This study was designed to give coaches insight into the motivation, and self-determination of players who have different roles on the team to ultimately assist with recruiting, retention, coaching preferences, and/or leadership adjustments. The purpose of this project was to examine what motivates and drives NCAA Division III female basketball athletes to compete and continue to work hard every day without the incentive of scholarships. Specifically, we compared the motivation (both intrinsic and extrinsic) and self-determination of players in different roles: starters, substitutes, and “benchwarmers.” Female intercollegiate basketball players (N = 53) from 8 public universities participated in the study. At the end of the season, participants completed a survey addressing their motivation and self-determination in basketball. Motivation and self-determination were measured by modified versions of the Self-Regulation Questionnaire- Exercise and the Self-Determination Scale, respectively. Moreover, based on the self-reported average playing time, participants were categorized as starters (20 or more minutes), subs (6-20 minutes), or benchwarmers (0-5 minutes). The three playing status groups were then compared on various aspects of motivation and self-determination. In terms of motivation, benchwarmers tended to score higher than starters and subs on items most related to intrinsic motivation (e.g., intrinsic motivation, identified regulation). However a one-way MANOVA indicated no significant differences in motivation based on playing status, F (8, 94) = 1.13, p = .35. The means of the benchwarmers, subs, and starters were quite similar on the selfdetermination subscales of perceived choice and self-awareness. Likewise, the results of a oneway MANOVA revealed no significant differences between benchwarmers, subs, and starters in perceived choice or self-awareness, F (4, 98) = 0.58, p = .68. While no significant statistical differences were discovered, bench warmers did tend to score higher on intrinsic motivation than did their counterparts who averaged more playing time. This trend should not be overlooked simply because there were no statistically significant differences, which may be due to a small sample size. Understanding what motivates all athletes regardless of playing status is an important step to improving performance, satisfaction, and retention of Division III athletes. For instance, knowing what drives the benchwarmer is important for coaches because these players are responsible for challenging the starters in practice and preparing them for the other team. Likewise, benchwarmers also act as an important source of support during competition. Moreover, coaches should seek opportunities to enhance the intrinsic motivation of subs and starters, as participating in Division III lacks some of the major external rewards such as scholarships and other incentives that come with playing at Division I or II.
Kelly S. Witte, Teri J. Hepler and Tiffany Morton
Deborah L. Feltz, Teri J. Hepler, Nathan Roman and Craig Paiement
The Coaching Efficacy Scale (CES) measures beliefs coaches have to affect the learning and performance of their athletes. While previous research has provided support for the model of coaching efficacy and the CES as an adequate measure of the construct, these studies have used paid high-school and college coaches. It is possible that the factor structure of the CES may not replicate for volunteer youth sport coaches. The purpose of this study was to explore coaching efficacy sources used by volunteer youth sport coaches. In addition, the validity of the CES was examined, using a 5-point condensed rating scale, among volunteer youth sport coaches before exploring the sources. The study involved 492 volunteer youth sport coaches from various team sports. Confirmatory factor analysis indicated that the CES had an acceptable fit to the data. The sources of coaching efficacy were examined via multivariate multiple regression and canonical correlation. Results indicated that more confident coaches had more extensive playing and coaching backgrounds, felt their players improved more throughout the season, and perceived more support than did less confident coaches, particularly in regard to technique and game strategy efficacy.
Deborah L. Feltz, Graig M. Chow and Teri J. Hepler
The Feltz (1982) path analysis of the relationship between diving efficacy and performance showed that, over trials, past performance was a stronger predictor than self-efficacy of performance. Bandura (1997) criticized the study as statistically “overcontrolling” for past performance by using raw past performance scores along with self-efficacy as predictors of performance. He suggests residualizing past performance by regressing the raw scores on self-efficacy and entering them into the model to remove prior contributions of self-efficacy imbedded in past performance scores. To resolve this controversy, we reanalyzed the Feltz data using three statistical models: raw past performance, residual past performance, and a method that residualizes past performance and self-efficacy. Results revealed that self-efficacy was a stronger predictor of performance in both residualized models than in the raw past performance model. Furthermore, the influence of past performance on future performance was weaker when the residualized methods were conducted.
Stephen Samendinger, Christopher R. Hill, Teri J. Hepler and Deborah L. Feltz
Background: The positive role of self-efficacy in directing a wide range of health-related interventions has been well documented, including those targeting an increase in physical activity. However, rarely do researchers control the influence of past performance and past self-efficacy perception ratings when exploring the interaction of self-efficacy and performance, allowing for a refined understanding of this relationship and the unique contribution of each factor. Methods: A residualized past performance, residualized self-efficacy hierarchical regression model was used to examine the effect of prior past performance and pre-exercise self-efficacy on performance with a health-related task (12 aerobic exercise cycling sessions). Results: The previous day’s residualized performance was a significant predictor of performance, as was same-day residualized self-efficacy (P < .001). However, residualized self-efficacy became a stronger predictor over time. Conclusions: While maintaining a consistent level of moderate–vigorous physical activity over 12 exercise sessions, participants increased their ratings of task self-efficacy, explaining an increasing portion of the variance in the self-efficacy–performance relationship days 9 to 12.