Computational Thinking as a Problem Solving Tool

Computational thinking is the process of breaking a problem into smaller parts, recognizing patterns, creating step by step instructions, and testing and revising when things do not work. When I think about it that way, it actually feels very aligned with teaching and learning. It is how I coach and how we help students improve in any subject.

This became most obvious to me when we talked about prompting AI. When you enter a vague prompt, you get a vague or unhelpful response. The tool is not mind reading. It responds to exactly what you give it. If the outcome is unclear, it usually reflects unclear input. The peanut butter and jam sandwich instruction video illustrates the same idea in a simple way. When the dad follows the directions exactly as stated, the result is a mess because the instructions lack precision. The humour works, but the deeper point is that we can only execute what we had been told.

That is what makes computational thinking so valuable. It forces you to slow down, clarify your intent, and organize your thinking into precise steps. When something does not work, it becomes feedback. It reveals where the thinking needs refinement.

In Physical and Health Education, this is not new. When teaching a complex movement, we do not just say “shoot the ball.” We break it down into components like foot placement, body position, timing, and follow through. If something is off, we isolate it, adjust, and try again.

Coding Beyond Math

I’ll be honest. When I hear the word coding, my first reaction is still not excitement. It feels technical and a bit removed from the kind of physical teaching I picture myself doing. But this week did give me some insight that coding is not really about the computer, but about deepening thinking. Additionally, before this week, I associated coding mostly with math. What stood out to me is how many non-math opportunities there are for integration.

In PHE, students could:

  • Design a simple interactive game that teaches the rules of volleyball
  • Create a Scratch animation that demonstrates how the heart rate changes during exercise
  • Build a digital tutorial for younger students on how to warm up safely

Coding becomes a tool that allows students to represent understanding in a different medium (cue multi-modal learning!).

Making Abstract Ideas Concrete

Another learning objective was understanding how coding can make abstract ideas more concrete.

Another learning objective was understanding how coding can make abstract concepts more concrete. In PHE, that feels especially relevant when we think about movement analysis.

In my biomechanics class, we filmed our sprinting and then analyzed our form to understand how body angles impacted speed and efficiency. We used tools like Kinovea to break down joint angles frame by frame, created free body diagrams to visualize force production, wore a Movesense sensor to track data, and used timing gates to measure performance. Instead of just hearing that “forward lean matters” or “hip extension drives speed,” we could actually see how the angles of our bodies influenced force and velocity. The math and physics stopped being abstract. They were visible in our own movement.

I can see how something similar could happen in a platform like Scratch. Students could design a simple sprint simulation where changing the angle of the torso or the force applied alters the speed of a character. Instead of memorizing ideal sprint mechanics, they could experiment. If the angle is too upright, speed decreases. If force application changes, acceleration shifts. It becomes a space to test and refine ideas.

The coding itself is not the point but it is making relationships visible. Just like in biomechanics, students could manipulate one variable at a time, observe the outcome, and adjust.

The Anna and Elsa activity from Code.org connects to this idea. Learners guide the characters to move and draw shapes on the ice, which means thinking carefully about angles and how many times a movement repeats. If the angle is slightly off, the shape does not come together the way you expect. That kind of immediate feedback makes geometry feel less abstract. Angles stop being numbers on a page and become something you can see unfold step by step.

Image from in-class work period attempting the Elsa + Anna Coding Activity

Gaming in Education

I have mixed feelings about games in education. I value play and engagement, especially in PHE where learning is already active and embodied. At the same time, I get cautious when something feels more like entertainment than actual learning.

I think some of that comes from my own experience. I remember being in the computer lab playing games like Gizmos and Gadgets and the TransCanada Highway driving game. I genuinely enjoyed them as they felt different and exciting. But if I am being honest, I do not remember what I was supposed to be learning.

Gizmos + Gadgets Game
Cross Country Canada Game

That is where my hesitation sits. I am not against games. I just think the purpose has to be really clear. If students do not understand why they are playing something or what they are meant to notice or practice, it can easily turn into “fun computer time” instead of meaningful learning.

The APA article helped solidified that. It did not say games are automatically good or bad for learning, but it emphasized that strong educational games have clear goals, immediate feedback, manageable challenge, space for reflection, and thoughtful support. That made sense to me as it is not about the game itself, but about the design behind it.

In PHE, we already do this through the TGFU method (Teaching Games for Understanding). We use small sided games and modified play to build tactical awareness and decision making. Those activities look like games, but they are intentionally structured. There is a clear learning focus underneath the play and we explicitly explain to the students WHY we are doing them, ensuring comprehension through guided questioning.

Even something like GetBadNews connects to this idea. It felt controversial in class, but I can see how stepping into the role of a misinformation creator could build critical awareness. The learning goal is explicit and you are not just playing but you are analyzing tactics through experience.

What I keep coming back to is clarity. Badges, leaderboards, or fitness points on their own do not guarantee depth. Without intention, gamification can shift the focus to winning or collecting rewards instead of actually understanding something. For me, the difference between distraction and depth comes down to whether the learning is visible and purposeful.

Video For Deeper Learning

The video “Top 5 Gamification Examples in Education” shows how teachers use games with levels, challenges, and rewards to increase engagement, but with clear learning goals behind them. It emphasizes that gamification works best when it is intentionally designed to support understanding, not just motivation. When games are structured around clear outcomes and feedback, they can deepen learning rather than distract from it.

Final Thoughts

This week helped me see coding and gaming less as add ons and more as tools. They are not replacements for movement, discussion, or hands on experience, but they can enrich them, especially in PHE and high-performance training.

Computational thinking builds clarity, patience, and structured problem solving.
Coding provides a creative medium for demonstrating understanding.
Games can increase engagement when they are intentionally designed.

As a future PHE educator, I want technology to serve learning, not the other way around. If coding and gaming helps students think more deeply, collaborate more meaningfully, and take ownership of their learning, then I can see myself including it in my classroom.