An Investigation into Factors that Contribute to the Perception of Disparities between Academic Achievement and Athletic Participation in High School Student-Athletes

Submitted by Dr. Kechia Seabrooks Rowles*(1)
(1)Athletic Coordinator for Rockdale County Public Schools in Conyers, Ga.

*Corresponding Author
Dr. Kechia Seabrooks Rowles
United States Sports Academy
85 Fox Glove Drive
Covington, GA 30016
krowles@rockdale.k12.ga.us

ABSTRACT
The purpose of this study was to analyze and compare various factors that contribute to the attitudes and perceptions held by public high school student- athletes towards academic achievement. During the 2014-2015 academic year, 323 student-athletes completed a 110 question survey packet that included, the Non Cognitive Questionnaire (NCQ), the Athletic Identity Measure Scale (AIMS), the Student Athletic Motivation Survey and Questionnaire (SAMSAQ), the Student-Athlete Role Conflict Scale and the Sport Commitment Model (SCM), providing information about different aspects of the academic achievement and athletic participation relationship, including level of educational aspirations and academic self-concept, the internal struggle between the student and athlete identity complexes, and motivational drives of student-athletes. Student Participation was strictly voluntary and contingent upon the willingness of coaches and parental consent. Student-athletes generally viewed themselves as student-athletes and believed it is worth the effort to achieve athletic success but not at the expense of their academic performance. Analysis showed that gender may play a statistically significant role in student-athletes’ perception of academic performance and athletic participation while grade level, age and race were less meaningful. The researcher hopes these findings may encourage further research, and potentially aid parents, coaches, counselors and teachers in assisting student athletes with maintaining a balance between academics and athletics.

Keywords:perceptions, disparities, academic achievement, athletic performance, student athletes, public school system

INTRODUCTION
Athletic participation is a vital component of the educational experience. With more than 7.7 million high school students competing in various athletic activities, interscholastic athletics involve both the competitions that occur on the field of play and in the classroom as well (National Federation of State High School Association, 2013). Interscholastic athletics are inherently educational and support the academic mission of schools. Interscholastic athletics are often referred to as extracurricular activities, which are not a part of the regular school curriculum, but provide students an opportunity for scholastic and athletic involvement in school. Interscholastic athletics are an extension of the classroom that provide teaching and learning experiences for all students involved and are linked to the objectives of the overall educational program (Massachusetts Interscholastic Athletic Association, 2009).

Students must garner a greater understanding of how their athletic participation correlates with their academic performance. Proponents of the Athletics as Educational (Thomas, 1986) doctrine argued that athletic participation was just as important to student development as the classroom experience and that athletic involvement supported student’s academic objectives and therefore, should not be treated as extracurricular but educational. Although, athletics were never intended to be educational some educational benefits have resulted from athletic participation. According to the National Federation of State High School Association (NFHS) athletic participation is a part of the overall high school experience and extracurricular activities support the academic missions of schools, are inherently educational and foster success later in life.

Athletic participation is a right that students earn by succeeding academically. Student-athletes should be expected to successfully balance both requirements by excelling in their academic study areas and their competitive sports. Lower SAT scores and class ranks of athletes may be a result of lesser degrees of academic preparedness and not due to sports participation as previously believed (Robst and Keil, 2000). Initial levels of academic preparedness and ability to meet eligibility requirements can either benefit or limit student-athletes as they continue their athletic participation through secondary schooling to the collegiate ranks. Bukowski (2001) reported that all state athletic associations recommended some, although limited, form of academic eligibility requirements for student participation in interscholastic sports. He found that the No Pass, No Play requirements ranged from course enrollment minimums to grade point average minimums. State associations do not enforce uniform guidelines for implementing eligibility policies therefore local school jurisdictions develop and impose eligibility requirement minimums. The inconsistency in policies creates a larger dilemma for students who aren’t required to meet the same academic rigor as others. This practice can lead to students’ development of poor study habits, decreases in educational values, and aspirations and low standardized testing scores.

Overall student-athletes are generally not prepared academically or socially for the demands of their athletic participation. The NCAA addressed the inadequacies of student-athletes reporting to college academically unprepared and took steps to ensure that student-athletes desiring to participate in collegiate athletics meet minimum academic requirements. During the spring of 2013, the NCAA tagged the phrase “2.3 or Take a Knee” (NCAA, n.d.) which informed prospective student-athletes of the changes in initial eligibility requirements. Simon and Van Rheenen (2000) believed that the rationale for the eligibility standards of minimum SAT/ACT scores and high school grade point averages were that they were reliable predictors of academic success.

Varying levels of motivation, goal orientation, level of competition, background demographics including gender, race and socioeconomic status (SES), contribute to differences in the impact of student-athletes athletic participation on their academic success (Simons, Van Rheen, & Covington, 1999, Duda & Nicholls, 1992). In addition, influential relationships between individuals in student-athletes’ lives, including coaches, parents, teammates and adult mentors impact the student-athletes’ level of academic motivation and the magnitude of emphasis the student-athletes places on the importance of success in their academic endeavors (Bell, 2009). School counselors and other student support services have a responsibility to student-athletes as well, to ensure they are successfully able to balance their academic and athletic obligations (Goldberg & Chandler, 1995; Chartrand & Lent, 1987).

The gratification athletes received for their athletic participation makes it easier for many student-athletes to prioritize athletics above academics (Simons & Van Rheenen, 2000). Students’ primary motivation is his or her identity and the quality of a school depends on how students fit in a school’s social setting (Akerlof & Kranton, 2002). Students must determine whether their ideal identity characteristics reflect those most popular within their social context (i.e. jocks or nerds). A stronger athletic identity could be result of student-athletes view that jocks are less engaged academically compared to non-athletes, therefore hindering both their confidence and performance in the academic setting. Simons and Van Rheenen (2000) determined that role strain is due to competing and energy demands of the athletic and academic roles and that student-athletes’ failure to develop a strong academic identity is due to a lack of commitment to academics resulting in them being nothing more than marginal students.

Measures of creating and implementing academic support programs to assist student-athletes with setting academic goals that will prepare them for and enhance their quality of life after athletics are beneficial, but fall short in answering the question of “Why do student-athletes excel in the sports domain and not in the academic domain?” While academic support programs focus on closing the academic gaps of the student-athletes via mandatory study hall and stringent academic monitoring, they fail to address underlying factors such as gender, race, socioeconomic status, home environment, family support systems, level of participation, variations in personalities, motivation and athletic identity salience all which may contribute to the student-athletes’ inability to perform in the classroom.

Other social context factors that impact academic achievement include the importance of sports in a school culture (Crosnoe 2001) and the coach’s attitude about school and education (Ryan and Segas, 2006). Coaches, teachers and parents play a critical role in fostering the student-athletes’ attitude and acceptance of the importance of meeting their educational goals. Parental involvement has been shown to significantly influence student academic achievement. Students whose parents are actively involved in their schooling by helping them with homework, attending extracurricular event, and monitoring students’ progress perform better academically, have stronger locus of control, and greater mastery orientation (Steinberg, Lamborn, Dornbusch, & Darling, 1992; Trusty & Lampe, 1997; Gonzalez, Holbein, & Quilter, 2002).

Methods
Participants
The sample consisted of 323 athletes (227 males; 96 females) from 7 different sport teams. The distribution of the subjects according to grade levels were: 9th grade (n=97), 10th grade (n=125) and 11th grade (n=101). Subject distribution by ages were: 13 (n=4), 14 (n=66), 15 (n=122), 16 (n=100), 17 (n=28) and 18 (n=1). The distribution of subjects according to ethnic identities were: Black (n=225), White (n=45), Asian American (n=6), Hispanic (n=28), American Indian (n=2) and Other (n=7). Subject distribution by sport was: Football (n=106), Softball (n=33), Boys Basketball (n=36), Girls Basketball (n=32), Boys Soccer (n=52), Girls Soccer (n=31) and Baseball (n=33).

Procedure
The data was obtained during the 2014-15 academic school year. After getting all necessary permission, the coaches were informed about the purpose of the study. After distributing and collecting parental consent forms, those students who returned forms completed the survey packet before the start of their competitive season.

Instrumentation
Non-Cognitive Questionnaire: The NCQ is a 23-item questionnaire designed to assess experiential and contextual intelligences, it consists of open and closed questions along with 18 items rated with a Likert-scale of 1 (strongly agree) to 5 (strongly disagree). Test- retest reliability estimates on NCQ scores for various samples range from .74 to .94, with a median of .85. Inter-rater reliability on scores from the three open-ended NCQ items ranged from .73 to 1.00 (Sedlacek and Adams-Gaston, 1992).

Athletic Identity Measure Scale: The AIMS is a seven-item instrument that uses a seven-point Likert-type scale with possible responses ranging from 1 (strongly disagree) to 7 (strongly agree) to measure athletic identity salience (AIMS; Brewer & Cornelius, 2001). The AIMS test-retest reliability (r=.89) and internal consistency (Cronbach’s alphas = .81 to .93) had been obtained (Brewer, Van Raalte, & Linder, 1993).

Student Athletic Motivation Survey and Questionnaire: The SAMSAQ measures athletes’ level of agreement with each statement measured on a six-point Likert scale, ranging from very strongly agree (6) to very strongly disagree (1). The SAMSAQ contains three subscales measuring athletic, academic and career athletic motivation with well-established psychometric properties measured by Cronbach’s alpha= .86, .79, .84, respectively (Gaston-Gayles, 2005).

Student-Athlete Role Conflict Scale: The Interference subscale of the SARCS consists of 12 specific instances and assesses the degree to which student-athletes perceive that the demands of being an athlete and the demands of being a student interfere with each other. Role Separation subscale of the SARCS assesses the extent to which the participants perceive being an athlete and a student as separate and distinct role identities. Participants used a 7-point Likert scale ranging from 1 (not really true of me) to 7 (really true of me) to indicate the degree to which each statement is true of them (Settles, Sellers & Damas, 2002). Alpha values for the Role Interference and Role Separation Scales of the Student Athlete Role Conflict Scale are 0.84 and 0.72 respectively.

Sport Commitment Model: The SCM is a 28-item survey that measures sport commitment based on five factors which include: the level of enjoyment, involvement alternatives, personal investment, social constraints and involvement opportunities. Participants indicated the level of truth that each statement applies to them by using a 5-point Likert scale with answers ranging from (1) strongly disagree to (5) strongly agree. Scalan, Carpenter, Schmidt, Simons and Keeler (1993) study demonstrated acceptable reliability in the final phase of the Sport Commitment Model with Cronbach’s alpha measures ranging from .66 to .77.

Analysis
The SPSS 20 was used to analyze the data, providing primary descriptive statistical analysis. Means and standard deviations values were tabulated by gender, grade level, age and ethnic identity. Two tailed independent t-test and One-way Analysis of Variance (ANOVA) were used analysis differences between the samples’ perceptions of academic self-concept, motivational drive, athletic identity salience, role conflict and level of sport commitment as determined by survey responses from the NCQ, AIMS, SAMSAQ, SARCS and SCM. The alpha level for statistical significance was set at p< .05.

Results
Descriptive statistics for the NCQ Subscales are presented in Table 1.The mean response for Academic Self Concept was 1.90 or agree. The mean response for Academic Negative Influence was 3.75 or close to 4 (agree). The mean response for School Climate was 2.13 or agree. The unequal variance t-tests was significant for Academic Negative Influence, t (227.12) = -3.80, p < .01. The females average response was significantly higher (M = 3.95, SD = .58) than the males (M = 3.67, SD = 72). Females indicated a stronger disagree with the academic negative influence than the males. The results of these tests indicate there are no significant differences among the grade levels, age or ethnic identity in the students’ agreement with the statements regarding the three NCQ subscales.

Table 1

Descriptive Statistics for NCQ Subscales

Variable Mean Standard
Deviation
Cronbach alpha
Academic Self-concept 1.90 .66 .71
Academic Negative Influence 3.75 .69 .59
School Climate 2.13 .61 .61

Note: NCQ based on 5-point Likert Scale where 1=SA, 2=A, 3=N, 4=D, and 5=SD

Table 2 presents the descriptive statistics for the SAMSAQ subscales. The unequal variance t-tests was significant for Academic Expectations, t (212.28) = 3.40, p =.001. The males average response was significantly higher (M = 2.59, SD = 1.36) than the females (M = 2.09, SD = 1.13). Males indicated their disagreement with the academic expectations items was not as strong as the females’ disagreement. The equal variance t-tests was significant for athletic involvement, t (318) = 1.99, p =.047. The males average response was significantly higher (M = 3.29, SD = 1.18) than the females (M = 3.00, SD = 1.17). Males indicated their disagreement with the athletic involvement items was not as strong as the females’ disagreement. The equal variance t-tests was significant for athletic confidence, t (320) = 5.43, p <.001. The males average response was significantly higher (M = 4.73, SD = 1.29) than the females (M = 3.87, SD = 1.34). Males indicated their agreement with the athletic confidence items was stronger than the females’ agreement. The equal variance t-tests was significant for academic interest, t (320) = 3.63, p < .001. The males average response was significantly higher (M = 4.61, SD = 1.27) than the females (M = 4.05, SD = 1.32). Males indicated their agreement with the academic interest items was stronger than the females’ agreement. The equal variance t-tests was significant for athletic motivation, t (321) = 3.56, p < .001. The males average response was significantly higher (M = 3.29, SD = 1.18) than the females (M = 3.00, SD = 1.17). Males indicated their disagreement with the athletic motivation items was not as strong as the females’ disagreement.

Table 2

Descriptive Statistics for SAMSAQ Subscale

Variable Mean Standard
Deviation
Cronbach alpha
Transferrable Skills 5.25 .83 .86
Athletic Involvement 3.20 1.18 .63
Athletic Confidence 4.47 1.37 .85
Academic Interest 4.44 1.31 .65
Academic Expectations 2.44 1.32 .75
Academic Motivation 5.34 .95 .85
Athletic Motivation 3.38 1.35 .54

Note: SAMSAQ based on 6-point Likert scale where 1=VSD, 2=SD, 3=D, 4=A, 5=SA, and 6=VSA

There was a significant difference on the Transferable Skills scale, F (2, 317) = 3.32, p = .038. Grade 10 (M = 5.40, SD = .67) had stronger agreement with the SAMSAQ items than grades 9 (M = 5.14, SD = .91) and 11 (M = 5.17, SD = .89). The results of these tests indicate there are no significant differences among the ages or ethnic identity in the students’ agreement with the statements regarding any of the SAMSAQ scales.

AIMS subscale descriptive statistics are presented in Table 3. The equal variance t-tests was significant for the AIMS, t (320) = 3.58, p <.001. The males average response was significantly higher (M = 5.66, SD = .97) than the females (M = 5.22, SD = 1.10). Males indicated their agreement with the AIMS items was stronger than the females’ agreement. The results of this test indicates there are no significant differences among the grade level, age, or ethnic identity in the students’ agreement with the statements regarding AIMS scale.

Table 3

Descriptive Statistics for AIMS Subscale

Variable Mean Standard
Deviation
Cronbach alpha
Athletic Identity 5.53 1.03 .82

Note: AIMS based on 7-point Likert Scale where 1=SD, 2=SWD, 3=D, 4=N, 5=A, 6=SWA, and 7=SA

Descriptive statistics for the SARCS subscales are presented in Table 4. The results were not significant for Academic Conflict, t (317) = 1.60, p = .111. As the mean was 3.37, both males and females indicated the items were somewhat not true for me. The results were also not significant for Role Separation (319) = -1.22, p = 224. As the mean was 5.50, both males and females indicated the items were somewhat true for me. The equal variance t-tests was significant for Negative Athletic Effect, t (317) = 4.81, p <.001. The males average response was significantly higher (M = 3.29, SD = 1.35) than the females (M = 2.51, SD = 1.26). Males indicated the negative athletic effect items were not as untrue for them as the females indicated. The results of these tests indicate there are no significant differences among the grade level, age or ethnic identity in the students’ agreement with the statements regarding the three SARC subscales.

Table 4

Descriptive Statistics for SARC Subscales

Variable Mean Standard
Deviation
Cronbach alpha
Role Conflict SARC Subscale
Academic Conflict 3.37 1.45 .83
Negative Athletic Effect 3.06 1.37 .75
Role Separation 5.50 1.35 .63

Note: SARC based on 7-point Likert Scale where 1=NRTM, 2=NTM, 3=SWNTM, 4=N, 5=SWTM, 6=TM and 7=RTM

Table 5 presents the descriptive statistics for the SCM subscales. The results were not significant for Sport Commitment, t (321) = 1.46, p = .145. As the mean was 1.77, both males and females agreed with the statements regarding sport commitment. The unequal variance t-tests was significant for Sport Enjoyment, t (245.0) = 2.07, p =.040. The males average response was significantly higher (M = 1.78, SD = 1.38) than the females (M = 1.49, SD = 1.10). Males indicated their agreement with the sport enjoyment items was stronger than the females’ agreement. The equal variance t-tests was significant for Sports Social Constraints, t (321) = -2.46, p =.014. The females average response was significantly higher (M = 4.00, SD = 1.13) than the males (M = 3.65, SD = 1.19). Females indicated their disagreement with the sport social constraints items stronger than the males’ disagreement.

Table 5

Descriptive Statistics for SCM Subscales

Variable Mean Standard
Deviation
Cronbach alpha
Sport Commitment 1.77 1.23 .98
Sport Enjoyment 1.69 1.29 .98
Sport Alternatives 3.53 1.16 .91
Sport Investment 2.04 1.23 .87
Sport Social Constraints 3.76 1.18 .83
Sport Opportunities 1.93 1.18 .91

Note: SCM based on 5-point Likert Scale where 1=SA, 2=A, 3=N, 4=D and 5=SD.

The results indicated there are no significant differences among the grade levels in the students’ agreement with the statements regarding any of the SCM scales. There was a significant difference among the ages on the Sport Investment scale, (6, 314) = 2.18, p = .045. The 17 year-olds (M = 2.36, SD = 1.49), 16 year-olds (M = 1.87, SD = 1.23), 15 year-olds (M = 2.20, SD = 1.29), 14 year-olds (M = 1.88, SD = .93) indicated they agreed with the SCM items. The 13 year-olds (M = 1.25, SD = .32) and 18 year-old (M = 1) indicated the strongly agreed with the SCM items. There was a significant difference among the ethnic identities on the Sport Social Constraints, F (6, 314) = 2.44, p = .026. The Black (M = 2.00, SD = 1.22), Hispanic (M = 2.56, SD = 1.34) and Other (M = 2.33, SD = 1.55) indicated they agreed with the SCM items. The White (M = 1.82, SD = 1.18, Asian American (M = 1.67, SD = .64,) indicated the strongly agreed with the SCM items.

CONCLUSIONS
A cause-effect relationship between athletic participation and academic achievement has yet to be determined; however, several studies have found a positive correlation between the two variables. Research has proven that athletic participation is not only beneficial in increasing students’ academic success and performance, but it also benefits other areas of the athletes’ personal, social and career development. Student athletes’ academic obligations cannot become secondary to their athletic participation. If athletic participation is the primary goal, a shift in focus is required by student athletes to sacrifice time, utilize resources, and devote a conscious effort to meet and maintain expected academic outcomes and become a student scholar. In addition, perceptions of athletic ability can impact emphasis placed on academics as some student-athletes may be encouraged to emphasis athletic prowess in lieu of educational achievement.

APPLICATIONS IN SPORT
While there is evidence that student-athletes feel they can be both students and athletes at the same time, it is also evident that there is a degree of uncertainty in student- athlete’s ability to excel academically. Though student-athletes possess the confidence to excel academically, emphasis placed on athletics over academics from their social support systems greatly impact student-athlete efforts in both domains. Parents, coaches, counselors and teachers must encourage and support student athletes with maintaining a balance between academics and athletics.

ACKNOWLEDGMENTS
The author would like to acknowledge Dr. C. Michael Harmon and Dr. Ethel Kloos for providing statistical analysis. In addition, the author wishes to thank the many coaches and athletes who participated in the study.

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