Date of Award

Spring 2017

Project

Capstone - Open Access

Major

Strength and Conditioning

Degree Name

Master of Science (MS)

First Advisor

Zi Yan

Abstract

Introduction. A collegiate athlete’s schedule is typically busier than a college student, requiring time for practice, competition, training, as well as normal college student responsibilities. Because their schedules are so busy, athlete motivation is a key determinant for sustained and improved performance. Methods. This study was a pre and post correlation study. In fall 2016, participants completed a pre and post SMS-28 questionnaire and a 2km ergometer aerobic capacity test. Collegiate Female Rowing team was recruited with 13 participants (ages 18-22). 4 weeks later, 7 participants filled out the SMS-28 questionnaire, based on a Likert Scale, and performed the 2km test. Results. The main finding of this study was the correlation between pre-motivation scores and difference in test times was measured by a correlation test with the following result; r=.220, p=.636, showing no significance. Secondary findings showed significant difference between pre-motivation and post-motivation scores and significant differences between test 1 time and test 2 times. Lastly, there is significance between years of experience and pre 2km times, which means rowers with less than a years experience of rowing will have significantly different 2km ergometer times compared to rowers with over a years experience. Discussion. The major findings concluded that there was no significant relationship between pre-motivation scores and 2km ergometer times. Secondary measures concluded that there was significant difference between pre-motivation and post-motivation scores and significant differences between test 1 times and test 2 times. Lastly, there is significance between years of experience and pre 2km times. Conclusion. From this study, it can be assumed that motivation levels will not predict increases in performance for a 2k-ergometer test in Female collegiate rowers. Training age, sample size, dropout rate, and scheduling of the second test could be influences on the data collected for the second round of testing.

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