Predictors of Academic Achievement Among Student-Athletes in the Revenue-Producing Sports of Men’s Basketball and Football

Abstract

Researchers have examined input or precollege and individual characteristics of student-athletes and on this basis have attempted to predict the student-athletes academic success. Much of this work has attempted to relate these predictions to demographic factors. Some studies suggest that differences in academic performance are influenced by academic criteria, while other studies reveal that psychological factors have a greater impact on the variation in academic achievement among student-athletes. Although these studies yield a considerable amount of relevant information with regards to selected predictors of academic performance among college student-athletes, few scholars have examined how student-athletes are impacted by the environmental influences within their college experience. The present study examines interaction with faculty measures as predictors of college Grade Point Average (GPA) for male student-athletes in revenue-producing sports. Data are drawn from the Cooperative Institutional Research Program’s 2000 Freshman Survey and 2004 Follow-Up Survey. The sample includes 459 football and basketball players attending predominantly white institutions. Regression results indicate that the impact of the contact or interaction between faculty and student-athletes is to some extent contingent upon the specific nature of the interaction. For example, faculty who provided help in achieving professional goals makes a relatively strong contribution to student success whereas faculty who provided encouragement for graduate school did not benefit male student-athletes equally for this study. Finally, the implications of these findings should be discussed among student-athletes, faculty, and advisors in order to improve the communication between faculty members and male student-athletes, enrich student-athletes’ academic productivity as well as their overall college experience.

Introduction

A substantial amount of research in past years has been conducted in an effort to determine significant predictor such as demographic, academic criteria, and psychological variables of academic achievement among student-athletes (Adler & Adler, 1985; Lang, Dunham, & Alpert, 1988; Lawrence, 2001; Purdy, Eitzen, & Hufnagel, 1985). Although these studies yield a considerable amount of relevant information with regards to selected predictors of academic performance among college student-athletes, few studies examine the life experiences or environmental factors that influence the academic success of the student-athlete while on campus (Comeaux & Harrison, 2001; Sellers, 1992). The environment encompasses all that happens to student-athletes during the course of their educational programs, which may affect and influence the desired intellectual outcome-to matriculate and graduate (Astin, 1993a).

The present study thus examines both demographic (input) and environmental variables in the prediction of academic achievement for student-athletes in the revenue-producing sports of men’s basketball and football. Specifically, this study examines selected demographic and faculty interaction measures of academic achievement among male student-athletes in revenue-generating sports. The results of the analysis are discussed in terms of their demand for future investigation on how demographic and interaction with faculty measures influence student-athletes’ academic success, as well as implications for present and future National Collegiate Athletic Association (NCAA) programming and policy.

Methodology and Research Design

Sample

The data in this study are drawn from the Cooperative Institutional Research Program (CIRP) 2000 Student Information Form (SIF) and 2004 College Student Survey (CSS) that is sponsored by the Higher Education Research Institute (HERI) at the University of California at Los Angeles (UCLA) and their Graduate School of Education and Information Studies. Although the reliability of the instrument has not been formally measured “during the past 30 years the CIRP has generated an array of normative, substantive, and methodological research about a wide range of issues in American higher education” (Sax, Astin, Korn, Mahoney, 1996). Research based on CIRP data was found to be most widely cited in American higher education research (Budd, 1990).

The specific sample analyzed for this study included 459 football and basketball student athletes attending predominantly white institutions. Given the longitudinal nature of this study only students who completed all items of interest (demographic and environmental measures) on both surveys were included. The sample was composed only of students attending four-year, predominately white institutions. While the sample was not randomly selected and is not nationally representative of the population, it does represent a large number of students from various higher education institutions.

Data Analysis

This study employs the Input-Environment-Outcome (I-E-O) model for studying college impact variables on students (Astin, 1993). “Inputs” refer to the students’ entering characteristics, “environment” is that which the student is exposed to during college, (i.e., faculty, peers, diverse views, etc.) and “outcomes” are the students’ characteristics after interacting with the environment (Astin, 1993). The power of Astin’s I-E-O model is its ability to allow researchers to measure student change during college by comparing outcome characteristics with input characteristics. In short, this framework examines the impact of various college environments on student outcomes, by controlling for inputs or students’ entering characteristics and environmental experiences.

Block stepwise regression was conducted to separate both input and environmental characteristics as the independent variables for the dependent measure, which is academic achievement. Within each block, (significant at p < .05) variables entered the regression in a stepwise fashion. The value of using a stepwise procedure design is that it allows for an examination of changing beta coefficients as each variable enters the equation.

Outcome Variable

The outcome variable focused on in this study is college Grade Point Average (GPA), a quantitative measure for academic achievement. Although there is only one dependent variable used, college GPA is a crucial variable for the purpose of this study, and a common outcome when investigating student and student-athlete achievement in higher education (Astin, 1993a; 1993b).

Input Variables

Achievement and academic characteristics (Block 1) consist of students’ characteristics before entrance to college. Achievement measures include the Verbal and Math SAT and high school grades, followed by an academic measure, studying and homework (pre-test). This is seen as an important input variable after previous exploratory analysis using study and homework as an intermediate outcome (See appendix A for variable list).

Demographic characteristics (Block 2) include measures on race and family background. For race, this study includes whites and African-American/black. Controlling for these two races was imperative, as there are a disproportionately high number of these races involved in revenue generating sports. Of the two races, blacks are expected to have the most significant effect on academic achievement compared to whites (Sellers, 1992). For family, measures include parental status (defined as the number of parents in the household of student). In addition, parental income is included as a measure, which is defined as an estimate of parents’ income by the student. Lastly, the mother’s and father’s education is included as a measure, which is defined as a composite of the mother’s and father’s educational attainment. It is anticipated that these input characteristics would have an influence on academic achievement among male revenue athletes because of strong indications from previous research (Sellers, 1992).

Environmental Variables

Measures of environmental characteristics (Block 3) are categorized into two groups: faculty support and academic characteristics (see appendix A for a complete description of the faculty and academic variables).

Table 1


Predicting Academic
Achievement (College GPA) among Male Revenue Athletes (N = 459 Freshmen
Entering in 2000)

BETA AFTER STEP
STEP VARIABLE R SIMPLE r 1 2 3 4
Input Entering:
1 High School GPA 47 47 47 39 36 36
2 SAT Verbal 50 35 21 21 21 20
Environment Entering:
3 Faculty provided help in achieving pro goals 54 22 18 18 18 14
4 Faculty provided respect 55 25 18 17 13 13
Not Entering:
Studying/HW (pretest) 13 04 04 04 04
Race: White 00 00 -03 -05 -05
Race: Black -08 -04 -02 -01 -01
Status of Parents 06 05 03 04 03
Parental Income -06 -01 -06 -05 -06
Father’s Education 09 05 00 00 00
Mother’s Education 09 06 01 02 01
SAT Math 26 08 -03 -02 -02
Studying/HW 21 11 16 08 06
Talking W/Teachers Outside Class 4
Studied W/Other Students 11
Faculty Provided Encourage for Grad School 22 18 15 09 07
Faculty Gave Advice About Education Program 15 12 11 01 -03
Faculty Provided Assistance W/Study Skills 02 04 06 -02 -04

 


Data Source: 2000 Freshman Survey (CIRP) & 2004 College Student Survey (CSS); Higher Education Research Institute, UCLA

Findings

Input Effects

This study represents an attempt to investigate the relative input characteristics on academic achievement among male revenue athletes enrolled in colleges and universities. Table 1 lists the input characteristics which reveals that high school GPA is the most powerful predictor of college GPA, a proxy for academic achievement (r = .47). This suggests that student with high GPAs in high school tend to get high GPAs in college. Such a finding was not surprising since high school GPA is the indicator that is more similar to college GPA in its composition. Moreover, the data reveals that the Verbal score on the SAT continues to have an influence on college GPA (r = .35). Similar to high school GPA, the data suggests that student-athletes who score high on the SAT Verbal tend to achieve higher academically in college. These two input variables do not change much as each step entered the regression. This indicates that these variables, as stated previously, are important in predicting academic achievement on male revenue athletes. Although SAT Math had a strong association to college GPA (r = .26), it did not enter the regression equation. However, once high school GPA entered at step 1 it dropped from (.26 to .08), suggesting the strength of high school GPA. Black students also did not enter the regression equation (r = -. 08), however, the data reveals that black student-athletes generally tend to enter college less prepared than whites (r = 0) in revenue generating sports.

It is of interest to note that parental status and income, and father’s and mother’s education, these variables did not enter the regression equation. The data suggests that there were no significant affects of these variables on academic achievement. Interestingly enough, the findings on mother’s and father’s educational attainment go against previous findings by Lang and her colleagues (1988).

Environmental Effects

Listed in Table 1, the entry of environmental experiences indicates some impact on academic achievement. This was largely because much of the effect of the environment is already accounted for by the input characteristics. However, the faculty support characteristics does give meaning to its relationship with academic achievement.

The data reveals that the environmental variable, faculty provided help in achieving professional goals, had a positive relationship with college GPA (r = .22). This suggests that students’ who receive assistance from faculty in achieving professional goals tend to performance higher academically in college. In addition, the data shows that there was a positive relationship between the environmental variable, faculty provided respect, and college GPA. This suggests that students’ who were respected by faculty tend to do better academically in college. While others faculty characteristics did not enter the regression equation, two variables did have strong relationships with college GPA (see table 1). Lastly, the academic characteristics, studying and homework, had a strong relationship with college GPA (r = .26), however, after step 1, it dropped (from .26 to .08), indicating the strength of high school GPA.

Conclusions

The present investigation provides evidence that both input and environmental characteristics do impact academic achievement among male revenue athletics participation in intercollegiate sports. Both high GPA and Verbal scores on the SAT continued to be strong predicators of academic achievement in college for both athletes and nonathletes. Moreover, this study showed that the impact of the contact or interaction is to some extent contingent upon the specific nature of the interaction. For example, faculty who provided help in achieving professional goals makes a relatively strong contribution to student success whereas faculty who provided encouragement for graduate school did not benefit male student-athletes equally for this study.

Given the relationship between input variables, academically oriented interactions and student-athletes’ success, the results have important implications for program design that can be used to assist college and university-level student-athletes in improving their academic performance. Beyond that, this study argues for institutions encouraging a wide range of forms of faculty communication and mentoring that are responsive to the needs of male student-athletes of different abilities. When developing such programs attention must be paid, within the structures, practices, and processes of the programs, to specific factors. Since some student-athletes enter college performing at lower academic levels than their peers, faculty, advisors and administrators must be well advised to appreciate their situation and work closely with these students in identifying factors that may impede or facilitate their academic talent development and/or self-identity. It is apparent, moreover, that programs in this area should involve faculty members as possible mentors to student-athletes to offer support and instructions about the importance of their academic pursuit. Further, since the quality and nature of formal and informal communication and faculty interactions with student-athletes is also essential to both academic achievement and overall college experience, mandatory academic and social activities (e.g. research projects, faculty attendance at sporting events and team lunches, etc.) between student-athletes and faculty members should be encouraged (Comeaux and Harrison, 2001). In doing so, faculty members will become more exposed to the culture of this special population of students and begin to cultivate meaningful relationships.

References

  1. Adler, P., & Adler, P. (1985). From idealism to pragmatic detachment: The academic performance of college athletes. Sociology of Education, 58, 241-250.
  2. Astin, A.W. (1993a). Assessment for Excellence. Phoenix, AZ: American Council on Education & The Oryx Press.
  3. Astin, A.W. (1993b). What matters in college? San Francisco: Jossey-Bass.
  4. Budd, J. M. (1990). Higher education literature: Characteristics of citation patterns. Journal of Higher Education, 61(1), 84-97.
  5. Comeaux, E. & Harrison, C.K. (2001). Ecological predictors of academic achievement among male student athletes in revenue- generating sports: A study of football and basketball participants’ interaction with faculty in higher education. A paper presented at the North American Society for the Sociology of Sport Annual Meeting in San Antonio, Texas.
  6. Lang, G., Dunham, R.G., & Alpert, G. P. (1988). Factors related to the academic success and failure of college football players: The case of the mental dropout. Youth and Society, 20, 209-222.
  7. Lawrence, S. M. (2001). The African-American athlete’s experience with race and sport: An existential-phenomenological investigation. Paper presented at the North American Society for the Sociology of Sport Annual Meeting in San Antonio, Texas.
  8. Purdy, D. A., Eitzen, D. S., & Hufnagel, R. (1985). The educational achievement of student-athletes using SAT and non-cognitive variables. Journal of Counseling & Development, 70, 724-727.
  9. Sax, L. J., Astin, A. W., Korn, W. S., & Mahoney, K. M. (1996). The American Freshman: National Norms for Fall 1996. Los Angeles: Higher Education Research Institute, UCLA.
  10. Sellers, R. M. (1992). Racial differences in the predictors of academic achievement of student athletes of Division I revenue-producing sports. Sociology of Sport Journal, 1 46-51.

Appendix A

Dependent Variable: College GPA

I. Input Block
Academic Background Characteristics

  • High School GPA
  • SAT verbal
  • SAT math
  • Studying/HW (pretest)
  • Talking w/ teacher outside class (pretest)
  • Studied with other students (pretest)

II. Input Block
Demographic Characteristics

  • Race: white
  • Race: black
  • Parental status
  • Parental income
  • Father’s education
  • Mother’s education

III. Environment Block
Faculty & Academic Support Characteristics

  • Study/HW
  • Faculty encouragement toward grad school
  • Faculty gave advice about educational program
  • Faculty respect
  • Faculty assistance with study skills
  • Faculty helped in achieving pro goals
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