Abstract
Gone are the days the content of a game was completely created manually and the gameplay was pre-scripted before the game release. Nowadays an increasing number of games use procedurally generated content to provide engaging gaming experiences. Most of the endless single player games generate content based on the difficulty of the challenges combined with the duration of the current game session, which leads to a similar gameplay experience to every player. In this dissertation, we address the problem of keeping the players engaged in a game for longer periods of time. One way to increase the gameplay experience of a game is to increase the feeling of progression. To solve this problem we propose a progression model that creates content based on the player skill. We theorize that, by providing a progression that is adapted to the player based on the player skill, keeping the variety of the challenges will lead to more engaging gameplay experiences. We propose a progression model for the endless level of the mobile game Smash Time. We believe to have created a progression model that is robust and dynamic enough to be used in different games and that excludes the need of using preset difficulty settings. The results from playtests with users suggest that the developed progression model is able to increase the number and duration of the gameplay experiences and has the potential to increase player immersion, creating more engaging gameplay experiences that may, ultimately, increase the overall lifetime of the game itself.