When I founded the Australian Data Science Education Institute in 2018, I was really excited about using authentic datasets and meaningful problems to engage kids with STEM skills, particularly programming. The deeper I go into this work, though, the more I realise that the value of meaningful problems and real datasets is not that it motivates kids to learn to code, although it does. It’s not that it shows them that STEM is something they can do, although it does. It’s not that it gives them a reason to engage with skills they might have thought were not relevant to them, although it does.
It’s that working with real problems means there’s no perfect solution. There’s no answer in the back of the textbook. Kids who work with real data have to first ask “what’s wrong with the data?” and then “what’s wrong with my solution?” – because when you work with real data there’s no such thing as a perfect dataset, and when you solve real problems, there’s no such thing as a perfect solution.
Suddenly kids are not working on neat, textbook problems to pass the subject, or even to get 100%. They are working on complex problems in their own communities that don’t have neat solutions, and they have to develop critical thinking skills to figure out all of the ways their solutions aren’t perfect. Especially if they get to implement their solutions and systematically evaluate the results.
This is game changing. Imagine if government programs, or flavour of the month business or education fads, came with critical evaluation built in by default. Imagine if every solution proposed came with a substantial list of pros and cons, and realistically identified the people who would be helped by the solution, and the people who would be harmed, as well as what the help and the harm would look like.
This is the world we can build if we normalise teaching kids by empowering them to solve real problems in their own communities, and if we focus on skills like critical thinking, ethical and creative problem solving, and compelling communication.
When I wrote Raising Heretics: Teaching Kids to Change the World, I set out to talk about the value of Data Science Education. It’s interesting to see the word cloud that appeared when I fed the whole book into a word cloud generator. The most important word there is not data, or coding, or even science. It’s Students. The emphasis in this word cloud is not on technical skills, it’s on people. And that’s what Data Science is about, when you get down to the crux of it. It’s about people. About purpose. About meaning.
ADSEI also produces a podcast, Make Me Data Literate. I did a word cloud of that, using transcripts where they exist, and the quotes I highlighted from each episode where I haven’t yet created transcripts. It’s equally evocative. Note that some of the keywords are people, think, and things. Because Data Science is meaningless without context.
You’ll notice that statistics do make an appearance, but they are just a small part of a large and complex whole. There’s nothing technical in there. Nothing beyond the reach of people who aren’t trained in data science. Everyone can work with these ideas.
That’s the essence of the work we do at ADSEI. We’re changing education to empower kids to solve real problems using Data Science and STEM skills. Project by project, we’re raising a new generation of heretics to change the world.
If you’d like to support us in our work, you can donate at https://givenow.com.au/adsei
For more about data science education, listen to Raising Heretics: the podcast, or buy the book on paper or as an ebook.
For fascinating data stories from a host of different disciplines, listen to Make Me Data Literate Podcast.
And have a safe, relaxing, and above all kind holiday season!