Master Maker: Understanding Gaming Skill through Practice and Habit from Gameplay Behavior – topiCS 2017

by Jeff Huang, Eddie Yan, Gifford Cheung, Nachiappan Nagappan, Thomas Zimmermann

The study of expertise is difficult to do in a lab environment due to the challenge of finding people at different skill levels and the lack of time for participants to acquire mastery. In this paper, we report on two studies that analyze naturalistic gameplay data using cohort analysis to better understand how skill relates to practice and habit. Two cohorts are analyzed, each from two different games (Halo Reach and StarCraft 2 ). Our work follows skill progression through 7 months of Halo matches for a holistic perspective, but also explores low-level in-game habits when controlling game units in StarCraft 2. Players who played moderately frequently without long breaks were able to gain skill the most efficiently. What set the highest performers apart was their ability to gain skill more rapidly and without dips compared to other players. At the beginning of matches, top players habitually warmed up by selecting and re-selecting groups of units repeatedly in a meaningless cycle. They exhibited unique routines during their play that aided them when under pressure.

Reference

Jeff Huang, Eddie Yan, Gifford Cheung, Nachiappan Nagappan, Thomas Zimmermann. Master Maker: Understanding Gaming Skill through Practice and Habit from Gameplay Behavior. In Topics in Cognitive Science: (2017), 2017. To appear

BibTeX Entry

@article{huang-topics-2017,
    title = "Master Maker: Understanding Gaming Skill through Practice and Habit from Gameplay Behavior",
    author = "Jeff Huang and Eddie Yan and Gifford Cheung and Nachiappan Nagappan and Thomas Zimmermann",
    year = "2017",
    journal = "Topics in Cognitive Science",
}