title: The fluid events model: Predicting continuous task action change.
abstract: The fluid events model is a behavioural model aimed at predicting the likelihood that people will change their actions in ongoing, interactive events. From this view, not only are people responding to aspects of the environment, but they are also basing responses on prior experiences. The fluid events model is an attempt to predict the likelihood that people will shift the type of actions taken within an event on a trial-by-trial basis, taking into account both event structure and experience-based factors. The event-structure factors are: (a) changes in event structure, (b) suitability of the current action to the event, and (c) time on task. The experience-based factors are: (a) whether a person has recently shifted actions, (b) how often a person has shifted actions, (c) whether there has been a dip in performance, and (d) a person's propensity to switch actions within the current task. The model was assessed using data from a series of tasks in which a person was producing responses to events. These were two stimulus-driven figure-drawing studies, a conceptually driven decision-making study, and a probability matching study using a standard laboratory task. This analysis predicted trial-by-trial action switching in a person-independent manner with an average accuracy of 70%, which reflects a 34% improvement above chance. In addition, correlations between overall switch rates and actual switch rates were remarkably high (mean r = .98). The experience-based factors played a more major role than the event-structure factors, but this might be attributable to the nature of the tasks.
authors.affiliation: a Department of Psychology , University of Notre Dame , Notre Dame , IN , USA.
authors.forename: Gabriel A
authors.initials: GA
authors.lastname: Radvansky
authors.forename: Sidney
authors.initials: S
authors.lastname: D'Mello
authors.forename: Robert G
authors.initials: RG
authors.lastname: Abbott
authors.forename: Brent
authors.initials: B
authors.lastname: Morgan
authors.forename: Karl
authors.initials: K
authors.lastname: Fike
authors.forename: Andrea K
authors.initials: AK
authors.lastname: Tamplin
mesh_terms: D019540:Area Under Curve; D001288:Attention / Q000502:physiology*; D002755:Choice Behavior / Q000502:physiology; D004777:Environment; D005260:Female; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D008960:Models, Psychological; D011237:Predictive Value of Tests; D011597:Psychomotor Performance / Q000502:physiology*
keywords: Event cognition; Event segmentation; Interactive events