Measuring Flow Using Psychophysiological Data in a Multiplayer Gaming Context

This paper investigates a prediction from flow theory according to which subjective feelings of concentration depend on the balance between perceived challenges posed by a task and one's perceived skills in mastering the task. The goal is to compare three different formalizations of balance (crossproduct, absolute difference, and quadratic effects of challenges and skills following a rotation of the predictor axes) with respect to how well each model predicts everyday life selfreports of feelings of concentration, which were obtained with the Experience Sampling Method from 208 talented high school students. Multilevel modeling with first-order autocorrelation structure is used throughout the model comparison. All models fitted reasonably well, accounting for nearly half of the variance. With reference to simple goodness-of-fit criteria, we conclude that both the rotated and the absolute difference models are to be preferred. Lastly, we discuss and compare the implications of the models for teaching, and outline extensions toward dynamic modeling and external modeling, by relating the subject specific effects of challenges and skills and of their balance with non-experiential variables such as personality traits and achievement measures.