Sean Tibor: Hello, and welcome to teaching Python. This is episode 102, and today it's all about learner variability. My name is Sean Tibor, I'm a coder who teaches, and my name is. Kelly Schuster-Paredes: Kelly Schuster, print is, and I'm a teacher who codes. Sean Tibor: So kelly it's pretty nice. We're actually getting back in the swing of things and recording two episodes in two weeks. I feel like this is back to our normal routine. Kelly Schuster-Paredes: It is incredible. It is incredible. And you are doing well at reminding me to get up and get recording. Sean Tibor: Well, we're making good progress and it's nice. Now, while you're on break and things are a little bit slower here, at the end of the year, we have a chance to think and be reflective and also a little bit more flexibility in our schedules to get together and actually record. Kelly Schuster-Paredes: It is kind of nice. And it's that little downtime where we in the past would shut down and kind of relax. And now I think this becomes our relaxation as this recording. Right? Sean Tibor: Yeah, I know. I look forward to it. Kelly Schuster-Paredes: I do, too. Sean Tibor: Why don't we just jump right in with wins of the week and keep things moving? Kelly Schuster-Paredes: Sounds good. So what's your win? I went first last time. Sean Tibor: All right, so my win this week has been that I've been writing more Python code lately, and a lot of it has been the opportunity to work on some of those projects you never get to during the rest of the year because it's not a priority, it hasn't bubbled up your list of things to do. And so right now it's really quiet. The end of the year is here. We have a change freeze, so there's no releases of new code. So it's a chance for me to spend a little bit of time going back and working on projects that are just kind of fun and interesting and I've always wanted to do throughout the year. So I'm working on some integration projects, a little bit of an event driven architecture for when things happen in our system, then other code should run. And so I'm working on something that if we have a security issue that comes up from our security scanning tools, that we can create an issue in GitHub automatically for that and be able to start working on that issue. So it's kind of cool to have these little things pulled together because it's a lot of manual steps that we haven't really done that well or that consistently, but if we can automate it, it will happen all the time. Kelly Schuster-Paredes: That's really cool. And you love that automation thing. Sean Tibor: It's the best. My project earlier in the week was automating some GitHub actions so that when we release new versions of TerraForm modules, it automatically tags them with a new version number, generates the change, log and release notes, and even pull some of the comments from the issue descriptions or the pull requests that are included in that release. So pretty excited about that coming together because it's just things that make our lives a little bit easier and a little bit smoother. Kelly Schuster-Paredes: I need that. I need some automation. I started doing a lot of things on GitHub and doing my own what are they called when they're like my personal commits? When you commit to a change on your own project. Maybe we should have, like an automation so it commits every 30 seconds so I don't have to write. Because I have been trying to be very thorough with constantly saving quickly and often and yeah, writing those commit messages. This is another main. I know it's not the proper way of doing things, but it's all just in the practice. Sean Tibor: Well, and I like commits when they actually cause action, make it more rewarding to run a commit. So I don't know if that made sense, but I noticed that I'm making more commits because it triggers test runs of our TerraForm pipelines, which is useful to be able to see if it's working or not. So you'll see more of those commits happening and they seem to fit well around. I've got this piece working, I'm going to commit it and test it. So anytime you can add automated testing to your pipelines or your commits after they run, it's a good way to keep things frequent and meaningful. Kelly Schuster-Paredes: Very cool. Well, how about you? Yeah. Kelly if you follow my LinkedIn, you'll know that I have passed four weeks of my boot camp and I have successfully and hopefully never again committed and finished a VBA script. After about two weeks of having nightmares and dreams about why I couldn't get things to run and waiting ten minutes for every time my script was running against this big data, And I remember talking to you going, oh my gosh, I can't do it. And you're like, let's send it. And I never did. And I woke up one night in the middle of night, probably about 01:00 A.m., and I was like, I did something to my variable and I dimmed it as a long and it was supposed to be a double. And if you don't know what dimming means, don't worry, it's horrible. Thank God for data types that are not call it inherited in Python, but given based on what you type, it's a lot easier than having to figure out which variable you're doing in longs and doubles and integers and don't ask me to explain because I don't really understand that much. But yeah, I fixed it and I solved it and it worked. And a million pieces of data points have been scripted and filtered and calculated and yeah, it was impressive. So that was huge. Sean Tibor: Good. It does make you appreciate all the nice little features of Python when you go back to it. And after working on a language that's maybe a little bit more strongly typed or has some more oldfashioned or less convenient mechanisms for doing things. It's nice to go back to Python where things just feel easy. Kelly Schuster-Paredes: Yeah. In my reflection, I was saying, if you're complaining about Python being slow, try running VBA and forget about indentations. You hate those indentations. We'll try reading a VBA script if you don't put indentations in. So there's a lot of kids that I learned to love about Python even more. It's very cool. Sean Tibor: Nice. Well, it sounds like you've had a lot of learning to do over the last four weeks. I've had a lot of learning over the same time frame, a lot of new things, a lot of things I'm trying to do and just expanding, and I think it fits really well. He sent me this article about learner variability that really kind of fit my brain and my mental model of how we learn things and also how we teach for a variety of learners. So why don't we jump right into our main topic and start discussing and figuring out what does this mean? Kelly Schuster-Paredes: Absolutely. Because I think this hits the nail right on the head for both of us about the average learner. Sean Tibor: The myth of the average learner, right, yes, exactly. Kelly Schuster-Paredes: The myth of the average learner. And this article came out in October of 2022, and when I was sitting there reading it, I was like, oh, my gosh, that's us. Sean Tibor: We know that it's Digitalpromise.org, I think is the publisher, I believe. Kelly Schuster-Paredes: Yeah. Digital Promise. Promise, correct. Sean Tibor: Yeah. So it's a PDF guide. I think it's about 1520 pages of summary information and description, but they also have contact information here. The guide was created by Jessica Jackson, and she got a lot of support from the Learner Variability project and the larger Digital Promise team. So I'm looking at the credits here, but the Learner Variability project is part of this Digital Promise, and it's really designed about how to teach effectively with a variety of different learners and a variety of different approaches. And I think this really fits because it mirrors a lot of what I experienced, especially as a new teacher, trying to figure out how to reach as many students as possible, how to engage as many students as possible. Right, absolutely. So what's the basic premise? Like, what is learner variability? Kelly Schuster-Paredes: Yes. Well, let's think so. First of all, this article, I think, was written with a math English mindset, so let's put that on the front page here, that it's not really meant for the computer science, but like us, we like to apply everything in computer science because it's the most important subject in the world. But it's just going into the learner variability that there is no such thing as an average learner. There's not this one size fits all for every child or every adult learner. And that our experience in life, our environments, everything that we feel about learning has an effect on our readiness, our ability to learn and accept new information. And it's just recognizing that every person, every student, every learner has this unique set of strengths and abilities that just impact the way that we learn. There's a lot of learning science about that, a lot of support that this learner variability exists. Which makes sense, right? We're all different so we all learn different. So we can't say everyone's going to learn this way, everyone's going to remember this way, everyone's going to apply what they learn this way. Sean Tibor: Great. But that sounds a lot like learning styles, right? That sounds like that whole concept that each person has a different learning style. Like I'm an audio visual learner or I'm a kinesthetic learner or audio only or visual or whatever or textual. How is this different than that learning styles idea? Kelly Schuster-Paredes: Well it's not saying that we learn in a specific way, it's just saying that we are different. So there's not really this learning style myth and it goes into it that we do have like a general three ways of learning and there's a different modularity of it but we learn through all three ways. We don't just learn through doing or listening, but we do it through all levels but we just do it slightly different. Sean Tibor: Well as I was reading through this and I'm kind of setting you up with questions here, but as I was reading through this it was really saying that we should be employing and learners employ a variety of methods at different times for different contexts, different applications. So to pigeonhole yourself or to say oh, I learned best when I'm listening means that you might be closing yourself off to other opportunities, right, as you learn. Or a teacher who says well all of my students learn really well in audio sort of way, so I'm only going to present audio. This is saying that there's variability both between learners but also within learners, right? So it's kind of interesting to see how as this is going through and talking about the various learning approaches or learning factors that it's not saying you have to do it one way or that there's a locked in way. Everyone is different and everyone can be different at different times and in different ways. Kelly Schuster-Paredes: And it goes into this article is really nice and I really like taking it apart because it talks about ways to design the curriculum for the learner and it goes through a series of steps and one of the first things it talks about is designing for that whole learner. And this is what we've said in the past, get to know the people that you're teaching to. Johnny sitting over in your classroom is completely different than Sarah who sitting in your classroom and they have different backgrounds, they have different social, emotional, I don't want to say issues, but different social emotional learning inside there's a lot of things that change that person. So you're designing for everybody. And this is hard, right? You're designing into a fully differentiated classroom, expecting to teach a wide spectrum of learners, and pretty much that sums up the life of a teacher, right? You literally have to know who your learners are, and you can't just say, okay, this person is my math person who does this, and I'm just going to design my entire lesson based on that. So it's about designing for the whole learner, for every learner and trying to find those connections for that student. Sean Tibor: Kelly it's interesting, as you look at this, they have this whole idea of learning factors, which really stood out to me as something that maybe intuitively made sense without being articulated explicitly, I guess. So looking at this, it's really talking about what factors go into or contribute to the effectiveness of learning. And they've got this broken out to your point between math and literacy here, but they also have, like, an adult learner factors as well, which is kind of nice. So this includes things like metacognition, right, or auditory processing attention. It has their background, right? Like, how well do they hear what's their physical well being? Sleep. So you can see where a deficit in any of these areas can affect other factors as well. So if you're low on sleep, maybe your emotion is also suppressed, right? So you're not as engaged and not as excited about what you're learning, or your attention span could be lower because you're drifting off all the time, or your speed of processing is inhibited. So what's really cool about this navigator that they created is that you can hover over any one of these factors and see how they are connected with other learning factors as well. Kelly Schuster-Paredes: And it's kind of nice just to put this into context of when you're starting to design your curriculum. So if we're talking about designing for every learner, it's actually thinking of that wide spectrum and trying to go from side to side. And I think a lot of teachers do this. I think if you read this article, you're like, yeah, I do that. But it's now going into more of a cognitive science approach and talking about this targeted approach of teaching. And you want to say, and I think we do this a lot as I'm teaching, to the kid that really, really hates computer science, who doesn't get it, who's really going to be hard, it's going to be hard to connect to. It's going to be that person that just comes in with that mindset of, I can't code, I can't do math, I can't do this, to that full other side of the spectrum who is like that total nerd in the background who's coding constantly. You're like, no, we're still just doing lists. Stop coding ahead. So you're having to design at these margins and really build an understanding for that whole child experience in your classroom. And I don't know about you, but it's hard. Sean Tibor: Well, I mean, it's definitely hard, but if you think about it, it really makes sense because if you're designing for the average student, right, this mythical average student that's right in the middle, that's kind of average at comprehension, average at intuition, average at average, average, average, right. What you design is going to be average. But if you're designing for the margins, you're designing for those really kind of exciting edge cases where people are more engaged or more interested. And I think the common misconception is something that also happens in marketing when you're designing for communications or how to effectively reach someone. When you identify these kind of edge targets or the marginal targets on the outside edges of where your students live, you feel like people sometimes mistake that for being, I'm designing it only for them, and they're the only people that will benefit from it. But this is more like casting a pebble into a pond. And that there's a ripple effect that occurs when you aim at the margins. It ripples out and it benefits people that are adjacent to those margins. Right? And if you do that in enough places, what you get is this nice effect where the ripples spread across your entire learner base. And though every student is more engaged because the effectiveness of what you're doing is much greater when you're designing for the margins instead of the middle. Kelly Schuster-Paredes: Yeah, and I think we had an episode, I don't remember where, and we'll try to find it for our show notes later, but where we talked about doing that learner profile, that student profile, figuring out who it is that you're teaching to. And that just goes into the basis. But now you're looking at the whole spectrum. The next topic that they talk about is designing based on evidence. And I love this. And this is not, again, something new, but it's something we all do. We try to get this background. Every great teacher goes out and try to understand this background information that your students have. Like, where are they coming from? How much do they learn? What are the things that you like? And I think you did this really well. That one lesson where you were talking about designing makeup. What was that? The video, the YouTuber who puts on makeup. And you're like, the kids aren't really interested in coding, but heck, they love this YouTuber, and we're going to bring this into the system. And yes, this wasn't hitting every student, but it was hitting a margin side of that classroom. And it was something that they could make a connection to. And it showed that you knew that those students and you knew that this is going to make them learn, it's going to make them effective learners. Sean Tibor: And it was still relevant because we were talking about algorithms and how they're step by step instructions, right? So it wasn't like I was going completely off script I just happened to find a rather unique way of engaging them with how instructions are followed right. The sequential nature of them or even branching conditions. And it worked really well in that particular case. But the only reason I was able to get there was because I asked my students, what are you interested in? Or can you think of an example of complex instructions that someone gives? And they said, well, there's this makeup artist on YouTube. Okay, let's go watch him do that. Right. It worked. Kelly Schuster-Paredes: Yeah. And it's that understanding of also their strengths and challenges. And for a kid to be sitting in your classroom and you're teaching computer science and it may not be their favorite subject, or it may not be something that they're good at, but the fact that they can sit there and go, oh, wow. My teacher really knows who I am. Or my teacher really wants to make a connection and do something that's interesting to me that's going to help that learner and that desire to learn increase. So it's just making those connections. We're more than just a person up at the front of the room regurgitating information. We are there to make connections and to help them make connections. Yeah. Sean Tibor: I mean, the enemy of good learning is not poor comprehension or poor understanding. It's boredom. Right? Boredom is the thing that is the enemy of any good learner. If we can keep them from being bored, if we can engage them and get them excited, that's where the real learning happens, because then everything switches on. Kelly Schuster-Paredes: Yeah. And that's what the next thing is. They talk about the design with the context. How do we make it so that there's like multiple perspectives, there's a whole understanding of our curriculum, how everything is in context and not just some fizz buzz. Was it FizzBuzz fuzz buzz? I don't know, whatever that is. Fuel bar and bar, all that stuff. And it's something that we can connect to. There's different perspectives. There's something that's engaging. Sean Tibor: Well, I thought this one was particularly interesting because we often think about especially the way that this was written, we think about the context of the learning in math as being very sequential. Right. So this student is now in pre algebra. Before this, they had, like, an honors math class that was more broad ranging, but next year they'll be going into algebra one. And so there's like this progression that's very well established and very well thought out. And in literacy, you have the same sort of thing here's, the curriculum of what the books that they're reading or what they're writing, they've established a strong grammatical foundation, and now they're going to get into more creative or persuasive writing. So there's always this thought of a lot of context, which is relatively easy to do. I mean, I say relatively easy, but there is context in math and literacy that is more longitudinal across their entire or learning experience from their early stages in pre K and kindergarten all the way through until upper school and even into college. In computer science, that's a little bit harder because not many places have twelve or 13 years of computer science. This might be the very first time someone is writing code or thinking about their computer as more than something that they can just watch YouTube on. Right, so how do you establish and create that context or acknowledge that there really isn't any context for this within computer science? How do you reach out and design your learning with more context outside of those paredes? Kelly Schuster-Paredes: Yeah, and I think also they go into the context of which I'm trying to make a connection here. But one of the questions they say is what about flexible sitting? What about the learning environment? And is that environment a place where they can make it would have some sort of context in the situation. And I was thinking about this. I think when people walk into our room still, it's still the same. Is that ability for a child to be wherever, whenever and for whatever they need? Obviously in a safe environment. Safe, not in a whatever, but whatever they need in order to learn. And I think that's weird for a lot of people when they either come to observe or they see me in action still. I've got kids on the floor, kids up against the wall, kids in the city. And their question is like, well, what if they're off task? And I'm like, well, then that's not in the place where they want to learn anyway. So if they're off task and they're uncomfortable, they're not going to learn. So it's got to be in that place where they have flexibility in their learning environment. Sean Tibor: Yeah, I mean, there's definitely the macro context in the big picture. Where are they learning right now? What's the context in the big way? But then there's also that micro context like what happened five minutes ago that's causing their learning to be off or does it smell bad in the corner of the room where they're sitting? And are they distracted by that? Right? That context matters at every level. And so again, it adds a lot of complexity to understand all this context and be able to incorporate it. I think the key is you can't do everything right? You can't hold all of that in your mind so you see what you can observe, see what you can gather in terms of information and understanding about the context and then do your best to adapt and adjust based on that new information. Kelly Schuster-Paredes: Yeah, absolutely. Sean Tibor: And I think this is particularly important in computer science. I want to keep bringing this back to the computer science view of it, right? Because when we're thinking about computer science, it can be a very internal focus, like using your mind, comprehend, think through problems, solve them and context is everything in that case to be able to really have good, solid, powerful learning happen? Kelly Schuster-Paredes: Yeah, absolutely. Going back to it then. So this question here skimming as I'm reading, talking, but I'm skimming this question. It's like when the student is perceived as an expert or offered a leadership role, how does that change their engagement? And I was like, wow, that's huge. Right. You have this person that is a leader, but if that person is always the leader in the class, then the people who are not leaders would not necessarily make that connection or engage or they might engage with the curriculum differently. So given that opportunity for everyone to be a leader, everyone to develop some sort of expertise in a certain area, definitely changes their context for learning, their engagement for learning. And it goes back to the whole thing of do you know your students? Right. So if you see that child that's constantly in the back and not really feeling like a leader or feeling empowered to learn, how can you change that? Sean Tibor: Yeah. It's also the ability to switch those contexts and get used to being in a different context as a learner. Right. So sometimes you're in the learning context where you know an area really well and you're just gradually or slowly expanding the edges of what you know right, versus going into a completely new area that you know nothing about and having to create understanding and knowledge from scratch. Those are two very different contexts where one, you're acting as the expert, maybe teaching others or showing them, and then the other one is you are a beginner, you're a noob. Right. You're trying to figure out how to create that knowledge, and having your brain be flexible enough to be successful in both contexts is a really important skill to have. Kelly Schuster-Paredes: Yeah. So another aspect is designing for powerful learning. And I've seen this in how you've taken on your new interns and just thinking about our own environment when we were working together was this powerful learning, this ability for learner agency, this ability to enhance that growth mindset, that it's a lifelong learning experience. I think as a teacher, one, you want to demonstrate that you are that person who designed your own powerful learning environment where you're constantly learning things. I told the kids, I'm like, I'm taking a course course, and I'm doing it for six months, and I'm doing it three days a week. And they're like, Why? And I was like, because if I only teach you basics for the rest of my life, what good am I? Yes, you're going to be better than me in a couple of years, but I want to keep learning with you. So I'm trying to be very student driven. I've got this positive growth mindset. I want you to have that as well and helping them to understand that these are the ways that you can use your strengths of learning more or these are the times when your weaknesses might hold you back. How are you going to overcome that? And here's the feedback and the information I'm going to provide you to help you grow a lot of stuff. Sean Tibor: Yeah, so many things here. So many things here to find out. I mean, I keep thinking about one student who was an 8th grader in my class, and at the beginning of the nine weeks, she said to me, mr. Tibor, it's really hard for me to learn things like especially reading. I have to read something three, four, five times before I really get it and understand it. And so I'm going to be really slow, and I'm worried about that. And I said to her, I said, I think this is actually going to turn around and you'll see that this is something that's a strength of yours, because other students may be used to reading things once, thinking that they have an understanding of it and they move on quickly. But you're going to read for depth and understanding and your brain and your habits are already trained towards that. So you're going to actually see that this will help you learn things better and you'll be able to establish a really great foundation of knowledge that you can use to create much cooler stuff later on. I said, So this is really like a superpower. It's not a weakness. I think you maybe just look at it in a different way. And she came back to me at the end of it when she was working on her project, and she was like, you are so right. I really feel like I know this, and I really feel like I was able to understand it in a way that I never understand anything. I'm good at this now. And it was like that powerful moment where she realized that something that she'd always viewed as a weakness was actually a strength if you were able to employ it in a productive way. Right. And so those powerful moments, that's a powerful learning moment because it probably changed the way she thinks about herself and the way she learns. Hopefully that goes to other areas of her learning as well. Kelly Schuster-Paredes: Yeah, I have to read this sentence because I have to quote this stuff and I think this sums it up, but it's like designing powerful learning calls on teachers to reconsider the role as content experts. And that thing is hard for a lot of teachers to say, I'm not a content experts. Kids all know I'm first to say that I'm not an expert in coding, but I am trying. And it continues and shift to one where they become partners in learning. I mean, partners in learning. That's such a beautiful thing to say, that I'm a partner. I'm here with you and I'm a partner in your learning. Modeling the skills and mindsets necessary as they empower students to explore their passions. And interests. And I think that came out in one of the lessons we've done in the past. And I try to do it depending on where my kids are, is that demonstration of learning. I don't do it every quarter. I can't do it with every quarter because some students are just not there to do it. But I remember it was actually my third quarter last year where I had this group of kids who were so variable, but all very passionate about learning, very interested in learning, but one wanted to learn about pictures, and one wanted to learn about graphs, and one wanted to learn about TensorFlow. And I was like, you know what? We're scrapping the curriculum right now. We're going to do a demonstration of learning, and we're going to all learn together. And they would come up to me, and they're like, well, how does this work? I'm like, I have no clue. Let's read the documentation together, because this is so new to me. And it was that ability to just let go, not be the expert, be okay with the kids finding their strengths, be okay with who they were at that point in time. And it's that group of kids that are still coming back to me, and they're like, oh, my gosh, compsite AP is so easy this year. And they're like, what we did last year was so hard. And I'm like, I didn't do it. You put it on yourself. You had that agency to choose that library. And that's, to me, probably the most powerful learning experience I've had as a teacher of just full on letting go for three weeks. Sean Tibor: Sure. It's such a mind shift, right? I know I've shared this story before, but it was like my first job out of college, and my boss gave me an assignment. He's like, I need you to go build this thing or figure this out and come back to me when you got it about halfway figured out, and we'll see if you're headed in the right direction. And I said to him, okay, well, what is this supposed to look like? When I'm finished? What is the definition? How do I know it's right? And he said, I don't know. That's why I have you. I hired you so that you can go figure these things out. And I realized that that totally changed the way that I thought about learning, because now it was no longer learning with some target in mind that the professor or the teacher had already created that I knew about, or that I knew there was an answer key. This is learning with no answer key. This is learning with no right answer. It's what's the best answer right? And you're the one who gets to figure that out. You're the one who gets to create that. And so when you empower students to do that, especially at younger ages, it changes the way they think about learning. And it's highly empowering because then the world starts to be things that they can go solve and fix and create and imagine and actually have the skills to turn that into something real. Kelly Schuster-Paredes: 100% going on with this article. The things that just pulled me in, and I was like, oh my God, I love this is these whole activities to reflect on as a teacher. And we do this a lot, and I try to reflect as much as possible because for one, writing it down and reflecting and thinking about it helps it stick to my head. In my head, I should say not to my head, but in my brain. And just the reflection in general is great. And there's this activity where it's talking about you as a learner. And if you're not learning, if you're not really taking that moment to recognize and learn more, then this sounds sean, but why are you a teacher then, if you're not a learner? And there's this one thing is like, reflect on how you are as a learner and what are your challenges. And just thinking about my recent challenges with I remember it was text. I was putting the texture. I was like, oh my God, I'm going to cheat. I'm going to look at this other assignment outlier online. And then I started to look at it, and I was like, no, not going to go there. And I did. I looked at it for a little bit, I'm not going to lie. But then I was just like, no, I'm not changing my code to fix it to this one. I'm going to go back and fix my crummy code. And it was talking about these strengths, and mine wasn't of defeat, but mine was like, I could not sleep. I kept thinking about this, and I was just like, perseverating, it's not the right word. But this constant thinking about why is this a problem? Is driving me crazy. And everybody in the house is crazy. So who am I as a learner? I'm a learner that's not going to let go of things, and it might be bad for my health. So how am I going to fix that? Sean Tibor: And just you're a tenacious learner. Kelly Schuster-Paredes: Tenacious learner. That's a very positive thing. But there are other kids out there. It's that kid who's constantly looking at the grade, constantly saying that they got a 98 instead of a 97, and how is it affecting them as learners? And how can we help to make connections and relate those strengths and challenges that you're having as a learner for that student? Sean Tibor: Yeah, actually, Daniel Chen is in the chat, and he just posted this here too. And I think this relates really well. It's like projects are the best way to learn for a lot of the reasons we've talked about here. But sometimes students don't see it that way, especially when they're hyper focused on a grade. And we've had episodes about that, like, when the grade gets in the way of learning, that the grade should be an outcome of the learning. Right. It comes after the learning happens. But students are so focused on the grades for a variety of reasons that they let that get in the way of their actual learning experience. And so I guess one of the questions to ask for teachers is, what's getting in the way of your learning? What's the equivalent of that being hyper focused on a grade that is getting in the way of your actual quality learning? Like, for me, I look at other people's code all the time, right. That's a literacy factor for me, is looking at how other people have solved problems. And it's rare that I'm copying and pasting their code. Usually I'm trying to understand why they did things and how they did it and then use that to inform the code that I'm writing. And so there's, like, some of that. The intellectual integrity is not so much about, oh, I can't look at other people's code. I don't want to take a shortcut to my learning. And sometimes that gets in the way of your actual learning because it's not necessarily a shortcut. It might be a way to help you quickly get the literacy because it has the context of the problem that you're trying to solve 100%. I did notice something on this activity, the self reflection for teachers that I thought was interesting. It kind of changed my thinking about this approach overall is under the literacy area of this kind of Venn diagram that they've created. One of the questions that they have is, do you feel comfortable using a computer and navigating the Internet? And that kind of digital literacy, that technical or technology literacy is something that in computer science is very important. Right. You can measure and assess someone's literacy in using the technology tools they have, whether that's their ability to understand a coding language or to have a coding environment that they can comfortably use to be able to create the code that they need to or the projects that they want to accomplish. And so as we're looking at this, I'm actually going to read through this again, but through the lens of computer science literacy in here. And also, how does the math side of this also connect when we look at the learning factors and everything, is it how much computer science is literacy based versus kind of math and computational based? Kelly Schuster-Paredes: Yeah. And I would say if you do nothing with this article except for look at this own reflection, then diagram, you've done, like, a professional Kelly development for a year. Because just these questions alone and this one really is one question really on the opposite side of the Venn diagram is something that really appeals to me, is like, do you find yourself anxious or stressed more than your peers? Sean Tibor: No. Kelly Schuster-Paredes: Definitely yes. Me constantly and it's not like I'm stressed about getting a bad grade, or I'm stressed about doing something wrong, or I'm stressed about not being able. It's more of that impostor syndrome that stresses me out. I'm getting there and I'm really going to be learning this, and I'm getting the problem solving and I'm answering with my breakout rooms, but then I'm like, oh my gosh, but I'm never as good as and I'll say, Daniel Chen, I'm never going to be as good as him with Pandas. And it's like you put these own pressures and it's that own social, emotional learning, and I adjust and hopefully one day I'll be as good as you, Daniel. But yeah, this self reflection is huge. And I'm going to read one more of the cognition is, are you able to multitask or quickly switch between different tasks that I'm 100% able to do, but finding myself the real question, should you should I know what other questions appeal to you on the Venn diagram? Sean Tibor: Well, what I was interested in here and what I noticed isn't really available or isn't on this question sheet. Maybe I'm missing it here, is this is all very much written in isolation. It's very self reflective and focused on self and doesn't really talk about things like, what's your PLM? Like, how many people can you reach out to to ask questions and get help? Daniel just wrote the chat. He's still learning things in Pandas. And I believe that because there's so much to learn, there's always new things to learn. But in our PLN, we could go to Daniel and say, hey, we're trying to figure out this thing in Pandas. Can you help us out? And he might know it, or he might be like, oh, I don't know that. Let me learn it really quickly, because for him, it might be just expanding a little bit of the edges of his knowledge, whereas for us, we might have a lot more to grow in order to get to the point where we could understand that. So I thought it was interesting, as you look at the self reflection, I would probably add something on to this as well, around how much support you have, how much community do you have around you that can help you be a more effective learner. Kelly Schuster-Paredes: Yeah, we need to put that design for PLNs. Sean Tibor: Well, they do have their contact information at the bottom. We can send Jessica a note and suggest some of that community PLM stuff. Kelly Schuster-Paredes: Yeah. And after the Venn diagram, there is a whole self reflection where you can go in and do this scale one to five. You're consistently doing this. It's an unfamiliar idea, and I think that's really interesting. And not only does it have space for you to mark your scale one to five, but it has you doing it three times throughout the year. So really seeing how you've changed throughout the year going in there. Sean Tibor: Yeah. I like that a lot. I like that a lot. It takes it from being a point in time and a WAFF exercise to being something you can track and hopefully see trends as you go to be able to see that you're improving across the areas of focus that you have. Kelly Schuster-Paredes: And one of I can't remember who it was when I tweeted, how do you learn? Or wasn't even a LinkedIn. And some person said to me, case studies. Well, there's also case studies in here. So you have a couple of case studies just to kind of read over and to help you think about learner variability. Sean Tibor: There's a ton of links in here too, with other resources. It's a great article. I think we need to send Jessica some love on Twitter and via email and say, thanks for publishing this because it really brought things together for me in a way that I hadn't really considered or had been in a lot of different disparate places. It's all kind of fitting together in a really nice framework here. Kelly Schuster-Paredes: 100%. And there's also micro credentials for those people that like to get them. Sean Tibor: Nice. Kelly Schuster-Paredes: Put that in there. Sean Tibor: Nice. Yeah. So what to do next with this? Definitely read it over, but this is a great time of year to be reflective, to really think about and assess how you're doing as a teacher and as an educator. And for me, I've got some new employees coming on early next year and it's a great time for me to look at it and say, okay, well, how do we make sure that what we're doing for onboarding and education is effective and working well? And so there's a good opportunity for reflection, I think, in a professional setting at this time of year too. Kelly Schuster-Paredes: Absolutely. And with me entering in the third quarter, third quarter is the longest. It's usually the best quarter because kids are settled and they're not either starting school or ending school at that moment, and they're just a great group of kids at that point of time. So going in there and trying to get to know my kids right away, and I'm going to have to pick a goal for that quarter. And I think this is a good place to start. Sean Tibor: Good, for sure. So let's see here. So what else is on tap for you for the rest of the break before you go back to school? Any major projects you focus more on? Your data science boot camp and staying ahead on that. Kelly Schuster-Paredes: Yeah, I have one more class before break and I have already finished my assignment that's due on the 9th and I'm trying to get ahead and really digging into Jupiter notebook. Love it. I do miss the fact of going into Colab and having everything in my drive and I'm trying to push myself to use my terminal or get bash or whatever they call it, use that more. But I'm just going to be learning and looking at sequel. And look, I feel like a real coder for once. I've been doing a lot. I've been doing some stuff on my GitHub. It is fun. I feel like I'm finally going over that hump. So, fifth year, five years is a charm. Five years. Sean Tibor: It's funny. One of my new co workers posted on LinkedIn, she took a screenshot of that get commit heat map that you have on your profile that shows you how many contributions you've made every day for the last year. And she put it up there as a very aspirational post. Like, here's where I want to get to in the coming year. And I was both flattered and also kind of surprised because I've been in the middle of it. I hadn't really thought about how much I was doing over time. And to see all of those green boxes over the course of the last year, sometime this year, I think I had over 2000, almost 2100 commits so far in 2022. But my best previous year was I think like 300, 400 a few years ago. So this is definitely a shift in the way that I'm writing code and the way I'm getting things done. Kelly Schuster-Paredes: That's very cool. One more thing on, and I don't know if you can still get into it, but I did get into one of those other Udacities programming for Data science with Python. It's one of those scholarships, and I say it with the air quotes because they lure you in this scholarship and it's a lot of people that get this scholarship and it's great and I love it. We took it for AWS. You and I did the same thing. But the hope is it's hard to get into the next level. And so out of the I don't know how many people, 1500 or whatever, only 50 get into the next actual nano degree. So those people that are in this who get in, congratulations, because it's a lot of work as well. Not just not a boot camp, but it's a learning on your own and a cohort of a lot of people on Slack. So if you haven't had the opportunity to check out any of those scholarships from Udacity, I recommend them because I love that AWS one we did, and this one's really cool about sequel and sequel and I forget what else, I'm only in SQL, so I'm doing this alongside my other boot camp. So my head is spinning. Sean Tibor: Nice, nice. Other updates for me, I did update an old blog post on our site about colab and not working with Google Workspaces for Education. It has been working for well over a year. I just forgot to update the blog post. So Chris Perry from Google reached out and said, hey, if it's possible, could you update this so people aren't confused? So there's been a little bit of an update on that blog post itself. If you found that, and that's how you found us. Google Colab works fine in education. It's a toggle control that you can use to turn on for your organization. It's still a great teaching tool. And I just wanted to mention that in case anybody was looking back at old blog posts. Not that we have a lot of them out there, but that one in particular has now been updated with a little bit of an update or new news about that. Kelly Schuster-Paredes: Good. And you made me remember, and I was trying to remember what it was about replicate, and if I tweeted it out, but replaced making a lot of improvements. And I think, gosh, what was the latest? Sh access or something like that into GitHub that one. I was like, oh, yeah. So that's huge. And the CEO, the owner, whoever it is, I forget who it is, replet, the guy who's behind Kelly, has really been doing a great push for education, trying to get a lot of educators in there, and they're always asking for any updates or feedback, because, to be honest, is a great replica. Is great. Sean Tibor: No, it works really well for quick coding sandboxes to get going. So always a lot of fun. And I'm glad to see that they continue to add those features there. Kelly Schuster-Paredes: Yeah, and I had something else, but I think it just slipped my mind. So that's it. Oh. Follow us on LinkedIn. We're almost at 150. And then Sean can be forced to do LinkedIn Lives with me. Sean Tibor: Yes. That way we can stream on LinkedIn also. So please follow us on LinkedIn. I think we're losing a few Patreon followers here and there. Normal people are figuring out where they want to spend their dollars, and sometimes we come up as a place where they can save a few bucks a month. So if you want to support the show and you want to add back some followers and become a patron of the show, I will put the link to the Patreon in the show notes so you can do that even if it's just a few bucks a month. It definitely helps out with the running costs of doing the show, but that is out there. Let's see here. I think that's it. Nothing much else to report. I just wanted to catch on a few of these little logistical things that have been happening around the show and hopefully more announcements and more fun stuff coming next year. In 2023. Kelly Schuster-Paredes: Yeah, 2023. Cool. Happy holidays. Sean Tibor: Yeah. We're on the fifth night of Hanukkah. Christmas is a few days away. Especially if I can get this episode posted later today, it'll still be timely and relevant. Kelly Schuster-Paredes: Very good. That's a goal for you. Sean Tibor: I made it last week. We'll see how I can do it this week. Kelly Schuster-Paredes: Excellent. Sean Tibor: All right, so for teaching Python, this. Kelly Schuster-Paredes: Is Sean, and this is Kelly signing off.