Relationship Between Academic Clustering and the Academic Performance of Student Athletes

The research questions developed for this study are used to investigate the nature of the relationship between academic clustering and the academic performance of student athletes. Academic clustering is the independent variable whereas the academic performance of student athletes is the dependent variable in this study. The study also seeks to explore the academic majors that are usually subject to academic clustering among student athletes. With respect to the purpose and problem statements, the following research questions will be used to achieve the objectives of this study.

Research Questions

Which Clustered Academic Majors are Common among Student Athletes?

This research question will be addressed using qualitative methods, which will seek to explore the various academic majors in order to determine which are most likely to be subject to academic clustering among student athletes. For this research question, qualitative data will be collected from cricket student athletes in the selected universities using documentation reports from the universities and conducting semi-structured interviews with the individual cricket student athletes in order to take note of their academic majors. Academic clustering is defined as the “occurrence of at least 25% of a single athletic team taking the same academic major” (Fountain & Finley, 2009; Gaston-Gayles, 2004; Sanders & Hildenbrand, 2010). This criterion will be used to determine which academic majors are clustered; afterwards, the various cricket teams will be evaluated for the tendencies of student athletes to cluster in particular academic majors. In addition, a portion of students taking a particular major will be compared with the general student population in order to determine any differences between the general student population and the student athletes’ selection of the academic major. Overall, the research question will seek to draw the patterns of major selection among student athletes and determine which academic majors are most likely to be selected by student athletes.

What are the Main Reasons Cited for Academic Clustering among Student Athletes, Academic Staff and Athletic Staff?

This research question will be answered using qualitative methods, which will seek to explore the main reasons/ justifications for academic clustering. Data will be gathered from student athletes (cricketers), academic staff and athletic staff regarding their reasons and perceptions about student clustering. For this purpose, an interview protocol will be developed, which will be administered to student athletes, academic staff and athletic staff using semi-structured interviews. Their testimonies, illustrations and stories will be recorded for further coding and analysis. The reasons for academic clustering will be grouped into: (a) the need for schedule flexibility by student athletes; (b) meeting eligibility requirements; (c) peer recommendations from their fellow athletes; (d) lack of college preparation; and (e) students pick academic majors that suit their respective interests or career aspirations (Suggs, 2003). A comparative analysis will be undertaken in order to compare the reasons for academic clustering as cited by student athletes, academic staff, and athletic staff. In addition, other reasons besides the aforementioned coding system will be categorized as others and specified in detail. The facilitator of the semi-structured interview will provide a clarification of the aforementioned reasons for academic clustering. For instance, with regard to the need for schedule flexibility, student athletes opt for majors that have more unrestrictive electives and several study options, which allows the athlete to fit his/ her studies to his/ her athletic schedule (Fountain & Finley, 2009). Regarding the evaluation and analysis of data, the researcher will make use of several interpretations to determine the linkages existing between the research outcomes and the research object with respect to the research questions. In addition, the researcher will remain open to new insights and opportunities.

What are the Attitudes of Student Athletes, Athletic Staff and Academic Staff towards Academic Clustering?

This research question will be addressed qualitatively in order to determine the attitudes and perceptions that student athletes, academic staff and athletic staff have towards academic clustering, especially with respect to the extent to which they agree or disagree with the practice. Data for answering this research question will be collected using semi-structured interviews administered to student athletes, academic staff and athletic staff (Creswell & Clark, 2010). The interview protocol used in this study will contain questions relating to the degree the participants agree with the practice and whether they perceive the practice of academic clustering as being good or bad to the students. The attitudes and perceptions of the student athletes, athletic staff and academic staff will be compared to determine any patterns of differences between them. For attitudes towards academic clustering, the qualitative information will be coded into two categories: those who agree with the practice and those who do not agree with the practice. Regarding the perceptions of participants towards the practice, qualitative information will be coded into two groups: those perceiving the practice as good to the students and those perceiving the practice as bad to student athletes.

How is Academic Clustering Related to the Academic Performance of Student Athletes?

This research question will be addressed using quantitative methods, which involve the use of statistical analysis to determine the nature of the relationship between the variables of interest (academic performance of student athletes and academic clustering). In this regard, academic performance of student athletes, which is the dependent variable, will be measured using GPAs. Data relating to GPAs of student athletes will be collected from their respective universities, with student athletes being divided into control and treatment groups. The treatment group will comprise of student athletes taking clustered academic majors whereas the control group will comprise of student athletes taking non-clustered majors. In order to determine whether academic clustering is related to academic performance, an independent sample t-test will be used to check if there are any statistically significant differences between the GPA means for students taking clustered majors and those taking non-clustered majors (Fountain & Finley, 2009). A statistically significant difference between the GPA means of the two groups will imply that academic clustering is related to academic performance, whereas an insignificant difference will imply that the two variables are not related, and thus, academic clustering has no impact on the academic performance of student athletes. For the case of significant differences, that is the variables are related, a higher GPA mean for student athletes taking clustered majors will imply that academic clustering improves the academic clustering of student athletes. On the contrary, a lower GPA mean for students taking clustered majors will imply that academic clustering has a negative impact on the performance of student athletes.

How does the Level of Satisfaction with Academic Major Selection Vary between Students Taking Clustered Major and Those Taking Non-Clustered Majors?

This research question will be addressed using quantitative methods to determine the differences in the level of satisfaction with academic major are selection. Data relating to this research question will be obtained using an online survey administered to student athletes, taking both clustered and non-clustered academic majors. A question with five-point likert scale was designed to capture the student’s level of satisfaction with their selection of academic majors (1 – extremely dissatisfied, 2 – dissatisfied, 3 – neither satisfied nor dissatisfied, 4 – satisfied, and 5 – extremely satisfied). The responses provided by participants were analyzed using one-way ANOVA, which is used in comparing the differences between the means of at least two groups in order to determine if there is a significant difference between the means. One-way ANOVA evaluates that the null hypothesis that two or more groups in a sample have equal mean values. In this study, one way ANOVA was used in comparing the means of participants’ responses between student athletes taking clustered majors and those taking non-clustered majors (Leedy & Ormrod, 2010). Statistical significance of the difference will be taken into consideration. An insignificant difference will imply that the level of satisfaction with the selection of academic major does not vary among students taking clustered and non-clustered academic majors. A significant difference (depending on the means) will point out which group is more satisfied with their selection of academic majors.

Research Hypotheses

Hypothesis testing will be done for research questions 4 and 5, using the quantitative data collected pertinent to each question. Each research question has a null hypothesis (insignificant relationship between the variables of interest) and an alternate hypothesis (significant relationship between variables). The following are the research hypothesis to be used in this study:

  • H10: There is no difference in the academic performance of student athletes, as measured using their GPAs of academic majors, between students taking clustered majors and those taking non-clustered majors;
  • H1a: There is a difference in the academic performance of student athletics, as measured using their GPAs in their respective academic majors, between student athletics taking clustered majors and those taking non clustered academic majors;
  • H20: There is no difference in the level of satisfaction with academic major selection, as measured using a five point likert scale (1 – extremely dissatisfied, 2 – dissatisfied, 3 – neither satisfied nor dissatisfied, 4 – satisfied, and 5 – extremely satisfied), between student athletes taking clustered majors and those taking non-clustered majors;
  • H2a: There is a difference in the level of satisfaction with academic major selection, as measured using a five point likert scale (1 – extremely dissatisfied, 2 – dissatisfied, 3 – neither satisfied nor dissatisfied, 4 – satisfied, and 5 – extremely satisfied), between student athletes taking clustered majors and those taking non-clustered majors.

References

Creswell, J., & Clark, V. (2010). Designing and conducting mixed methods research. New York: SAGE.

Fountain, J., & Finley, P. (2009). Academic majors of upperclassmen football players in the atlantic coast conference: An analysis of academic clustering comparing white and minority players. Journal of Issues in Intercollegiate Athletics , 2, 1-13.

Gaston-Gayles, J. (2004). Examining academic and athletic motivation among student athletes at a division I university. Journal of College Student Development , 45 (1), 75-83.

Leedy, P. D., & Ormrod, J. E. (2010). Practical research: Planning and design. Upper Saddle River, NJ: Merril.

Sanders, J., & Hildenbrand, K. (2010). Major concerns? A longitudinal analysis of student- athletes’ academic majors in comparative perspective. Journal of Intercollegiate Sports , 3 (2), 213 – 233.

Suggs, W. (2003). Jock majors: Many colleges allow football players to take the easy way out. The Chronicle of Higher Education , 49 (17), 33.