Automatization in psychology refers to the finding that, as a result of extensive practice, skill execution requires progressively fewer attentional resources as expertise is acquired. In an early descriptive account of this phenomenon, Fitts (1962) proposed three phases of skill acquisition. In the cognitive phase, the learner tries to understand the nature of the skill to be learned. Next, in the associative phase, the learner practices the correct movement patterns until he/she is largely error-free.
Finally, in the autonomous phase, the learner’s activity is typically described as being automatic or unconscious. Subsequently, Fitts and Posner (1967) postulated that performers progress from a controlled, conscious, and declarative mode of information processing (i.e., at the novice stage) to a more automatic and proceduralized mode of processing (i.e., at the expert stage). Automated processes are believed to be “fast, stimulus-driven, and characterized by a lack of intention, attention, and awareness” (Saling & Phillips, 2007, p. 2). Automatization confers a number of benefits on the skilled performer. For example, in complex cognitive tasks, such as chess, it allows skilled players to benefit from parallel processing, which enables him/her to understand the relative position of different pieces on a chess board at a glance (Reingold, Charness, Schultetus, & Stampe, 2001). In sporting tasks, automated processing of the mechanical components of a skill (e.g., wrist break in a putting stroke) allows the expert athlete to focus on strategic elements of performance (e.g., where to aim on a severely sloping green). Automaticity is also believed to facilitate cognitive processes such as advanced cue utilization (i.e., the athlete’s ability to make accurate predictions based on contextual information early in an action sequence) and visuospatial pattern recognition (the ability to detect patterns of play early in their development).
As a result, automatization allows athletes to make quick and efficient decisions in dynamic environments where time constraints allow them little
opportunity to deliberate upon a course of action. Unfortunately, automatization may have costs as well as benefits. For example, Toner, Montero, and Moran (2015) argued recently that highly automated behaviors can, on occasion, lead to a variety of performance errors and cognitive lapses (e.g., inattentional blindness or failing to notice something even though one is looking at it). Clearly, expert performers may need to guard against excessive automatization if they wish to avoid ‘arrested development’ (Ericsson, 2004).
References
Ericsson, K. A. (2004). Deliberate practice and the acquisition and maintenance of expert performance in medicine and related domains. Academic Medicine, 79, S70 S81.
Fitts, P. M. (1962). Factors in complex skill training. In R. Glaser (Ed.), Training research and education. Pittsburgh, PA: University of Pittsburgh Press, [Reprinted 1990. In M. Venturino (Ed.), Selected readings in human factors (pp. 275 296). Santa Monica, CA: Human Factors Society].
Fitts, P. M., & Posner, M. I. (1967). Human performance. California: Brooks/Cole Publishing Company.
Reingold, E. M., Charness, N., Schultetus, R. S., & Stampe, D. M. (2001). Perceptual automaticity in expert chess players: Parallel encoding of chess relations. Psychonomic Bulletin & Review, 8, 504 510.
Saling, L. L., & Phillips, J. G. (2007). Automatic behaviour: Efficient not mindless. Brain Research Bulletin, 73, 1 20.
Toner, J., Montero, B., & Moran, A. (2015). The perils of automaticity. Review of General Psychology, 19, 431 442.
***Contributed by John Toner & Aidan Moran for Hackfort, D., Schinke, R. J., & Strauss, B. (Eds.). (2019). Dictionary of sport psychology: sport, exercise, and performing arts. Academic Press. https://amzn.to/3ZxARzT
