Entscheidungsleistung und selbstgeneriertes Wissen zu Mustern in der Handballverteidigung: ein Fall von „representational redescription“

Author:

Magnaguagno Lukas,Hossner Ernst-Joachim,Schmid Jürg,Zahno Stephan

Abstract

AbstractIn sport games, perceptual–cognitive skills are discussed as a decisive aspect of players’ expertise. However, an understanding of the relationship between these skills and actual game performance is limited, particularly, regarding the role of pattern identification and situational-probability estimation in performance. The present study thus aimed to examine how identification of teammates’ defensive qualities relates to decision-making performance in a 3:3 virtual-reality defensive task. Examining data collected in two previously published studies, we analyzed the relationship between explicit pattern detection and response correctness, and also as a function of players’ experience. Experience was operationalized as either expertise level (Experiment 1) or task-specific experience (Experiment 2). As expected, the explicit detection of a game-specific pattern was found to be facilitated by experience. However, the results imply that it is accumulated experience that enhances decision-making performance rather than the degree of self-generated explicit knowledge. This finding supports the notion of “representational redescription” as introduced by Karmiloff-Smith (1994). For sports practice, this suggests that the pattern identification demonstrated by skilled athletes should not be overestimated as a predictor of game performance, while the explicit provision of knowledge might be beneficial for less-skilled athletes, particularly in situations of high uncertainty.

Funder

University of Bern

Publisher

Springer Science and Business Media LLC

Subject

Physical Therapy, Sports Therapy and Rehabilitation,Orthopedics and Sports Medicine

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Super Long Range CNN For Video Enhancement in Handball Action Recognition;2024 3rd International Conference on Artificial Intelligence For Internet of Things (AIIoT);2024-05-03

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