Welcome to Pitch Your PhD – Shownotes

Season 1, Episode 9

Teaching Programming with Dr Linda McIver

Dr Linda McIver is a pioneer in authentic Data Science and Computational Science education, who is also the founder of the Australian Data Science Education Institute and author of Raising Heretics: Teaching Kids to Change the World.

And there is absolutely no reason we can’t be teaching programming in the context of real problems and actually getting the kids to solve issues and problems in their own lives, in their own communities, in their own schools, doing something real, doing something where they can see the value. 

In this episode, Linda spoke to Catherine in detail on her PhD journey that led her to finding how she can engage with students when teaching programming and how she would like to create an impact  through her teaching STEM skills to solve real life problems in the world.

This is a “kind of, sort of, vaguely close” copy of the words from this episode.

IT IS NOT 100% accurate.  We are very sorry if we have spelt something completely incorrectly.  If it means a lot to you to have it corrected, email us at mel@ramaley.media

Pitch Your PhD- Linda McIver

[00:00:00] Catherine: Hello and welcome to pitch your PhD. My name is Dr. Catherine Ball. Our guest today was a terrible student growing up. She was unmotivated, unfocused. Didn’t know how to study and really did not see the point. But as is the case of just about everyone I’ve spoken to so far on this show, when you follow your interests and your passions, life turns out pretty well today on Pitch your PhD, I’m joined by the amazing Dr. Linda McIver after high school, Linda followed her interests and did an undergraduate degree in biology. But in the first year of her degree, she had a spare elective to use a square to spare, one might say. So on a little whim. She selected computer science, which was completely left of field, but it can be funny where the smallest whim can lead us. After finishing her undergrad, Linda backpacked around Europe and landed a job at a software company.

[00:00:56] And while that job did not work out, it continued the [00:01:00] nudge towards computers science. Back home, all her friends were doing honors and post-grads and in a great example of peer pressure, they convinced her to come back to university where she managed to get herself onto an honors course, studying computer science, knowing a career in the software industry held no real interest for her. Linda started thinking about a life in academia. Linda, welcome to pitch your PhD.

[00:01:26] Linda: Thanks Catherine.

[00:01:27] Catherine: I have been looking forward to this conversation for many, many, many weeks, knowing that we were going to drag you onto this podcast to talk about your journey. So I’m going to fan girl over you for a little bit, but let’s just, let’s start with something that I’d like to actually, ah, I actually wanted me to disagree with this.

[00:01:43] You weren’t a bad student, surely were you?

[00:01:46] Linda: I was, I was a shocker. I did the absolute minimum. I, you know, was disengaged. I didn’t study. Didn’t know how to study it. Didn’t particularly want to know how to study, just kind of coasted through. And I was lucky to have [00:02:00] a good enough memory that I could coast through and do okay. So I could never really see the point of, trying, cause I just didn’t have anything to try for.

[00:02:09] Catherine: It’s interesting. Isn’t it? I was the reasonably the same too that in primary school and secondary school, it’s just so easy to see. You don’t have to try. And then when it starts getting harder, cause you’ve had it so easy all of that time, you’ve almost, you don’t know how to push yourself to learn because it’s always been just a walk in the park.

[00:02:22] Linda: Yeah. And it’s a problem, that I saw when I was teaching for really bright kids that, you know, as when they hit something they can’t do it’s catastrophic. So the earlier they hit that, the better. To learn how to deal with that.

[00:02:36] Catherine: And so for you finding what you really care about was a bit of a windy, windy journey. So, I mean, your journey was like many, actually that I’ve spoken to you start off down one path, you think about one thing and then suddenly left a field. You’re sucked into this vortex of inspiration. So tell us a bit about your pathway from undergraduate through to PhD.

[00:02:54] Linda: So, as you said in the intro, I didn’t intend to do computer science. I intended to do a degree in [00:03:00] biology. In fact, my interest was genetic. and I did this one, elective and in first year in computer science and, I still don’t quite know how it happened, but by third year computer science was the only thing I was studying.

[00:03:13] I know I kind of, I didn’t want to go on with genetics because they were going on to do plant genetics. And I was interested in bacterial and human genetics, but that seems like a pretty shortsighted reason to make a decision. So anyway, I was really interested in, the more, advanced bits of computer science, artificial intelligence, and natural language processing and image processing.

[00:03:34] And I found all those really fascinating. by the end of it though, I had really still no idea what I wanted to do.

[00:03:40] Catherine: I’m still not quite sure.

[00:03:45] Linda: Well, I would say I found mine at about, uh, about my mid forties. I found mine. So you got some time? yeah, I, I was offered, I mean, the intro pretty much covered how I wound up doing honors. and it’s [00:04:00] important to note, I didn’t get the marks to get into honors, so I had to kind of break the door down and, and that’s a really important lesson because.

[00:04:07] You can do the things you want to do, even if at first you get blocked in some way, so you don’t get the marks so you don’t hit this or that criteria. There are ways you can find the ways, you know, sometimes there’ll be an extra year of study or sometimes it’s just a matter of knocking the right door down.

[00:04:22] And I was lucky. I had support from a few people kind of on the inside, a few friends who were already doing the PhDs and who put the hard word on their supervisors to help me out. so, you know, again, I did honors and I really enjoyed it, but I wasn’t super motivated. I still sort of didn’t see where I was going.

[00:04:42] And when you don’t see where you’re going, it’s hard to rush to get there. You know, there’s no, no real reason to, to work hard when you don’t know what you’re aiming for. And then I was very lucky at the end of my honors degree because Damien Conway, who at the time was an academic, offered me a project that I thought was just [00:05:00] fascinating.

[00:05:00] And I also really wanted to work with Damien because he’s amazing. And the project was to design a programming language to make learning, to program easier and that fascinated me. And I didn’t really have a. Uh, goal for doing a PhD. At that point, it was just like, this is a really interesting project.

[00:05:16] Let’s give it a go. I got, uh, a scholarship to do it, and it was not one of the prestigious scholarships. It was a departmental kind of the scholarship they offer you when they want you to come in, but you know, you didn’t really make it to a real scholarship. So, you know, I was never, never one of these outstanding, amazing performance.

[00:05:34] and then the PhD was a wonderful experience, but the one thing that I learned more than anything out of that PhD was that a programming language, especially for teaching programming was exactly the wrong thing to do. Um, Kids don’t want to learn toy languages. They don’t want to learn for the purpose of learning.

[00:05:51] They want to learn for the purpose of doing something real and actually learning a toy language is quite de-motivating because they can’t see the point because they can’t apply [00:06:00] it to real problems. And that was the Genesis of my entire teaching philosophy. And, you know, the whole reason I started to stay in Data Science Education Institute and everything, it was just like, that was the seed, which is motivation matters more than anything and doing something real is how you get motivation.

[00:06:19] Catherine: I need that on a t-shirt

[00:06:21] okay. So let’s have a look back at your PhD. So where you are now is flying high. And obviously when you do a PhD, you don’t necessarily see how well you’re going to come out of the end of it, because I love one of your quotes here that starting a PhD is easy, but finishing a PhD is hard.

[00:06:37] Catherine: Tell us about your PhD journey.

[00:06:39] Linda: So mine was a bit atypical, a low, I suspect all PhD journeys or atypical one way or another. I got very sick a couple of years into my PhD. I’ve got chronic fatigue syndrome. And so I was unable to work for a significant portion of time. And when I was able to work, it was kind of only part-time. I was exhausted all of the time and I [00:07:00] had this terrible brain fog.

[00:07:01] It was really hard to think it was, you know, what we call now long COVID I had that only for a different virus. so it was tough and it slowed things down a lot, but, What I felt by the end of the PhD, it became clear to me that what you really needed to finish a PhD more than anything.

[00:07:18] You know, you’d say to people, I’m doing a PhD in computer science, they go, oh, you must be so smart. really what you have to be is, bloody-minded and persistent, like that’s, that’s what it takes to finish a PhD. It’s not about wild intelligence. It’s about just toughing it out because you do the fun part, which is finding out, developing the thing you want to develop, finding out the things you want to find out, and then you have to write it up that is torturous or can be, uh,

[00:07:47] it depends on the support that you have, but it also depends on, you know, what you’re trying to say and figuring out what you’re trying to say after you’ve done this really deep dive into a topic and got really embedded in it is actually extraordinarily [00:08:00] difficult.

[00:08:00] Catherine: Yes. I mean, I have mentioned in previous podcasts, that I call my PhD, my permanent head damage. Um, because again, it comes down to the tenacity to finish rather than the intelligence around asking the question. And I remember the typing, the the hours and hours of typing and what we could have done if I’d had like told to type, you know, the whole end note.

[00:08:20] Did you have end note as part of your thesis writing?

[00:08:22] Linda: No, I did not use end note. I was, um, I did it all by hand, which was a mistake.

[00:08:28] Catherine: Oh, I had to do it by hand at the end, because I’d moved between two different versions of word and, oh my gosh. .

[00:08:33] Catherine: So you mentioned that you’ve had a few hard times during the actual PhD journey, some health issues. And, um, what other obstacles did you kind of experience once you’ve landed the PhD and got going. were there any of the obstacles that you experience.

[00:08:46] Linda: Oh constantly. one of the biggest obstacles was inside my own head. I’d read a paper that was really good. And I’d be like, oh my God, I can’t possibly equal this. I’m a disaster. And, you know, throw myself off the metaphorical cliff. This is hopeless. I’m not [00:09:00] good enough to do this. That was my biggest, um, My biggest obstacle was, and that I kept having to overcome that, you’d beat it to the ground.

[00:09:08] And then a week later you’d have to beat it to the ground again.

[00:09:11] It was. Everything. Every obstacle I came up with my head would tell me, see, this is proof that you can’t do it.

[00:09:17] Catherine: Imposter syndrome.

[00:09:18] Linda: Big time. And I’ve still got that, you know, I, I’ve often said that people who don’t the only people that don’t get imposter syndrome are a sociopaths

[00:09:26] Catherine: Yes,

[00:09:27] Linda: I think it’s a natural kind of, self-doubt. You know, anyone who cares about what they’re doing is going to doubt themselves sometimes. But the trick is not to let it overwhelm you. And I could have walked away so many times and my best friend also was killed in a car accident, partway through my PhD and that, um, that was a rather derailing as well. Uh, Yeah.

[00:09:51] it was quite the time, my twenties, um, but you know, I was really lucky. I, I got married quite young and So all of those [00:10:00] experiences I was, living with with my husband, who’s extraordinarily supportive and, you know, just he’s my rock. So, like I said, it’s, bloody-minded persistence that gets you through. It’s not any particular intelligence. I don’t think.

[00:10:13] Catherine: So there were dark times, but they were good times as with all things. I find PhDs to be quite so positive. I’d probably quote, um, Dickens actually is the best of times. And the worst of times, isn’t it. Inside your PhD sometimes. Um, so what were the most rewarding parts of your PhD? When did you really kick imposter syndrome up the, you know, proverbial and, and really get on.

[00:10:32] and what did you enjoy about your PhD?

[00:10:35] Linda: It was the moments when I felt likeI’d really uncovered something, you know, when I’d found out something new and I realized something important. so I was, doing a lot of tutoring at the same time as I was doing my PhD and towards the end, I was also doing a lot of lecturing. And when I felt like I’d had that connection with the students, and then I could tie that back to the educational parts of the PhD that was.

[00:10:57] That was the bit that always drove me. And, [00:11:00] you know, when I look back now, I can say that looking from the outside, it probably would have been easy to tell that this person was going to go and actually be a teacher, not just an academic, you know, there was a progression here that was inevitable, but I didn’t know it at the time.

[00:11:14] Catherine: You mentioned your PhD supervisor and you’ve mentioned your husband and they are, two absolute, magnets when it comes to direction through your PhD, right? So you can either have a good PhD supervisor or a bad PhD supervisor, and I’ll let you, uh, fill the gaps in on my experience there.

[00:11:29] But who was the most helpful or inspiring person for you on your PhD journey?

[00:11:34] Linda: That would have been Damien. Yeah.

[00:11:36] He was not that much older than me, but he was definite father figure, you know, academically, but also personally, he became a really close friend and we’re still in touch today. and you know, a lot of people when they’ve finished, their PhDs would rather stab themselves in the eye with a fork than ever speak to the supervisor.

[00:11:51] So I’m very aware of how lucky I am. But, Damien was so amazing and we’re still such good friends and he was, he had such [00:12:00] faith in me, right from the start, even offering me the PhD when I wasn’t, one of the standout, candidates, he could see something in me that I couldn’t s ee and I don’t think anyone else could see at the time either. you know, I’ll email him now proud about something I’ve done and he’ll email back this amazing. That’s great about how fabulous I am. And it’s just, you know, he’s still wonderfully supportive and encouraging and just a beautiful human being.

[00:12:26] Catherine: Did you ever ask him what it was that he saw in you?

[00:12:28] Linda: No, I didn’t. I’m not going to email him today.

[00:12:32] Catherine: Sometimes I think we have like fairy godmothers and godfathers, don’t we? . So you know how you go into schools and you see future Linda McIvers may be, he saw a future Damian Conway in you.

[00:12:43] Linda: maybe he did. And, uh, that would be quite the compliment I have to say.

[00:12:47] Catherine: Well, there you go. I feel like a needs to be had today.

[00:12:51] Linda: I think so I was also really lucky in that I shared an office with a bunch of really, supportive and encouraging guys. and we [00:13:00] were quite quite the team. So the guys I shared an office with were doing completely different things with different supervisors. So it wasn’t really a research group, but I kind of battened on towards the end of my PhD to a different research group, which was the, uh, at the time I think it was called the constraints and diagramming group.

[00:13:15] And we did a little bit of work together, which is how I started to connect with them. But, they had a really good culture. They. They went out to lunch together every day they would socialize from time to time and they, you know,  they built that human connection as well as the research connections. they were all like, it was a family in a lot of ways.

[00:13:36] And that is something you don’t see enough in, particularly in computer science faculties, where, academics can be quite the lone wolf. and not necessarily as sociable as you might like, but that building of a supportive human connection, as well as the research ideas is I think is fundamental to getting through the PhD because, you know, life will throw things at you, and the PhD [00:14:00] will be hard and you need to feel like people around you have got your back. And will listen if you’re having a tough day and all that kind of stuff. And that was, that was really important in getting me through as well

[00:14:10] Catherine: Yeah, the culture of the PhD group is quite an interesting one. I’ve seen all shades and all rainbows of that. Um, it sounds like you’ve had a wonderful experience of a PhD supervisor and a wonderful culture in your office, which is amazing.

[00:14:21] Catherine: So when we look back at your thesis, what are the things that you have found have helped society most, or have evolved along time and actually are really applicable even now so many years after you finished your thesis.

[00:14:34] Linda: So the thesis title was syntactic semantic and social issues in introductory programming education, some versions of the title drop the and social part, but I think it’s important and the things that really came out of it. as I said before, motivation is number one, the idea that almost doesn’t matter what language you use, as long as the kids feel like they’re doing something real that will overcome all obstacles, which is not to say that you can’t make it [00:15:00] easier with your language design, if you, you know, the designers of Python and C++ and Java and all those kinds of things could learn a lot from, the human factors of programming. Unfortunately, it’s an area where the research doesn’t necessarily connect well with the practice.

[00:15:16] One of those things where everybody thinks they know what needs to be done, and no one’s looking at the research, Yeah.

[00:15:22] I think really motivation is the big one. The idea that, I think all kids can learn to program, this idea that it’s some kind of magic skill that only some people can access is just nonsense.

[00:15:34] It’s the latest nonsense. And it’s kind of trying to make those of us who could already program feel better. I think anyone can learn to program, but they have to want to.

[00:15:42] Catherine: It’s like, why do we still allow these elitist terminologies to almost stop people from accessing it in an egalitarian way?

[00:15:49] Linda: It’s a form of gatekeeping.

[00:15:51] Catherine: But the thing is why would we want to gatekeep? What could actually help progress society

[00:15:55] Linda: Well, I think it’s also a form of bonding. It makes us feel better to be part of [00:16:00] the group who understands this stuff. You know, it makes us feel special. it’s a kind of, building a, a family around the people who understand this stuff and the people who don’t there is something in human nature that wants to draw those lines that people like us, and then people who are not like us, and this helps identify the people like.

[00:16:17] Catherine: So your PhD obviously, um, had a multifaceted positive effect overall on your life. So how does it continue to add value to your work and who you are and what you do today

[00:16:28] Linda: Yeah, that’s the interesting thing. Everything in my life has given me something which supports the work that I’m doing now. So, after my PhD, I went straight into lecturing. So I was an academic for, over 10 years. And then we had a big round of redundancies offered and I wasn’t going to take one, but I was, my second child was due and there was going to be, you know, the same amount of work to do, but two thirds of the people to do it and all that kind of stuff.

[00:16:55] And so I wound up taking a package. And I did have a whole range of things in that [00:17:00] time. I was, a project officer for the Australian breastfeeding association. I did some pro bono communications work for Oxfam Australia. I did freelance writing. I just, I did a lot of different things. And then, when the opportunity came up to get involved in the school that there was this new school starting up, John Monash science school and they wanted to develop a totally new computer science curriculum for it. And so I got involved in that and within a year I was actually teaching at the school and I realized that I had found where I wanted to be, but everything that I had done up to that time fed into you, making me a much better teacher than I would have been, otherwise. I had all of this life experience, but also all of this communication experience and, all of the ideas in my PhD around teaching, you know, I was suddenly actually able to put them into practice.

[00:17:51]  And then, Looking back now I can see that every career move has been an attempt to, to have more impact. So I was doing [00:18:00] computer science, education research, but I didn’t feel like it was translating into the classroom. So I went into the classroom and then from the classroom, I realized that I had figured out how to teach kids STEM and how to get them engaged with STEM.

[00:18:12] And that’s what we were talking about before with doing real things, you know, actually teaching STEM skills as tools that you can use to fix problems in your own life and in your own world. And when I figured that out, I realized I wanted to get that out to everybody, not just to the kids in my classes. And so that’s why I left teaching and started the Australian Data science Education Institute. And at first I looked around and I was like, I’m going to find who’s doing this kind of work and I’m going to join them and we’re going to make it happen. And I looked around and I looked around and that just, no one was doing it. So I had to start my own organization.

[00:18:47] Catherine: Hmm, I can relate to that so hard. So

[00:18:49] Catherine: and I might say something controversial here. Would you agree with me if I said to you that when we look at how we teach coding in schools, I actually am a believer that it should be taught in a language [00:19:00] classroom, not a STEM classroom,

[00:19:02] Linda: That’s an interesting concept. I haven’t thought about that before. Um,

[00:19:07] Catherine: because

[00:19:07] Linda: I mean, It is a language and it’s a way of thinking and it’s, you know, it’s almost a different culture that has potential, but I actually don’t, I don’t think it matters who teaches it or where you teach it. I think it matters the context.

[00:19:21] What are you giving the kids today? And there is absolutely no reason we can’t be teaching programming in the context of real problems and actually getting the kids to solve issues and problems in their own lives, in their own communities, in their own schools, doing something real, doing something where they can see the value.

[00:19:40] Catherine: Top-notch I would love to ask you, you know, what have we learned about how kids learn coding and kids learning coding languages if they speak more than one language at home, if English isn’t their first language I’ve been told anecdotally that actually makes them better code writers, better computer language writers.

[00:19:57] If they speak more than one language at home already. [00:20:00] Have you seen that in your work?

[00:20:01] Linda: That’s so interesting. I have not seen any research in that and I haven’t sort of been looking for it. I wish you’d said that to me when I was teaching. Cause I might’ve looked for it. but one thing that we do know is that the first language that people learn for coding really shapes the way you approach coding and your attitude to coding.

[00:20:18] There are so many different programming paradigms where you can learn functional programming or object-oriented programming or procedural or logic programming and all of these different styles of programming change the way you perceive programming and the way you try to solve problems. we’re very much, you know, my supervisor Damian was very keen on the.

[00:20:38] Um, on the saying to a man with a hammer, everything looks like a nail. and when you give people a programming language, you’re giving them a style of tool they, then that’s what they apply. You know, that’s how they choose to solve their problems.

[00:20:50] Catherine: I need that on a t-shirt as well. .

[00:20:51] Catherine: So, when it comes to learning a programming and learning code, are you seeing a difference in the generations in school now we’ve got digital natives. I mean, you and I are digital immigrants [00:21:00] and we’ve got digital natives now that are born with a while. If they’re privileged enough, they’re born with a computer in their mouth.

[00:21:05] I mean, that’s not all of the children in Australia and we know that there’s a huge digital divide coming. What are you seeing in terms of patterns and what have you learned from when you studied this and inside your thesis, in terms of the socialI’m really glad that you didn’t drop that the social aspects of learning and your primary coding language

[00:21:20] Linda: I think the interesting thing here is that, we have this term digital natives and yes, these kids have been playing games and they’ve been texting and they’ve been, on Instagram and Snapchat and all the rest of it. It doesn’t mean they understand anymore about technology. and what we have seen is that the gender divide in kids choosing technology is actually, if anything, magnifying, it’s certainly not getting any better and the messages that are being put out about girls just aren’t interested in this are getting stronger and stronger and louder and louder girls can’t do this. Girls aren’t good at this. Girls aren’t interested then naturally interested in biology. [00:22:00] Just that drives me insane when I hear that, Um,

[00:22:03] it’s just not offered the same opportunities and they’re not giving the same toys and they’re not given the same chances. So, what I see in classes is that kids are terrified of programming. They think it’s something that they can’t do. And when they come in believing it’s something they can’t do, that’s a massive barrier that you have to get over before you can actually get them learning. Anyone can do it. But you have to get past the fear factor and you have to get the motivation. And I find the same with teachers. So now I teach teachers rather than students. And if I market my workshops as data science workshops, I get no signups because data science is terrifying.

[00:22:38] If I market them as STEM workshops, then they come and then I can teach them data science because actually data science is easy. Data science is collecting data, analyzing data and communicating data. And anyone can do that. I have five-year-olds doing that.

[00:22:53] Catherine: some statistics that I’ve been peeling back, the layers of as I’ve been writing the book I’m currently writing, was one of them was by [00:23:00] 2022, which is effectively next year, 70% of global GDP will be digitized. It will be digitalized or digitized in some way, shape or form. Then when we start talking about things like artificial intelligence and machine learning, which are different things that people think are the same.

[00:23:16] and we look at how data is being collected. I will say data cause I’m British at how data’s being collected. even on the smart devices, even on the software we’re using right now, that information is being captured, how we’ve got we’ve got audio, deep fakes, video deep fakes. We’ve got fake news.

[00:23:30] We’ve just got fakery everywhere. There’s something that needs to be done around digital and stem literacy. And I’ve said this before, and I hope you agree with me that, STEM literacy is a human right. Like digital literacy is a human right. We should be able to decipher, digest, disseminate, and also disagree with everything that we see.

[00:23:48] How do you feel? Oh, thank you

[00:23:51] Linda: 100%. One of the big issues that we have is that we have these companies that big FAANG [00:24:00] as they call it Facebook, Amazon, Apple, Netflix, and Google. There are others as well, but you know, in companies like Uber, which are changing the way our society works, the way our lives work. And we have no say in that.

[00:24:17] And as long as we don’t understand data science and we don’t understand STEM and we don’t have enough technological literacy, to be able to say, “hang on a minute, this isn’t the way we want this to go. We would like to have some say thank you in the direction of our society”. We need to be able to challenge them when they go, “ah, That’s too hard. We can’t do that technologically”.

[00:24:39] Most of the time they actually can. They’re choosing not to, but you have to have the literacy to be able to turn around and say that golden, hang on a minute. You have to do better than this. This is you are taking away our job security, it taking away our working rights on out, you know, all of these hard won entitlements.

[00:24:56] You’ve just thrown them away. Maybe we want them back. Maybe we want [00:25:00] to say this is not The way we want to go. Yes. We love to be able to get our takeaway delivered any time of the day or night, but there are things we’re not prepared to sacrifice to do. So we’re not even having that conversation yet. And we need the literacy.

[00:25:14] Catherine: The literacy, absolutely key star, a scary statistic. I’d love your opinion on this. The Australian Institute of company directors did some research earlier this year, where they worked out that fewer than 3% of all company directors in Australia have formal STEM skills

[00:25:29] Linda: It doesn’t surprise me at all. I did some research for the book, for my book, where I looked at, the background of, politicians and terrifying proportion of them come from, business, legal and lobbying backgrounds. There are so few that come from any kind of stem discipline and have any of this technological knowledge.

[00:25:46] And we’re seeing that. the impact of that in our response or lack there of, to climate change in our, wildly varying understanding and capacity to deal with COVID, it’s a massive, massive [00:26:00] problem. And if everyone had STEM skills, if everyone had STEM that your say, and in particular data literacy say that would be a radical change to the way we approach these kinds of problems.

[00:26:12] Catherine: Now there’s a controversial example, X it involves a controversial politician. Somebody who I would say doesn’t sit within my political persuasions, but there may be people listening to this podcast, which it does. Was that a person who was prime minister of the UK in the 1980s, Margaret Thatcher, she actually led the global sort of political movement against CFCs because she understood what CFCs were doing to the ozone layer because she had a chemistry degree. So she was a scientifically trained politician that understood what CFCs were doing because she was a chemist. And so, you know, when we look at climate change now, and we know that the physics of climate has not changed its fundamental understanding of how the climate works has not changed since the year I was born, 1979.

[00:26:55] There’s no debate around how climate is moving and how the climate is changing. [00:27:00] And yet we have this inertia. We have a boundary layer of inertia just underneath and also encompassing our senior most senior politicians. Do we need to do stem for moms and dads?

[00:27:11] Do we need to produce some sort of stem education for parents? I mean, you talking to the teachers in that having a bigger effect than talking to the kids. Have you talked the parents?

[00:27:20] Linda: Well, I think this is part of what my book is trying to do, which is to get the idea across that these skills are they’re not. You know, we teach them in schools as a matter of toys and we teach them as a matter of fact and right answers when actually science is constantly evolving. You know, one of the issues we’ve had with COVID has been people saying, Oh, you keep changing your tune.

[00:27:43] Therefore, you don’t know what you’re talking about. And we’re like, no, this is science working science should keep changing its tune. As it gets more information, it’s got to update the hypothesis and respond to incoming information. That is the nature of science, but it’s not the way we teach it.

[00:27:58] and so the book is a patch [00:28:00] to change the education system, but it’s also, a manifesto if you like for adults to go well, hang on. What you’ve been taught is not necessarily what you needed to know.

[00:28:11] Linda: So the book’s called Raising Heretics, teaching kids to change the world. And it really stems from this idea that kids can learn STEM skills in the context of problems where they’re actually solving problems in their own lives and their own communities. And they using STEM skills to affect positive change in the world.

[00:28:29] But it’s also one of the most crucial ideas that’s come out of the work I’ve done with without say, is that teaching kids using real problems means that there is no right answer. So you can’t just look it up in the textbook or take it to the teacher and get a ticker across you can’t get a hundred percent.

[00:28:46] What you get is you get a solution to a real problem, and then you have to evaluate your own solution and say, How good is it? Why does it work? Where does it fail? Who does it help? Who does it harm? Now imagine if we [00:29:00] routinely asked those questions about programs that we implement in the real world.

[00:29:03] Imagine if the government implemented a program to imagine if robo debt had been in, it had been evaluated that right. And they looked at it and said, who’s it help? Who does it harm? and these, we routinely evaluate the outcome of our own solutions. And if you learn in school that, there is no right answer.

[00:29:21] There is no such thing as a hundred percent there’s this works or this way, it doesn’t work in that way, can be improved. That’s true of all situations in the real world, but it’s not the way we teach kids. So imagine the difference in the world. If kids came out of school already, knowing that real problems don’t have perfect solutions and every solution can be improved and every solution must be evaluated.

[00:29:46] That is, I think, nevermind the data science nevermind the programming. That is one of the most important things that I’m teaching here.

[00:29:54] Catherine: I’m nodding so much. I think my head might fall off my neck. think [00:30:00] what’s your well, I mean, the title, raising heretics for me, I thought it was fabulous. Can you walk us through how you chose that title and what does it actually mean?

[00:30:08] Linda: So here’s the thing you need to know about me. I’m terrible at naming things. I’m a long form writer and I write quite well long form, but I’m very bad at short punchy things, but I was having coffee with a friend once back, when that was something we could do and, um, I was explaining to her what I do, if it was a friend from school and we hadn’t caught up for a while, so she didn’t know what I was doing.

[00:30:28] And I didn’t explain that it was teaching kids critical thinking and, you know, teaching them to challenge the status quo and question orthodoxy. And she said, oh, so you’re raising heretics then. And I just rocked back in my seat. I was like, that is, yeah. That’s perfect. I love that. And I developed a talk around that, which listed all of these scientific heresies that, you know, that changed the world.

[00:30:50] Like, everything from Galileo figuring out that the earth revolves around the sun through to Barry Marshall, drinking, Helicobacter, pylori, uh, Alice [00:31:00] C. Evans, finding out that you have to pasteurize milk to prevent people getting sick, you know, all of that kind of stuff. And, uh, that was the seed of the book

[00:31:08] Catherine: Would you call yourself a heretic?

[00:31:10] Linda: Oh, absolutely.

[00:31:11] Yeah. a heretic and a troublemaker. I have a friends that I have regular coffees with and we call ourselves the unbossables. I think it’s really important. You know, I use the word in the book and like, we need unbossiables. We need heretics. We need people who go, okay. We may have always done it this way, but do we have to, maybe there are better ways.

[00:31:32] Catherine: We need the rebels. We need the outliers. We need the people that sat outside system and think differently. Some people might say that the school system isn’t built for that, the school systems like a sausage factory, you go in, you get broke ground up and then you’ll get spat out and look exactly the same.

[00:31:45] Would you subscribe to that notion?

[00:31:46] Linda: Absolutely. That’s. I mean, that’s the central point of the book, which is that the way we teach education teaches kids to get the right answer, teaches kids, to use the expected technique, to do things the way they’re taught to do them, to do things the way [00:32:00] everyone else is doing them, where we’re producing with our education system.

[00:32:04] We’re producing kids who are very good at setting down, doing what they’re told and doing the same as everybody else. One of the bits of research that I discovered while I was doing my PhD, which has stayed with me because it’s so horrifying and illuminating as that four year olds are very, very good at thinking out of the box.

[00:32:22] They’re very creative. They come up with solutions that are left of, out of left field and the whole thing, as soon as they start school that drops off and it plummets very, very quickly. School is training us not to be creative, not to be heretical, not to be difficult. And quite frankly, we need some very difficult people right now.

[00:32:41] Catherine: Oh, gosh, we need some difficult people right now. We just need some people that recognize that they don’t have all the answers.

[00:32:47] Catherine: Where can people find more about you and about the book? Where do we send them to?

[00:32:51] Linda: Straight to the Australian Data Science Education Institute website. So that’s adsei.org, A D S E I and that you can find the book there and you [00:33:00] can find all about the work that we do and ways to donate to the charity.

[00:33:04] Catherine: So, I could just chew the fat with you for hours and hours, but I guess fundamentally my career path wouldn’t be what it was without my PhD. Would your career path and where you are now, would you be where you are now without your PhD?

[00:33:17] Linda: No, I can’t imagined getting here without the PhD. Like it was the cornerstone of everything I went on today, taught me so much and it was torturous and it was painful getting to the end, but that taught me something as well. that taught me that, you know, I was watching people around me dropping out and it taught me that I could actually stick it out and I could, I could persist and I could do something big and I could do something difficult.

[00:33:42] And it’s the cornerstone of everything I’ve ever done. It’s all like every step in my career has been, has taken everything I’ve done before and sort of refined it into something that I can use to, to have impack

[00:33:54] Catherine: Nevertheless, she persisted. Thank you so your time today, Linda,

[00:33:59] Linda: It was wonderful [00:34:00] to talk to you,