(bright music)

Welcome to the VEX Robotics Educators Conference. I'm very excited to give this presentation today. It's actually the first time I'll be presenting on this particular topic, so I'm really interested to hear your questions afterward.

I'm a former classroom teacher. As I like to say, my introduction into STEM was driven by my students. I have no background in computer science or engineering, so this will be quite different from the presentation you just saw from Professor Touretzky. I can barely change a light bulb, which was my knowledge base when I first got started in STEM. A lot of the work we do at VEX Robotics is aimed at lowering the barrier of entry for teachers like me, who were initially scared to death to start with STEM education in their classrooms and are still searching for effective ways to teach STEM. That's really going to be the focus of the presentation I'll be giving today.

I left the classroom in 2016. It's a long story about how and why I left, but one of the things I was doing at the time was creating curriculum focused on STEM and computer science. Around that time, Dr. Jeanette Wing, a professor at Carnegie Mellon who later joined Microsoft, wrote a profound paper on computational thinking. She referred to computational thinking as the fourth R—reading, writing, arithmetic, and computational thinking. She argued that computational thinking was the new essential skill of the 21st century that all students needed to know. This caught my attention, and I felt that our curriculum around STEM and computer science should have computational thinking as a hallmark and foundation.

This was specifically influenced by Dr. David Weintrop. Here's a picture of Dr. Weintrop presenting at our conference last year. Funny enough, he's not presenting this year because he's on sabbatical in Mexico, trying to learn Spanish. Dr. Weintrop wrote a paper in 2016 that had a huge impact on me regarding computational thinking. As someone who had just left the classroom after 20 years of teaching sixth-grade math and science, his paper resonated deeply with me. He argued that if you were not teaching computational thinking in your math and science classes, you were not teaching real-world math and science. Real-world mathematicians and scientists use computational thinking every day.

I read that sentence probably 150 times because I thought I was a pretty good teacher, yet I was not teaching my math and science students computational thinking at all. I couldn't think of one teacher I knew who was using computational thinking in their math and science classrooms. Dr. Weintrop provided evidence showing how modern-day mathematicians and scientists use computational thinking, which kept me up at night. We were not preparing our students to work in these fields because we were not incorporating computational thinking. Moreover, David emphasized that by introducing computational thinking, students not only learn the math and science better but also prepare for real-world applications.

Thank you for your attention, and I look forward to your questions and discussions.

They're able to learn it in a much better fashion, in a much more profound way. This totally blew my mind because this looked nothing like my math and science classrooms when I taught, nothing like it. I wanted to write a letter of apology to all my former students after reading David's work, right?

Just as an example of this, I love this article. This article came out about four months ago in "The New York Times". The science section of "The New York Times" is fantastic. If you're ever looking for STEM things to share with your students, real-world applications of STEM, I cannot emphasize enough the science section of "The New York Times". This is "Vets Make House Calls for Killer Whales". This was an article, and they had a video in the article, which you see right here.

Talking about how scientists use computational thinking, this is a fantastic example of that. So what's going on here is that, and I didn't know any of this, but here's the killer whales. Okay, so killer whales are endangered. Scientists are trying to learn more about them, and these plumes that you see, the killer whales, as you see in the video right there, the plumes that come out of their blowholes contain all of this information about the whales, and all this important information about them. But how do you gather that information from the orcas? Orcas travel in very unpredictable patterns, and when they exhale with their plumes, it also happens very unpredictably. So the scientists used drones to try to predict where the orcas were going to be, and then to try to predict when they were going to come to the surface and have the plumes come out with their blowholes. Then they have the drones go to the orcas, and basically have a Petri dish on them to collect the information, take it back to the ship, and then they can analyze the information using the drone.

That's STEM education today, right? That's STEM today in a real world. That is, so when Professor Weintrop back in 2016 was talking about computational thinking, this is a great example of it right here. So when he was talking about scientists and mathematicians using computational thinking, this is such a fantastic example of it.

So this is our challenge, right? This is the challenge that we have as STEM teachers. How do we provide students with these deeply engaging learning experiences, but we struggle to do that in educational systems that so oftentimes standardize approaches? We oftentimes work in conflict. What do we mean by that? We have a lot of students that we have to educate. We have a lot of students that we have to educate, so often in order to be able to do that effectively, sometimes we feel like we have to do things at scale. In order to do things at scale, you have to do those things uniformly.

Now, that works great in software applications like VEXcode, which you have to deploy all over the world. Like VEXcode works on everything, works on Android, works on iOS, works on desktops, so in order to be able to reach that scale, you gotta be able to do things uniformly. Everything has to work the same, right, so in software applications, that's great, but in classrooms, maybe not so great, maybe not so great. Why? Because our students are different. Our classrooms are different, our challenges are different, the needs are different, so how do we create these deeply engaging learning experiences when oftentimes we're pushed to do things in a very standardized way?

And then, how do we oftentimes do that in computer science also, right? If you think about teaching computer science, so Professor Touretzky got this question after his talk.

Thank you for your attention and for being part of this important conversation. Let's continue to innovate and inspire in our teaching practices.

"Do we still need to teach computer science?" When thinking about teaching computer science, fundamentally, it relies upon students understanding symbols, just like in a math class. A plus sign and an equal sign are symbols that mean things. In computer science, you have symbols as well, which are your programming languages. However, you have to turn those symbols into meaning.

In our math classes, we often have students engage in a very hands-on way. We use manipulatives and sometimes robots, making it engaging. In our computer science classes, we often do things in a very passive way. The challenge is twofold: sometimes we do things in a very standardized way, and oftentimes in a very passive way. Unfortunately, this is what a lot of our computer science classes look like. So that's our challenge.

Another researcher I was very lucky to meet was Claire Cameron. I talked about Professor Weintrop, and Claire Cameron has a fantastic book I highly encourage you to read. Her book, "Hands On, Minds On," discusses how engaging students in a hands-on, minds-on way is a fantastic method to combat this issue. Everything we learn about how students learn and how we apply that to math and science classes, we often forget in our computer science and STEM classes.

Where I want to take this now is to transition into what I hope is a solution: the idea of synergistic learning. If I go back to Professor Weintrop for a moment, in his 2016 paper, he discussed teaching students computational thinking through creating both computational and physical models. In the article where I talked about using drones to capture information from orcas, you're using computational models to collect data and figure out where the orca will be, when the plume will come out of the blow, and using that information to help the orcas. This involves both computational and physical models.

Synergistic learning talks about the interplay between computational and physical models, the synergy between them. Professor Cameron's work emphasized giving students the opportunity to go back and forth between computational and physical models, promoting active learning instead of passive learning.

So how do we actually do that? I'm going to show you examples of this and how we've built it into the VEX AIM curriculum. This is something you see a lot now in the next generation science standards, beginning with a phenomenon. If you're familiar with our curriculum for VEX, this is something we do in VEX 123, VEX IQ, CTE, and all the curriculum on education.VEX.com. Every STEM lab we have starts with this approach. It could be a challenge, like a freeze tag STEM lab for VEX IQ. Here's the freeze tag competition: how are you going to get the highest score you possibly can?

I wish I could take credit for this, but I can't. This actually comes from Tony and Bob, two engineers and the co-founders of VEX. This is the VEX ecosystem.

Thank you for your attention and for considering these ideas. I hope they inspire you to think differently about teaching computer science and STEM education.

This is the competition of VEX, right? So we're all here for the VEX Robotics Championship. They're going to have the finals on, I think, Friday, and then they're going to do the game unveil, right? They're going to do the game unveil for next year's game, and the kids are going to immediately start working.

When it happens in the dome, there'll be 12,000 kids absolutely losing their minds. I talk about this in the introduction of my book. Five years ago, I was walking out of the game unveil with Bob, and Bob looks at me and he says, "These students have no idea how much work they just signed up for," right? I could have fallen over because that's the magic that all of us are looking for in our classrooms. Rigor, but fun, right? Rigor, but engagement. That's what we're all looking for in our classrooms, and here you had students that were literally losing their minds, like they're at a rock concert over a bunch of rigor, right?

So that's what we're trying to do here. We're trying to capture their attention through a robotics competition, right? For something like AIM, it's kick one of the sports balls through a goal. For CTE, it's palletize these discs, right? But we always try to do that for the students, and after we have them do, we have them watch that phenomenon. Now, what we want you to do is start to build a conceptual model, right?

If you are a competition coach, right, this would be familiar to you: these two steps right here, conceptual model, now start developing a game strategy, right? But for us in the classroom, it's like, "Okay, start to build a conceptual model, and then build a rule around that conceptual model," right? Start thinking about how you're going to address definitely like what actually happened there? What is actually going on? How did that phenomenon actually take place?

The mistake that we oftentimes make in our classrooms is we go from here, okay, to here immediately. Second, in a robotics or a STEM classroom, we show them a challenge. We show them a challenge, and our students, we immediately have them start building a solution to that challenge, right? Give them time to think, give them time to think, ask them to document, ask them to ask questions, okay?

So then now we get into the computational model and the physical model, and the interplay between those two things, and all throughout that process, what we want to do is we want to document and discuss. Again, I think the best way to really understand this, and I'll come back to this, is to actually see it at work in the curriculum, and we're going to look at this through VEX AIM.

The reason why VEX AIM is a great application of this is because VEX AIM has a controller. I can drive it, okay? The beautiful part about VEX AIM, and Professor Touretzky in the previous presentation showed you some amazing applications of VEX AIM, right, some amazing applications of VEX AIM, but the other beautiful thing about it is that you can code VEX AIM in blocks. You can use touch button coding on VEX AIM, so you can see it over there during the demo, but you can also see it in one of the workshops that we have, okay?

You can use touch button coding on VEX AIM, but you can also drive VEX AIM with your controller, and Professor Touretzky said something really important during his presentation. I hope it wasn't lost on all of you when he talked about the robot is in our world, right?

The robot is in our world just like we are, so the opportunity to drive the robot through the maze with a controller, and then think about the code, right, think about the code, and then test it again with the driving, and then try some code again, that going back in between the physical model, which is driving the robot, or using the touch button commands on the robot, and then also the computational model, which is the code itself, that is the synergistic learning, going back and forth between those two parts. That's what AIM gives you the opportunity to do because you have the controller that comes with the robot, and you also have the touchscreen, but of course, you also have the coding software that goes along with it.

So with AIM, there's Amy. We learned how to drag a block out, and attach it to the starting block, download your project. This is an example of the direct instruction that we have in our curriculum itself. So if we go back to this part right here, this is where we are helping the students build a conceptual model, and build a rule. This is the scaffolding that we have built inside of there for you, so this is not completely and totally open-ended, right? The students are going to need some scaffolding during these first initial parts. You're going to have students in your classroom that they've never coded a robot before. It might be their first experience coding in something like conditional loops, or conditional blocks, or coding with loops. Whatever that thing is, we want to make sure that we provide that scaffolding for you at the very beginning.

That's why we have these videos located inside the curriculum like this right here, where we walk you through all these particular things for you. Now what's really nice about this is that this allows then you, the teacher, to be the facilitator, right? You do not have to do the direct instruction. We do the direct instruction for you, okay? This allows you to walk around the room. This allows you to do whatever it is that you want to do in the classroom, and then we can actually do the direct instruction for you. I don't know about you, I was a much better teacher period two than I was period eight, right, and I oftentimes taught completely different period two than I did period eight, okay? This eliminates that. This eliminates that, okay? This makes sure your students are getting the same instruction throughout the day also, okay?

So when the students are thinking about the concepts, and they're beginning to develop that rule inside their head, this is the direct instruction that scaffolds it for them. Now, they're going to go through, after they watch the video, or after the direct instruction video, these are the types of questions that we're going to have them write down in their journal. Now it could be a journal. You could think of it as an engineering notebook, right, that they would use in a competition. I don't care what name you attach to it, but these are all the different things that we are going to put in there.

Something that we really emphasized in the VEX AIM curriculum, more so than we did in our previous iterations, is student discourse, right, having students have these conversations amongst themselves in a group, and really fostering that in our teacher notes, and also in our professional development course that we have for VEX AIM. This is something that we talk to the teachers a lot about, is how to really develop this in the classroom that you have good student discourse among these things that you're talking about with the students in there, right? So questions like you can notice here, these questions are open-ended. What did you notice about moving the robot with button coded compared to driving? What did you see in the video to support your ideas?

Thank you for your attention and dedication to fostering a dynamic learning environment. We hope this curriculum enhances your teaching experience and empowers your students to explore and innovate.

List at least two questions you have about using button coding to move the robot to a location. These are open-ended questions that we ask after, as part of the process we discussed earlier, when students have the opportunity to create a rule. This was something mentioned in the paper about synergistic learning. The key takeaway is that we've done all this for you.

When it talks about unpacking disciplinary concepts, creating integrated domain maps, and determining the curricular sequence, we've done all this for you. You are all busy enough, so we've developed the curriculum, and you don't have to worry about creating the challenges. We've also handled the assessment, which I'll discuss in a minute. You don't have to worry about the scaffolding, but you can adjust it based on your students' needs.

That's why I love the educator's lounge so much. If you look at what Jamie has done with VEX GO and literacy with VEX 123, it's not something we created from our office. He's taken what we've done further, building on the foundation we've established with VEX 123. We have STEM Labs that discuss using VEX 123 in English language arts classrooms. Jamie has taken it further because we've done all this work for you. We aim to do the same with VEX AIM, providing the scaffolding so you can address the individual needs of your classroom or school.

Now we get to the part where you're going to build the computational model, and this is where students will begin working on their own. We've developed task cards embedded throughout the curriculum. The basic flow is that we give you a challenge at phenomenon, followed by direct instruction. Students think through the questions, develop a rule or idea, and then test it. They will work on their own or in groups, using the task card as scaffolding.

The task card includes a checklist to ensure they remember what they're doing and criteria for success. More discussion questions are provided, and students can document their work. In the curriculum, this is a Google Doc, allowing you to update or edit as needed. Students can document their thoughts and begin building the computational model, testing their rule and idea.

After building some code, students will drive their robot, alternating between coding with VEXcode and physically driving the robot. This synergy involves going back and forth between driving and coding. Brainstorm ways to improve your project. The great thing about coding a robot is that your first answer is never the right answer.

Thank you for your attention and dedication to enhancing your students' learning experiences. We appreciate your hard work and commitment to education.

The first solution's never going to be the complete solution, so what this gives you an opportunity to really do is to help iterate yourself and iterate away through the solutions you see with the third bullet right here. Iterate on your own project to make it match the new driven behaviors. This is a great way for students to really explore what they're doing with their computational model, which is the code itself with the driving aspect of the robot.

And you can see here just an example of driving the robot with the VEX AIM controller. You can go see a demo of this at any time over in the Educator Lounge. We also have a couple of VEX AIM workshops where you can see this in action also, okay?

Just again, when students both drive the robot, physically experience the input, output relationships, and code the robot, they construct abstract logical sequences. They engage in this bidirectional reinforcing process. That's the synergistic learning. To go back to that book I referenced earlier from Claire Cameron, this is the hands-on, minds-on synergy that makes computational thinking more accessible and more meaningful, right?

So we do not want students sitting passively behind computers learning computational thinking that way. That's what we don't wanna be. That's what we don't want to have happening. Giving students a robot is a great way to do that. Obviously, giving them a robot makes it easier for them to collaborate. It gets them out of their seats. It gives them that, you know, again, as Professor Touretzky said, it's something in our world just like we are. But now driving the robot and going back and forth, that bi-directional relationship in between coding the robot and driving the robot, that hands-on, minds-on synergy really allows us to take that next step.

But undergirding all of this, right, something I haven't talked about yet, and a very important part of this, undergirding all of this is the idea of documenting and discussing throughout, right? It's hard to kind of represent this with a flow, but this is something again, student discourse, having them talk throughout the entire process and really fostering it is a very important part of this. This is just another example of the task card that we talked about earlier.

Now, I'd be remiss if we didn't talk about learner variability, right? It would be great, kind of as I talked about at the beginning of the speech, if all of our students learn the same way, but we know that's not the case, right? That is the art of teaching, okay? Our students do not learn the same way, so learner variability is something that we need to think about at the beginning of the learning process, not at the end of the learning process.

When I was a teacher in the classroom, learner variability is something that I was always told to think about at the end of the learning process. What do I mean by that? I would go and I would teach a lesson, and then at the end, I would work with a special education teacher, and we would make, you know, adjustments to the assessment. We make adjustments to the lesson. As I learned from working with Dr. Israel, who is doing a workshop behind me right now, that's like trying to shove the blueberries back into the muffin after the muffins are made, right? But if you make a blueberry muffin, you're supposed to include the blueberries at the beginning. You put them in the batter, and then you have a nice blueberry muffin at the end, right? That's thinking about learner variability first, right?

So how do we do that? How do we think about learner variability first with our students? How we do that, with this synergistic learning and with our VEX AIM curriculum, with all the curriculum that we do, is through making assessment student-centered, right?

Thank you for your attention and for being part of this important conversation. I hope you find these insights helpful in your teaching journey.

"McKenna, is this going to be graded?" I used to get that question all the time, and every single time I got that question, I would get upset. Upon further reflection, the reason why I would get that question was because my students were just naturally responding to the incentive structure that I created in my classroom. That was what was important to them, okay, was the grade. That was the thing that I was creating incentives for in my classroom. That was it.

In my language arts class, I would ask my students to write an essay, okay, and I would take hours to grade it. I would underline things, highlight things, write comments on things, and give it back to the students. What would they do? They'd flip through all four pages, look at the grade at the end, and then throw it away. That made me angry too, but again, the incentive structure I created in my classrooms was that the only thing they needed to care about was that thing at the end. Assessment was something that I did to the students as opposed to something I did with the students, okay, and that's a big difference.

When you do assessment with your students, not only are you changing the emphasis in the actual incentive structure that you build in your classroom around assessment, but it also allows you to think about learner variability. That's really the most important thing. When you co-create learning targets with your students, it really allows you to think about and have conversations with your students about what it is that they're learning and how they're learning, okay. This really unlocks how to build learner variability into what it is that you are doing in your classroom.

Now, the big question that we always get with this every time I start talking about assessment and learner variability as it aligns to student-centered assessment is, "What about reliability?" If I do this in my classroom, and we do student-centered assessment, and I sit down with a group of my students, and I say, "Okay, we want to be able to code our VEX AIM robot to solve this particular challenge, what do you think that we're going to have to learn in order to be able to do that? Let's create some learning targets together," and we talk about in our curriculum how to actually do that effectively with the kids. The question always arises, "What about reliability?"

I like to throw that back out and say, how reliable are your grades now? Are you actually grading learning, or are you just grading performance, okay, because learning oftentimes revolves around struggle, okay, and when we eliminate that struggle, that's just performance. I'll speak for myself, probably 85% of what was in my grade book when I taught was performance, right? So if I'm teaching something and I go to my student in my classroom, and they're having a hard time with it, and I work through it with them and give them the answer, that's just performance, okay? That's not learning. Learning involves struggle, okay, and oftentimes it looks like the students are really struggling through something. That's when learning is actually happening.

That's the great thing about STEM. We refer to that as the engineering design process, right? I fail, right, I change something, I iterate, I document on it, try something again, it fails again, do something else, right? That's called the engineering design process in STEM. We welcome that, okay? That's a great opportunity to actually gauge true learning as opposed to just performance.

I don't have a lot of time to get into this a lot about how to actually do this, but we have a ton of resources in our curriculum and online.

Thank you for your attention and commitment to improving education. Let's continue to foster environments where true learning can thrive.

We also actually have a class in VEX Professional Development Plus that talks specifically about how to do things like co-create learning targets with your students around knowledge, reasoning, skills, and products. If you have questions about this, I'll be more than happy to talk with you about it and go into as much detail as you'd like. This is how you're actually able to achieve real learner variability with your students—by making your assessment student-centered.

In our curriculum, as you see right here, here's the phenomenon. They watch a video about what's going on, ask them questions, and now the students are given an opportunity to co-create learning targets with their teacher.

So in summary, synergistic learning is a framework; it is not a script. I don't want you to feel like this is a specific thing that you have to follow like it's a recipe. It's not that; it's a framework. If you think about it, what it's really talking about here is giving students an open-ended challenge, giving them an opportunity to think about it, reason, and talk about it, and then hopefully giving them opportunities to go back and forth between physical and computational models.

This is, by the way, why I fell in love with robotics. I can barely change a light bulb—literally can barely change a light bulb. I did not fall in love with teaching robotics because I think robots are cool. I don't spend my free time coding robots. I do not. I fell in love with teaching robotics because I was always trying to find meaningful things to teach my students. I was trying to find real-world applications for my students, and I just feel that robotics is the best organizer for it.

If you want to teach computational thinking to your students, if you want to use physical and computational models, robotics is a fantastic organizer for it. Is it the only one? No, but I think it's a great one, and as Professor Touretzky even talked about in his presentation, it's a very cheap one also. VEX 123, VEX GO—these are not expensive tools that you can utilize in your classroom to be able to do this. It's all about having students explore computational and physical models, productive student discourse, right? Really, if students are documenting and talking, they're thinking, so really having productive student discourse in the classroom and really focusing on that, that's not going to happen overnight.

I'm going to give a talk—I'm not sure when. Nicole will remind me when. I'm giving a talk about the VEX continuum later on. Dr. Willson is standing in the back over there in the corner. His school, Woodland Hills, has implemented the VEX continuum, and they're a great example of this. Their kindergarten, first, and second-grade students are doing this here, so by the time they get to middle school, they will have a good discourse. This is something that's hard to do if you're like a STEM teacher on an island in your school, admittedly, but if your school district is implementing STEM across multiple grade levels, then this productive student discourse is something that you'll be able to do. But that's just difficult to do if you're the only one doing it, admittedly.

Always begin with learner variability. Do not think about learner variability at the end. Always think about learner variability at the beginning. I like to think about it by focusing on student-centered assessment. It's not the only way to do it, but that's how I like to think about it.

If you have questions for me, I'll answer some questions now, but you can always chat with me in our VEX Professional Development Plus Community. We have great conversations around topics like student-centered assessment, synergistic learning, our products, or anything else that you'd like to discuss there. Nicole will be around with the microphone. I'll be more than happy to entertain your questions.

Thank you.

One thing that you touched on was the reliability piece. My particular district, I'm from South Carolina, is trying to move towards a personalized learning model. In my class, I'm a PLTW teacher for the school, and I'm the Head Coach of our middle school robotics team too. The one thing about learner variability that was really nice is that through personalized learning, you have to give academic feedback. You're not double grading. A lot of teachers think they're grading things twice, but you're providing actual meaningful feedback so the kids can learn because that's really why we're all here, right? (laughs) We want them to learn.

If you just teach it, and then give them an activity, and then test them on it, some of them are going to be fine, some of them not so much, and you miss the opportunity to close those knowledge gaps. In my classroom, in all three grade levels, I take the time to grade. Our labs last multiple days because I have them turn in everything at the end of the day. I go through, make comments, and go back to them the next day with their group, and say, "Listen, you are missing the mark here," and then the light bulb goes off with them.

Does it take more time? Yes. Do I meet everything that I'm supposed to? Well, no, because it depends on the pace of the kids. I have different kids every semester in my class, and some of them are very bright. They really like STEM, and some of them are there because all of the other electives were full, and so now I've got to make lemonade with lemons, and do the best that I can with students that are somewhat disinterested, or they think it's too hard. The outside-the-box thinking is, and I do that model, I mean the PLTW model is set up there for you. They do the introduction, they have to do the design process on paper, and then I go over that with them. I'm like, "Well explain it to me," and then that's where they get kind of panicked because they've copied something from someone else, or they just don't really understand where I'm coming from with it. Through that, "Just explain it to me," they end up learning more in that little five-minute or less conversation with me, and then it propels them through the rest of the project.

No, that's 100% right. Myron Dueck wrote a fantastic book, D-U-E-C-K, about assessment and making it student-centered. Just that aspect of it is actually forcing the students to explain their thinking, explain their reasoning, that's how you can really reliably see what they learned. I agree with that a thousand percent, yes.

We have one more question in the back.

Thank you for the presentation. I have a question regarding, maybe it's a little more personal to you Mr. McKenna, so you said you're not a classroom teacher anymore, right?

Not anymore.

Do you think right now after you know so much about computational thinking, not only would you consider going back to being a classroom teacher, what subject would you like to teach?

So would I go back into the classroom right now? No, I would not.

The reason I would not is because Bob Mimlitch and Tony Norman, the two founders of VEX, give me the opportunity to have a much bigger impact than what I would have in the classroom. I'm about to go introduce the VR workshop, so just VEXcode VR. Tim told me yesterday that there are over 11 million unique users with VEXcode VR in something over like 180 countries. That impact is something I could not achieve in my classroom. If you would've told me 20 years ago that I'd have this opportunity, I would've told you that you're absolutely crazy. That's one aspect of it.

The other aspect is a gentleman named Mr. Sun. He was a Vice President of Caterpillar. He went back to Vietnam, where he grew up and was born, and he's very passionate about teaching STEM. STEM allowed him to have a great career with Caterpillar. He goes to some of the most remote areas in Vietnam to teach STEM in those schools. He uses VEXcode VR and VEX 123 to teach STEM to those teachers. Being able to make connections with people like him is invaluable. I probably talk to him once every two to three months about how things are going. I met him through Andy Lee, who's here and runs our office out of Hong Kong. Being able to do that and have that impact is something I would not be able to do in my classroom. It's not because I'm crazy talented or smart; it's just because of the opportunity that was given to me. I've been very lucky, and that's why I would do that.

Thank you for the question. I think we're good with that. It is 11 o'clock, so I think the new workshops and everything start at 11:10.

Thank you very much for your time. Thank you very much for your attention.

(audience claps)

Thank you. Thank you, Jason.

(bright music)

VEX Robotics Educators Conference.