepen learning. Programmes such as CodeGreen can provide an excellent starting point.
Do not let resources become a barrier. Computational thinking can be developed without expensive equipment. A printable Bee-Bot with a magnet can be moved around a whiteboard grid just as effectively for many tasks.
We also use STEAMkits throughout our school. These are no-tech challenges where pupils have no option but to collaborate, problem solve and think critically. In many ways, removing the technology can make the thinking even more visible.
The resource matters far less than the challenge built around it.
Whether pupils are working with a Bee-Bot, ScratchJr, a micro:bit, LEGO or a handful of classroom materials, the aim should remain the same:
create opportunities for pupils to think.
We may not know exactly what our pupils’ future workplaces will look like, but we can help them develop the habits they will need to succeed there: curiosity, resilience, reasoning, creativity and the confidence to tackle unfamiliar problems.
Computational thinking gives us another powerful way to develop those habits, and to create stronger mathematical thinkers in the process.