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Data science – Bring data to life with these KS2 project ideas

Image of data points

Mary Gregory from the ONS introduces a new data science project for primary schools and explores how teachers can bring data to life…

Mary Gregory
by Mary Gregory
Fractions medium-term plan
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Data science uses technology, statistics, and specific topic knowledge to extract useful information from data, which helps us understand our world. 

Supporting pupils to build interest and confidence in the use of data from an early age is critical, putting them in the best position to navigate future challenges. We need to instil in children an instinctive ability to employ critical thinking when they encounter data and information. By doing so, children can also better understand how they contribute to data collected by organisations, digital platforms, apps, and, increasingly, artificial intelligence – with and without their knowledge.  

The skills of data scientists are in demand. Data science is increasingly seen as an essential skill for lots of jobs. Demystifying data science is an important step in helping spark an interest in the subject. Hopefully, it will increase the number of young people interested in a career in data science and help more young people engage in data and coding.   

Data science appears in many parts of the English, Northern Irish, Scottish and Welsh curricula – including geography, science, mathematics, computing, ICT and understanding the world, as well as health and wellbeing.  

How to demystify data science

When you turn on the TV, you might see discussions about big data, which can feel quite mysterious and anonymous. And yet, big data is relayed to us during things like weather forecasts, presenting information in ways we can all understand.  

Working with data can be broken down into four main activities:  

  1. Collecting – gathering data 
  2. Analysing – asking questions about the data
  3. Interpreting – establishing what the numbers tell us 
  4. Presenting – how best to tell people about the findings 

How to interest children in data science

We can engage more children in data science by making it relevant to them. For example, the playground survey does this by linking the activities to a place that children are familiar with and visit nearly every day.  

It is also important to make data science fun and intriguing. A good way to do this is thinking about how the children can collect their own data, using surveys, counting or measuring (see panel).  

One of the most exciting things about data science is discovering new information. This could be a class project, for instance, investigating biodiversity in the playground or, at the other end of the scale, a big national project such as the census. Asking children about the information they have gathered and what they think it means is an essential in helping them to interpret data. Here are some prompts that will help children think about data:  

  • Does the number make sense? Is the number too big or too small to be real? What is the context for the number? 
  • Do you trust the number you’ve been given? Who collected the data and how did they do it? Do you think it is reliable?   
  • What does the number mean for your own decisions?   

For example, what if you were told your class uses 300 pencils a day? Would you believe this number? If you were told your school uses 300 pencils a day? Would you believe this? What if it was the headteacher who told you? Would that make you trust the information more? Would you trust it enough to decide how many pencils you need to buy? 

Talking about data science

The opportunity to spark a class discussion about information children have gathered, and what they have interpreted, is valuable and reflects part of the role of being a data scientist. There are lots of ways your pupils can do this: 

  • Talking about their findings with classmates or delivering a class presentation. 
  • Writing about their findings or creating a video report. 
  • Sharing information in an assembly (particularly good for larger projects like the playground survey). 

Teaching primary-aged children to think like data scientists might seem an ambitious aim; but, in fact, it’s largely a case of looking at activities you are already doing through a slightly different lens – and in doing so, giving your pupils key tools they will need to successfully navigate the world in which they are growing up. To get involved with the BBC micro:bit playground survey and contribute to a national data set, visit

Day-to-day data examples 

  • Modes of travel to school – How did children travel to school? What was the most popular mode of transport? What was the average distance travelled by different modes? 
  • Biodiversity in the playground – This activity is part of the playground survey. How many plant and animal species are there in the playground? Are there more animals or plants? Were you surprised by your data? Can you see any patterns? 
  • Making predictions – Based on the size of their class, can your pupils estimate how many children are in the school? Or if you have a reward system, can they estimate how many points have been given out in school this week?   

Data exercises 

  • Getting outside – Leaving the school grounds to count items such as vehicles, buildings or animals. 
  • Carrying out a survey – Children could contribute to a survey, for instance, to decide which sport to do during PE. Or they could survey children in another class, e.g. to gather information about school dinners and packed lunches and compare this with their own preferences.  
  • Having physical props to support learning – e.g., counting books and pencils in the classroom, or comparing playground temperatures with the BBC micro:bit. 

Mary Gregory is interim director of Population Statistics for the Office for National Statistics. 

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