Problem Solving and Conceptual Models

When I was in college I decided I wanted to learn how to play the guitar. I was about to proudly graduate and to compensate for my correspondingly large college boy ego I needed to try something I would be horrible at. I figured that hearing myself squealing away on a new instrument would remind me that I wasn't that much of a hotshot, and as a bonus I'd have something I could play at parties if I ever decided I had too many friends. Basically, I was still a child, and I beg your forgiveness.

When I first started practicing on my cheap Squier, the sounds I was producing sounded less like music and more like an angry hornet's nest trapped in a shoe box. This killed my enthusiasm for practicing, partly because I didn't want my roommates to murder me, partly because I wasn't that invested in practicing in the first place, and partly because I didn't want our pet dwarf hamster to go deaf. I realize now that it was silly of me to worry, as our house parties were definitely more obnoxious and she survived those. 

Most importantly, I decided that it was the guitar's fault it sounded bad, thus absolving me of any responsibility for my crimes against musicality. (Like I said, I was a child.) So, like a good little almost-college-educated problem solver who loved to procrastinate, I dedicated myself to fixing my guitar.

First, I specified my goal: 3 of my strings produced a muted, buzzing noise, while the rest produced what could be considered notes, so my goal would be to make the bad strings sound like the good strings. Next, I tried to figure out the specifics of the problem, mostly by playing more bad music and listening closely to what was happening. I figured out that the horrible buzzing only happened when I held down the strings in specific spots, which suggested that the strings themselves weren't the problem, but rather the relationship between the strings and the guitar's fretboard.

In essence, I was exploring my conceptual model of how a guitar works—thinking through the concepts and ideas I held in my mind that described how I believes notes were made on the instrument. If my conceptual model had been wrong, I might have tried replacing the strings. Instead, I changed the angle of the fretboard, and eliminated the horrible buzzing. From then on, the horrible noises produced by my guitar were solidly my fault.


Around the same time, my household was having problems with the washing machine—it wouldn't start its spin cycle, leaving our clothes soapy, soggy, and dirty. No one living in the house had any clue how a washing machine actually worked, internally, and we knew it. So we tried to build a mental model with a method used by infants everywhere: we did things and watched what happened. We turned knobs, kicked it, shook it, pressed buttons in different orders, slammed the top hatch down... and suddenly it started. Suddenly we had some information to add to our conceptual model: the washing machine wouldn't start its spin cycle with the top hatch open, and the top hatch "thought" it was open unless it was slammed closed. We were super excited that we had solved the problem ourselves.

Unfortunately, our conceptual model was completely wrong, and when the washing machine wouldn't start the next day we slammed the hatch with comical amounts of force with no effect. Eventually we hired a professional to diagnose the issue, and his conceptual model was markedly more accurate than ours. It took him about 3 minutes to tell us that the machine's fuse had blown.


Conceptual models support problem solving. If conceptual models are wrong, it doesn't really matter how well we know the exact result we want—we won't be able to see what we need to do to achieve it, or worse, we'll think we see exactly what we need to do while actually having no clue. Then, when we don't get the result we expected, we'll get frustrated.

Some conceptual models are completely ingrained through years of exposure. When we enter a dark room we unconsciously slap walls searching for a light switch because we know there has to be a nearby way to turn on the lights. When we encounter problems involving less ingrained mental models, we take in passive auditory and visual clues and poke and prod in order to build one. Sometimes, when all of the elements of the model are visible, easily isolated, and give direct feedback when manipulated (like with a guitar), we can build strong conceptual models quickly. Other times, when the elements are hidden and feedback to prodding is limited (like with an old washing machine) the models that emerge are weaker or simply wrong.


Games present players with problems to solve, and players rely on their conceptual models of how the game works in order to solve them. Frustration occurs when the player's conceptual model doesn't match the real model that was designed and implemented into the game. To make matters more complicated, game designers' systems and models are often things players have not spent a lifetime interacting with, which means we can't really ever assume familiarity on par with light switches. Also, many players will bring related conceptual models from other life experiences or other games and attempt to apply them to problems and challenges they encoutner in a new game. And lest a designer get lazy, it is very easy and not uncommon for us to design problems that seem simple on the surface, but that actually build on top of conceptual models that are ingrained into those who regularly play a certain type of video game. Players unfamiliar with those games are then left unsupported and lost.

As game developers, we want to avoid player frustration, so we need to carefully and clearly communicate what our models are so that players can grasp the concept fully enough to put pieces together—but not so fully that all of the presented problems are solved for them by the game. We want to be more like a guitar than a washing machine: visible, isolated parts that provide instant positive and negative feedback when investigated, where causes and effects are clear rather than misleading, where solving a problem feels more like exploring and playing than an endless endeavor of random tactics that might hopefully result in some clean clothing.