Raising Heretics – why should we?

This is an excerpt from the Introduction to Raising Heretics: Teaching Kids to Change the World, which is due for publication on August 1st. We’ll publish more excerpts here from time to time, so check back for more!

In this book, I want to show you how Data Science Education is key to nurturing a rationally sceptical, creative, ethical, problem solving population who can save the world.
I’m going to do that by looking at the problems we have in the Data Science and Technology communities today, and how those communities are shaping our world – problems and all – in Chapter 1: “Who’s in Charge?”

Given that Data Science is in the driver’s seat, taking us towards a future we are not yet equipped to understand, Chapter 2: “The Shape of the Future”, talks about what the future could look like if everyone had enough data literacy to form evidence based policy, support high quality science, and have a say in the shape of our future.

Of course, if we want an evidence based society that treats science with respect, we need to understand how science actually works. Too often a change in our understanding of something – whether it’s climate change, a virus, or our diet – leads us to think that science got it wrong. Scientists, however, know that this is how science progresses; by improving our understanding of complex systems. That means that sometimes what we think we know about science today turns out to be wrong tomorrow. This is science at its best. Unfortunately there is a perception in the wider community that science is solved. And science education reinforces that idea quite firmly. Chapter 3: “Science is Solved”, looks at the way we (mis)understand science, and how we can fix it.

I’m then going to explore the issues with our current education system in more depth. There is no such thing as perfect data, yet we treat data with more reverence than it deserves. Our entire education system is built on the idea of being measurable, yet all too often “measurable” winds up being the opposite of “meaningful”. Chapter 4: “Measurable or Meaningful, pick one,” considers how we got here, and how we can create an education system that focuses on meaningful outcomes, and develops our students into rational, ethical heretics.
All of these goals require us to get comfortable with the idea of uncertainty. To be prepared to challenge the status quo, query accepted wisdom, and even to question our own findings. Chapter 5: “Accepting the Unexpected,” focuses on why uncertainty is important, and how we can get comfortable with it, especially in education.

Why should you take my word for it? Chapter 6: “Projects with Impact,” goes into detail about how Data Science projects work, with case studies from my own teaching, and Chapter 7 outlines templates for Data Science projects involving community projects and more global issues, with examples of units ADSEI has created right across the curriculum, from Humanities to STEM.
Finally, how do we get there from here? Chapter 8: “What now?” maps out what we need to do to overhaul our education system and raise all of our children to be rational heretics, so that they can understand the world, and then save it.

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