The article discusses the application of probabilistic modeling to analyze user behavior during gameplay. Researchers aim to fit a model to baseline behavior data and use it to evaluate how changes in input modalities affect gameplay. Key behavioral features such as interkey interval and Pac-Man's turning time will be measured to reflect player actions and efficiency. Data collection occurs during baseline sessions recorded under controlled pre-test and post-test conditions, providing a framework for understanding player performance and adjusting design parameters accordingly.
The goal is to fit a probabilistic model onto baseline behavioral data to assess observed data likelihood when changing input modalities or design parameters.
We will focus on Player actions, specifically interkey intervals and turning time, which reflect a player’s efficiency and responsiveness during gameplay.
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