Guidelines for doing a cognitive science project, Part 1: Problem definition

In this series of posts, I try and establish a guidelines that now, in hindsight, would have been very useful to know before embarking on doing a cognitive science project. This particular post is about the problem definition process.

          The first step while undertaking any project is problem definition. I consider this to be an art because I see no hard and fast rules to follow for problem definition. Essentially, it is a trade-off between activity and planning. While you don't want to mindlessly set out on a wild goose chase without any clear direction, at the same time, you cannot be stuck in a rut trying to plan out every detail. I think the right balance is to start doing something while at the same time trying to find all the flaws with the direction of what you're doing. Sounds paradoxical, but the only way to keep the creative juices flowing is by actually creating. 

           The project that me and my team were doing was studying how people make predictions about the outcome of football matches (you can call it soccer, but I refuse to call it anything but football). Football is a sport that I love, play and follow, and this was while the Euros were going on so seemed like a great project to do. 

            As I have stressed earlier, it is really important to get started doing something. Had we got stuck trying to dissect the sentence "people predict the outcome of football matches", we would have quite possibly given up right there. Since the project was on cognition, and in this case, human cognition, the best way to get started was introspection. This way, you don't end up bothering anybody else by asking them to predict a ton of football games and at the same time, you don't sit around wondering where to go with the project.   

            The introspection resulted in the realization that emotions were playing a big role and the reasons could be literally anything: "I lived in France so France would win", "I love Italian cuisine so Italy would win". Being an engineer, I love to model things and use the model for predictions. But with reasons so arbitrary, and such a plethora of factors, any kind of analysis let alone prediction seemed a far cry indeed. 

            However, now that I had an idea of the rabbit hole that emotions could lead to, this helped me find things that drive me away from this rabbit hole. We revisited the problem statement and instead of predict, we said bet on. Thus the new problem statement became: "How do people bet on the outcomes of football matches"? This immediately scoped down the problem because now the situation wasn't just trying to see how people support teams, it was trying to analyze who they would put their money on. This made the problem amenable to all forms of model building with its associated analysis and predictive power.
             In conclusion, don't be surprised if cognitive science projects start off being rather broad and rather vague. Start doing something, start trying to build a model and this activity will make you think about the task and better directions would emerge.