Episode 35
 Sean Tibor: Hello and welcome to teaching Python. My name's Sean Tibor. I'm a coder who teaches, 
Kelly Paredes: and my name's Kelly Schuster Paredes, and I'm a teacher who codes. 
Sean Tibor: This is episode 35 not just coders. So today we're going to be talking about people who need to learn how to code, who are not coders, are not necessarily going to be software developers, and how do we reach them. So Kelly, 
Kelly Paredes: it's like, it's an episode for me. 
Sean Tibor: I know, right? Like this is, this is all about you. Kelly. Let's, let's talk. So it 
Kelly Paredes: feels like I'm sitting on a couch right now. I know. We 
Sean Tibor: were joking because we have new, a new audio equipment that we're working with this this week. New headphones to try to make sure we can hear ourselves better. And it sounds like we're on NPR. So I feel like welcome to all things considered. 
Kelly Paredes: I'm going to try not to giggle so much cause it's really in my ears, but it's all thanks to our sponsors. Yeah. 
Sean Tibor: So we're, um, we've got a couple of new sponsors that, uh, recently we've had a partnership with, uh. With code challenges and pie bites. So a lot of good things have been happening recently related to sponsorship, and that's all going towards helping us produce this podcast. So it gets to you and your earbuds a little bit faster. 
Kelly Paredes: Sounds good. Are we going to start the winds of the week? 
Sean Tibor: Sure. Would you like to go first, Kelly? 
Kelly Paredes: Yes, please. So you don't steal it. I don't know what's worse. Me going first or me going last. But I want to go first today because in, in light of our conversation with, um, everyone should learn to code and not just become a programmer. Um, I think the win of the week is we introduced a new unit in the seventh grade and it's about how do we use libraries in Python to save time and make life easier? And although the kids. Aren't necessarily diving in and making products yet. It's just opening the window, their eyes to what's going on in Python and how the things that are being developed in the background or from other people, um, can actually be used to make good products. 
Sean Tibor: Yeah. I think they're really seeing it in that seventh grade context of, you know, you are in middle school, you're learning a new concept. In this case, Python programming. And then having the kind of curtains drawn back a little bit so you can see, Oh wow, there's so much more here that I wasn't seeing right away because I was focused on learning the basics to start. So I think it's been a really good unit. I, I've been teaching it alongside you and watching the students really start to go, Oh wow. I didn't know it could do that. Or there's a whole library for this. That's great. Um, and it's interesting to hear their justifications cause they get a choice in which library they want. Right. To learn about. And so we've had everything from, well, I'd really like to be able to use  to be able to do my math homework for me too. I'm using scientific Python because our OSI PI, because it sounds really interesting to be able to use Python with science, which they're right. It is. Um, and then I'm going to learn about Aero because it's just a cool name. Like. Okay, good luck. Have fun with that. 
Kelly Paredes: Yeah. Uh, my best part of it for me is the fact that I asked them to put on a Likert scale of, of the libraries that they've looked at and whether they're gonna use it and they're saying, how do you put it on a scale? And I was like, Oh, if I can open up on the front page and read it from pie pie, then you know, it's gotta be a good high level. I might Likert scale. And they're like, give us an example. I was like. Matplotlib 
Sean Tibor: nice. Yeah, it's, it's really cool. They're, they're looking at all sorts of libraries and not just easy ones. They're looking at map, plot lib, pandas. They're looking at PSI PI, and we just want them to see that there are people doing a lot of really great work out there so that you don't have to do as much work on your own. Why reinvent the wheel? 
Kelly Paredes: Right. And you found one. We keep finding them, so we keep finding more interesting ones to put on the list. You found the translate. 
Sean Tibor: Yeah. I found a Google translate library that three lines of code lets you access Google translate and get translations, uh, for text. It's pretty cool. 
Kelly Paredes: Yeah. It's got a high likeability three lines of code. 
Sean Tibor: Yup. Exactly. Exactly. 
Kelly Paredes: Okay. So my wind was good this week. What's your, when 
Sean Tibor: you had a really good one? I have to say, I don't think I can measure up to that. Um, honestly, my win this week is that we are having our first match of the `sports club, uh, that I'm, uh,, uh, sponsoring in the middle school. So we're. Trying to do something a little bit different. Uh, especially for those students who may be like some sports but aren't really into sports. The, we're doing something where we are competing with other teams playing a game called rocket league, which is basically RC cars playing soccer online. And we have our first match, uh, today actually against a team from Albuquerque, New Mexico. So , it's rare that our regular sports teams  get to play across state lines, but we're doing it with our first match, which is kind of fun. 
Kelly Paredes: It's going to be great. I can't wait to see parts of it. 
Sean Tibor: Yeah, it should be really great. The kids are excited about it. The other team's excited about it, and it's all coming together in this booming area of e-sports. So if you're not familiar with it, definitely give it a Google search and check it out. Um, some of the championship matches are just mind blowing in terms of how big they've become. The. Uh, players are celebrities in their own rights. The prize purses are huge in a lot of cases. So, um, we're just trying to have some fun with it and wearing some of those basic, uh, sports benefits of discipline, teamwork, strategy, coordination, all of those things that help us become better people. And we're using video games and e-sports as a way to do that. 
Kelly Paredes: Very cool. So onto our episode. 
Sean Tibor: Yeah, we have a topic right. 
Main TopicKelly Paredes: We actually got this tie up topic, um, from a question that we were asked. Um, how do we, the, I'm trying to think of how the question was actually formulated cause it was really, it was, it was really well done. It was to the more  it was more or less, you know, let's, let's put things in perspective. Not everyone you teach is going to code. I'm like, yes. I think that's pretty a pretty well known fact for computer science teachers. We're not necessarily. Making sure that everyone we teach, it's going to be a programmer in the, 
Sean Tibor:  and let's be precise, not everyone is going to be a software engineer or a computer science major in college. There's, a specific need for that in a specific interest area. And I think anybody who's been in computer science or has touched upon it. In academia has seen that it's, it's a very specific discipline and it covers a lot more than just how to code. It covers a lot of the ways that we think about how we compute and calculate and how we process information and represent it and store it. And it's a very broad category in a lot of ways. And it can include things like robotics and AI and machine learning and all these other things that come under the umbrella of computer science. But even with as broad of a topic as computer science. Not that many of our students are actually going to go off and be computer science majors or be computer scientists with a formal education. So that brings the question. You know, what are, what's the purpose of teaching every student how to code? And we do teach every student how to code in our middle school. 
Kelly Paredes: Yeah. And I think I did a, I did what I always do. I go out and I start researching because I started thinking there, the hour of code is starting next week, and there was this huge push that everyone should learn how to code. The hour of code goes around. We started block coding, coding started becoming into the school. And so I started researching and. I found three articles and all of them were from 2017 which I thought was interesting. So maybe this is a reoccurring topic, but I think it's a good one. 
Sean Tibor: So maybe 2017 was the golden age of why everyone should learn how to code articles on Google. Right. And so nothing better has come along since in the index, I guess. 
Kelly Paredes: Well, maybe we'll try to make it better. 
Sean Tibor: Um, I mean, I think it's, it's an interesting question. Um, and I think that. There's many layers to it. And there's many different ways that you can look at this. Um, for me as someone who's always thought of computer science as a very applied practical sort of skill set or knowledge base, um, and that's because I'm not a computer science major, right? I, I was in a program that was more applied computer science to business problems and very practical. And I also went to a university that had a very practical focus on computer science and the uses of it, right? So. For me, I always think of computer science as being very practical. So one view that we can take, or the first view is that it lets us solve problems in a faster, easier, more efficient way. So it makes things easier for you if you know how to program, but that's not the only way to look at it. Right. Um, what's another way that you look at at Kelly in terms of like the, the teaching mind, why we teach computer science, 
Kelly Paredes: and I think. I think as I start going into coding more, I've, I really have noticed a difference in the way of my thinking of how I approach problems. Um, how I, I start looking at how to abstract the details and start to, to group things. So for me, it's this way of, of having some sort of structure in my life for solving problems. How do I tackle that? And, and it changed. It changed when I started coding because I knew literally nothing about Python. I knew literally nothing about, I mean, maybe a little bit from, from Lego programming and Mindstorms with the loops and, and the basic chord of programming. But that concept of really chunking. And understanding that a problem has to go through a certain certain set of steps in a certain, in a specific way, and being able to break that down as has really structured my, my problem solving. Yeah. 
Sean Tibor: I think that's a really good point. And that's something that is really different for a lot of students that.  what we really want them to do, or the purpose of learning is really learning how to think, how to retrieve information, how to process it, how to be insightful, how to be creative, how to find those, those ways to uniquely approach the world around you. and for me, looking at the way that students look at the world.  and I think many adults too, we get ingrained in our approach and our viewpoint, our perspective on how we think about things. And so many problems become impossible because they're just too big, right? Or no one's ever solved that before, so we can't solve it now. Um, and where it's different with a computational thinking mindset or a coding mindset is that any problem can be solved if it's broken down. You know, to the simpler parts, right? That deconstructive approach to solving problems is very, very powerful. And it's deceptive because it seems like it's anything, you know, it can be solved that way. Um, and yet what it turns into is like there are some problems that are still so complex that we haven't figured out how to break them down. Right? 
Kelly Paredes: Absolutely. And, and the funniest thing for me is we're trying to teach this. I wouldn't say it's necessarily abstract, but in some areas it is abstract. This abstract way of thinking in this abstract way of thinking logically to to teenagers and pre teenagers, and knowing that this whole idea of abstract thinking doesn't really develop until after they're 1314 1516 years of age. So it's kind of like we're helping that. That neural connection and their brain to start firing. We're, we're, we're making there. There's some Nabsys happen and we're, we're leading that pathway of how do they solve these problems. 
Sean Tibor: Yeah. I think  at this age, it's really about getting them started on that path. The one step down that path, and I think about it with our . Computer science, the the kids that are going to go off and be a biologist or be a lawyer or be a teacher. How do we give them those experiences now so that they can think, Oh, well, I know how to solve this problem, or I can solve this problem. Because one time I saw something like that that was similar when I was in middle school or when I was in high school, or something along those lines. So just that starting them on the path of thinking a little bit differently about. The challenges that they face or the world around them? 
Kelly Paredes: Yeah. I think another one on my list, and the more I think about this, the more time, more examples I can give, but we actually help them learn how to use computers better. There are so many skills involved. Just an email last night, miss, there's a, my computer program has frozen and it's not doing anything. I think you need to fix this problem. And you answered it beautifully today. Um, you were using a while loop. Perhaps your computer program got stuck in this problem of trying to go through the code and never had a break. And the girl's eyes lit up and she was like. Oh, right, 
Sean Tibor: right. Well, it, it helps you understand how machines calculate for us, how they compute, how they think through problems. Right. Um, it. And it's a really important skill to have that at least the smallest of insights into how a computer's working behind the scenes or some of the exposures to computing concepts. Because it gives you a framework in which to understand how the. You know, computers that surround us on a daily basis actually function and know, you know, maybe you'll be able to solve some of your own problems or get yourself unstuck when problems arise from the computers that you're trying to use. 
Kelly Paredes: Absolutely. I also, I remember this other conversation I had with the student about, um. Algorithms, and we were talking to AI and it these light bulb moments that don't really get to happen unless you are in a place where you're constantly using a computer and you're talking about. Concepts with the computer. So I think for our non coders, just that ability to one, know where the asterick key is. Um, no how, how a little bit, the basic understanding of how websites work, how things happen in the background, I think, I think that's a really huge benefit. 
Sean Tibor: Right. And you know, I, we, 
Kelly Paredes: sorry. 
Sean Tibor: Yeah. We've been talking about this a lot in the context of, Oh, well, we're giving basic knowledge or foundational knowledge for people that they can use later in life. But the reality is too, is that, you know how many data scientists are out there now that are not traditionally trained programmers. But they still use Python code on a regular basis as a core part of their job, right? Or researchers who are trying to analyze a ton of data and so, or, um, scientists or doctors or lawyers who have to parse through a ton of information related to case law or case history or any of those things. Um, how many people. Are going to be using a tremendous amount of code in their careers or who are already using a tremendous amount of code, but maybe don't, don't have that classic computer science education. So we're still starting them on the path and whether that path is five more steps down the line, or 500 or 5,000. Towards their, you know, sophisticated coding or the role that coding and programming plays in their lives. This is something that they have to start at some point and the earlier we can start them, the sooner they can find out if this is something that they're good at in, they can estimate the length of their journey that it takes them on. 
Kelly Paredes: Absolutely. . Another point about. Non programmers, non future coders is I think it, it opens the door to looking at math and science differently. I notice a lot of times we bring in data. Online, we show them when we collect weather that we can actually go and scrape, um, weather reports or information online. Or we can collect data in part and put it into graph and really analyze it. And we can do math and we can do simple math. And having them work through those math problems and tell a computer how to calculate that math problem really gives a new, um, light into what they're learning. 
Sean Tibor: Well, I think it's, it's more than just the. Different framework or the new new way of viewing math through this lens of computer science. When you apply a computer to a lot of these math and science problems, it unlocks capabilities that you just otherwise wouldn't have. You wouldn't be able to solve, you know, 10,000, uh, equations with a paper and pencil and a reasonable amount of time unless you're some sort of genius savant. Right. Um. But you 10,000 equations on a computer can be done in a fraction of a second. Right? Setting up the problem or setting up the algorithm in computer science or on a computer is the effort. The actual execution is something that you can, you know, use to better understand science or better understand math. How could you look at, you know, or you know, you could look at, here's the weather for the last week. Here's the temperatures that we measured every day for seven days and have a basic understanding of, of what's happening. But. What happens when we say, now here's 10,000 weather records, right? Or here's 100,000 here's every weather measurement that's been taken at this weather station since it first began, you know, 130 years ago, and it's every daily measurement that's been taken. Go do something without, what does that look like when you can start to look at the science of weather over time, when you're not encumbered by the mechanics of doing the calculations, when you can use the computer as the tool that does the calculation for you. 
Kelly Paredes: And it's funny, it takes me to the point my son in lower school is learning how to speak out to talk out the math problems, to explain why he's doing something. And. That whole point of the mathematical computation that you were just saying, if the kids could just copy three X plus two and put it into a computer. It would still produce what they produce in the classroom. But it's funny when you have to tell a kid, well, what is three X? What does that really look like? What is that really happening? What's really happening with that three X? They kind of look at you like you're weird. You know? They don't really get that fact that it's three times and variable, and when you start to talk that way in the, in the computer world and you're telling them that, that has to go into the computer, that way you're, you're developing this understanding and mass. That sometimes I think we neglect in the math classrooms. 
Sean Tibor: Yeah. I think it's, it's challenging. I know that I didn't have a lot of that. Right. It was a lot of those concepts came later when I was learning computer science when I was learning how to code, so. Being able to understand that and deepen my relationship with math, even as the math itself kind of got simpler, right? Like the math that I use on a regular basis as a programmer is pretty basic stuff, but I do a lot of it. Right. I'm, I, and I tell that frequently to the students is that this is what computers are really good at. If you solve the basic problem, you can then do that. As almost as many times as you want over and over and over again with different inputs and it costs you very little to do that so you're not spending more time to do more calculations. You spend the time setting up the problem and then letting the computer do the heavy lifting for you, 
Kelly Paredes: which is one of the reasons why we learn how to code, because programming makes things easier for us. Automate the boring stuff. We can't say that enough if, if, if you don't really want to be a programmer. Fine. If you don't really want to be a coder or do that in the field, fine, but you, I know my life would be a lot easier if I had some more skills in order to automate more things in my life. So this, this benefit that I feel we're giving the middle schoolers and this age group. They can continue to build on and really make things better and easier for them in the long run. 
Sean Tibor: Exactly. I think that's really going to help them think about the, where they spend their time. Right. And the time is the only commodity we can't make get more of. Right. We can't get more time in our day. We can't get more time in our lives. And so the question is how do we use that time. To the most effective, you know, point where we see the best benefit for ourselves and for those around us. So I think that's where programming helps us, you know, use that time better. Right. And use it in a, in a smarter way. And I think. You know, one of the things that is kind of the antithesis of that is when it gets hard, right? And when things get tough, when the road gets Rocky on solving that problem or creating that thing that you're making or trying to, I just figure that one thing out. How do you know what's persistence versus folly, right? Like how do you know your limits and how do you expand them?  and I think that's where programming and computer science can really teach you a great deal of persistence because things are not going to work the first time. They're just not going to.  it's rare that I write code and I , run it and everything works perfectly the first time, maybe for two or three lines of code, but certainly not for anything more than that. 
Kelly Paredes: And I love that about you. When you're teaching, you always remind them, listen, I've been coding a long time. You're not seeing what I was like and when I was 16 and 17 and spending hours and hours and hours trying to do something. We emphasize that aspect a lot that I've been learning for a year and a half. I showed them that I would get frustrated. I have my calming down spray. I bang on the table sometimes when I hit hit a moment where I can't program and Sean and you say to the kids, yes, ms parade is, is having her frustration at least. So that persistence though, that. Bill. We want to show them that we, we got that from learning how to code. 
Sean Tibor: Right. And the persistence. Really, the payoff from that is that, you know when things are tough or that when you haven't solved a problem, that the yet word belongs in there, right? Like, I haven't solved this problem yet. I haven't figured this out yet. Yet, or I'm going to figure this out. It's just a matter of working through the problem. So it's that confidence that comes from, you know, time spent and time and the effort that earns you. The ability to say, I know I'm going to get this. I know I'm going to figure it out. And you know, it's funny, I was talking with a Julian's acquirer from pie bites about this, and he was talking about this idea that we pitched, I dunno, a couple dozen episodes ago about how when you're working on a project. When you have it finished, when the time that you're spending on it right is not returning that much value to you to set it down. Right.  there's a point where it doesn't pay to be more persistent or to invest more time into a project because you're not going to get the value back from it, but then to wait six months and come back when you've grown and when you've become a better programmer, that you'll be able to pick it up and keep moving. Now the relevant part of this for non coders is that that approach is not unique to coding. It's not something where you have to be a computer science major to have persistence. Like we don't have a, right. To say that, right? Like computer science majors haven't earned a monopoly on, on persistence. Right? So that can be used in many, many other fields. Knowing that I can figure this out and I will make it work because I've done it in the past and I know that I can. And that confidence that's earned through persistence is really important, you know, for non coders, for people who are working in other professions and have learned how to code along the way. 
Kelly Paredes: Yeah. And it's, it's an educational buzzword, you know, growth, mindset, resilience, persistence. Um, 
Sean Tibor: I think grit is being used, right? 
Kelly Paredes: So, yes. Um, it is one that was around, it's been, it's been coming up in our social, emotional skillsets that we're supposed to develop. Time moment when we see the kids realize that if they just stick with it and we tell the kids that aren't really getting coding, we say, listen, it's not that the kids around your smarter, it's not that the kids around you are better at coding is because they've put in a little bit more time. And they've given a have a little bit more persistence at trying to solve the problem. Then you have some more or 
Sean Tibor: simply that at this stage it's a little bit easier for them, right? Like this part of learning how to code is easier and you may pull ahead of them later when it's easier for you. Right. And I remind students that, especially, I had one student who came up to me and said, you know, I'm a little bit slower than the other students when it comes to reading. Like it's a diagnosed thing. I'm not just saying that. You know, like I am slower when it comes to reading. And I said to the student, but I don't care how fast you get there. that's not the important part. It's not a race to figure out who can be the best  Python program or the fastest. It's really about who's going to learn it and learn it well, and you start using that. So I said, use your difference as your strength, which means that if it takes you a little bit longer, it probably means that you're going to read it slower, which means you're probably going to read it better, and you're going to understand it deeper. So use that as your strength so that you can be that superstar programmer. Even if it takes you a little bit longer to get there. Who cares? No one's measuring how long it takes. 
Kelly Paredes: Yeah. And I forgot to add one to the list, and you made me remember. You know, I always say it in the class and we say it a lot. The secret to life, well, I say it, the secret to life is reading. So programming, if you're not going to be a coder, at least you're going to learn how to read and read slowly. So that triggered a thought for me. We constantly tell the students, you have to slow down. You have to read the problem for what it is. What it's telling you. Look for all the details. And I think that skill is something that we actually overlooked on the list, and we're putting it on there. 
Sean Tibor: Yeah. You know, I think the other thing that I would add though, the item that's not on my list either, is that I think programming teaches you to value diversity and different viewpoints and the ways that people solve problems in different ways. And that's one of the things I love about meeting people in this space, is that. There's no one right way to solve a problem. and we're all focused on how do we figure this out? Or how do we make this thing, or how do we do this a little bit better? How do we think about our, how do we just be more creative? Right? And that's what I love is, is seeing what, how other people think. And coding is a window into the way that people think. And that. You don't get that in a lot of other places. I mean, actually you do in a lot of places, right? But not in this way where you can literally go on, get hub and access someone's brain or the collaborative efforts of many people's brains. And when you look at their code, it doesn't matter what they look like. Or what they sound like, or how tall they are, or how short they are, what color their hair is, right? Like those are all parts of who they are. And those are the parts that have created this code that you're looking at and you're able to see. And to see someone come up with a beautiful solution to a problem that you couldn't have come up with yourself is one of the most thrilling parts of being a computer science. And that's why this diversity within our community is so beautiful because it helps us. See people for who they are and what they can contribute, not just what they look like or what they sound like. And I think that's one of the things that I like to bring across in the classroom is it doesn't matter where you're coming from, it doesn't matter what you look like or who you are. Anyone can write code and anyone can come up with a really interesting piece of software, really interesting approach to a problem or a product or a service or whatever it is, no matter where they're coming from. And I think that that is a really. Amazing opportunity. 
Kelly Paredes: Absolutely. That's, that was beautifully said. I have nothing to add to that, that, that just hit everything in my, um, my bias curriculum that I've been looking at to help us get. So yes, check. We do that in computer science. Um, I think another point is when we're coding, when we're showing them things or when you're showing them things that they've done, we, we. Open the doors to allow them to understand their world, what's going on behind the scenes of everything, and start to look at their phones differently. Look at the TV differently. Look at Alexa differently and say, wow. That's actually someone's done that. Someone's, someone's made that someone's coded, that someone's written the program and spent the hours and I'm just writing a rock, paper, scissors activity, and that took me forever. What did it take that person to do? To develop what. We have now 
Sean Tibor: probably a lot of banging their head against the table 
Kelly Paredes: and a lot of calming spray. 
Sean Tibor: Yeah. I think that's really important and it works. It looks, you look at it from different perspectives. One is the ability to see the technology differently that they use on a daily basis, especially for our students that have grown up. You know, using an iPad from birth basically, right? Or using technology from very early ages. They see this differently now for having taken a computer science course. I think the other thing that's useful for non coders particularly is the ability to see the world differently through this programming lens. Right? And that we haven't even really gotten into things like object oriented programming or ways that we represent real world objects. But one of the things that I really like. Is when we start talking about functions and how to package up, um, content, you know, or package up repeated functions, repeated actions, instructions, you know, so that they can be more modular and reusable. And we start making those. Analogies to the lives that they lead, that they lead. The, the middle scores, like brushing your teeth in the morning is a function, right? And it has smaller parts to it. There's smaller actions as part of it, and as part of bigger functions and it can be reused. And all of these things that help them see, Oh wait, the world around me can be viewed through a very different lens than the one I currently employ. And for the kids who start to see that, it changes a lot of other. Ways that they see the world. Also, when they start to see, not just hear all the things that I do, or here's the way that the world is, but they start to see the way the world could be. And that to me is really interesting because they start to see. Problems that can be solved. They start to see ways that they can take action locally in the world around them to understand their world a little bit, a little bit better, to make their world a little bit better, to relate to people a little bit better when they start to see that this is something that they can actually have an impact on. 
Kelly Paredes: It was really cool. We just had an assembly and what the speaker asked the kids to, here's an open mic. Why don't you pitch , your elevator pitch and, and. For some possible products that you think would be beneficial to the world and some of the solutions, I'm not so sure. Maybe they would have been there without the computer science background, but I think we have a lot more kids talking about sensors and, and things that they can do in order to modify or benefit their lifestyle and they're really using that. That problem. That's problem solving tactic and digging into those solutions. Those things that they know if they create, will make their place in this world better, 
Sean Tibor: right? It's a very local view of what's going on. And I, I mean that as the highest compliment, right? Because what they see and hear on the news all the time are the big issues, right? Here's the climate change, or here's politics, or here's international relations or terrorism or whatever. And he's big. Huge problems that they really don't feel relate to them. You know, in many cases are replaced by problems that they can actually solve and that they can do something about. And that is a really great way to start seeing the world around you rather than being this world that you can't change and you can't improve upon to being, here's a bunch of things that I can do something about. 
Kelly Paredes: Absolutely. 
Sean Tibor: Okay. So that gives us, I mean, I think I've lost count of all the different reasons here. 
Kelly Paredes: Now we're just making this up as we got, and I was kidding. 
Sean Tibor: I think these, but these reasons are broadly applicable. And that's the one things that we really like about this. When. We talk to parents when we talk to other educators, when we talked to administrators or when we speak, we explained that the, the important lessons that we're teaching are not necessarily the Python syntax, the Python language, the way that you implement a Lambda function in Python, for example. 
Kelly Paredes: He's just a big nerd with the, you know, at just up as a Teddy bear. 
Sean Tibor: I just, I love all of these, these technical aspects of Python, but, but really. The big lessons that we're teaching are about persistence. They're about being able to view the world differently. It's about how to think through problems, how to have the confidence to pick yourself back up and try something new when you fall down or when it doesn't work. How do you handle that? , how do you fix it? So these bigger lessons, I think, are more way more applicable across areas like, you know, engineering, computer science, math. Right? Like you see those heavily there, but then when you start to apply them to other areas, it's like, wow, wait a minute. This totally works for art, for music, for dance, for sports, for, um, uh,  for English, for social studies, for history, all of these areas are really, um, places where you can apply a lot of these same lessons as well. 
Kelly Paredes: And lastly, I have to say that. We've got something special teaching computer science. I think not Sean and I, but all computer science teachers. If you take that moment to really dig into the social emotional learning and even the computational thinking skills that are involved in computer science, you get to see the students that many other teachers do not get to see. Cause sometimes. They're stuck on a content and a way of doing things where if you engage in. Unknown pro, you know, unknown solutions or give the students things that you don't have the answers to. Like, I don't know, half of those libraries we were talking about today and I said to them, that's a one. I wouldn't even look at that one because it's confusing to me and I'm able to get to know a student better. And I think at the same time. That allows that child to get to know themselves better and these things, I'm not sure they come out all the time and all the other core curriculum, we have this ability to really break down the walls of saying, listen, this is new. This is, there's new things coming out there and we're gonna, we're gonna work through it and we're going to help you learn how to work through things. 
Sean Tibor: Yeah, and my final thought on this, or my last thought is that this is not just about this age, it's not just about middle school. These lessons, these things that you can learn are. Excellent to learn at any age. Right? Um, and that's what keeps our minds young and pliable and fresh is when, you know, like, but in all seriousness, teaching someone who's 50, 60, 70, how to code for the first time or, or even later or even younger or wherever it is, if you're in college, learning how to code so that you can go often and do you know, neurobiology better. It's going to change the way that you've viewed the world. It's not just a tool. Potentially a new mindset or a new approach or a new way of looking at things and vice versa. So if you're an entrenched computer science person, right? Um, if you've been trained classically, if you have all these things, you know, maybe it's time to go take that pottery class, right? Or take a, an English class or history or, or a science class, something that gets you to think differently about the world also, because it does go in both directions. 
Kelly Paredes: Absolutely. Absolutely. Well, we were very touchy feely today. This is a very social, emotional learning episode, and this is one of passions of ours, and we do actually talk about this a lot at our school. 
Sean Tibor: Yeah. I think it's just something that Worksighted about, and that's one of the things that we like to share with our students too, is just our enthusiasm for this is really important, interesting, challenging work. And. You know, aren't we all lucky to be part of it? Aren't we lucky to be able to do this every day? It's pretty cool that this is what we get to experience on a daily basis when we are learning how to code and learning how to teach it and learning how to learn. 
Kelly Paredes: Absolutely learning how to learn. That's my favorite sailing. Looking for learning to, 
Sean Tibor: Oh, looking for learning. That's, that's good. I always like to see the learning happen. Like it's, it's amazing to watch that light bulb moment and, and that's a lot of, a lot of fun. And then we get to do that a lot in the computer science classroom. 
Kelly Paredes: So let's wrap it up if you have anything else to share. I mean, we were trying to think of a good solid list. There's so many other things. Always curious to hear your thoughts on what are some top skills that you. Bring out with years from your students when you're teaching computer science, not just the programming. I'm happy to share it with us at teaching Python, 
Sean Tibor: you know, honestly, the other one that I'd love to hear from, I'd love to hear from people who, I know many of our listeners are not necessarily, teachers are not necessarily teaching full time, but if you're a coder, what's a memory that you have from when you first learned how to teach that changed your perspective or changed your viewpoint about the world around you? Um. You know, or you know, in your career, like how did adding coding to change the way that you approached what you, you know, cared about most in your professional life? Absolutely. All right. So with that, we'll sign off. So for teaching Python, this is Shawn. And this is Kelly signing off.