Commandment #6: Learning

This post is part of a series of articles detailing the BrainGoodGames Design Commandments. You can see the full list here.

Raph Koster explains in his novel “A Theory of Fun” that perhaps the most important source of enjoyment in a game comes from learning. I absolutely agree with this claim, and framing things in this way can allow us to make many inferences about the ideal way to design our games.

As explained in my recent article, carefully crafted ambiguity allows a designer to continually present the player with novel and yet at least somewhat comparable situations to those they have encountered before. In this context, players are able to use their existing knowledge of a game’s system, without being able to rely on rote memorization of solutions to succeed. As they receive feedback (most importantly through whether they won or lost), they can develop new insights into the system (i.e learn).

However, this is not quite enough, because there is another way that learning can be prevented that is quite common. If the game situation is too easy to figure out for the player, they can simply pick an arbitrary strategy and win, without weighing/considering several options (strategic thinking). If the game situation is too hard/beyond their capability to figure out, then all of the strategic paths they come up with will be equally ineffective (resulting in a loss). Either way, learning is stifled. 

Fortunately, multiplayer match-based games have already come up with an ingenious solution to this problem: a matchmaking/ladder ranking system! In such a system, players are (theoretically) matched against opponents that provide suitable difficulty for them. As Keith Burgun points out, such a system can also be applied in a single-player context in much the same way. As players win, the game gets harder, and as they lose, the game gets easier. At some point, they will be placed into matches of an appropriate challenge level (which allows for optimal learning!). This process can even be sped up by doing a “placement match” to estimate what rank/difficulty they should start at. 

This does beg the question of how to scale the system mathematically to increase the challenge in a way that does not feel arbitrary (not to mention designing a system that rewards learning in the first place). This is one of the primary challenges of designing a single-player strategy game in my opinion, and needs to be considered early on in the process. It is absolutely possible to come up with satisfying answers, and provide reasonable scaling up to a very high level of skill.

The single-player ladder system in Minos Strategos.

As one final point, I want to mention that a system such as this has the added benefit of reflecting a player’s growth and learning in a tangible way! By ranking up a player is able to see with some degree of certainty that they have in fact improved at understanding the system strategically, which is an awesome side effect.