Presented by

  • Dr Linda McIver

    Dr Linda McIver
    https://adsei.org

    Dr Linda McIver pioneered authentic Data Science and Computational Science education with real impact for secondary students and founded the Australian Data Science Education Institute in 2018. Author of Raising Heretics: Teaching Kids to Change the World, Linda is an inspiring keynote speaker who has appeared on the ABC’s panel program Q&A, and regularly delivers engaging Professional Development for Primary, Secondary, and Tertiary Educators across all disciplines. A passionate educator, researcher and advocate for STEM, equity and inclusion, with a PhD in Computer Science Education and extensive teaching experience, Linda’s mission is to ensure that all Australian students have the opportunity to learn STEM and Data Science skills in the context of projects that empower them to solve problems and make a positive difference to the world.

Abstract

There's a lot of talk about boosting the pipeline. About getting more women and non binary folks into tech in general, and Data Science in particular. But as long as we focus on recruitment and, at a pinch, university education, as means to address the problem, we will continue to fail. We need to bring Data Science into schools from the very beginning, but I have good news and great news. The good news is that we are already building data science into education, and kids are loving it. The great news, though, is that Open Data gives us the power to give kids powerfully meaningful and engaging projects, and school Data Science gives us the sheer people power to solve serious data problems at the same time. We all know there's more data out there than the field of Data Science could analyse even if we collectively forego sleep and food forever, but if we stop giving kids textbook datasets that teach them nothing meaningful about using Data to understand and change the world, then we can throw kids raw, messy, and above all REAL data and challenge them to make sense of it. What if we taught probability using gender pay datasets instead of black and white balls in an urn? "Charlie is a non binary software engineer. Given that they have been working in the field for three years, what is the probability they are receiving the same pay as James, a cis white man?" But, of course, we need open pay data in order to run that project! When we give kids real things to do, and the power to create change, they see the purpose of tech & data science skills, and are eager to learn. Black and white balls in an urn don't have nearly the same impact. The more open data we have, the greater the potential for projects that empower kids to make real change in their communities. YouTube: https://www.youtube.com/watch?v=0KyQwgJR3fw LA Archive: http://mirror.linux.org.au/pub/everythingopen/2023/clarendon_room_a/Wednesday/Raising_Heretics_on_a_Diet_of_Open_Data.webm