Learning to learn, and what games are good for
Riot removed the ability to download replays from arbitrary League of Legends accounts. That matters to third-party match-history and analysis sites that depend on those files. As I understand it, a replay records the actions taken in a match as simulation data, rather than saving a video. That makes it possible to examine what happened in the game without trying to extract the same information from footage. I do not know how many of these services depended on replay downloads, but losing access creates an obvious problem for the ones that did.
That got me thinking about the arguments around AI, changing work, and the ability to learn a new skill. The part I keep coming back to is learning how to learn: understanding how you build knowledge, how you recognize progress, and how you might use that process again. What follows is a hypothesis I am trying to work out. The examples are mostly my own, and they cannot establish a general theory of learning.
The skill you need before the meta-skill
I suspect most people have some subject they take to more readily than others. I do not know why that happens. It might have a great deal to do with what someone encountered while growing up, what interested them, or what they had a reason to practice. I have not tested any of those explanations.
My stronger hypothesis is that learning how to learn is extraordinarily difficult until you have reached some level of mastery in one thing. To examine a learning process, you need a process you can look back on. You need to have experienced the difference between understanding something poorly and understanding it well enough to recognize a mistake, make a judgment, or work out something new from what you already know.
The difficult part is recognizing that change in yourself. We can study metacognition in structured settings, but ordinary life does not necessarily prompt someone to ask how they learned a skill. I suspect that part of the appeal of self-help books is that they offer a framework for noticing and evaluating progress. That is an interpretation of why people use those books, not a finding I have established.
Once you are good enough at something to see when a piece of work looks wrong, you have a way to examine your own improvement. You can look back and ask what helped, where you got stuck, and whether any part of that process would help you learn something else.
This reminds me of how I understood my parents when I was a child. I could barely tie my shoes, and either of them could tie a knot that looked perfect to me. Then my mother could turn around and tie a different kind of knot to hold up a parasol. I remember wondering how adults seemed to know how to do everything. I now associate part of that experience with wisdom: having enough examples of learning and problem-solving to talk about the process itself. Advice can sound obvious or even a little ridiculous when you have not yet had the experience that lets you evaluate it.
What games are actually good at
Games have given me a lot of those smaller experiences. Part of why I play is the feeling of getting better at something. Another part is social. Friends I grew up with have moved away, and getting into Discord together while we play a game can feel surprisingly close to being in the same room. In one tank game, we are all represented by these little vehicles, moving around and talking to each other. The game gives us something to do together while we talk.
For learning, the property that interests me is the size of the experience. A game gives you a set of mechanics to understand and practice. You can become meaningfully better over tens or hundreds of hours, then look back at how you got there. That is a much shorter arc than many skills people spend years building.
I have played about fifty hours of Factorio. At the beginning, I barely thought about ratios or belt speeds. I would build a machine producing blue science and wait for it to make enough to unlock the next research level. Now I think about throughput before laying things out. If I am building engine units, I start with the batch I want to produce, work backward through steel and gears, and plan the belts around the later science production that will need those engines. I described twelve engine units as the smallest useful batch for one layout I was considering. The point is how differently I approach the problem now, not whether twelve is a universal production ratio.
Fifty hours is very little time compared with how long I have spent learning to program. I have spent roughly ten years of my adult life coding, including time working at Microsoft, and I still compare myself with people who could take a complicated request and produce an elegant design almost as they typed. I remember seeing colleagues build structures that passed function pointers around and called them at the right moment, without holding on to all the intermediate data. Watching how quickly they reached those designs made me aware of how much I still had to learn. After fifty hours of Factorio, by comparison, I could already look back at a complete shift in how I built a factory.
That contrast is what makes games interesting to me. You can take a bounded experience of learning, examine it, and ask what you would do differently the next time. I would like to know whether that kind of reflection helps people learn another game or another skill more efficiently. My own experience gives me a reason to ask the question, though it does not answer it.
I also have a story that initially felt like evidence of a specific skill transferring between games and the physical world. I played a great deal of Rocket League in high school. By my senior year, the FIRST Robotics team held tryouts for the person who would drive the robot. The adults running the team had set up an obstacle course. I remember other students taking around five or six minutes, with some runs lasting longer. My first attempt took about a minute and ten seconds. They asked me to drive it again in reverse, and I completed the attempts quickly enough to be chosen as the driver. We went to Worlds that year. Our robot was very well built, which mattered at least as much as who was driving it.
The experience felt familiar because Rocket League had given me practice steering a vehicle from camera angles that do not match its direction of travel. You might be flying backward toward your own goal, adjusting an input while the ball and your car are moving in different directions. In robotics, the robot could be a long way away, partly out of view, and moving around a corner. I did not need to see it from behind to work out the controls. At the time, I took that as a transfer from playing Rocket League to driving the robot.
The paper that complicates the story I just told
Yasitha Rajapaksha, a colleague of mine at NC State, published a study at CHI 2026 with John Thomas Bacher and Tiffany Barnes on how game features and spatial skills interact with performance and perceived difficulty in a block-based 3D programming puzzle game 1. Players program a bot to move a block through an environment while trying to minimize its movements. The activity was designed around an idea from programming: you first work through a repeated action, then identify the part that stays the same and the part a loop can generalize.
As I recall the result, performance in the game was strongly associated with self-reported prior video game experience and performance on a spatial reasoning test, and how much the game itself taught was difficult to establish. That sentence is my memory of the findings rather than a reading of the paper. The citation is there so it can be checked against what the paper actually reports.
This is the difficulty with claiming that a game teaches a specific skill. People arrive with different experience and abilities, and those differences can explain some of what looks like learning during play. A carefully designed game can still help someone learn. The challenge is separating that effect from what the person already brought to it.
That same problem applies to my robotics story. I had played Rocket League for a long time, but I may also have had strong spatial reasoning before I played it. I cannot go back and test what I would have done at the tryout without those hours in the game. The similarity between the two tasks tells me why the robot felt familiar. It does not establish which parts of my performance Rocket League caused.
I still suspect games are useful for learning how to learn. They give you bounded experiences in which you can notice yourself improving, then ask what changed. What I am less comfortable claiming now is that a particular game taught a skill simply because I later used something that felt similar. That is the distinction I would want a study to test.
References
Tagged learning-sciences · games · metacognition
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