Predicting the future in perceptual-motor domains: Perceptual anticipation, option generation, and expertise
Document Type
Article
Publication Date
1-1-2015
Abstract
© Cambridge University Press 2015. Introduction In complex, dynamic environments, successful performance often depends on the ability to make accurate predictions. Skilled prediction includes the ability to anticipate the future state of the current situation prior to acting on it, to predict a personal future position prior to pursuing an intended course of action, as well as to predict how a course of action will shape the future situational state (Poulton, 1957). Impressively, experts can make such predictions under temporal and/or informational constraint. In this chapter, we focus on the ability to anticipate situational outcomes as a principled basis for understanding and improving skilled performance. Much research has detailed the experts’ ability to recognize a situation as familiar and select a good course of action (e.g., Klein, Calderwood, and Clinton-Cirocco, 1986). However, this research has been less concerned with identifying the structure of recognized situations (cf. Vicente and Wang, 1998), or how experts use perceptible information to generate on-the-fly predictions about how situations will unfold. While researchers have described the cognitive characteristics of being situationally “aware,” the focus has been on the perceptual errors, or deficiencies in understanding, that might lead to a lack of situation awareness (e.g., Endsley and Rodgers, 1998; Jones and Endsley, 1996). As a result, less emphasis is placed on the most interesting aspect of situation awareness - the ability to project into the immediate future and predict the outcome of the situation (see Sulistyawati, Wickens, and Chui, 2011).
Publication Title
The Cambridge Handbook of Applied Perception Research
Recommended Citation
Suss, J.,
&
Ward, P.
(2015).
Predicting the future in perceptual-motor domains: Perceptual anticipation, option generation, and expertise.
The Cambridge Handbook of Applied Perception Research, 951-976.
http://doi.org/10.1017/CBO9780511973017.056
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/7736