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Abstract

The purpose of this study was to measure the perceptions of student-athletes concerning the coaching competency of 15 head men’s basketball coaches at the Division II level in the National Christian Collegiate Athletic Association (NCCAA). The study utilized the 24-item Coaching Competency Scale (CCS) to collect data on 138 student-athletes participating in men’s basketball from 15 NCCAA member institutions and examined four specific categories: character building competency (CBC), game strategy competency (GSC), motivation competency (MC), and technique competency (TC). Multivariate Analyses of Variance (MANOVA), Analyses of Variance (ANOVA), and Analyses of Covariance (ANCOVA) were computed to examine group differences for the 24 coaching competency factors. Results indicate that player-related factors of starter, non-starter, captain, non-team captain, and academic level were not significant predictors of the combination of coaching competency.

Keywords:

Student-athlete experience, player perceptions, coaching competencies, coaching evaluation, small college, college basketball, college basketball coaches

Phillips, M. B., & Jubenville, C. B. (2009). Student-athletes’ perceptions of men’s basketball head coaches’ competencies at 15 selected NCCAA Division II Christian colleges. Journal of Sport Administration & Supervision 1(1), 39-51. doi:10.3883/v1i1_phillips; published online April, 2009.


 
Relationships between coaches and student-athletes remain integral components of the development of both groups’ performances. Coaches constantly structure evaluations about student-athletes based on numerous variables and continually seek ways to improve the quality of those relationships to optimize the talent of each student-athlete. Slepicka (1975) postulated that the quality of the coach-athlete relationship has a great impact on the performance of athletes. Bortoli, Robazza, and Giabardo (1995) added postulations that positive coach-athlete interactions tend to enhance motivations, induce pleasant emotions, and create satisfactory and positive climates.

While coaches are constantly making evaluations about their athletes, student-athletes are also formulating assessments about their coaches’ personalities and behaviors. These perceptions of coaching competency could alter student-athlete performances and could offer important insights into valuable information needed to improve this relationship (Cratty, 1983).

Along with the many different ROLEs coaches perform, coaches are also placed under public scrutiny and are constantly evaluated by the media, players, alumni, fans, and student bodies. These groups place such an enormous amount of pressure on coaches to win until the single most important criterion for evaluation becomes the bottom line of winning (Margolis, 1979). This mentality has led to intense pressure within the coaching profession (Axthelm, 1986). Margolis (1979) stated, “The values and virtues attributed to organized competitive athletics have been widely-publicized in an effort to gain respect for school sports programs ... Unfortunately, the pressure and demands on many coaches have caused them to subvert these values and betray the virtues attributed to sports in order to achieve the bottom line – winning” (p. 12).

The increased emphasis on accountability highlights the importance of coach evaluation as a process that can benefit all parties involved and help maintain effective coaching by allowing coaches to improve their knowledge and skills, as well as to evaluate their strengths and to assess areas for needed improvements, which solidifies congruency between the coach and athlete (Barber & Eckrich, 1998). Alexander (1985) noted that evaluations of coaching personnel are as necessary for proper kinesthetic education as classroom teacher evaluations and administrative assessments. MacLean and Chelladurai (1995) note, “At the individual level, performance appraisals (a) reinforce and sustain good performance and/or improve performance, (b) provide insights into career goals, (c) pinpoint areas of strengths and weaknesses, and (d) suggest training needs” (p.195). What must be clearly understood is that the evaluation process is intended to provide an objective point-of-view from the participant, i.e., the evaluation process should provide coaches an opportunity to enhance their abilities and to relate more effectively with the student-athlete (MacLean & Chelladurai, 1995).

Related literature suggested that student-athletes should play a central ROLE in evaluating their coaches. Myers, Wolfe, Maier, Feltz, and Reckase (2006a; 2006b) stated that athletes’ perceptions and evaluations of a coach are believed to play a critical ROLE in coaching effectiveness. Solomon (1999) reported that athletes are capable of evaluating coaches’ personalities and behaviors related to the coaching ROLE. Kuga (1993) argued, “Athletes seem to recognize the value of coaching evaluations and are capable of identifying competencies which they perceive to be important to a coach’s performance” (p. 86). Because of their regular and direct contact with coaches, athletes seem to be well qualified to assess their coaches’ personalities and behaviors (Kuga, 1993).

According to Jubenville (1999), assessment of the coach-athlete relationship has evolved into a focal issue for modern athletes due to the growing concern over changes in the way they perceive the authority of coaches and the ROLE of athlete’s progress in small college athletics. In past years, coaches have not been less interested in their athletes’ perceptions of them; however, as player morale has become an ever-increasing factor in team performance, the evaluation of coaches and interest in athletes’ perceptions of coaches have become prerequisites for determining maximum coaching effectiveness and achievement (Jubenville, 1999). If coaches better understand the opinions of their athletes concerning their coaching ROLEs, they are then positioned to adapt their coaching styles to improve team unity and elicit from their athletes a more competitive spirit (Weiss & Fredrichs, 1986).

Purpose of the Study

The purpose of this study was to measure the perceptions of student-athletes concerning the coaching competency of men’s basketball head coaches at the Division II level in the National Christian Collegiate Athletic Association (NCCAA).

The study’s three hypotheses were analyzed through the use of Multivariate Analyses of Variance (MANOVA), Analyses of Variance (ANOVA), and Analyses of Covariance (ANCOVA). The following hypotheses were tested at a .05 alpha level of significance (α = .05).

Hypothesis 1: Student-athletes who were classified as starters will report higher coaching competency scores than student-athletes classified as non-starters.

Hypothesis 2: Student-athlete who were designated as team captains will report higher coaching competency scores than student-athlete who are not designated as team captains.

Hypothesis 3: Student-athletes classified as juniors and seniors will report higher coaching competency scores than student-athletes classified as freshmen and sophomores.

METHODOLOGY

This study focused on student-athletes’ perceptions of the competency of their head coaches at 15 Christian colleges and universities in NCCAA Division II men’s basketball teams. The teams chosen to participate in this study were selected from 49 NCCAA Division II institutions. Of the 49 Division II men’s basketball programs, 23 teams were targeted based upon their selection into the region or post-season national tournament during the 2006-2007 season. The 23 teams targeted for the study were a convenience sample that appeared to be representative of the population studied based on the authors’ previous coaching and athletic administration experiences. Initial contact letters were mailed to the athletic administrators of 23 member institutions, 15 of whom returned the completed items by the established deadline. Student-athletes who participated in the study were identified by an athletic administrator at their respective colleges and universities and asked to complete a questionnaire indicating their perceptions of the competency of their men’s basketball head coaches. Student-athletes were also asked to submit demographics information related to three independent variables, including: designation as a starter or non-starter, designation as a team captain or non-team captain, and academic level (freshman, sophomore, junior, and senior).

Participants

Participants selected for this study were male college student-athletes at 15 selected colleges and universities in the NCCAA Division II level. The population consisted of 138 student-athletes who were considered to be members of their institution’s men’s basketball team during the 2006-2007 season. The total number of participating student-athletes was determined by the returned questionnaires from each of the athletic administrators at the participating colleges and universities.

Procedures

To study the three proposed research hypotheses, this study’s authors utilized the Coaching Competency Scale (CCS) created by Myers, Wolfe, Maier, Feltz, and Reckase (2006b). Athletic administrators/head men’s basketball coaches at 15 of the 23 NCCAA Division II schools agreed to participate in the study after being contacted by letter. Packets for the study containing the permission form, proctor instructions, informed consent statement, athlete demographics, and the questionnaire were mailed to each of the athletic administrators/head men’s basketball coaches. Athletic administrators/head men’s basketball coaches at each participating school were instructed to identify an objective third party proctor to administer and return the questionnaire and were provided proctor instructions for administering the questionnaire to the student-athletes. An informed consent form was placed in the packet, which indicated the purpose of the study, the voluntary nature of the study, the confidentiality of the study, and the instructions to complete the anonymous questionnaire. The informed consent form clearly stated that the participant had the option to decline participation in the study, and the proctor was also given instructions to read the informed consent to all participants and ask anyone to dismiss himself prior to completing the questionnaire. The completion of the informed consent statement and questionnaire took approximately 40 minutes. The packet also contained a student-athlete demographics sheet which was filled out by each student-athlete. Once participants completed the required materials, the student-athletes were instructed to return the completed information to the proctor. The proctor was asked to collect the data and mail it back to the researcher for analysis. The researcher received 141 questionnaires from 15 colleges and universities by the established deadline.

Of the 141 questionnaires received, two were signed and dated by student-athletes but had not been completed and were removed from the study. One other questionnaire was completed by a coach and was removed from the study. The final sample population consisted of 138 student-athletes enrolled in the 2006-2007 academic year at 15 of 23 colleges/universities who agreed to participate in this study for a 65% rate of return.

Survey Instrument

The instrument selected for the study was the Coaching Competency Scale (CCS) developed by Myers et al. (2006b), who developed the 24-item questionnaire for lower-division intercollegiate team sport athletes (Myers et al., 2006b). Myers et al. (2006b) stated, “The intended purpose of the questionnaire is to measure the athletes’ evaluation of their head coach’s ability to affect their learning and performance” (p. 113). Myers et al. (2006b) went on to explain that coaches must provide certain areas of competency to their athletes, including instruction that develops specific skills for the sport being coached, effective motivational skills, effective practices that instill social/emotional growth, and promotion of character and sportsmanship (Myers et al., 2006b).

Table 1. Descriptive Statistics For Individual Coaching Competency
Coach n* M SD
1 9 3.03 0.30
2 10 3.22 0.52
3 11 3.11 0.26
4 8 2.52 0.88
5 11 3.24 0.34
6 8 2.49 0.47
7 7 3.21 0.26
8 9 2.95 0.37
9 12 3.57 0.27
10 5 2.98 0.49
11 7 3.54 0.57
12 13 3.54 0.45
13 6 3.67 0.22
14 9 3.43 0.42
15 13 2.17 0.62

N = 138, *number of players on the team

The CCS was designed to measure four different categories, including character-building competence (CBC), game strategy competence (GSC), motivation competence (MC), and technique competence (TC). According to Myers et al. (2006a), of the 24 items on the questionnaire, “CBC was specified to measure four items and was defined as the coach’s ability to influence athletes’ personal development and positive attitude toward basketball. GSC was specified to measure seven items and was defined as the coach’s ability to lead during competition. MC was specified to measure seven items and was defined as the coach’s ability to affect athletes’ psychological mood and skills (Myers et al., 2006b). TC was specified to measure six items and was defined as the coach’s instructional and diagnostic abilities” (p. 452).

Data Analysis

The study’s three research hypotheses were analyzed by using Multivariate Analyses of Variance (MANOVA), Analyses of Variance (ANOVA), and Analyses of Covariance (ANCOVA) statistical methods. These tests were computed for the independent variables of starter or non-starter (2-group), team captain or non-team captain (2-group), and academic level (4-group). An alpha level of .05 was used for statistical significance (p ≤ .05). Data was analyzed using the Statistical Package for the Social Sciences (SPSS) Version 15.0.

Rationale for Hypotheses:

The specific rationale for the hypotheses addressed in this study included the following:

Hypothesis 1: Student-athletes who were classified as starters will report higher coaching competency scores than student-athletes classified as non-starters.

Rationale for Hypothesis 1: Previous research has indicated that the amount of playing time can affect athletes’ attitudes and responses toward coaches (Jubenville, 1999; Jubenville, Goss, & Phillips, 2007; Kuga, 1993).

Hypothesis 2: Student-athlete who were designated as team captains will report higher coaching competency scores than student-athlete who are not designated as team captains.

Rationale for Hypothesis 2: Previous research indicates that student-athlete leadership ROLEs affect their attitudes and responses toward coaches (Chelladurai, Haggerty, & Baxter, 1989; Dupuis, 2006; Johnston, 1997; Jubenville, 1999).

Hypothesis 3: Student-athletes classified as juniors and seniors will report higher coaching competency scores than student-athletes classified as freshmen and sophomores.

Rationale for Hypothesis 3: Previous research indicates that academic levels affect student-athletes’ attitudes and responses toward coaches (Chelladurai & Carron, 1983; Horn, 2002; Jubenville, 1999; Kuga, 1993; Salminen & Liukkonen, 1996; Solomon, 1999; Terry & Howe, 1984).

Limitations of the Instrument

The term coaching behavior was used in consistency with Horn (2002), despite the claim by Myers et al. (2006a; 2006b) that no instruments can completely and accurately measure competencies needed by modern coaches (Myers et al., 2006a & 2006b).

RESULTS

Regarding the independent variables of starters and non-starters, non-starters totaled 69 subjects (n = 69, 50.0%), with a mean total coaching competency score of 75.54 and a standard deviation of 16.67. Starters consisted of 69 subjects (n = 69, 50.0%), with a mean total coaching competency score of 72.99 and a standard deviation of 12.91 (see Table 2).

Regarding team captains and non-team captains, the population consisted of 113 non-team captains (n = 113, 81.9%), with a mean total coaching competency score of 74.91 and a standard deviation of 15.18. Those subjects who were a team captain totaled 25 (n = 25, 18.1%), with a mean total coaching competency score of 71.32 and a standard deviation of 13.54 (see Table 2).

Table 2. Descriptive Statistics For Starter, Team Captain, and Academic Level
Categories of Coaching Competency
Predictor Level n CBC GSC MC TC Total score
Starter

No

69

M

3.57

3.17

3.02

3.00

75.54

SD

0.57

0.73

0.85

0.80

16.67

Yes

69

M

3.6

3.00

2.87

2.95

72.99

SD

0.52

0.60

0.80

0.60

12.91

Team Captain

No

113

M

3.60

3.11

2.99

2.99

74.91

SD

0.52

0.69

0.82

0.72

15.18

Yes

25

M

3.60

2.94

2.74

2.90

71.32

SD

0.53

0.60

0.84

0.62

13.54

Academic Level

Freshmen

51

M

3.61

3.08

2.92

2.90

73.73

SD

0.45

0.65

0.78

0.63

13.68

Sophomore

30

M

3.71

3.24

3.17

3.11

78.37

SD

0.43

0.58

0.80

0.57

12.85

Junior

33

M

3.61

3.15

2.97

3.02

75.03

SD

0.48

0.62

0.84

0.78

15.12

Senior

24

M

3.42

2.78

2.71

2.90

69.21

SD

0.76

0.82

0.91

0.88

18.47

Total

138

M

3.60

3.08

2.95

2.97

74.26

SD

0.52

0.67

0.83

0.70

14.91

Regarding academic level, the population consisted of 51 freshmen (n = 51, 37.0%), with a mean total coaching competency score of 73.73 and a standard deviation of 13.68. Sophomores totaled 30 subjects (n = 30, 21.7%), with a mean total coaching competency score of 78.37 and a standard deviation of 12.85. Juniors totaled 34 subjects (n = 34, 24.6%), with a mean total coaching competency score of 75.03 and a standard deviation of 15.12. Seniors totaled 23 subjects (n = 23, 16.7%), with a mean total coaching competency score of 69.21 and a standard deviation of 18.47 (see Table 2). The total mean coaching competency score was 74.26 with a standard deviation of 14.91 (see Table 2). Also included in the table are the mean scores of each predictor on each of the four categories of coaching competency (see Table 2).

Three-Way MANOVA

A three-way Multivariate Analysis of Variance (MANOVA) with starter (yes, no), captain (yes, no), and academic level (freshmen, sophomore, junior, and senior) as between-subject factors were used to evaluate the combination of dependent variables: character building competence (CBC), game strategy competence (GSC), motivation competence (MC), and technique competence (TC). MANOVA indicated that the combination of class, captain, and starter is not a significant predictor of combination of coaching competency categories. No factor or interaction factors were found to be significant (see Table 3).

Table 3. Multivariate Test For Predicting Categories of Coaching Competency
Predictor F dfn dfd p λ
starter 0.736 4 122.0 0.569 0.976
team 0.112 4 122.0 0.978 0.996
class 0.735 12 323.1 0.717 0.931
starter * team 0.518 4 122.0 0.723 0.983
starter * class 0.586 12 323.1 0.853 0.945
team * class 0.235 8 244.0 0.984 0.985
starter * team * class 0.520 4 122.0 0.721 0.983
alpha = .05

Individual MANOVAs

Individual MANOVAs were conducted to test whether individual factors were significant in predicting the combination of categories of coaching competency. Results showed that predictors starter (F4,133=1.563, p=.188, Wilk’s λ = .955), team (F4,133 = .87, p = .484, Wilk’s λ = .974), and class (F12,346.9 = 1.273, p = .233, Wilk’s λ = .892) were not significant.

One-Way MANOVA

Since the questionnaire was administered to 15 different teams and evaluated 15 different coaches coaching competency, a one-way multivariate ANOVA was conducted to test whether the predictor coach (1 through 15) was significant in predicting a combination of CBC, GSC, MC, and TC competency categories. Results showed that the combination of categories of coaching competency was significantly different across the levels of predictor, F(56,468.9 = 3.896, p < 0.001, Wilks’ λ = 0.226).

Univariate One-Way ANOVA for Coaching Competency

The univariate one-way Welch ANOVA also showed that the total score on the competency scale was different across coaches, F(14, 42.16) = 7.63, MSE = 124.326, p < .001. Separate Welch ANOVAs were run to test individual competency categories and all produced significant results (see Table 4).

Table 4. Univariate Tests For Predicting Individual Categories of Coaching Competency
Category Welch’s F dfn dfd p
cbc 3.405 14 42.6 0.001
gsc 8.686 14 42.524 0.000
mc 14.127 14 42.535 0.000
tc 7.127 14 41.912 0.000
Total score 7.627 14 42.159 0.000
alpha = .05, predictor = coach

Univariate One-Way ANOVA for Individual Factors

Univariate one-way ANOVAs were conducted to test whether individual factors were significant predictors of categories of coaching competency with no control for the coach. Results for starter, team, and class are given in tables 5, 6, and 7 respectively. Results showed that no factor is a predictor of any of the categories or the total score on the competency scale.

Table 5. Univariate Tests For Predicting Individual Categories of Coaching Ccompetency
Category Welch’s F dfn dfd p
cbc 0.279 1 131.774 0.598
gsc 2.313 1 130.433 0.131
mc 1.124 1 135.658 0.291
tc 0.196 1 125.809 0.659
TotalSum 1.010 1 128.007 0.317
alpha = .05, predictor = starter
Table 6. Univariate Tests For Predicting Individual Categories of Coaching Ccompetency
Category Welch’s F dfn dfd p
cbc 0.002 1 35.373 0.967
gsc 1.648 1 39.404 0.207
mc 1.807 1 34.887 0.188
tc 0.406 1 40.028 0.528
Total Score 1.376 1 38.553 0.248
alpha = .05, predictor = team

Table 7. Univariate Tests For Predicting Individual Categories of Coaching Competency

Category Welch’s F dfn dfd p
cbc 0.995 3 62.006 0.401
gsc 1.862 3 63.943 0.145
mc 1.302 3 63.702 0.281
tc 0.897 3 62.707 0.448
TotalSum 1.578 3 63.015 0.203
alpha = .05, predictor = class

Controlling for the Quality of Coaching

Evidently from previously discussed results in this study, the personal qualities of each coach have the only significant influence on the evaluation of individual categories of coaching competency by student-athletes and the total score of the scale, necessitating control for this extraneous factor in this design. Simply stated, this method of control allows the researcher to identify and extract the influence of the quality of the coach variable. Quality of coach, therefore, would not represent a source of random fluctuation. The mean score for each coach was computed by averaging the totals scores of all players on the team (see descriptive statistics in Table 1). Separate one-way MANOVAs with control for coaching competency were conducted with factors starter, team captain, and academic level. Results showed that predictors starter (F4,132 = 2.183, p = .074, Wilk’s λ = .938), team captain (F4,133 = 1.773, p = .138, Wilk’s λ = .949), and academic level (F12,344.2 = 1.282, p = .227, Wilk’s λ = .891) were not significant. However, a noticeable decrease in p-values in the predictor starters (from p = .188 to p = .074) and a somewhat smaller decrease in the predictor team (from p = .484 to p = .138) is evident. Individual univariate ANCOVAs with control for coaching competency showed that starter was a significant predictor for game strategy competence (F1135 = 4.82, p = .03, Adj R 2= .447), and team was a significant predictor for motivation competence (F1,135 = 5.267, p = .023, Adj R2 = .510) (see Tables 8, 9, and 10).

Table 8. One-Way Univariate ANOVA Predicting Coaching Competency Controlling For Goodness of Coach
Category F dfn dfd p
cbc 0.248 1 135.000 0.619
gsc 4.820 1 135.000 0.030*
mc 2.823 1 135.000 0.095
tc 0.484 1 135.000 0.488
Total score 2.629 1 135.000 0.107
*- significant result at alpha = .05, predictor = starter
Table 9. One-Way Univariate ANOVA Predicting Coaching Competency Controlling For Goodness of Coach
Category F df1 df2 p
cbc 0.015 1 135.000 0.904
gsc 3.526

1

135.000 0.063
mc 5.267 1 135.000 0.023*
tc 0.991 1 135.000 0.321
Total score 3.702 1 135.000 0.056
*- significant result at alpha = .05, predictor = team captain
Table 10. One-Way Univariate ANOVA Predicting Coaching Competency Controlling For Goodness of Coach
Category F df1 df2 Sig.
cbc 1.257 3 133.000 0.292
gsc 2.518 3 133.000 0.061
mc 1.506 3 133.000 0.216
tc 0.114 3 133.000 0.952
Total score 1.795 3 133.000 0.151
alpha = .05, predictor = academic level

Reliability and Power

Cronbach’s alpha estimates were .79 (CBC), .91 (GSC), .94 (MC), and .88 for (TC) respectively. The estimate for the entire scale was .96. The Spearman-Brown split-half reliability estimates were .80 (CBC), .91 (GSC), .94 (MC), and .87 for (TC) respectively. The Spearman-Brown split-half reliability estimate for the entire scale was .94. These coefficients suggest very good to excellent internal consistency for the coaching competency model. According to Cohen (1992), the proper number of subjects to receive a medium effect size at alpha = .05 is 64 subjects. Therefore, power is not a concern in this study.

DISCUSSION

Insight gained from the perceptions of the student-athlete could result in improved experience for both the student-athlete and coach as well as develop player and coach potential and result in a deeper connection between the coach and the player.

Hypothesis 1: Student-athletes who were classified as starters will report higher coaching competency scores than student-athletes classified as non-starters.

Analysis of student-athlete responses using a three-way MANOVA test found no significant differences in student-athletes’ perceptions of the combination of coaching competency categories between starter and non-starter playing status of the student-athlete. Individual MANOVAs were also run to detect if individual factors could predict the combination of categories of coaching competency. This test also found no significant differences in the student-athletes’ perceptions of the head coach. A univariate one-way ANOVA was run to detect whether individual factors were significant predictors of categories of coaching competency with no control for the coach. Results from this test found no significant differences in student-athletes’ perceptions of head coaches. Accordingly, this hypothesis was rejected. Such a finding correlates with the results of studies by Jubenville (1999) and Jubenville, Goss, and Phillips (2007). This lack of significance could be explained in the relative lack of difference between the participation times of starters and non-starters. As noted by Jubenville (1999), in NCAA Division I and Division II levels, one group of student-athletes may play during a majority of the contest, while another group may only play sparingly. Conversely, in lower division college athletics, due to smaller roster sizes and/or the mission of the team’s intercollegiate athletics department and/or institution, most student-athletes could play a majority of the time and could possibly play an important ROLE in the contest (Jubenville, 1999).

However, after conducting a one-way MANOVA to test whether the predictor coach was significant in predicting a combination of the competency categories, that the combination of categories of coaching competency were discovered to be significant. Therefore, since differences were significant across levels of coach predictor, this extraneous factor necessitated control. Individual univariate ANCOVAs with control for coaching competency showed that the predictor starter was a significant predictor for game-strategy competence. The results showed that non-starters had a higher perception of their coach on game strategy competence than did starters.

Hypothesis 2: A student-athlete who is designated as a team captain will report a higher coaching competency score than a student-athlete who is not a team captain.

Analysis of student-athletes’ responses using a three-way MANOVA test found no significant differences in student-athletes’ perceptions of head coach between captains and non-team captains. Individual MANOVAs were also run to detect any individual factors in predicting the combination of categories of coaching competencies. This test also found no significant differences in student-athletes’ perceptions of head coaches. A univariate one-way ANOVA was run to detect whether individual factors were significant predictors of categories of coaching competency with no control for the coach. Results from this test found no significant differences in student-athletes’ perceptions of head coaches based on captaincy or non-captaincy. Accordingly, this hypothesis was rejected.

One explanation of these results could be the small number of team captains involved in this study. This study included only 25 team captains out of a possible 138 subjects. With the sample of the captains being so low, sufficient variance between the subjects to show significant results may not have been present.

The results of the one-way MANOVA showed that coach was a significant predictor of the combination of coach competency categories. Therefore, the significance of the personal qualities of each coach necessitated control for this extraneous factor. Individual univariate ANCOVAs with control for coaching competency showed that the predictor of team captain was a significant predictor for motivation competence. Results showed that non-team captains had higher perceptions of their coaches on motivation competence than did team captains.

Hypothesis 3: Juniors and seniors will report a higher coaching competency score than student-athletes who are freshmen and sophomores.

Analysis of student-athletes’ responses using a three-way MANOVA test found no significant differences in student-athletes’ perceptions of head coaches between the four academic levels (freshman, sophomore, junior, and senior). Individual MANOVAs were also run to detect individual factors in predicting the combination of categories of coaching competency. This test also found no significant differences in student-athletes’ perceptions of head coaches. A univariate one-way ANOVA was run to detect whether individual factors were significant predictors of categories of coaching competency with no control for coaches. Results from this test found no significant differences in student-athletes’ perceptions of head coaches. Accordingly, this hypothesis was rejected. Such a finding correlates with results of studies by Jubenville (1999), Jubenville, Goss, and Phillips (2007), Salminen and Luikkonen, (1996), and Terry and Howe (1984) but contradicted results from a study by Solomon (1999), which indicated that student-athletes’ academic levels did indeed show a significant difference in perceptions of head coaches.

After use of a one-way MANOVA to test whether the predictor coach was significant in predicting a combination of competency categories, the combination of categories of coaching competency was found to be significant. The mean score for each coach was computed by averaging the total scores of all student-athletes on the team. The overall competency of each coach was used as a covariate in the ANCOVA procedures in an attempt to control the influence of coach goodness on players’ difference in evaluation. Individual univariate ANOVAs with control for coaching competency showed that academic level (freshman, sophomore, junior, and senior) was not a significant predictor for game strategy competence. However, the result indicated a value of p = .061, which is very close to the arbitrary alpha level of p < .05.

One point of interest in this study concerning academic level is the overall success of several of the teams in this study during the 2006-2007 basketball season. Three of the 15 schools surveyed in this study competed in the National Christian Collegiate Athletic Association (NCCAA) national tournament. This tournament is a 12-team tournament based upon the ability to either win a regional tournament or receive an at-large bid. Therefore, of the 49 total teams competing at the Division II level, three of the twelve teams that competed at the national tournament were included in the study. Also, two of the 15 teams surveyed in this study competed in the Association of Christian Collegiate Athletics (ACCA) national tournament, a 10-team invitation-only tournament. Both teams in the ACCA national tournament ultimately competed against each other in the national championship game. Therefore, a logical assumption could be made that several coaches involved in this study were relatively competent coaches and that the perceptions of the student-athletes simply conveyed those circumstances.

RECOMMENDATIONS

Recommendations for Further Study

Separate Welch ANOVAs were run to test individual coaching competency categories, and each produced significant results, clearly indicating that the student-athlete perception of the coach is strictly dependent upon the coach and can truly depict the importance of the coach in the coach/student-athlete relationship.

The evaluation of coaching competency categories among the student-athletes surveyed did not differ across starter, non-starter, captain, non-team captain, and academic level (freshman, sophomore, junior, and senior). These results coincide with previous research by Myers et al. (2006a). In that study, the authors concluded that the unidimensional model fit the data poorly and the multidimensional model marginally fit the data. The factors in the retained model were also moderately to highly correlated, as was the case in the current study. Internal reliability ranged from very good to excellent as was also the case in the current study.

In Myers et al. (2006a), the authors noted limited discriminant validity between items from the GSC and TC subscales and that definition refinement could lessen the overlap among the subscales. One last correlated observation about the current study could be that its design was not comparable with the Myers et al. (2006a) study. One distinct possibility could be that the type of sport utilized in the current study was incompatible with the sports utilized in the Myers et al. (2006a) study. For example, Myers et al. (2006a) utilized men’s soccer and women’s ice hockey teams.

Other miscellaneous recommendations include the following:

This study should be replicated with other men’s collegiate basketball teams at the NCCAA level.

Further studies should be conducted concerning other team sports to continue to help support and study the coach/student-athlete relationship.

Considering that the CCS has only been utilized in lower divisions of intercollegiate athletics, studies utilizing this same instrument at the NCAA Division I level of intercollegiate athletics would likely prove interesting.

Expanding demographics to include coaches’ years of experience, winning percentages, and coaches’ intercollegiate athletics participation could provide insight into coaches’ years of experience correlate with coaches’ winning percentages.

This study should be replicated with men’s and women’s collegiate basketball teams at the NCCAA level to compare differences in student-athletes’ perceptions of coaches between male and female collegiate basketball players.

For a whitepaper summary of this article, visit: http://hdl.handle.net/2027/spo.6776111.0001.109



Dr. Michael B. Phillips is an assistant professor in the Department of Exercise Science, Physical Education, and Wellness at Tennessee Technological University.

Dr. Colby B. Jubenville is an associate professor and director of the Center for Sport Policy & Research at Middle Tennessee State University.

The authors gratefully wish to acknowledge the NCCAA for its cooperation and support for this research project.

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