Sean Tibor: Hello and welcome to Teaching Python. This is episode 80 Reaching for the Stars with Python. My name is Sean Tibor. I am a coder who teaches. Kelly Schuster-Paredes: My name is Kelly Schuster Perez, and I'm a teacher that codes. Sean Tibor: And today we're joined by a guest that I'm really excited to have on the show. Dr. Becky Smethurst from Oxford is joining us to talk about pretty much everything from the Earth to the stars and everything in between. And maybe we'll even learn a little bit about black holes. And I think the Blobby ones are your favorite, right? The ones that don't spend as much are really interesting. So we're so excited to talk to you, Becky. Welcome to the show. Becky Smethurst: Thanks for having me. Yeah, I was trying to think I'm an astrophysicist two coach, I guess going by you. Sean Tibor: And I'm sure that you do a bit of teaching as well with your YouTube channel, your books. Do you do any lecturing as well? Just pulling random strangers over on the street to tell them about? Becky Smethurst: I don't do any teaching yet. I'm research focused, so I haven't got my hands on any unsuspecting undergraduates yet at the University, but it's more like I get pulled aside on the street or like on trains when you get into conversations with people and it's a three hour train journey. What do you do and you have to make a decision there and then whether to tell physicist because you either get trapped next to them for 3 hours, I'm bombarded with questions or they get up and leave. Kelly Schuster-Paredes: Honestly, do you ever say no? I just work at Tesco. Sean Tibor: I'm an accounter ego for NASA. Just work with numbers all day. Becky Smethurst: Yes. Sean Tibor: Well, welcome to the show before we get too much into our main topic, and I think we have a wonderful conversation ahead of us. We'd like to start where we always do with the wins of the week. And as is our customer going to make Dr. Becky go first. So Becky over to you. Something good that's happened in the past week, inside or outside of the laboratory. I guess wherever that may be. Becky Smethurst: My win of the week was that I have finally done something I've been putting off for far too long, which was responding to something called a referee report. So when you write up your science, one of your colleagues anonymously reads it and comments on it, and then you have to respond and defend what you've done. And I have this one. And I've been selling it for about a month and I finally did it. And I'm like, that is a win that I will definitely celebrate. Kelly Schuster-Paredes: Awesome. Sean Tibor: That's very great. Kelly, how about you? Kelly Schuster-Paredes: Can I still your code? Sean Tibor: Go ahead. Becky Smethurst: Okay. Kelly Schuster-Paredes: So we had this great idea, which was a new assignment after taking the JetBrains course of refactoring and learning how to work with teams. And Sean starts talking about refactoring and clean up spaghetti code. I said, oh, we should write a really easy program. And when I say we I say you I mean, really you we should write a really easy program and put some functions in and make the kids refactor it. And it was really well done. And Sean did an amazing job at it, and it's just a good idea. It was just a great way to really solidify the understanding of print functions with returns and arguments and parameters. And we had probably about, I think, five out of our 30 kids that got it within the first class period, and now they're starting to get it a little bit more. But it was just a neat, higher level assignment, and it was really cool. So I think it was a good one. Sean Tibor: Yeah. In my class today, I had the kids who finished it during the last class period acting as pure tutors, walking around and helping other kids solve it. So I get to kind of listen to the way that they're instructing other students and making sure that they're not just giving them the answers. But they were having a really great time going around and helping them out. And I had to remind them that, no, you can't touch their keyboard, they have to do the typing. But it worked out really well. And I think just that exercise of starting to see code not just as written text that can't be changed, but as the expression of ideas and instructions that you can restructure and rearrange to do the things that you want it to do. I think for at least a good chunk of our students, they got the hang of that and they started to see it happening. So that was really gratifying this week. Kelly Schuster-Paredes: I wish we should have filmed some of that. That was good. The light bulbs are coming, and they're like connection. So that's always a good win. Sean Tibor: So for me, my win this week, since we're not going to do the refactoring, my win this week was the security team that we have on campus drives around on these little Segway motorized carts, and they don't really make those vehicles anymore, and they're not really supported. They don't have spare parts for them. And they had broken one of the handbrake handles on it that was made out of aluminum, and they brought it to me and said, hey, can you help us do this? So I got to employ all of my self taught mechanical engineering skills to model this thing out in CAD and get it 3D printed in one of our innovation labs, and it actually worked. It was so cool. I got it to fit on there, and they can actually stop the scooter now. So I told them, look, don't go joy riding downhill or anything with it, but at least this should work for you. And it was really satisfying to see that fit in place and be functional. Kelly Schuster-Paredes: You missed the rest of the conversation when he left, he was like, I think we should just start 3D printing all of our parts. And I'm like, oh, God, he's a full time job of just reprinting everything. Excuse me? This badge is broken, and you 3D printed. Sean Tibor: It's really satisfying, though. That idea of seeing something that you have created on the screen and made digital and turning it into something that you can hold in your hand is really satisfying. So we're trying to do more of that with our students as well. So they're doing more with programming, electronics and sensors and things like that. And that's one of the things that I'm excited to have this conversation in a few minutes about is how do we take that idea of code and general ideas and turn that into something tangible, something that they can look at and say, oh, I see how this could help me solve real problems. So, Kelly, we won't make Becky go first on the fail of the week. That's usually up to us. Do you have a fail that you'd like to share? Unknown: No. Kelly Schuster-Paredes: I mean, my fail got solved after I was going to do it as a win, but I'm not going to do the win, but I was failing a lot on my codes. I passed it, so that was actually a win, and I was jumping up and down. I finished my course of a 57 hours project. It took me, like, 110 hours instead of 57. Now, I just think the power of I was telling the students I was like, okay, I'm going to run this code, and I would run it. And you even said, I can't believe you're running the code in front of them. I'm like, it could show that I failed. I'm, like, let me do this change. Nope. You didn't pass. You failed this test. So it's like that opportunity just do a lot of failing in front of the students to show them that it still happens all the time. Sean Tibor: Well, my fail is a minor fail, but it's one of those things that is kind of humbling in a small way, like I was leaving the classroom the other day, and I went to go lock the door and without noticing it, my key popped off my key ring when I was pulling it back out of the lock. So the door shut, and I realized that I had just left my key in there, and I had to go do the walk of shame over to the front office to say, May I please borrow the spare key? Because I've locked it in there, and it's not a big fail, but sometimes it's just one of those things like, yeah, I can be just as absent minded about the day to day things as anybody else. Unknown: Absolutely. Sean Tibor: Becky, anything goes horribly wrong in your world this week. Becky Smethurst: It's very similar to my fail. I always say the reason I do a lot of outreach and science communication is to just show people that scientists are just normal people and give people transparency into what life as an academic and a researcher is like. And I feel like this week, I've demonstrated how utterly normal astrophysicists can be in the sense that we are not actually, we may be intelligent, but we're not that clever because I went shopping for, like, a duvet, I guess comforting the us. Right. And I was pulling it off the shelf. It was in a big cardboard box. And somehow I still don't know. I clocked myself in the face with it hit, like, corner right into the eye. And I was just in the middle of the shop. And I was just like, I was just imagining some sort of, like, freeze frame, like in a film. Sean Tibor: Well, you proved that gravity is still working just fine, right. Kelly Schuster-Paredes: As an experiment. That's funny. Sean Tibor: Well, we've all had those days, and I'm glad that we can show for our students, for the people that we're communicating with, that we don't have to be perfect to be making progress, to be understanding new things. Like, sometimes you're going to get yourself in the face or you're going to lock your keys in the door. It happens, and then you pick yourself up and you keep going, right? Unknown: Definitely. Sean Tibor: So let's shift into our main topic. I am really excited to talk with you, Becky, after hearing you on the show with Michael Kennedy about your work with Python and Astrophysics, and I know that Mike is a very big math guy. He loves all those sorts of things and you could just hear in the conversation how much he enjoyed. And I'm sure his audience enjoyed talking with you about this. And I suppose when you step back and think about it, coding and astrophysics go very well together. There's a lot of data. There's a lot of processing and understanding. And I think, of course, we've seen a lot of those huge milestones in astrophysics come out that the big releases that have come out about whether it's taking a picture of a black hole or researching and finding out more information about exoplanets and how we discover those. It makes a lot of sense. Could you tell us a little bit about how you became interested in this field and kind of how you have been learning and using code to be able to do your research? Becky Smethurst: Yeah. I mean, I think it wasn't necessary. I became interested. It was more of a if you don't learn to code, you can't do this thing that you love. So I wasn't even introduced to code until I was at University in my second year, and it was only when I got into my final year when you do a research project. It's like half your grade for the entire year. And I was doing this research, and I realized, oh, I have to use this thing that at that point, I did not like I didn't understand why it could be useful, I think, and that might have been the way that I was taught us that we can get into that. But I think without it, I don't think there's a single colleague of mine that does not use code in some sense. So I am what's called an observational astrophysicist. I go to telescopes. I take data. I use data from what's called survey telescopes as well, where the data is all open. And I will analyze that data, whether it is an image or something. We call it a spectrum where you split the light up into its component wavelength. All of that needs to be processed and analyzed. And then you need to work out what that data means. So that might mean running a model and fitting a model for that day. So that's all code as well. And then also you've then got to write up the paper. And really, we do that with code as well, because we use latex to do that for those who are familiar. And then, of course, you then say to your other colleagues, who, instead of being observational or theoretical, they might run simulations like this is what I found. And we don't understand this. Can you try and simulate it? And then, of course, they'll then use code to make a simulation of the universe in some way. So there's so many different areas where it's used. I don't think any of us could do our job without it. Kelly Schuster-Paredes: I find that so remarkable, because I have a background in science nowhere near astrophysicist, but I'm a biology on the other side of the spectrum, biologists. But back in the days when I was in College, you didn't need to think you didn't have code. You didn't have code in high school. And the idea of ever having to use code was not even a thought, not even a second in your mind. And we often get that conversation with students. I don't understand why we have to learn to code. I'm not going to be a programmer. I'm not going to use this. And it's changed so much. You said you didn't start learning to code until College. Is that how the most of your colleagues also started? Did they start learning to code later in life, or was it something that they did before? Becky Smethurst: I would say so, yeah. The majority of at least people who finish their PhD and are currently what we call postdoctoral research or a professor. Majority of those will have learned either at College or picked it up. So there is sort of a well known thing in astrophysics, but we're all self taught. Basically, we got a basic sort of briefing at College and then everything else we've learned on the job through our PhDs, usually because it's a very niche thing that we end up doing, whether it's removing noise in an image and processing that image to clean it up, or whether it's building a simulation of the entire universe. That's not something you tend to be able to find a tutorial online. We're all very subtle, and none of us really have that much formal training. I think that's changing with a lot of PhD students we're seeing coming through where school curriculums have changed and they're being exposed to more code at school, whether that's starting with something like HTML or something like that and moving on to MATLAB or something like that. People have that sort of grounding there before they get to University, necessarily. And they already understand the usefulness of code. But you still have some undergraduates where like I did in my final year project, realizing to do this research for my grade, I really need to become more comfortable with coding. And with Python, you still have students that come through that are also making that realization, whereas you have some that are like, yeah, I've been doing this for years. I'm so comfortable doing it. So it is a problem I think we necessarily need to solve, but I'm sure it's not a problem just for astronomy or astrophysics. I think it's probably a problem across the Sciences that a lot of us are not formally taught, and that leads to terrible coding practices, like the syntax and the formatting is all wrong and nobody comments anything I can understand that. All right. Kelly Schuster-Paredes: One more question. But what before and I'm sure with the development this is sorry. Let me frame my thought a little bit because I'm so excited before the telescope. That's a different story. But there was always this data coming in. What did they use before all this code? Was it just Excel spreadsheets? Becky Smethurst: Yeah. We've been using code for actually quite a long time, especially simulations. The earliest simulations were run on, like four trials in the 70s. Right. So that's been going for a long time. In terms of observations. We were stuck using photographic plates, huge, big cumbersome plates that would need to be exposed and all that kind of stuff and then developed. And it was actually one of the reasons why digital cameras were invented because astronomers were pushing the technology forward going, this is horrendous. We can't measure the brightness of something to any accuracy, because all we're going off is sort of how white does it look on a photographic plate when it's been developed. So it's an interesting one that obviously then led to the development of the digital camera or the CCD, as we call it, a charge coupled device. One of the first places that was used was the Hubble Space Telescope when it was launched in 1990. Unknown: Right. Becky Smethurst: And then since then, we pretty much all got one of them in our pockets now on our cameras. And so that was when code really took off, when it's not just single photographic plates you're working with, you can actually see the change in astronomy go from. I have a sample of ten things that I have studied in great detail and worked out, traced by hand and stuff. These graphs of whatever the brightness is doing in this image. We now have telescopes with digital cameras on that can serve as multiple images in a night that we then have to process. And then you want something that can automate it for you with the increase in data that you have with the digitized of it. So it's almost tied to that. In a sense, I feel like astronomy by inventing a digital camera detector sort of doomed themselves. I love coding. You know what I mean? Kelly Schuster-Paredes: It's okay. Sean Tibor: It's a cascading effect, right. Like you start with one thing and it has all these downstream effects on the way that the work is done. And some people find that Daunting and others find it challenging, right. And exciting and everything. And I guess it's kind of the attitude that you choose to adopt. Becky Smethurst: Yeah. One of the downstream effects as well is that we then so obviously, when you have all these digital images and you need some processing again, it's an astronomy pushing forward the routines and functions and programs that were written to do that image analysis to do the cleaning up to bring images together. If you're using multiple telescopes, things like that, then that's used by the medical imaging community to clean up MRI and CT scans and analyze those. So it's that downstream effect again, is that a lot of those techniques that were developed by astronomers through the 90s and stuff were then put into medical imaging. Kelly Schuster-Paredes: I was just going to say that sometimes the whole thing about coding and I'll let Sean say his is sometimes Sean will go and work an hour to solve a problem that you could do in ten minutes. But it's ten minutes times ten minutes every single day where his program that took an hour now just saves the time. And I guess that's kind of the way it helps for you. Yes. It's a lot of data to process with all these images, but that just saves a lot of work in the future of not knowing or stuff like that. But Sean was saying about his medical field. Sean Tibor: I was just saying that's an area that I'm a little bit familiar with, and it's amazing how much that field has changed as well, along the same route where you go from X ray films and CT films through to, like, this whole digital processing pipeline of gigabytes or even terabytes of data for a single study. It's amazing how much these fields intersect and overlap in terms of the need. It's just instead of looking outward, we're looking inward, right? Unknown: Yeah. 100%. Sean Tibor: So one of the things I wanted to dig into also about this and kind of the way that you have seen this develop and the way that you came into the field. One of the challenges that we have for our students is helping them understand that relevancy of coding early on. Right. The nice thing about the silver lining, I guess, to learning how to code in College is that you're in the middle of the thing that you've chosen to do that, you know, like, I want to go in this direction, and I want to take this further for a lot of our students who are 10, 11, 12, 13 years old, yet they don't even know what they like to do yet, like what their interests are. So one of the things that we wanted to ask you about today so we could share with our students is, how do you find an interest like that? How did you find your interest? Was it something that you always had and it just developed over time, or was it something that kind of sparked later on? And then when you see that, what do you do with it? And how does that work for you as an astrophysicist? Becky Smethurst: Yeah. It's funny. You should say you were introduced to code when you knew what you were doing already by that point, because hilariously. They didn't teach us code with any Astrophysical astrophy example, which is very frustrating. I was the space kid, right? I was the eight year old that wanted books on space rather than a bike or a telescope rather than a bike or something. And that never really left me for a while. I got distracted by Dolphins because I was also the dolphin kiss. Everybody knows, Kelly, that was the best Dolphins. So for a while, it was like I wanted to be a marine biologist. If you'd asked me eleven years old, I would have told you, a marine biologist, it was always a science thing that I really wanted to do. My dad always said, if you do something you love, you'll never work another day in your life. And to me, that meant, okay, every time I have to choose subjects, I choose the subjects that I love the most. The subjects that when you have a pile of homework, you pick that off the top of the pile first to do rather than the English essay that I always left till half. Now, for me, it was math. Kelly Schuster-Paredes: It was physics. Becky Smethurst: It was chemistry, and we actually in the UK. We narrowed that down at 16. So in our last two years of high school, we only do four subjects. And that for me, was math, small maths, physics and chemistry. I left biology behind. Sorry, Kelly. And then using my University degree, I was just like, I want to do something like this. And the idea that I could go on and do astrophysics physics that I loved at school combined with the space that I had always been interested in was a dream to me. So, like finding that interest, it wasn't like I had to set myself very hard to be honest, it was always something that I would have asked about would happily chat about for an hour until somebody stopped me. And I think it came from curiosity. As a child, I think that never really left me. Kids always ask why, why? Why this why that? And I kept asking questions. I didn't seem to grow out of it. And eventually you start asking questions that your parents don't know the answer to and your teachers don't know the answer to and the library books down the road don't know the answer to. And you realize no one does. No one knows the answer to what's inside a black hole or anything like that. Or how far is the most distant Galaxy ever or something like that? Because we can only see as far as we can see. And so when you get to that stage, you realize that you want to start answering the questions that you don't know the answer to or as humanity doesn't know. And you can contribute to almost the answers in the textbooks. Right. Because why I like science was that there would always be a tick next to it from the teacher if you got the question right. Whereas in English, I say it was like I don't agree with what you said here. And I'm like opinions. I wanted the facts that were ticked. Realize that actually research is no one's going to tick it. No one's going to give you the right answer. You have to to get data to do your sort of experiment with it and sort of convince people that what you've deduced from that is the right answer and find more evidence in support of it. And so it's very different to how you get into it at school a little bit. But I think the exploratory side of stuff and the stuff we don't know is what makes it so fun and why I enjoy it so much. Sean Tibor: The follow up to that is that I'm sure that there are plenty of scientists, not just astrophysicists, who love to stay within the realm of their community. Right. Like within astrophysics, speaking primarily with other astrophysicists or related fields. But you've also chosen to take this very outward looking role as well to help educate and communicate your science to others. Can you tell us a little bit about that role and some of the things that have been both rewarding and that challenging? And then how do you explain things that are very complicated, potentially, if you were to speak to other astrophysicists about it in a way that everyone who's intelligent maybe, but doesn't have the context or the language or the vocabulary can understand it and appreciate it? Becky Smethurst: Yeah. I mean, I definitely always knew I wanted to do this kind of education, as you call it, outreach science communication, because I was very aware I've been very privileged to have access to educational Institute in the UK that other people don't in other countries and the education I've had, I want to share it. I don't feel like knowledge should be behind big, high brick walls of universities. It should be shared, especially because taxpayers pay for a lot of research funding as well. So you kind of want to give back and explain what you've been doing. But the idea is that if you can Google a question that you've been curious about, and the only results that will come up are papers that are written for other astrophysicists, a member of the public is going to really struggle to read. I struggle to read a lot of papers. Sometimes they're very dry. And so being that sort of middleman, if you will, that can sort of interpret. And that's how it's funny that you should say it is a different language, because that's how I've always seen it as being the interpreter, being able to read a scientific paper and go, this is what they've done. This is what it means. This is why we care. I think it's really important, and I do have to think it's not necessarily a different language. It's just who you're talking to. I always picture my mom because she left school at 16. She's very intelligent, but she's not necessarily informed, educated. And so I'm kind of like I wouldn't use the same language that I would use to talk to a colleague that I would talk to my mum with. It would be a lot more casual, first of all, which is how we all I think like to just have a chat with a person. And so I think embodying, that means that you start to think differently and you don't think in sort of every day I'm at my desk crunching through data and very concerned about this one particular thing. You start to think as if you are just having a conversation with someone. And with that, I find that it comes easier to think, well, how would I explain this? And yeah, okay. I do have to sort of backtrack and think, okay to explain this. They need to understand this all the way back up and say, oh, I need to start here. And there is always a base point you have to pick. And usually I pick around about sort of like, what did I learn at about 1415 years old at high school. And I'll go from there and I'll sort of remind you, like, remember that little thing that you learned at high school? You were like, what was the point in learning that? Well, it all Cascades down to this thing. And this is why we can, for example, measure the mass of a supermassive black hole because we Kelly on the Doppler shift that you learn about high school, whether the pitch of sound waves change because it gets stretched and squashed as things move and move away from you and towards you. And so that's the difficult bit is remembering what it was like to not know stuff, and that is very difficult remembering what it's like to not know. And I think knowing someone like my mum, who doesn't necessarily is very helpful in that sense. And also my sister. I love my sister so much. She's my best friend, but I'll never forget. When we were on holiday once, she was looking up at the sky in the day, and she was like, you can see the moon during the day. She's like, 21 at this point, it took me 21 years to realize you could see the moon during the day at some point, and you have an astrophysica. It's just a welcome reminder that people don't retain the information that you do. They retain different information and they care about different things. And you have to remember what it's like to not know all that stuff because we were all there once, right? Kelly Schuster-Paredes: Absolutely. And I'm sorry I wrote a list I'm writing. So I want to recap all this because there are so many good things in there. I always like to put myself myself in the perspective of when I'm yelling at Sean going, but I didn't get it. So if I don't get it, they're not going to get it because I'm a little bit behind him and his skills. But a lot of the issues I think sometimes of getting us into code and getting girls into code is sometimes the instructors are not playing that interpreter part. Their language is different. It's not a casual conversation. It's like the Ram and the hard drive and the plugs, and it's not making those connections. Today. I was just reading something and I was like, this is not for beginners. It clearly is not making a connection for me. I'm stuck here and it just jumped to this level, and it's not clear. I like your idea about the base point and backing up to X level, we sometimes get so caught up with what we know. We forget that it took those 15 steps to get there, and most importantly, always. Luckily, I still always remember there's always still something that I'm learning. So what was it like not knowing functions? I remember the day when Sean was teaching it, and I had been teaching functions already two years, and he said something and I was like, Holy cow, I just understood that for the first time ever. And I was like, that is why no one gets functions because I just understood it after two years of teaching it. So it's great points for everybody out there, like when you're teaching informed language, casual conversations. What's missing? Sean Tibor: Go ahead. The other thing I was going to mention is that one of the things that stuck with me from my, I believe, was in graduate school. We were talking about communications and the role of jargon the technical language that's specific to your field and how it can be unintentionally used to exclude people or intentionally used to identify members of your tribe. Right. And I think that always stuck with me. And it was something that I've tried very hard to break myself up to make sure that I can continue to include people with the language that we use or intentionally used by someone because they think it makes them sound more intelligent. Right. We've had this conversation with colleagues, too, where they've said, what we really need to use is employee the precise language that has the specificity of intent and meaning that's relevant to the area. And I said, yeah. Kelly Schuster-Paredes: In order to pass the test. Sean Tibor: Right. Because using the big cumbersome words has always led to greater understanding. Right. Kelly Schuster-Paredes: No one ever. Sean Tibor: No one ever. It doesn't help. But what I found, at least in my kind of coding and technology of the world, is that the harder I work to explain something in clear and more understandable language, the better that furthers my understanding of what I'm trying to explain, right. That I become more facile with the knowledge that I'm working with. Have you found that in your work as a researcher? Also, that when you're trying to explain it, it leads to better and more creative understanding on your side. Becky Smethurst: 100%. Yeah. Like taking something back down to that level. I think you don't truly understand something until you try and explain it to somebody else. And, for example, like, Hawking radiation. It's probably something you've never heard of. It's named after Steven Hawking. Steven Hawking was like, hey, black holes could actually give out some radiation and reduce in mass and therefore evaporate. And I was like, Cool. Stephen Hawking, I believe you. I remember being like, oh, no, I have to actually explain this. And I was like, yeah, it's like a quantum thing that we don't really understand and whatever. And I was like, Well, that's not good enough. I need to explain it better. And I was like, I actually don't understand this myself. I've always just taken it as a given. And then you go off and do reading and you find an explanation and you go, yeah, but that's not a good enough explanation because you haven't explained this and you end up using it and piecing it and piecing it until you're like, right. Okay. And I even found that with some of the stuff where it's more commonplace or something where you sort of start explaining something you say, oh, it's this because of this. But why is it that? And then you have to remind yourself of something like that. And I think it just comes down to the fact that you cannot explain something so that other people will gain the understanding unless you have a full understanding of it. And I find with Jargon, I think it does not help at all because I found at least. And I don't know if other people found this, but if someone introduces a new word to me, in terms of jargon. And even if they say this is what it is and explain it once I find it very difficult to then follow the argument of whatever they're saying next, like follow the narrative if they keep saying that word, because every time they say that word, I have to remind myself what it means, and then I miss what they're saying. And I don't follow the narrative. Or I don't necessarily appreciate the wider context of what they're saying because I don't understand that word, and I constantly keep having to remind myself what it means. And so I think it's easier to use different words sometimes, even if they're not quite scientifically accurate. Like when you talk about Blobs at the beginning as well. There's a set of galaxies they're called elliptical galaxies because they are elliptical in shape. Now, an Ellipse is a word I use every day. It's a squashed circle. It's not a perfect circle. A circle is just a very special type of Ellipse. Again, I said Ellipse so many times in that sentence, people are still reminding themselves what it means. It's just easier for me to describe those galaxies as Blobs because you immediately know what that looks like, what it means. It's not scientifically accurate in any way. It's more fun to say, and I think people enjoy it more, but it also lends more to understanding because you can then follow whatever argument I'm not going to say next. When I say Blob, galaxies are the biggest galaxies or Blob. Galaxies are redder in color than other galaxies and stuff like that because you're not constantly reminding yourself what you're not having to think like, what is an elliptical Galaxy? What is she talking about? Kelly Schuster-Paredes: I love all that. I think this is as an educator, we sometimes take for granted when we're introducing new vocabulary. And in the first four weeks of teaching Python, I introduce everything up to list four loops, wild truths, concepts, objects, variables, Fstrings, and we say them over and over again, and we define them over and over again. And that's something to always keep in the forefront. You expect it just because you said it 20 times that the student is going to recall that. But I love what you just said. Sorry, I write down everything when you don't understand the word that's being used. You sometimes miss the narrative. And I think that's something that a lot of teachers forget after the years because we have that I've taught in 6th grade Python 25 times 26 times. But it's always important to remember that it might be that one word that they're stuck on. Not necessarily the idea, the concept of coding, but that one word that got lost in the narrative that they lost very powerful. Sorry, I had to write things down and rethink it. Sean Tibor: Well, I want to see if we can get maybe some practical advice for our students, too, as well in that idea of trying to connect their interests with coding, show them some things that are relevant. And I was going to ask if you could share any ideas that you might have in terms of coding projects for beginners that relate to astronomy. So that if someone is interested in space, if they're that eight year old girl, that's like, I love space. And now you're telling me I have to code, how can we help her see space is better with coding something. That's a nice starter project or idea. Becky Smethurst: Yeah. So we actually have a conference series in astronomy called Astronomy, which is like, how can we make astronomy better because of the online world? And we always have a hack day. And I remember so clearly someone on Hack Day did this project within, like, 6 hours, and they were a competent code or whatever. So maybe it could be, like a semester project or something for kids. But they took, you know, how you get, like, these little kits where they come with various different bits of cogs and gears that you can put together to make whatever. It was like four pieces that he put together to make basically, like, a pointing stick, which he then stuck a sticker of a shark on. And he called Space Shark. And essentially what you would do is he wrote a little program using a raspberry Pi where you can type in, like, Jupiter or Saturn, and the little space shark on the stick would go and point at wherever Jupiter was at that exact moment. Unknown: Right. Becky Smethurst: So it's kind of like you can download these apps where you can sort of pointed at the sky, and it will tell you what you're looking at. Can you imagine doing that in your own backyard being like, which one of these is Jupiter? Is it's really good fun? Because how you do that is you can look it up, say, on the NASA website, you grab the coordinates that Jupiter and Saturn are at right now, and then you calibrate your thing. So it knows what coordinate it's currently pointing at. Like, if you point it straight up and it's like, okay, so that coordinates over there, and it's a nice little repeatable thing that you can do with Python. And it's just coordinates on the inside of, like, a sphere. So it's really quite fun because it's almost like if you could learn about latitude, longitude and then be like, but there's latitude, longitude in space as well. And we can code something to point at something that's at this latitude, longitude. Kelly Schuster-Paredes: I can see Sean out. Sean Tibor: I'm already thinking about what Lego pieces. We need to be able to make that work. Kelly Schuster-Paredes: I can see it, though. He's going to project it with some sort of IoT WiFi on his ceiling and just be like, okay, here's Jupiter with a little Lego turning thing. We're not going to see him for a couple of weeks. He's going to come in with bags underneath his eyes. That's fabulous. Sean Tibor: One of the other questions I had for you was about basic experiments. So one of the things I'm always fascinated by is like the way that early scientists meaning, like Greeks, would prove the circumference of the Earth or something like that, using techniques, anything that would be like a nice experiment that someone could do with code that you can think of. That would be like, maybe it's looking at some sort of Doppler shift data. Right. Because we give them lists of information. Or is there something we could a list of information we could give them about space. That would be kind of a cool experiment. Becky Smethurst: Yes. You could give them a list of the timing that the moon IO disappears and reappears around Jupiter. The Moon IO takes 42 hours. So just under two days to go around Jupiter. Right. And you can see this with the telescope, you can see four of its main moons, and you can see them moving night after night after night. So they could even record those timings if you want. But with this data, you can measure the speed of light because as the Earth also goes around the sun, say, in June, it is closer to Jupiter. So the time between the time that bio takes to go around Jupiter, you measure a shorter time, and then six months later, in December, the Earth is further away and the light has to travel further. And so you get a delay on the time that you measure that it reappears from behind Jupiter on its orbit. With that delay and knowing how distant the Earth is from the sun, you can work at the speed of light. Unknown: Wow. Becky Smethurst: All right. Sean Tibor: I will come back to you to check my math. Becky Smethurst: That was done in the 1600s by Ola, Roma and Cassini. They were trying to do it because they were trying to figure out a way to determine the local time wherever you are in the world so that you knew your longitude. If you were at Sean, you can compare it to, like, say, the time in Paris or something in the time where you were. And you knew how far around the world you were or something like that. It was just that, like Galileo came up with this and expected sailors to observe the position of IO using a telescope on a moving ship in the middle of the sea. And it wasn't quite feasible. But if you have these timings now that you can just grab from sort of, like a year's worth of timings, you can measure the speed of light, which is really cool. Kelly Schuster-Paredes: That's super cool. I wanted to ask them not to switch gears, but I want to ask because I loved watching. I started watching your videos, and then I just, like, playlist just kept going. I was just like, oh, they're so entertaining. Great quality videos. How are you making these things because I think hopefully knock on wood. We're not going back to having to do everything with videos and COVID. But the kids have said that my quality of videos are not 100% awesome, so I would love to make them better. What do you do? What do you use? Becky Smethurst: What are some tips I have basically an SLR that my party uses to take photos, but like, it's a standard camera pretty much. But I also use my phone. It's not necessarily about the quality of the video itself necessarily, but audio I found is a big deal. She will say podcasting you'll do, but in terms of, like, shot set up and lighting and audio quality, that's stuff I learned on the job. If you go back and watch my earliest YouTube videos, they're terrible. They're so bad. And it's because you learn on the job, like with code, right? The more you do it, the more comfortable you become with it. And I've just managed to decide what I like and how I do something like, do I like the look of that? Yes or no. And I've kind of figured out a niche. That's what I like, and that's how I like them to look. And I do that all the time. And I've learned how to edit on the job. I didn't know how to video edit or anything like that. And again, that's improved just with three years of doing this every week and come up with just a routine of how to fit it into life, home work, life balance with YouTube making and everything as well. It helps. Obviously, I have all this knowledge in my head already. I do have to do bits of research for a video, but it's all there just waiting to just spill out as soon as I have an idea. And I literally sit in this very room that I'm going to podcast now and talk to myself for an hour after camera. It's good fun. And you just have to rein yourself in and decide what to put in a video and what to leave out. And that's often a hard decision as well, but they're really good fun to make. I think also as well with science, your to do list, sometimes you're not taking off items until a year or two years down the line until you finish a project. So this is quite a nice. This is very logical with the code. You're very into the data and stuff. You have to be creative with ideas, but it's very logical. And so this is a very nice creative outlet. It's very different to code and to everyday sort of research and everything like that. And also every week I get to tick off like I did that I achieved something this week, which is quite nice. Sean Tibor: Well, I do have to say I was watching the Maldives video last night and I was blown away by the shooting star that you captured in the background. That was the coolest thing. Becky Smethurst: I was like, yeah, I'm going to go enjoy the sky and I was like, you're missing it. You just shoot while you're filming. Sean Tibor: Which is amazing because it's such a serendipitous moment, and I think you only get those things when you're recording or when you're shooting. You don't get that otherwise. And it probably is an even better moment when it's an astrophysicist with a shooting star in the background. Kelly and I are recording talking about code, but it's still amazing and it was so much fun to see that. So we've been really enjoying your videos. We are going to post a link to the channel in the show notes, and we also will post a link to your book as well, which is fabulous. My daughter and I have been reading it every night before bedtime. We talk about the concepts and ideas I have been learning a tremendous amount because it's really fun and interesting and expands your mind. It's wonderful. So we'll post a link to that. Is there anything else we should plug for you that people should check out that you're doing because people need more doctor Becky sure. Becky Smethurst: There is a specific video that's about five specific ways that I do use code as an astrophysicist. So if people are still curious about that, then I think they should definitely check that one out. And I also interview one of my colleagues who is from the simulation side of things on how you actually go about writing a simulation of the entire universe and a computer. Like, where do you even start? Basically. So that was a really good chat as well that's linked from that video. Sean Tibor: So when anyone tells you like, oh, we can't include that in our code because it's too much. We can say this guy has the entire universe. Kelly Schuster-Paredes: Girl, let's correct. That is a female. I watched that video too, because that's what first got me hooked. It was a great video. It's one that I think if you're a scienceteacher or mathsciencecodingteacher, that it definitely is not to knock down code. Org and how they had all these Rockstar, actors and actresses and basketball players. But to actually hear a real astrophysicist talk about why she uses code, that's pretty cool. So check on my book. Sean Tibor: We do have quite a few of our students who have never listened to our podcast before. They've already told us we're definitely listening to this episode. Becky Smethurst: I can't wait to share with them. Sean Tibor: Well, Becky, thank you so much for joining us. If you'd like to learn more about Dr. Becky's research, check the show notes, more of her channels. If you'd like to get in touch with us and tell us about how much you love this episode because it's amazing. You can find that at our website, Teachingpython FM. We're at Teaching Python on Twitter. Kelly Schuster-Paredes: Kelly, any news or updates to share this week Innovation Institute is coming in April, and Sean and I are actually keynoting this year. So if you want to learn more, it's a virtual conference makes it a lot easier. You don't have to go anywhere before that spring break, and we'll post that up there, too. Sean Tibor: Sounds good. All right. So for teaching Python. Kelly Schuster-Paredes: This is Sean, and this is Kelly signing off.