Accessible Python education for schoolgirls using Avocados, Zombies, and Korean!
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Tan, Chiin-Rui
Imagine this school scenario: an entire year group of students aged 11-12, the majority completely new to coding, undergoing 6 hours of compulsory lessons on Python for Scientific Computing. Now imagine these outcomes: • Students wanting to continue coding from the lessons outside of class in their own time • Students asking to replicate the lesson computing environment at home • Students disappointed for the lessons to come to an end and asking for more • Students struggling in Science discovering intrinsic ability in computing, bringing new enjoyment and confidence And lastly, imagine that all the students are girls! This talk will share this actual case study of a pioneering Python education initiative implemented at a secondary school for girls in London, UK for a cohort of 120 students. The audience will gain actionable insights of the factors that enabled these children to develop basic but working proficiency of a mainstream scientific data stack using typical school IT resources. Ultimately, this talk aims to increase awareness of Scientific Computing & Data Science as potentially effective and empowering Python education for young people.
 Sheen is going to talk about access to Python education for schoolgirls using avocados, zombies and Korean. That sounds amazing. Okay. Okay. Well, good morning, or at least good morning from London. I hope you're having a good year of Python. I'm sorry we couldn't be doing this in person. I'm sure we're all sorry, actually. It's been a pretty stressful couple of months, I'm sure for everyone. But at least we're here sharing online and I'm having a one sided conversation with you, which is quite weird, but same for everyone. Okay. So I'm just going to start. Let me just adjust so I see less people. Okay. So accessible Python education for schoolgirls using avocados, zombies and Korean, which in more general terms, oops, make sure I can move my slides, would be about accessible Python education using scientific computing and data science. So I would also just want to say like in normal presentation, I'd want to ask, you know, I'd want to understand yourself as an audience. I'd like to understand, you know, your backgrounds and your interests and, you know, are you educators? Are you school teachers and so on and so forth? But I can't obviously do that. So what I'm going to do, I think the way I'm going to try and use this time, I'm basically just kind of try and highlight the aspects of this story. The slides are actually meant to be, they're actually overly detailed. They're supposed to be standalone. So I'm just going to set this expectation up front just so you understand how I'm going to present. The slides are meant to be standalone. So if you don't listen to talk, you can understand it fully. It's also supposed to compensate for the fact that obviously we're using English. And that's obviously not the most accessible for everyone. So I've written out a lot of the text so that it's easier to follow. So hopefully that's useful. What I'm going to do is jump around in the slides a little bit and just highlight the main points I want to make so that we can have a conversation because I think there's a really big opportunity in this kind of space for school children, school girls to access scientific computing. I don't have all the answers. You'll find that out. But I want to start a discussion and I'd really like to talk to yourselves and collaborate and get your feedback. So okay, what I will go into detail is what the point of this talk is. So I'm just going to set the expectation up up front. So from my observations, at least in the UK, technical education for teenagers seems to focus on these kinds of things. So, you know, this is I'm a very visual person. I'm probably going to talk through the visuals more than the text. So if you ask a child who's doing coding, what they're doing, it's going to be very likely one of these kind of options, Raspberry Pi, Arduino, Minecraft, mods, scratch. Really interestingly, I had to make this point. There are actually a lot of computing teachers in UK schools who are like VB.net. Yeah, I know it's a blast from the past for a lot of people, but that is the reality. So my point is that when it comes to learning Python, the work that my startup is doing in UK schools is demonstrating that scientific computing and data science education can actually be really effective for some teenage students. So basically, this talk is going to present a case study. It's going to be of a scientific data stack education based in a London girl's school. And I'm going to show the kind of successful learner outcomes that can be delivered by this kind of stuff. So I hope this is familiar to you. I'm probably not great. So I'm going to have to assume that people sort of understand what Jupyter and these kind of technologies are. But we can obviously talk about the breakout if you want more detail. So basically, by the end of this talk, hopefully there's more advocacy for scientific computing and data science as accessible Python education for teenagers. Because after all, why should us grown-ups have all the computational fun? And it is a lot of fun. I'm not going to lie. I'm biased. I love data science. But I also want to make the point, so I'm just going to check my discord, that even before the pandemic, I actually found scientific computing. I actually found data science actually really helpful for my mental health. So if I felt really stressed out or really out of control as someone who is higher on the autistic spectrum, actually doing coding often helped me feel more. It gave me a focus. It made me feel more comfortable. And actually, that's been something I've turned to as well in this pandemic. So in the UK, we've really not handled this COVID very well at all. I'm not going to get political about it. But I'm still effectively in lockdown. And although we've been very privileged in the UK in a lot of ways, it has been tough. And in the same way which data science has helped me cope better in this time, I really want to make sure or really want to give that opportunity to other young people who maybe also might find data science and scientific computing something really positive for their well-being and not just from a kind of job tech future perspective. So something I have to point out out front. Obviously, we're talking about children. They're safeguarding. So the students are not going to be disclosed or identified in any way. So they're going to be anonymous. I will have a use visuals mainly from this is one of the Mito communities which I founded, my main one. But if you kind of want to have a sense of the kind of audience I'll be talking about. If you are familiar with Harry Potter, basically Hermione in the first year of Hogwarts is the right kind of age and gender. Sorry, that will give you a bit of a proxy. But without the magic stuff because that's fun but not real. Okay, so here am I. I am a tech entrepreneur. I have been working for really quite a while now. I think probably the point I want to make is that I don't come from a formal education background. So I actually, I'm a social scientist. Yes, I know it's kind of weird that I've ended up in Python via R. So this is the first community I founded was called the R ladies Cone Club which turned into R ladies London, which then became a founding member of our ladies global. But you know, here we are here I am at your Python for the second time. And so how did I really get into education so over my career I really found that I had a, I had seemed to have a certain particular ability to explain, you know, technical content to non technical people. And then that was something I turned into community outreach, obviously here with R, and then with the AI club. And then I managed to turn that fashion into a full time job. So I founded an tech startup with a social mission, which is around democratizing opportunities for young people to level up their modern computing literacy. Now, that is not a sales pitch. Actually is generally because I need to set the context for the case study, which is about a project which my startup was commissioned by a girl school. Again, I'm not going to identify the school, it may or may not be represented by this image here. So I'm not going to set the exact fee to decide. But it, the project was around delivering a boot camp for non coders to develop Python proficiency. And I just wanted to give a shout out to the project sponsor, who I can name. Just giving permission. So this is Madeline Cooper, who's actually a she actually did math at Cambridge. And so she is the person at the time who initiated this unique pioneering project. And we'll talk about the pioneer aspects. Actually through the talk. Again, I'm going to go through all the details. The key things I want to pull out here is that it was compulsory. Okay, so this is unlike, you know, the kind of meetups seen that we probably know and love, where people opt in here. These girls did not opt in. They were forced to, they were forced to undergo this boot camp, all 120, 11 to 12 year olds, and five of the teachers. So hopefully that sets some context. Okay, project deliverables. So what was actually delivered. So remember it was boot camp. I decided, of course, to go with Python for scientific computing, as the sort of the computing application. So I chose this data stack, scientific data stack to introduce the girls to. And of course, the Jupyter notebooks, as referenced here. And the structure of boot camp. So we said six sessions. So that was in the last slide. So I structured as basically building blocks with obviously relevant scaffolding because, as I said, non coders, from non coders to to this in six sessions, or frankly, six hours is obviously a stretch. And actually, because it was a stretch, I knew it was going to be challenging. It was, it was designed to be challenging. That's the kind of person I am. I'd like to stretch myself and stretch other people. So the project goals, in terms of the way it was presented to the girls was basically, you know, I was like, Listen, I know, it's like you're 11 years old. It's like, you probably don't code if you do code, you know, I mean, fantastic. But I'm going to seem that, you know, you don't have any experience. And that's absolutely normal. I didn't code when I was 11. I didn't code when I was 20. So I said, in this boot camp, anywhere you can get up on this on this pyramid, I called it, I said is, you know, is a bonus. So anything you can develop in terms of your computational thinking, critical thinking, creative thinking, fantastic. I guess one thing to point out here. So, unlike, I guess, other kinds of educational experiences, especially in this kind of school, which was is very academic. You know, I said, don't compare yourself. No comparison, no competition, you know, you're on your own path, and you have your own pace. So just focus on that. Okay, I'm going to see why you can still hear me because I just feel like I'm just like talking to myself, which I quite frankly could be so sorry, that's why I keep checking on this. It's perfect. It's perfect. Okay, cool. Yeah, just let me know. I don't want to be babbling. Okay, so project outcomes. So there were a small minority of the cohort who had done some coding for some Python, but of course not scientific computing. So, you know, from a quantification quantified from a quantify perspective, we had 100 new teenage pythons, all girls identified girls and new coding champion teachers, which was super awesome. But you know, I think I'll let the girls, they're sort of testimony. Excuse me testimonials, do the do the talking for me, although I'll, I guess I'll read out their testimonials but anyway. So, I guess the things to highlight is that, you know, from a sentiment perspective, I mean, they on the whole, you know, they really enjoyed it. In fact, so much sorry that one of them said that they love Python, which I'm not gonna lie was really wonderful and you know, it's still a really, really happy memory for me. But yeah, so you know, from these kind of responses you can see they basically they just wanted to keep doing it they wanted to do at home. They wanted to, in fact they downloaded and conda at home by themselves. They wanted to keep doing it again after the bootcamp was ending they want to get next year. They didn't want to go back to normal class. You know, it was just awesome. Okay, this is a point I do want to make. So, obviously I didn't know the students. I didn't know their backgrounds. Some of the teachers pointed out to me that there were girls who, you know, in science, for example, they were struggling. They weren't historically known for doing, particularly well on that subject but actually in the bootcamp we were basically with Python. They were actually excelling, you know, they were sort of, you know, doing better than you know other their sort of classmates who had done coding before. And, you know, for me that was just really powerful and again, that's just emphasized that you know I feel like science scientific computing and data science could really give young people the opportunity to discover something that they really enjoy and are good at, you know, and I really want to make sure they have those opportunities to discover that. So, these awesome outcomes. So why really. Of course, as a data scientist would want to know. So, I think basically this is what I want to stress is that I'm not saying all experiences, especially not a tech education I'm not saying they're always, you know, negative user experience. Although sometimes, you know, I'm not gonna lie sometimes they are, but in this case, you know, for me my analysis was very much that, yes, there are negatives, you know, there are things we don't enjoy. I mean, I don't know about you but I don't get a lot of pleasure out of, you know, installation and set up. And that kind of troubleshooting is not my favorite. I, I also know documentation is really important. I like other people's documentation. I am not. It's not something which fills me with joy writing my own documentation. So, you know, these would be the kind of negatives. But, you know, I think in this experience, I guess, I just want to draw out that, you know, I tried really, really hard to sort of decrease the negatives, or, you know, make the things which might be bad less bad, and the things which were good to really make them as good as possible, and better. So, I kind of drew out sort of six specific features. So just adjusting myself because I'm sitting sitting on the floor. So, six key features that I identified which kind of had the biggest impact on kind of creating that really good user experience so I'll go through these in turn, just to highlight the ones in yellow are the features which made the user experience less bad. The ones you mean, or the features which made the user experience better. So, let's talk about that. Okay, so the most important one was really the choice of open source software. Well, the choice to use open source software as opposed to proprietary. So, if you work in schools, you have experienced schools, maybe children, I'm sure you'll be aware that the school environment, the IT environment is dominated by proprietary software. Again, you know, there are reasons I'm sure this is just my outsider perspective looking in. But for me, it was really important to introduce for scientific computing to introduce Jupiter and Anaconda. Because of the open source sort of nature. So for me, it really overcame a lot of potential barriers or a lot of barriers which are often in place with other technical education experiences, such as the some of the ones which I mentioned at the beginning, but you know, I'm not going to cast any shade. So, I guess the most important thing is that, you know, there's no cost in terms of procurement cost. That's really important. So, you know, yes, this was an independent school, a private school, so this is not a state funded school. So they, you know, they do have more resources than, you know, the average UK school, but, you know, we have to serve. We can't assume that everyone there, you know, the students especially. So in terms of their ability to use the software outside of school. So, that stack, you know, I set up Anaconda and Jupiter or Anaconda, the open source distribution, you know, that's now installed in that school in their labs. So I knew the students could access at school. Of course, I wanted them to also be able to install at home if they could. And the fact that it was free was obviously a really beneficial aspect. So, you know, it was just basically whether they could or whether they had the time, which also thinks the other point I want to make is that I really, you know, I mean, I know, I know those reasons why but, you know, for me, for children and for something like computing, which is so, you know, such a critical literacy. I don't like that there was a trade off between the quality of software and basically what, you know, a child's family or, you know, legal guardian on behalf of a child can afford that as something which, you know, I feel is really exclusive, clearly. So open source software is really positive for that. There are other things, so, you know, Anaconda doesn't need that much connectivity. But, you know, if you are an adult with basic digital literacy, it's relatively straightforward to install. And at least for these girls, I can't say for all teenagers but, you know, after I gave them initial explanation and a bit of practice, you know, no problem, they're autonomous. They could do it all on their own, which is, you know, again, why it was so easy for them to set up at home. Okay, so really quick tip. The Coronaze app, so shout out to developer Nicola Holshu, I hope I pronounced your name correctly, who's created this fantastic open source app for iOS. So I do use this with another school where the girls have iPads and it works really, really well. And again, open source, amazing. Okay, so prototyping focus is a really, for me, was really impactful in terms of creating a better user experience. So again, I just got to focus on the visual really. Basically, I basically got them to do data tricks, or at least at the beginning, you know, because remember, first time coders, there was, you know, for some girls a bit of trepidation, you know, it was really sort of unfamiliar, I'm sure there's probably some negative stereotypes as well. And, you know, and to be fair, I was making them do, making them learn, you know, professional level data stack. So I'm not really surprised that it was a bit intimidating. But data tricks. So especially using Unicode, that really worked really well. So obviously here you can see, you know, this is a good way of, so obviously they got the code point for avocado, the avocado glyph. This is helpful for them learning how to use the print function. So mathmask operators. So, you know, I was like, okay, how many avocados should we make? Let's try 100. You know, you have a go, how many would you want to make? So it turns out we discovered that on a sort of standard Windows PC, you can make about a thousand, no, about a million avocados before it sort of starts to crash. But obviously no damage, you know, just restart. So from that kind of data trick, then you can start doing some more fun data tricks. So this works really well as well for young children, young or teenagers. So that's a bit of what I'd like to call emoji math. So so you can see basically how that kind of prototyping as opposed to, you know, kind of long tedious sort of set exercise, you can see how this, hopefully you'll see this, this is quite fun for children. So originality. This is the one I'm just going to also talk about more detailed. Oops. This one. Oh, sorry. This chord, but that's not a message for me. Let's go for originality. So this is quite related to the last point about prototyping. So, you know, we said it was a bootcamp, you know, they had to learn a specific syllabus, you know, which obviously I'd greeted with the school beforehand. So, you know, in terms of these building blocks that was set. But what I, the way I designed the experience was that, you know, we'd learn a building block, we'd learn some sort of confusing information. But then I really encouraged them to think about a kind of a context to link it to so in the kind of cognitive psychology domain. This is what's called knowledge transfer. So it's obviously a term for some of you, which is got picked up by deep learning. But the idea is that you, you basically fuse old knowledge with new knowledge. So this is your old knowledge, or your sort of existing memories. And this was the new knowledge, the computing. And basically when you relate the two, it becomes, well, you learn it more effectively and it also becomes more fun. So let me give you an example. These are things basically the girls, some of the kind of things that the girls came up with. So, you know, you can see why that was quite fun in a Python class. So these are two examples. Here we go. We talked about avocados here, the zombies and the Korean language. So the building block here is obviously conditional statements. And then the context of the prior knowledge is technical term was about zombie apocalypse. We did these. These were two things we did together, like as a class. So, you know, I basically set up the conditional statements and then said, you know, ask them to input, you know, what, what kind of a status is that they think, you know, we should have in this program. And then, you know, what kind of actions should we have. So that was really fun for them. And then also another example. So this was obviously around introducing dictionaries, or you know, generates the concept of data structures. And then we used Korean, or I chose Korean as a topic because I assumed correctly that girls that age would at least be familiar with kpop, if not fans of kpop. In fact, they were fans of kpop. So they were really delighted to learn how to say hello in Korean, which is I hope you pronounce that correctly. So I said, in case you ever meet BTS, which is a really famous kpop band. So they love that. Okay, I'm just going to whack through these, the last points quite quickly, because I want to kind of finish in the next four minutes so that we can have some sort of questions. Okay, so, you know, low latency. So the point I want to make here is that there are times in technical education, definitely at the adult level, where, you know, you're trying a tutorial you're trying something out. It's like, it's a lot of effort. Okay, well, that's, okay, whether regardless of whether it's effort, you know, you do something, and you want to find out whether you're right or wrong. Okay, now you don't really mind too much, if it's wrong, but you kind of want to know, right, you don't want to be waiting like an hour and then go, oh, rubbish, you know, there was whatever was just literally this one character, you want to find out fast, so you want to fail fast. Okay, great if you succeed fast, but the worst is basically in terms of speed is if things are slow. So something which I think really helps in this bootcamp was that so obviously drawing back to this visual was that you could debug faster or sooner because you could find out your error quicker. So this is related to so you know that sequence of avocados and tomatoes, which is supposed to be a sequence. So you can see if they basically they missed out the the nested parentheses, then you get one avocado and 1000 tomatoes, which is not, of course, the intention, but you can find that out really quickly. And actually, it's not that bad, you know, you don't mind getting it wrong, because, you know, it's kind of fun to try and solve, at least in this context, you know, they seem to find it, you know, kind of, you know, just something to try and figure out what was happening, and not they don't feel bad about themselves or frustrated. So hence, less bad user experience. Okay. Okay, really quickly. This slide is about the fact that between myself, and then my colleague, so, Dario so dogs remember well. So we were the Python instructions for this course. It, you know, it was noticed by the teachers that the fact that, you know, Dario and I are not, should we say, the sort of stereotypical modernist tech identities and all background, you know, was noted as by the teachers. So, you know, this is a very academic school, but it's also an ethnically and culturally diverse school. And so, you know, teachers noticed that this, the fact that these were the people in front of them, you know, doing coding, you know, okay, yes, Dario has a very technical background that you know he's won awards from the Royal Society for technical things, computational food dynamics, which I obviously don't understand because I have an economics background. But you know, again, that sort of challenges the stereotype that you know someone who comes from a social science degree, you know, can end up doing, you know, quite, quite cool stuff, which I won't talk about because this is not really the talk for it. But anyway, so that was a positive or less bad user experience that could have been. And then there is the fact that everything was sort of set in as much real with context as possible. So, you know, we talked about the pop culture and the funds of aspects and the originality. Because this school is very academic, I also knew that the girls would care about, you know, certain universities, certain kinds of disciplines, you know, certain kinds of organizations and so I basically made as many links as possible with the Python that they were learning, and these kinds of real world things, which definitely helps them or would have made a better user experience. Okay, so to summarize the user experience, those were sort of six key features obviously there are more. But that sort of drove a better user experience, which drove the awesome outcomes that we saw. Of course, that's quite a mouthful really to go through all those different, different aspects. I think in the most simple terms the way I describe it is that the project was successful, because the girls got to discover how to do new relevant things they couldn't do before, and also upgrade things they were currently doing, which I like to call unlock and power up. And not just students but also the teachers so this isn't going to make a lot of sense if someone looks at these slides standalone but this is a, this is a gift, just a little thank you from one of the teachers who had really appreciated the bootcamp experience, you know, for the students but also for herself. So, the other thing I want to mention is that this case study, you know, I've said scientific and computing education is effective. Of course, there are different approaches, I like to divide it into direct and indirect so this case study would have been direct because it was very Python first. So, you know, it's a Python bootcamp, you've got a Python syllabus, you know, yes then we tie in with your sort of existing familiar knowledge. But, you know, the Python is always the kind of driver. However, there's a, an indirect approach which I use with other schools which is really effective. So, the way that works is that you know, you've got their interests. You can sort of pick one which is sort of more common to say or work more students share that so that they are in design. And computationalize and in this instance, for example, you get code art. So, like I said, you know, the girls discover or the students would discover how to do new things. So maybe they've never done fractals before fractal art like this, or maybe they already do fractal art, but actually maybe doing in Python, it gives them, you know, more power, more functionality, and basically, it sort of makes something they're doing already better. So I guess it's the point really about meeting kids where they are, not where you are, or not necessarily where you want them to be, but where they are today. So, in conclusion, I hope I've convinced you to at least consider that Python for scientific computing day and science isn't just for grownups. You know, it can really spark joy for teenagers and adults. So why not let teenagers have a go. And that was all I had planned. So thank you so much for listening to my talk. And please get in touch, or, you know, hopefully we'll have questions. Thank you. Thank you. So, you know, what are you calling these kids to girls? We do charge for projects, where sort of possible but you know we do do pro bono work as well. So if you're a volunteer, we would definitely like to find a way of working with you but in terms of other ways, school girls. I think, you know, there are there are initiatives to outreach Python, obviously to, you know, to everyone. I think, for me, the scientific computing is really the aspect where, you know, there isn't necessarily that kind of opportunity or access and availability. So I would have to say, I mean, I also I couldn't say for sure but I fairly certain I haven't seen really anyone else doing what we're doing, or at least not with schools, or kind of on a more successful basis. I know there there is a there is a market leader in the UK who I believe they do do something similar but they charge a lot. Let's just put that way. And it is outside of school and in certain areas so I guess the sorry the quick answer really is, please go in touch, you know, in the breakout room maybe. Yeah, I think, I think you can. So there is a you, you can continue this question in the in the discord channel for this track, but there is also a channel in particular for this talk, the name of the channel is talk school school years. Sorry. I think it was okay I think I saw earlier. I think it's quite into school girls. I have it here is Python for school girls. Yes, sorry. And so it's talk Python for school. And then one more question. Leel is saying great talk. How did you find the structure say, in terms of technicians supports and your coworkers that were involved in the project. What was their, their prayer background background. There, sorry, was it time for the background of your coworkers. Oh, find infrastructure right like if you have the support technical support that kind of things. Oh, my great workers, we are a small team. It is, how do I find it was a how do I find my coworkers or their background. Well, my background, the my coworkers tend to have a kind of more general data science background. And then I kind of tend to use my experience. My experience in industry, basically hacking, you know, it solutions or, you know, just basically making things work. So it tends to be me. So in fact, it is me coordinating with the school it departments, which is painful. I'm sure people are aware of that. I hope to answer the question but yeah, please, we'll talk about the breakout room if that didn't provide the information. So it's time for one more question. So if anyone wants to ask the question live, you can click the button to raise your hand and I can enable the microphone. So, let's go. Okay, so I think we're done. Thank you very much. Thank you so much.
 Sheen is going to talk about access to Python education for schoolgirls using avocados,  zombies and Korean. That sounds amazing. Okay.  Okay. Well, good morning, or at least good morning from London. I hope you're having a  good year of Python. I'm sorry we couldn't be doing this in person. I'm sure we're all  sorry, actually. It's been a pretty stressful couple of months, I'm sure for everyone. But  at least we're here sharing online and I'm having a one sided conversation with you,  which is quite weird, but same for everyone. Okay. So I'm just going to start. Let me just  adjust so I see less people. Okay. So accessible Python education for schoolgirls using avocados,  zombies and Korean, which in more general terms, oops, make sure I can move my slides,  would be about accessible Python education using scientific computing and data science.  So I would also just want to say like in normal presentation, I'd want to ask, you know, I'd  want to understand yourself as an audience. I'd like to understand, you know, your backgrounds  and your interests and, you know, are you educators? Are you school teachers and so on and so forth?  But I can't obviously do that. So what I'm going to do, I think the way I'm going to try and use  this time, I'm basically just kind of try and highlight the aspects of this story. The slides  are actually meant to be, they're actually overly detailed. They're supposed to be standalone. So  I'm just going to set this expectation up front just so you understand how I'm going to present.  The slides are meant to be standalone. So if you don't listen to talk, you can understand it fully.  It's also supposed to compensate for the fact that obviously we're using English. And that's  obviously not the most accessible for everyone. So I've written out a lot of the text so that  it's easier to follow. So hopefully that's useful. What I'm going to do is jump around in the slides  a little bit and just highlight the main points I want to make so that we can have a conversation  because I think there's a really big opportunity in this kind of space for school children,  school girls to access scientific computing. I don't have all the answers. You'll find that out.  But I want to start a discussion and I'd really like to talk to yourselves and collaborate and  get your feedback. So okay, what I will go into detail is what the point of this talk is. So I'm  just going to set the expectation up up front. So from my observations, at least in the UK,  technical education for teenagers seems to focus on these kinds of things. So, you know,  this is I'm a very visual person. I'm probably going to talk through the visuals more than the text.  So if you ask a child who's doing coding, what they're doing, it's going to be very likely one of  these kind of options, Raspberry Pi, Arduino, Minecraft, mods, scratch. Really interestingly,  I had to make this point. There are actually a lot of computing teachers in UK schools who are  like VB.net. Yeah, I know it's a blast from the past for a lot of people, but that is the reality.  So my point is that when it comes to learning Python, the work that my startup is doing in  UK schools is demonstrating that scientific computing and data science education can actually  be really effective for some teenage students. So basically, this talk is going to present a case  study. It's going to be of a scientific data stack education based in a London girl's school.  And I'm going to show the kind of successful learner outcomes that can be delivered by this  kind of stuff. So I hope this is familiar to you. I'm probably not great. So I'm going to have to  assume that people sort of understand what Jupyter and these kind of technologies are. But we can  obviously talk about the breakout if you want more detail. So basically, by the end of this talk,  hopefully there's more advocacy for scientific computing and data science as accessible Python  education for teenagers. Because after all, why should us grown-ups have all the computational  fun? And it is a lot of fun. I'm not going to lie. I'm biased. I love data science. But I also want  to make the point, so I'm just going to check my discord, that even before the pandemic, I actually  found scientific computing. I actually found data science actually really helpful for my mental  health. So if I felt really stressed out or really out of control as someone who is higher on the  autistic spectrum, actually doing coding often helped me feel more. It gave me a focus. It made me  feel more comfortable. And actually, that's been something I've turned to as well in this pandemic.  So in the UK, we've really not handled this COVID very well at all. I'm not going to get political  about it. But I'm still effectively in lockdown. And although we've been very privileged in the UK in a  lot of ways, it has been tough. And in the same way which data science has helped me cope better in  this time, I really want to make sure or really want to give that opportunity to other young people  who maybe also might find data science and scientific computing something really positive for their  well-being and not just from a kind of job tech future perspective. So something I have to point out  out front. Obviously, we're talking about children. They're safeguarding. So the students are not going  to be disclosed or identified in any way. So they're going to be anonymous. I will have a use  visuals mainly from this is one of the Mito communities which I founded, my main one. But if you  kind of want to have a sense of the kind of audience I'll be talking about. If you are familiar with  Harry Potter, basically Hermione in the first year of Hogwarts is the right kind of age and gender.  Sorry, that will give you a bit of a proxy. But without the magic stuff because that's fun but not  real. Okay, so here am I. I am a tech entrepreneur. I have been working for really quite a while now.  I think probably the point I want to make is that I don't come from a formal education background.  So I actually, I'm a social scientist. Yes, I know it's kind of weird that I've ended up in  Python via R. So this is the first community I founded was called the R ladies Cone Club which turned  into R ladies London, which then became a founding member of our ladies global. But you know, here we are  here I am at your Python for the second time. And so how did I really get into education so over my career I  really found that I had a, I had seemed to have a certain particular ability to explain, you know, technical  content to non technical people. And then that was something I turned into community outreach, obviously here with R, and then  with the AI club. And then I managed to turn that fashion into a full time job. So I founded an tech startup with a social  mission, which is around democratizing opportunities for young people to level up their modern computing literacy.  Now, that is not a sales pitch. Actually is generally because I need to set the context for the case study, which is about a  project which my startup was commissioned by a girl school. Again, I'm not going to identify the school, it may or may not be  represented by this image here.  So I'm not going to set the exact fee to decide. But it, the project was around delivering a boot camp for non coders to develop  Python proficiency. And I just wanted to give a shout out to the project sponsor, who I can name. Just giving permission. So this is  Madeline Cooper, who's actually a she actually did math at Cambridge. And so she is the person at the time who initiated this  unique pioneering project. And we'll talk about the pioneer aspects. Actually through the talk. Again, I'm going to go through all the  details. The key things I want to pull out here is that it was compulsory. Okay, so this is unlike, you know, the kind of meetups seen that  we probably know and love, where people opt in here. These girls did not opt in. They were forced to, they were forced to  undergo this boot camp, all 120, 11 to 12 year olds, and five of the teachers. So hopefully that sets some context. Okay, project  deliverables. So what was actually delivered. So remember it was boot camp. I decided, of course, to go with Python for  scientific computing, as the sort of the computing application. So I chose this data stack, scientific data stack to  introduce the girls to. And of course, the Jupyter notebooks, as referenced here. And the structure of boot camp. So we said six sessions.  So that was in the last slide. So I structured as basically building blocks with obviously relevant scaffolding because, as I said,  non coders, from non coders to to this in six sessions, or frankly, six hours is obviously a stretch. And actually, because it was a  stretch, I knew it was going to be challenging. It was, it was designed to be challenging. That's the kind of person I am. I'd like to  stretch myself and stretch other people. So the project goals, in terms of the way it was presented to the girls was basically, you  know, I was like, Listen, I know, it's like you're 11 years old. It's like, you probably don't code if you do code, you know, I mean,  fantastic. But I'm going to seem that, you know, you don't have any experience. And that's absolutely normal. I didn't code when I was 11.  I didn't code when I was 20. So I said, in this boot camp, anywhere you can get up on this on this pyramid, I called it, I said is, you  know, is a bonus. So anything you can develop in terms of your computational thinking, critical thinking, creative thinking, fantastic.  I guess one thing to point out here. So, unlike, I guess, other kinds of educational experiences, especially in this kind of school, which was is very  academic. You know, I said, don't compare yourself. No comparison, no competition, you know, you're on your own path, and you have your own pace.  So just focus on that. Okay, I'm going to see why you can still hear me because I just feel like I'm just like talking to myself, which I quite frankly could be so sorry, that's why I keep  checking on this.  It's perfect. It's perfect.  Okay, cool. Yeah, just let me know.  I don't want to be babbling.  Okay, so project outcomes. So there were a small minority of the cohort who had done some coding for some Python, but of course not scientific computing.  So, you know, from a quantification quantified from a quantify perspective, we had 100 new teenage pythons, all girls identified girls and new coding champion teachers, which was super awesome.  But you know, I think I'll let the girls, they're sort of testimony. Excuse me testimonials, do the do the talking for me, although I'll, I guess I'll read out their testimonials but anyway.  So, I guess the things to highlight is that, you know, from a sentiment perspective, I mean, they on the whole, you know, they really enjoyed it.  In fact, so much sorry that one of them said that they love Python, which I'm not gonna lie was really wonderful and you know, it's still a really, really happy memory for me.  But yeah, so you know, from these kind of responses you can see they basically they just wanted to keep doing it they wanted to do at home. They wanted to, in fact they downloaded and conda at home by themselves.  They wanted to keep doing it again after the bootcamp was ending they want to get next year. They didn't want to go back to normal class.  You know, it was just awesome. Okay, this is a point I do want to make.  So, obviously I didn't know the students. I didn't know their backgrounds.  Some of the teachers pointed out to me that there were girls who, you know, in science, for example, they were struggling. They weren't historically known for doing, particularly well on that subject but actually in the bootcamp we were basically with Python.  They were actually excelling, you know, they were sort of, you know, doing better than you know other their sort of classmates who had done coding before.  And, you know, for me that was just really powerful and again, that's just emphasized that you know I feel like science scientific computing and data science could really give young people the opportunity to discover something that they really enjoy and are good at, you know,  and I really want to make sure they have those opportunities to discover that.  So, these awesome outcomes. So why really.  Of course, as a data scientist would want to know.  So, I think basically this is what I want to stress is that I'm not saying all experiences, especially not a tech education I'm not saying they're always, you know, negative user experience.  Although sometimes, you know, I'm not gonna lie sometimes they are, but in this case, you know, for me my analysis was very much that, yes, there are negatives, you know, there are things we don't enjoy.  I mean, I don't know about you but I don't get a lot of pleasure out of, you know, installation and set up. And that kind of troubleshooting is not my favorite.  I, I also know documentation is really important. I like other people's documentation. I am not.  It's not something which fills me with joy writing my own documentation. So, you know, these would be the kind of negatives. But, you know, I think in this experience, I guess, I just want to draw out that, you know, I tried really, really hard to sort of decrease the  negatives, or, you know, make the things which might be bad less bad, and the things which were good to really make them as good as possible, and better.  So, I kind of drew out sort of six specific features.  So just adjusting myself because I'm sitting sitting on the floor.  So, six key features that I identified which kind of had the biggest impact on kind of creating that really good user experience so I'll go through these in turn, just to highlight the ones in yellow  are the features which made the user experience less bad. The ones you mean, or the features which made the user experience better.  So, let's talk about that. Okay, so the most important one was really the choice of open source software. Well, the choice to use open source software as opposed to proprietary.  So, if you work in schools, you have experienced schools, maybe children, I'm sure you'll be aware that the school environment, the IT environment is dominated by proprietary software.  Again, you know, there are reasons I'm sure this is just my outsider perspective looking in. But for me, it was really important to introduce for scientific computing to introduce Jupiter and Anaconda.  Because of the open source sort of nature. So for me, it really overcame a lot of potential barriers or a lot of barriers which are often in place with other technical education experiences, such as the some of the ones which I mentioned at the beginning, but you know,  I'm not going to cast any shade. So, I guess the most important thing is that, you know, there's no cost in terms of procurement cost. That's really important. So, you know, yes, this was an independent school, a private school, so this is not a state funded school.  So they, you know, they do have more resources than, you know, the average UK school, but, you know, we have to serve. We can't assume that everyone there, you know, the students especially.  So in terms of their ability to use the software outside of school. So, that stack, you know, I set up Anaconda and Jupiter or Anaconda, the open source distribution, you know, that's now installed in that school in their labs.  So I knew the students could access at school. Of course, I wanted them to also be able to install at home if they could. And the fact that it was free was obviously a really beneficial aspect.  So, you know, it was just basically whether they could or whether they had the time, which also thinks the other point I want to make is that I really, you know, I mean, I know, I know those reasons why but, you know, for me, for children and for  something like computing, which is so, you know, such a critical literacy. I don't like that there was a trade off between the quality of software and basically what, you know, a child's family or, you know, legal guardian on behalf of a child can afford that as  something which, you know, I feel is really exclusive, clearly. So open source software is really positive for that. There are other things, so, you know, Anaconda doesn't need that much connectivity.  But, you know, if you are an adult with basic digital literacy, it's relatively straightforward to install. And at least for these girls, I can't say for all teenagers but, you know, after I gave them initial explanation and a bit of practice, you know, no  problem, they're autonomous. They could do it all on their own, which is, you know, again, why it was so easy for them to set up at home. Okay, so really quick tip. The Coronaze app, so shout out to developer Nicola Holshu, I hope I pronounced your name correctly, who's created this fantastic open source  app for iOS. So I do use this with another school where the girls have iPads and it works really, really well. And again, open source, amazing. Okay, so prototyping focus is a really, for me, was really impactful in terms of creating a better user experience.  So again, I just got to focus on the visual really. Basically, I basically got them to do data tricks, or at least at the beginning, you know, because remember, first time coders, there was, you know, for some girls a bit of trepidation, you know, it was really sort of unfamiliar, I'm sure there's  probably some negative stereotypes as well. And, you know, and to be fair, I was making them do, making them learn, you know, professional level data stack. So I'm not really surprised that it was a bit intimidating. But data tricks. So especially using Unicode, that really worked  really well. So obviously here you can see, you know, this is a good way of, so obviously they got the code point for avocado, the avocado glyph. This is helpful for them learning how to use the print function. So mathmask operators.  So, you know, I was like, okay, how many avocados should we make? Let's try 100. You know, you have a go, how many would you want to make? So it turns out we discovered that on a sort of standard Windows PC, you can make about a thousand, no, about a million avocados before it  sort of starts to crash. But obviously no damage, you know, just restart. So from that kind of data trick, then you can start doing some more fun data tricks. So this works really well as well for young children, young or teenagers.  So that's a bit of what I'd like to call emoji math. So so you can see basically how that kind of prototyping as opposed to, you know, kind of long tedious sort of set exercise, you can see how this, hopefully you'll see this, this is quite fun for children.  So originality. This is the one I'm just going to also talk about more detailed. Oops. This one. Oh, sorry. This chord, but that's not a message for me. Let's go for originality.  So this is quite related to the last point about prototyping.  So, you know, we said it was a bootcamp, you know, they had to learn a specific syllabus, you know, which obviously I'd greeted with the school beforehand. So, you know, in terms of these building blocks that was set.  But what I, the way I designed the experience was that, you know, we'd learn a building block, we'd learn some sort of confusing information. But then I really encouraged them to think about a kind of a context to link it to so  in the kind of cognitive psychology domain. This is what's called knowledge transfer. So it's obviously a term for some of you, which is got picked up by deep learning.  But the idea is that you, you basically fuse old knowledge with new knowledge. So this is your old knowledge, or your sort of existing memories. And this was the new knowledge, the computing.  And basically when you relate the two, it becomes, well, you learn it more effectively and it also becomes more fun. So let me give you an example.  These are things basically the girls, some of the kind of things that the girls came up with. So, you know, you can see why that was quite fun in a Python class.  So these are two examples. Here we go. We talked about avocados here, the zombies and the Korean language. So the building block here is obviously conditional statements.  And then the context of the prior knowledge is technical term was about zombie apocalypse. We did these. These were two things we did together, like as a class.  So, you know, I basically set up the conditional statements and then said, you know, ask them to input, you know, what, what kind of a status is that they think, you know, we should have in this program.  And then, you know, what kind of actions should we have. So that was really fun for them. And then also another example. So this was obviously around introducing dictionaries, or you know, generates the concept of data structures.  And then we used Korean, or I chose Korean as a topic because I assumed correctly that girls that age would at least be familiar with kpop, if not fans of kpop. In fact, they were fans of kpop. So they were really delighted to learn how to say hello in Korean, which is  I hope you pronounce that correctly. So I said, in case you ever meet BTS, which is a really famous kpop band. So they love that.  Okay, I'm just going to whack through these, the last points quite quickly, because I want to kind of finish in the next four minutes so that we can have some sort of questions.  Okay, so, you know, low latency. So the point I want to make here is that there are times in technical education, definitely at the adult level, where, you know, you're trying a tutorial you're trying something out.  It's like, it's a lot of effort. Okay, well, that's, okay, whether regardless of whether it's effort, you know, you do something, and you want to find out whether you're right or wrong. Okay, now you don't really mind too much, if it's wrong, but you kind of want to know, right, you  don't want to be waiting like an hour and then go, oh, rubbish, you know, there was whatever was just literally this one character, you want to find out fast, so you want to fail fast.  Okay, great if you succeed fast, but the worst is basically in terms of speed is if things are slow. So something which I think really helps in this bootcamp was that so obviously drawing back to this visual was that you could debug faster or sooner  because you could find out your error quicker. So this is related to so you know that sequence of avocados and tomatoes, which is supposed to be a sequence. So you can see if they basically they missed out the the nested parentheses, then you get one avocado and 1000 tomatoes, which is not, of course, the intention, but you can find that out really  quickly. And actually, it's not that bad, you know, you don't mind getting it wrong, because, you know, it's kind of fun to try and solve, at least in this context, you know, they seem to find it, you know, kind of, you know, just something to try and figure out what was happening, and not they  don't feel bad about themselves or frustrated. So hence, less bad user experience. Okay. Okay, really quickly. This slide is about the fact that between myself, and then my colleague, so, Dario so dogs remember well.  So we were the Python instructions for this course. It, you know, it was noticed by the teachers that the fact that, you know, Dario and I are not, should we say, the sort of stereotypical modernist tech identities and all background, you know, was noted as  by the teachers. So, you know, this is a very academic school, but it's also an ethnically and culturally diverse school. And so, you know, teachers noticed that this, the fact that these were the people in front of them, you know, doing coding, you know, okay, yes, Dario has a very technical background  that you know he's won awards from the Royal Society for technical things, computational food dynamics, which I obviously don't understand because I have an economics background. But you know, again, that sort of challenges the stereotype that you know someone who comes from a social science degree, you know, can end up doing, you know, quite, quite cool stuff, which I won't talk about  because this is not really the talk for it. But anyway, so that was a positive or less bad user experience that could have been. And then there is the fact that everything was sort of set in as much real with context as possible.  So, you know, we talked about the pop culture and the funds of aspects and the originality. Because this school is very academic, I also knew that the girls would care about, you know, certain universities, certain kinds of disciplines, you know, certain kinds of organizations and so I basically made as many links as possible  with the Python that they were learning, and these kinds of real world things, which definitely helps them or would have made a better user experience. Okay, so to summarize the user experience, those were sort of six key features obviously there are more.  But that sort of drove a better user experience, which drove the awesome outcomes that we saw. Of course, that's quite a mouthful really to go through all those different, different aspects. I think in the most simple terms the way I describe it is that the project was successful, because the girls got to  discover how to do new relevant things they couldn't do before, and also upgrade things they were currently doing, which I like to call unlock and power up.  And not just students but also the teachers so this isn't going to make a lot of sense if someone looks at these slides standalone but this is a, this is a gift, just a little thank you from one of the teachers who had really appreciated the bootcamp experience, you know, for the students but also for  herself.  So, the other thing I want to mention is that this case study, you know, I've said scientific and computing education is effective. Of course, there are different approaches, I like to divide it into direct and indirect so this case study would have been direct because it was very Python first.  So, you know, it's a Python bootcamp, you've got a Python syllabus, you know, yes then we tie in with your sort of existing familiar knowledge. But, you know, the Python is always the kind of driver. However, there's a, an indirect approach which I use with other schools which  is really effective. So, the way that works is that you know, you've got their interests. You can sort of pick one which is sort of more common to say or work more students share that so that they are in design.  And computationalize and in this instance, for example, you get code art. So, like I said, you know, the girls discover or the students would discover how to do new things. So maybe they've never done fractals before fractal art like this, or maybe they already do  fractal art, but actually maybe doing in Python, it gives them, you know, more power, more functionality, and basically, it sort of makes something they're doing already better. So I guess it's the point really about meeting kids where they are, not where you are, or not necessarily where you want them to be, but where they are today.  So, in conclusion, I hope I've convinced you to at least consider that Python for scientific computing day and science isn't just for grownups. You know, it can really spark joy for teenagers and adults. So why not let teenagers have a go.  And that was all I had planned. So thank you so much for listening to my talk. And please get in touch, or, you know, hopefully we'll have questions.  Thank you.  Thank you.  So, you know, what are you calling these kids to girls?  We do charge for projects, where sort of possible but you know we do do pro bono work as well. So if you're a volunteer, we would definitely like to find a way of working with you but in terms of other ways, school girls.  I think, you know, there are there are initiatives to outreach Python, obviously to, you know, to everyone. I think, for me, the scientific computing is really the aspect where, you know, there isn't necessarily that kind of opportunity or access and availability.  So I would have to say, I mean, I also I couldn't say for sure but I fairly certain I haven't seen really anyone else doing what we're doing, or at least not with schools, or kind of on a more successful basis.  I know there there is a there is a market leader in the UK who I believe they do do something similar but they charge a lot. Let's just put that way.  And it is outside of school and in certain areas so I guess the sorry the quick answer really is, please go in touch, you know, in the breakout room maybe.  Yeah, I think, I think you can. So there is a you, you can continue this question in the in the discord channel for this track, but there is also a channel in particular for this talk, the name of the channel is talk school school years.  Sorry. I think it was okay I think I saw earlier. I think it's quite into school girls.  I have it here is Python for school girls. Yes, sorry.  And so it's talk Python for school.  And then one more question. Leel is saying great talk. How did you find the structure say, in terms of technicians supports and your coworkers that were involved in the project.  What was their, their prayer background background.  There, sorry, was it time for the background of your coworkers. Oh, find infrastructure right like if you have the support technical support that kind of things.  Oh, my great workers, we are a small team.  It is, how do I find it was a how do I find my coworkers or their background. Well, my background, the my coworkers tend to have a kind of more general data science background.  And then I kind of tend to use my experience.  My experience in industry, basically hacking, you know, it solutions or, you know, just basically making things work. So it tends to be me. So in fact, it is me coordinating with the school it departments, which is painful.  I'm sure people are aware of that.  I hope to answer the question but yeah, please, we'll talk about the breakout room if that didn't provide the information.  So it's time for one more question. So if anyone wants to ask the question live, you can click the button to raise your hand and I can enable the microphone.  So, let's go.  Okay, so I think we're done. Thank you very much.  Thank you so much.
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