Action sequencing, timing, and chunking in Space Fortress

Recent cognitive modeling research has been uncovering the complex mechanisms whereby humans learn to combine instruction and experience to acquire rapid and precise complex skills. One promising way of exploring sensorimotor learning during skill acquisition is to look at the details of motor behavior. In this project, we focus on action timing and action sequencing in a SF video game instantiation with complex dynamics called YouTurn. We first explore the structure of keypress chunks over forty 3-min games in SF YouTurn. We then investigate skill acquisition and inter-individual skill differences in terms of action sequencing variability and action timing variability. Finally, we fit linear models to see whether measures of action sequencing variability and action timing variability could predict skill in SF YouTurn.