Journal of
Physical Education and Sport Management

  • Abbreviation: J. Phys. Educ. Sport Manag.
  • Language: English
  • ISSN: 2141-6486
  • DOI: 10.5897/JPESM
  • Start Year: 2010
  • Published Articles: 82

Full Length Research Paper

The 9 credit rule: A look at its impact on academic advising for intercollegiate football athletes

Joshua Castle
  • Joshua Castle
  • Indiana University of Pennsylvania, United States.
  • Google Scholar
Robin Ammon
  • Robin Ammon
  • University of South Dakota, United States.
  • Google Scholar
Les Myers
  • Les Myers
  • University of North Carolina at Chapel Hill, United States.
  • Google Scholar

  •  Received: 26 August 2014
  •  Accepted: 17 October 2014
  •  Published: 31 October 2014


The purpose of this exploratory study was to examine the impact the NCAA’s 2011 9 Credit Rule would have on football academic advising strategies. The legislation requires players to earn nine credit hours in every fall term or be suspended for the first four games the following season. For this study, a survey was distributed to Football Academic Advisors at NCAA Division I institutions. Subjects were asked if the 9 Credit Rule has changed their advising strategies regarding: at-risk students, incoming freshmen, clustering and the use of elective credits. The subjects were also able to provide open ended responses regarding strategies they plan to implement to help students from becoming ineligible. According to the data, due to the 9 Credit Rule, 69.4% of responding advisors planned to change their advising strategies for all student athletes. Additional results specified that 83.1% of the respondents were more likely to change their advising strategy when dealing with at-risk student athletes. Additionally, 73.1% of the responding advisors indicated they were more likely to change their advising strategy for incoming freshmen. Over 58% of the responding academic advisors stated they were more likely to use elective credits earlier in a student-athletes’ career and 60.6% would be more likely to cluster student athletes into specific majors. The responses indicated that, on average, 6.1student athletes/program would have been affected by the rule if the legislation had been enacted in 2010. One respondent went so far as to surmise that 30% of their student athletes would be ineligible for the first four games of the following year. The NCAA’s 9 Credit Rule has the potential to impact numerous athletic departments across the United States. Knowledge and awareness of the implemented legislation is the first step for football academic advisors in the monitoring of their student-athletes. Additional studies will be necessary to determine if the legislation has caused major changes in academic advising for football players including an increase in the clustering of student-athletes in specific academic majors.

Key words: Extracurricular activities, human resource management, mixed methods approach, physical education, volunteer.


In 2004, the NCAA introduced a new academic reform called the Academic Performance Program (APP). The genesis of the APP legislation was to ensure that intercollegiate academic institutions were accountable for the graduation of their student athletes. The Academic Progress Rating (APR) was part of the new reorganization instituted by the National Collegiate Athletic Association (NCAA). It was intended to act as a more accurate way of gauging whether student athletes are making progress in their degrees (Christy et al., 2008). Since its inception in 2004, records indicate the APR rule has been improving graduation rates. In 2007, the APR for all Division I athletics was up three points from the previous year (Hosick, 2008). However, this increase has not been uniform in every sport. Nationally the APR scores for football athletes decreased over several years, which prompted the NCAA to create an additional piece of legislation (Hosick, 2008).

In 2011 the NCAA implemented a 9 Credit Rule which requires football players to earn nine credit hours every fall term or be suspended for the first four games the following fall.

If the student-athlete earns 27 credit hours before the start of the next fall, he can (once in a career) “earn” back all four games. For the remaining seasons, he can earn back two games if he earns the 27 credit hours by the end of summer session (Hosick, 2011). Obviously this rule can impact a coach’s ability to put particular athletes on the field at the beginning of a season. Therefore, it becomes a possibility that some teams and athletic departments may try to circumvent the rule in some fashion.

In 2010 the NCAA negotiated a new TV rights deal for its men’s “March Madness” basketball tournament with Turner Broadcasting and CBS Sports. It is estimated this new $10.8 billion 14-year deal will result in $740 million to NCAA member institutions (Wolverton, 2010).

The continuous expansion and growth of the NCAA’s media rights deals has caused many individuals to focus their attention not only on the conferences and the universities receiving this new income, but also on the athletes making up the rosters of these teams. While the NCAA as well as their conferences enrich themselves with the media contracts, it becomes plausible that the academic pursuits of the athletes may be compromised to keep their institution’s athletic departments competitive.

One area under scrutiny pertains to the academic majors some athletes are guided towards by their academic advisors.

While one major may be of particular interest to an athlete, the rigor of the program may be perceived to be difficult. As a result the advisor encourages that athlete to select another less demanding choice. Sometimes this results in what is termed “clustering”. This situation occurs when numerous athletes are guided to select majors considered to be less academically strenuous than other academic alternatives.

This phenomenon tends to impact large numbers of athletes from high-profile sports. Academic clustering is one of the many underlining issues within the debate on college athletics and academics” (Schneider  et al., 2010, pg. 65). The factors leading to the selection of these clustered majors, the academic credentials of those teaching the clustered majors as well as the existence of “friendly” faculty members within the clustered majors, and the role some coaches and athletic academic support members play in the selection process add to the focus placed on this issue. Finally, special admission procedures for less academically prepared student-athletes may also impact the clustering of majors. If student-athletes are being directed by athletic department personnel to base their academic choices on the concept of staying eligible for athletic participation instead of acquiring the life skills necessary to be successful upon graduation questions will continue to plague NCAA member institutions.

Schneider et al. (2010) stated “Academic clustering is one of the many underlining issues within the debate on college athletics and academics” (pg. 65). However, it is not a new problem. Over 25 years ago, Case et al. (1987) conducted the first study that showed the existence of clustering. After reviewing the media guides of over 100 men’s basketball teams, the researchers found clustering in nearly every sampled university. Their study defined “clustering” as when 25% or more of any team’s roster of major eligible students is enrolled in the same major. Their results of their research also indicated that every clustered major came from non-science based majors.

Fountain and Finley (2009) looked at the Atlantic Coast Conference (ACC) football teams over a one year period and found every school had at least one clustered major. They also discovered that eight of the eleven schools (73%) had two clustered majors. Schneider et al. (2010) followed a similar method as the previous two studies and examined the media guides for the Big 12 Conference football teams over three different years to determine whether academic major clustering occurred. Their data demonstrated that clustered majors existed at every school. The data gathered from several of the more nationally prominent teams indicated over 50% of the team’s roster were enrolled in the same major.

In 2011 a study conducted by Fountain and Finley (2011) was the first to take a longitudinal look at the problem of academic clustering. The two researchers looked at one major NCAA Division I football team and examined ten years of media guides. They focused on clustering as a process versus a one year snapshot. Their results indicated that clustering occurs over time within the career of an athlete, as the clustered major was often chosen later in the career of the student- athlete. When comparing white and minority student-athletes, the researchers found minority athletes to declare clustered majors earlier in their career, while white athletes often were in other majors before moving to the clustered major. All of these studies (Case et al., 1987, Fountain and Finley, 2011, Schneider et al., 2010) indicate the phenomenon of academic clustering is a reality and one study showed that clustering impacts both minority as well as white football athletes.

The pressure to win impacts coaches and athletic directors in numerous ways. In 1987 a variety of transgressions resulted in Southern Methodist University (SMU) receiving the NCAA’s “death penalty”. More recently stories involving the University of Southern California’s Reggie Bush, multiple athletes from the Ohio State University football program and agents allegedly paying athletes over multiple years have been the focus of various news stories (Staff, 2011). Sometimes, the pressure to win influences individual decisions regarding recruiting the best athletes, regardless of academic aptitude or preparation. The NCAA imposed sanctions against the University of North Carolina in 2012 pertaining to academic improprieties involving multiple football players (Ganim, 2014).

In order to maintain the eligibility of these academic risks, as well as to assist their other less risky athletes, coaches and athletic administrators provide a multitude of athletic academic support services. The job of academic advisers has two parts; first they advise athletes on their academic careers through college, to help the student pursue the education/career of their choice, and secondly, to keep the student eligible to compete in NCAA com-petition (Busch, 2007). The challenge academic advisors face is the competing values these two jobs bring together. As a result a potential conflict of interest may exist. While academic support staff is available for the athletes their careers rely upon the continued eligibility of the student athletes. Unfortunately some of these athletes may not possess the academic wherewithal to navigate the academic rigor inherent in college. There-fore, similar to coaches and athletic department administrators, these individuals also face challenges to keep their charges eligible. This in turn may elicit potential solutions such as the clustering of academic majors.

Carodine et al. (2001) recognized the need institutions have to provide support services to athletes and provided a framework for what athletic support services should look like. Their framework contained the same sort of potential contradiction facing athletic academic support services across the country in that athletic academic advisors are not only giving advice on academic matters, but are often the primary members of the university staff providing advice on the athletic academic eligibility issues. When it is time for an athlete to declare a major or to possibly change a major, the question arises if the eligibility of athletes is entering the mind of the athletic academic advisors providing the advice (Brady, 2008; Capriccioso, 2006; Steeg et al., 2008; Suggs, 2003). Kulics (2006) discovered 15% of the athletes in her study reported being told by athletic academic advisors to change a major to stay eligible. As part of the same study, over 60% of athletic academic advisors reported advising athletes to change a major for eligibility reasons.

Athletic academic advisors are often placed in no-win situations when working with athletes who are naïve about the effort needed to be successful in  any  college  major, much less for those majors identified with high paying post-collegiate careers. When recruiting athletes, coaches are quick to point towards all of the major choices available and the academic support systems in place to ensure academic success.

Unfortunately, the athletic academic advisor is primarily the person responsible for being the academic reality check for the athlete (Brady, 2008). When faced with athletes who are making academic choices based entirely upon academic eligibility, these advisors face the difficult situation of providing advice as to what academic path or major will provide the least resistance (Steeg, 2008; Steeg et al., 2008). Coaches are also involved with the academic choices being made by athletes. Their advice sometimes runs counter to that being provided by athletic academic advisors. In high profile sports such as football, athletic academic advisors are often placed into positions of conflict with head coaches who are paid millions of dollars a year. The question of the role coaches play in eligibility situations, especially in the selection of a major is also an area of concern. In some situations, athletic academic advisors have felt like part of the head coaches staff or were treated as such (Brady, 2008).

For the purposes of this exploratory study, the researchers examined the impact the 9 Credit Rule has on intercollegiate football academic advising strategies. The four research questions analyzed for this study are:

1. Will football academic advisors change the way they advise students due to the “9 Credit rule?

2. Will football academic advisors change the way they advise at-risk collegiate athletes due to the “9 Credit rule?

3. Will football academic advisors change the way they advise in-coming freshmen collegiate athletes due to the “9 Credit rule?

4. Will football academic advisors be more likely to cluster collegiate athletes in less academically stringent majors due to the “9 Credit rule?

These questions were formulated after consulting with several football academic advisors and scholars con-ducting research on intercollegiate athletics.


This current study utilized an online questionnaire. Data were analyzed using descriptive statistics. The survey was a modified version of an APR questionaire used in a previous study with Directors of Football Operations (Castle, 2010). The first section of the survey included an explanation of the study, a subsection for obtaining the participant's informed consent, and directions for the survey. The second section gathered information regarding demographic characteristics about the population. The information gathered in the second section included: Age range, gender, level of education, ethnicity, type of college or university in regards to Bowl Championship Series (BCS), non-BCS and/or Historically Black Colleges and Univeristies (HBCUs), and conference affiliation.

The third section of the instrument contained questions regarding the advising strategies of the program before and after the inception of the 9 Credit Rule. A seven point Likert type scale was used including the groupings of extremely less likely,  less  likely,  slightly less likely, no change, slightly more likely, more likely and extremely more likely, subjects were asked general questions about their advising strategies. In addition to the seven point Likert scale, a "Don't Know" response was included as an option. Also included in this section were several questions regarding the graduation of student athletes, and the dedication of resources to academics by the program and the athletic department due to the “9 Credit Rule.” These questions had predetermined responses from which to choose. In the fourth section of the survey academic advisors also had the option of answering an open ended question, “Please provide us with some of the advising strategies you will implement to help keep student athletes from becoming ineligible due to the 9 Credit Rule.

All 264 NCAA Division I Football Academic Advisors were directed via e-mail, to a secure data collection site to complete the survey. The Academic Advisor email addresses were solicited via their athletic department websites. The online questionnaire was used to obtain the advisors perceptions and changes of academic advising due to the 9 Credit Rule. After accessing the secure online data collection site (Qualtrics), the respondents were directed to read an introduction and directions about the research study.


Of the 295 subjects, 121 chose to respond to the survey resulting in a 41% response rate. In order to achieve a 95% confidence with a ±7% margin of error 122 subjects needed to respond.  There is no strategy for determining a response rate that involves a specific percentage of a limited population (Suter, 1998). “Low response rates alone do not necessarily suggest sampling bias” (Sax, Gilmartin and Bryant, 2003).

Three quarters of respondents indicated that their age was between 25-44, (76%) N=92. Of the respondents, 102 (89%) had earned a graduate degree, while 19 (11%) had earned a bachelor’s degree. The mean number of years serving as academic advisors was 8.65 years.  At the time the surveys were collected every NCAA Division I conference was represented. Table 1 shows the responses by NCAA Subdivision.




Sixty-six (70%) of the respondents indicated they believed the 9 Credit Rule would not raise their football programs APR score. However, 60 (64%) of the respondents felt this policy would change the way football coaches approach the academics of their collegiate athletes. Respondents felt the 9 Credit Rule would have impacted 6.3 athletes if instituted a year before. Meaning that on average six athletes would have been declared ineligible to participate in the first four games of the next year per program.

Research Question 1: Will football academic advisors change the way they advise students due to the  9  Credit Rule?

The results of Research Question 1 indicated respondents were “slightly more likely” to change the way they advised football players due to the 9 Credit Rule (M= 5.01, SD= 1.43). Of the respondents 55 (57.2%) indicated they were either “slightly more likely”, or “more likely” to change their advising strategy. Twenty-three (23.9%) indicated “no change” in their advising strategy.

Research Question 2: Will football academic advisors change the way they advise at-risk collegiate athletes due to the 9 Credit Rule?

When asked if academic advisors will change the way they advise at-risk football players due to the 9 Credit Rule, the advisors were “slightly more likely” to change (M= 5.71, SD= 1.51). Thirty-two (33%) of the respondents indicated they were “more likely” and 34 (35.3%) were “extremely more likely” to change their advising. Only 10 (10.4%) of respondents indicated they would “not change” the way they advise at-risk football players.

Research Question 3: Will football academic advisors change the way they advise in-coming freshmen collegiate athletes due to the 9 Credit Rule?

The results from Research Question 3 indicated the respondents were “slightly more likely” to change the way they advised incoming freshmen football players due to the 9 Credit Rule (M= 5.31, SD= 1.6). Twenty-seven (28.7%) indicated they would be “extremely more likely” to change their freshmen advising, 21 (22.3%) would be “slightly more likely”, 20 (21.2%) felt they would be “more likely” while 18 (19.1%) believed it would “not change” the way they advise incoming freshmen athletes.

When asked if advisers would be “more likely” to use elective courses earlier in students’ careers 21 (22.8%) respondents indicated they would not change their advising strategy due to the 9 Credit Rule (M= 4.79, SD= 1.69).  However while the mean was much lower and 24 (26%) supported no change the advisors indicated they were “more likely” to change. When combining the “slightly more likely”, “more likely” and “extremely more likely” responses, and 53 (57.6%) indicated some type of change in advising freshmen football players with the use of electives due to the 9 Credit Rule.  

Research Question 4: Will football academic advisors be more likely to cluster collegiate athletes in less academically stringent majors due to the 9 Credit Rule?

Responses from the fourth research question indicated advisers were “slightly more likely” to cluster students in less academically stringent majors due to the 9 Credit Rule (M= 5.04, SD= 1.6). However, 27 (30%) of the respondents indicated they were not going to change the way they placed students into majors. “Slightly more likely”, “more likely”, and “extremely more likely” accounted for 54 (60%) of the responses. Finally, 21 (23.3%) indicated they were “extremely more likely” to cluster students in less academically stringent majors (Table 2).



Open ended responses

When analyzing the open-ended responses football academic advisers indicated one way they planned to change their advising strategy was by increasing the monitoring of their athletes. Of the respondents that answered the open-ended follow-up question 25 (40.2%) stated they were going to increase the monitoring of their students. This included increases in weekly grade reports, increases in communication with professors, increases in degree planning, increases in study hall/ tutoring hours, and increases in class attendance monitoring.

In order for athletes to be eligible for NCAA competition, they must be enrolled full-time at the institution. Typically, this equates to a minimum of twelve credits. Some advisors would only place them in the minimum in order for the athlete to focus on a small amount of course work during the season. Thirteen (21.8%) of the respondents stated they were going to change their advising strategy by ensuring students were enrolled in at least 15 h of course work, with 3-6 h of electives. Several also mentioned they would be less likely to allow a student to drop a course. Academic advisors might be thinking that passing the course with a D would be more beneficial to eligibility regarding the 9 Credit Rule than the decline in an individual’s grade point average.  

Additionally, 8 (13.1%) of the academic advisors indicated they would advise students to take “less stringent” courses in fall. Some also indicated they would be less likely to use Pass/Fail Option. Others, 3 (4.9%) stated they would stagger the use of electives as a sort of “Insurance.”

Twenty-six (42.6%) of the surveyed academic advisors believed requiring athletes to select a major earlier, increasing progress reports and monitoring, providing additional planning with freshmen, requiring freshmen to enroll in an academic learning strategies class, and implementing policies to identify at-risk students earlier in their academic careers were strategies they planned to change for incoming freshmen. Only 7 (11.4%) of the respondents addressed the issue of clustering. All seven indicated the APR would have a negative impact on students and would force students into specific majors. Some of their statements included: “I believe the APR is working and a rule like this will only force students away from majors they are truly interested in.”  Another respondent stated, “Finally, I will have no choice but to allow our at risk players to only pursue certain degrees.” One of the more interesting responses was:

I doubt this rule will have any effect other than promote clustering and football student-athletes taking less academic chances in the fall term. Students who come up short in the fall will then take even less chances in the next term(s) in order to regain their eligibility--further ensuring a growth in clustering/less academically demanding majors.

As previously mentioned the clustering students into specific majors could force student athletes to pursue majors not of their choosing. One respondent was quoted as stating, “I fear that this rule will unintentionally penalize student-athletes who would otherwise have a solid chance of completing a degree but must ‘settle’ for an alternative for fear of jeopardizing their future eligibility.”

Other changes

Five (8.1%) of the respondents commented on the need to emphasize the new rules to both athletes and coaches. One respondent indicated:

We have been talking about it all summer and making sure the awareness is there. There is a huge colored sign hanging at the front door of the football building that they see every day.  We have worked with the coaches to remind the guys all the time that they have to focus on their academics.

Seventy-seven (81%) of the academic advisors indicated this legislation will not change the academic quality of recruited athletes. However, it is believed coaches will increase their interest in academics during the fall semester. Because of the rule, 60 (64%) respondents indicated coaches will take more of an academic interest. This may include increases in individual academic meetings by the athletes’ position coach or increased updates from football academic advisors. While there may be an increase in emphasis on academics during the fall for football coaches and players, one thing that respondents indicated will not change is number of resources dedicated to athletic academic offices. Subjects were asked, “With this new legislation do you predict an increase in money/resources to your program from the athletic department to ensure collegiate athletes do not become ineligible,” 74 (78%) indicated they expect no increase in money or resources.


The academic reform measures NCAA leaders have approved recently have been held up as evidence that the NCAA takes education seriously. Higher minimum grade point averages, Academic Progress Rates, and stiffer penalties for teams that do not meet the academic progress benchmark back up the claim that players are, as NCAA President Mark Emmert puts it, "students who happen to be athletes," not the other way around. Unsurprisingly, faculty and some other officials have been more critical. At the annual NCAA convention in January 2012, some speculated the measures may lead to higher graduation rates, but only because athletes will be driven to take easier classes or succumb to academic fraud (Grasgreen, 2012).

The 9 Credit Rule has the potential to further divide the competing values that academic advisers face in their jobs. The recent educational goals of the NCAA have been to raise academic standards and if APRs are raised, more students graduate faster, and more students graduating equals academic success (Grasgreen, 2012). An interesting query becomes will the new 9 Credit Rule accomplish this goal and will there be any unintended consequences? The rule is in line with other recent measures requiring athletes to spread out their credit hours for more consistent academic progress, rather than take just a few hours during the season and have trouble  fitting everything else in during the spring and summer semesters (Grasgreen, 2012).

The results from the current study indicate some respondents believe the 9 Credit Rule will change the way football academic advisors work with students, especially when working with at-risk athletes.  However additional research is necessary to determine if the 9 Credit Rule will create the intended change or will it create new problems and issues. Change produces a degree of uncertainty, especially when it is unclear as to the impact it will have on the affected individuals (Slack and Parent, 2006). The effects of change are impacted by the people that must implement the change.  In this case academic advisors could be resistant to this change. Slack and Parent also mentioned resistance to change occurs when there are differing opinions to the benefits of the proposed change. When 70% of football academic advisors feel the 9 Credit Rule will not raise APR scores there is a question of whether this legislation will be successfully implemented. Whether the 9 Credit Rule raises APRs and ultimately graduation rates is yet to be determined. What must be considered are the unintended consequences; First, the idea of academic clustering. The results of this study indicated 60% of football academic advisors are more likely to cluster students due to the 9 Credit Rule. Respondents indicated “Finally, I will have no choice but to allow our at-risk players to only pursue certain degrees”, and “Students who come up short in the fall will then take even less chances in the next term(s) in order to regain their eligibility -- further insuring a growth in clustering/less academically demanding majors”. These responses could be due to the advisors own self-interest. Athletic advisers are fired when students become ineligible, academic fulfillment is not always part of the equation (Grasgreen, 2012). Patti (1974) stated job security is another factor for individuals to be resistant to change. But this decision is not always entirely the academic advisors. Some athletes will take the path of least resistance, meaning if they have a choice between academics and eligibility, a lot of times they're going to choose eligibility (Grasgreen, 2012; Lederman, 2003).

Some athletic advisors believe “clustering” may become more prominent due to the APR. One respondent stated:

Our unit does not advise based on how to keep students eligible, which this legislation is encouraging. We will continue to encourage students to excel in the classroom; however, more emphasis will now have to be placed on eligibility, as opposed to academic excellence. We can now, officially, be classified as "eligibility brokers" instead of "academic advisors." In the best of worlds, the NCAA would have changed the initial eligibility standards so students who enter college are actually prepared to do college work.

Action by the NCAA to change initial eligibility standards is on the horizon. In 2016 incoming freshmen will need a 2.3 grade point average (GPA) in high school, which is up from the current 2.0 GPA. Before their senior year they will also need to have completed 10 of the required 16 core courses, and complete all 16 within four years (Sherman, 2012).

The second unintended consequence of this legislation has to deal with the increase in monitoring due to the 9 Credit Rule. With increased monitoring there is a risk of alienating professors. One of the ways academic advisors indicated they were going to increase monitoring athletes was by increasing communication with professors either through grade reports or attendance checks. Will this increase be seen as harassment? Or will professors see this as an extra burden?

Another unintended consequence is the possibility of a further divide between the “have and have-nots” among college football programs and athletic programs. Despite "more monitoring" being the most common measure advisers expect to take to help students meet this new legislation, 78% indicated they do not expect to receive more money or resources for it. With more monitoring comes more expense. Some respondents agreed stating “the 9 Credit Rule will have the biggest impact on institutions that do not have the resources to provide the level of academic support collegiate athletes are receiving at BCS institutions", and another respondent commented "Once again widening the gap in another area between the 'haves' and the 'have-nots’”.


After reviewing the result there is clear need for future research in this area. In particular the NCAA needs to analyze the data to see if the 9 Credit Rule truly meets its intended outcomes. In order for this to occur the unintended outcomes need to be identified and additional research needs to investigate the impact of the 9 Credit Rule on these outcomes. The NCAA needs to monitor the academic clustering of athletes and look to see if the 9 Credit Rule advances the use of clustering. In order to help prevent the types of problems found in this study, athletic programs need to add resources for academic advisors due to the anticipated increases in monitoring they will be required to do. Finally, the NCAA must initiate more effective initial eligibility standards.


The authors have not declared any conflict of interests.


Brady E (2008). Athletes' academic choices put advisors in tough balancing act. USA Today. 



Busch A (2007). Seeking a life after college football. Sports Illustrated.



Capriccioso R (2006). Tackling favoritism for athletes. Inside Higher Ed.



Carodine K, Almond K, Grotto K (2001). College student athlete success both in and out of the classroom. New Directions for Student Services, 93:19-33.


Case B, Greer HS, Brown J (1987). Academic clustering in athletics: Myth or reality? Arena Rev. 11: 48-56.


Castle J (2010). The impact of the academic progress rating on the retention and recruiting strategies of NCAA Division I football programs (Unpublished doctoral dissertation). University of New Mexico, Albuquerque, NM.


Christy K, Seifried C, Pastore D (2008). Intercollegiate athletics: A preliminary study examining the opinions on the impact of the academic performance rate (APR). J. Issues Intercollegiate Athletics. 1:1-10.


Fountain JJ, Finley PS (2009). Academic majors of upperclassmen football players in the Atlantic Coast Conference: An analysis of academic clustering comparing white and minority players. J. Issues Intercollegiate Athletics 2:1-13.


Fountain JJ, Finley PS (2011). Academic Clustering: A longitudinal analysis of a Division I football program. J. Issues Intercollegiate Athletics 4: 24-41.


Ganim S (2014). UNC fake class scandal and NCAA's response wind their way to Washington. CNN.



Grasgreen A (2012). More credits, more clusters. Inside Higher Ed.



Hosick M (2008). Reform's in roads evident with APR release. The NCAA News.



Hosick M (2011). New rule should boost APR in football. The NCAA News. Retrieved from


Kulics J (2006). An analysis of the academic behaviors and beliefs of Division I student-athletes and academic administrators: The impact of the increased percentage toward degree requirements (Doctoral dissertation). Retrieved from


Lederman D (2003). Major issue: Athletes' studies. USA Today.



Patti R (1974). Organizational resistance and change: The view from the bottom. Soc. Serv. Rev. 48(3), 367-383.


Sax L, Gilmartin S, Bryant A (2003). Assessing response rate and nonresponse bias in web and paper surveys. Res. Higher Educ. 44(4):409-432.


Schneider R, Ross S, Fisher M (2010). Academic clustering and major selection of intercollegiate student-athletes. College Student J. 44(1):64-70.


Sherman M (2012). New eligibility standards on the way.



Slack T, Parent M (2006). Understanding sports organizations. Champaign, IL: Human Kinetics.


Staff. (2011). Top 5 'pay to play' scandals rocking college football. The Week.



Steeg J (2008). UNLV athletes question degrees in university studies. USA Today.



Steeg J, Upton J, Bohn P, Berkowitz S (2008). College athlete's studies guided toward 'major in eligibility'. USA Today.



Suggs W (2003). Jock majors. The Chronicle of Higher Education.



Suter W (1998). Primer Educ. Res. Boston, MA: Allyn and Bacon.


Wolverton B (2010). NCAA agrees to $10.8-billion deal to broadcast its men's basketball tournament. The Chronicle of Higher Education.