Self-regulated learning predicts skill group differences in developing athletes |
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| Affiliation: | 1. 125 University Private, Montpetit Hall, MNT 416B, School of Human Kinetics, University of Ottawa, Ottawa, Ontario, K1N 6N5, Canada;2. 125 University Private, Montpetit Hall, MNT 226, School of Human Kinetics, University of Ottawa, Ottawa, Ontario, K1N 6N5, Canada;3. 4700 Keele St, Norman Bethune College 338, School of Kinesiology and Health Science, York University, Toronto, Ontario, M3J 1P3, Canada;1. Department of Sport, Health and Exercise Sciences, University of Hull, Cottingham Road, Hull HU6 7RX, UK;2. Department of Psychology, University of Huddersfield, Queensgate, Huddersfield, HD1 3DH, UK;1. University of Trieste, Department of Life Sciences, Italy;2. De Montfort University, Division of Psychology, United Kingdom;3. University of Trieste, Department of Medicine, Surgery and Health Sciences, Italy;1. University of Manitoba, 66 Chancellors Circle, Winnipeg, MB R3T 2N2, Canada;2. University of Ottawa, 75 Laurier Ave E, Ottawa, ON K1N 6N5, Canada |
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| Abstract: | ObjectivesSelf-regulated learning (SRL) likely plays a crucial role in expert development by helping individuals optimize their practice (Zimmerman, 2006). However, limited sport studies have examined expert/novice differences in SRL, and almost none have used a self-report SRL measure. Therefore, the purpose of this study was to examine SRL differences in three progressively skilled athletic groups: recreationally competitive, less-elite, elite.DesignA cross sectional study using a self-report survey.MethodWe vetted the Self-Regulation of Learning − Self-Report Scale (SRL-SRS; Toering et al., 2012) survey for face validity with an expert panel. Subsequently, 272 participants (200 m, 72 f; ages 18–35) completed a sport-training version of the SRL-SRS, which included modified items according to panel recommendations and refinements for factorial validity. Participants also completed survey measures for weekly practice and performance level. Logistic regression analyses served to determine: a) how composite (overall) SRL processes, and b) how six constituent SRL processes, explained performance level.ResultsGreater overall engagement in composite SRL was associated with being in the elite group compared to less-elite and recreationally competitive groups. Of the constituent SRL processes, only self-monitoring predicted membership in the elite and less-elite group compared to the recreationally competitive. Additional analyses revealed planning, self-monitoring, effort and self-efficacy separately predicted membership in the elite group, relative to the less-elite group, and recreationally competitive group.ConclusionsElite athletes self-monitor more frequently and may integrate other constituent processes better within a SRL cycle. |
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| Keywords: | Self-regulation Sport practice Expertise Self-monitoring SRL-SRS |
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