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Students’ perceptions of the campus climate can affect their success and outcomes. Student-athletes’ experiences with campus life are unique. The Student-Athletes Climate Study (SACS) is a national study of over 8,000 student athletes from all NCAA sports and divisions. The purpose of the study was to examine the influence of individual and institu-tional characteristics, as mediated by climate, on student-athletes’ (a) academic success, (b) athletic success, and (c) athletic identity. Results indicated that differences in outcomes existed based on institutional and individual characteristics. It was also clear that cli-mate mattered. Six of the seven climate scales influenced the outcomes, and differences in outcomes based on sexual identity, Division, and featured sport participation were more salient when climate was taken into account. Positive aspects of climate led to increases in outcomes in almost every relationship. Implications for researchers and practitioners are discussed, as well as specific suggestions of initiatives to improve the climate to promote the success of all student-athletes.

Keywords: student-athlete, climate, academic success, athletic success, athletic identity

The Influence of Climate on the Academic and Athletic Success of Student-Athletes: Results from a Multi-Institutional National Study

Susan RankinDan MersonJason C. GarveyCarl H. SorgenIndia MenonKarla LoyaLeticia Oseguera

Susan Rankin is a retired Associate Professor and Senior Research Associate in the Higher Education Program and the Center for the Study of Higher Education at The Pennsylvania State University; sxr2@psu.edu. Daniel Merson is the Principal of Dan Merson Academic & Research Consulting; DanMerson@gmail.com. Jason C. Garvey is an Assistant Professor of Higher Education in Student Affairs & Educational Leadership at the University of Vermont. Carl H. Sorgen is the Associate Director in the Office for Teaching & Learning at Wayne State University. India Menon (no current affiliation). Karla I. Loya-Suárez, is an Assistant Professor of Educational Leadership at the Univer-sity of Hartford. Leticia Oseguera is an Associate Professor and Senior Research Associ-ate in the Higher Education Program and the Center for the Study of Higher Education at The Pennsylvania State University.

702 The Journal of Higher Education

Current research surrounding student-athletes’ collegiate experiences is growing, but limited in that it is typically restricted to single institu-tions, small samples, and/or one NCAA Division. In a comprehensive overview of the literature on the topic, Gayles (2009) discussed the limited number of data sources available and highlighted the need for more national-level data.

The purpose of the Student-Athlete Climate Study (SACS) was to examine the influence of individual and institutional characteristics, as mediated by climate, on student-athletes’ (1) academic success, (2) athletic success, and (3) athletic identity. The three outcomes were also examined based on various demographic (e.g., gender, race) and institutional characteristics (e.g., Division, sport). Based on the results, initiatives to improve the climate to promote the success of all student-athletes are offered.

Foundational Perspectives

The following review provides an examination of the research regard-ing variables and constructs included in SACS: (1) campus climate; (2) student-athlete identity; (3) student-athlete academic success; and (4) student-athlete athletic success.

Campus Climate

Climate is defined as the “current attitudes, behaviors, and standards of employees and students that concern the access for, inclusion of, and level of respect for individual and group needs, abilities, and potential” (Rankin & Reason, 2008, p. 264). Negative campus climates hinder educational attainment and healthy development, whereas students who experience a campus as supportive experience positive learning out-comes (Pascarella & Terenzini, 2005; Reason, Terenzini, & Domingo, 2006).

Hurtado, Milem, Clayton-Pedersen, and Allen (1998) developed a four-dimensional model to examine campus racial climate including: (1) institution’s historical racial/ethnic inclusion/exclusion, (2) structural diversity, (3) psychological climate of perceptions and attitudes, and (4) behavioral climate of campus relations. The Transformational Tapestry Model (TTM) (Rankin, 2003) conceptualizes campus climate as consist-ing of three interrelated factors: (1) students’ experiences with the cam-pus environment, (2) their perceptions of the environment, and (3) their perceptions of institutional actions. These conceptual models illuminate the relevance of both institutional characteristics and individual percep-tions in determining the campus climate.

Student-Athlete Success 703

Research indicates that students experience campus climates differ-ently based upon social group membership (Rankin & Reason, 2005, 2008; Worthington, Navarro, Loewy, & Hart, 2008). Although institu-tions attempt to foster welcoming and inclusive environments, they are not immune to negative societal attitudes and to discriminatory behav-iors (Williams, 2013). Consequently, the campus climate has been described as “racist” for students and employees of color (Harper & Hurtado, 2007; Rankin & Reason, 2005), “chilly” for women (Hart & Fellabaum, 2008), and “hostile” for lesbian, gay, bisexual, and transgen-der community members (Rankin, Weber, Blumenfeld, & Frazer, 2010).

There is a complex relationship between college athletics, student-athletes’ demographics, and campus climate. Recent studies regarding faculty and student perceptions of athletes have shown that campus community members sometimes question athletes’ intellectual abilities, academic motivation, or treatment by the university (Comeaux, 2012). These athlete microaggressions are perpetuated by both faculty and stu-dents and especially occur in the classroom with people perpetuating the dumb jock stereotype: low intelligence, little academic motivation, and recipients of undeserved benefits and privileges (Simons, Bosworth, Fujita, & Jensen, 2007).

In terms of racial and ethnic identity and the campus environment, extensive research exists that suggests that African American student-athletes are aware of how their racial identity evokes negative ste-reotypes from peers and faculty on campus (Melendez, 2008; Singer, 2008). Singer (2005) and Lawrence (2005) discussed manifestations of racism related to leadership and decision-making opportunities for Afri-can American athletes. Martin, Harrison, Stone, and Lawrence (2010) and Oseguera (2010) separately found that African American student-athletes perceive different expectations for Black athletes versus their White peers and that this is exacerbated for student-athletes in revenue versus nonrevenue generating sports. Differential treatment of African American athletes may relate to low graduation and high attrition rates, and necessitates an understanding of broader environmental contexts in higher education (Hawkins, 1999).

Research about women student-athletes has traditionally focused on their athletic ability, body image issues, or sexual identity (Harrison & Secarea, 2010; Knight & Giuliano, 2003). The athletic experience for women is one of isolation, because of their smaller representation, when compared to men (Riemer, Beal, & Schroeder, 2000). Bruening, Arm-strong, and Pastore (2005) examined the intersection of gender and race for African American women and discussed the effect of silencing by media, athletic administrators, coaches, and other student athletes.

There is a dearth of literature examining the experiences of transgen-der student-athletes, with the authors focusing on the difficulties they experience in athletics (Lucas-Carr & Krane, 2012). The only other body of work regarding transgender athletes focuses on athletic policies surrounding their participation (Buzuvis, 2011).

The limited research on sexual identity in intercollegiate athletics suggests that the athletic environment does little to encourage and sup-port nonheterosexual identities. In fact, student-athletes who are open about their sexual identity face higher levels of discrimination (Hekma, 1998). The environment encourages heteronormative subordination of lesbian, gay, and bisexual, or queer (LGBQ) identities. The literature offers that sexual diversity on athletic teams is only tolerated as long as LGBQ student-athletes do not “make it an issue” (Wolf-Wendel, Toma, & Morphew, 2001).

Based on the literature, students’ perceptions of their educational environment play a major role in student success. The literature also indicates that various social identity groups perceive the campus climate differently and their perceptions may adversely affect student outcomes such as learning. Unfortunately, comprehensive research on the expe-riences of student-athletes, an important social identity group on col-lege campuses, is noticeably absent in the climate literature. Existing literature on campus climate for student-athletes does not holistically account for institutional environments or students’ social identities and other institutional characteristics.

Student-Athlete Identity

Student-athletes have two particularly salient identities in the uni-versity setting, academic and athletic (Comeaux & Harrison, 2007). Athletic identity has been defined as the extent to which a person iden-tifies with the role of an athlete (Brewer, van Raalth, & Linder, 1993). One measure of athletic identity posited by Brewer et al. (1993) allows researchers to measure how strongly students perceive their status as an athlete. Student-athletes with higher levels of athletic identity are less likely to understand and to express other parts of their identity. Similarly, the higher the level of athletic identity, the more difficult the student-athletes’ transition to college, the lower their connectedness to the institution, and the less their interaction with students outside their teammates (Lubker & Etzel, 2007).

Settles, Sellers, and Damas Jr. (2002) found that athletic and aca-demic identities cannot be perceived as one identity without student-athletes experiencing conflict. It is suggested that if student-athletes have a high athletic identity, it detracts from their academic roles (Lally

& Kerr, 2005; Yopyk & Prentice, 2005). However, research also sug-gests that student-athletes can have a strong athletic identity that does not necessarily decrease the importance of the student role (Gaston-Gayles, 2005; Harrison & Lawrence, 2004). Kimball (2007) found that student-athletes have a strong sense of identity which helps them bal-ance their lifestyle as athletes in high-profile sports.

Student-Athlete Academic Success

There are unique aspects of the student-athlete collegiate experience that create substantial challenges for their academic success, including athletic culture, extreme time demands, and the often uneasy marriage between athletics and academics. Comeaux and Harrison (2011) con-ceptualized a model for college student-athlete academic success, noting that a variety of factors across precollege characteristics, initial commit-ments, social systems, and commitments influence academic success. Gaston-Gayles (2004) examined academic and athletic motivations among student-athletes and found that their ACT scores, ethnicities, and academic motivation significantly related to academic performance. On a typical week when their sport is in season, 82% of student-ath-letes report spending over 10 hours/week practicing their sport, while 40% report spending over 10 hours/week playing their sport (Potuto & O’Hanlon, 2006). A survey of 21,000 NCAA athletes across all Divi-sions indicated that most athletes spent close to 40 hours/week partici-pating in their sports; major football players reported spending almost 45 hours/week, and most athletes stated they spent more time on their sport than on their academic work (Wolverton, 2007).

Student-athletes’ academic performance in college increases when the institution has a dedicated and supportive faculty and staff (Harrison, Harrison, & Moore, 2002). Umbach, Palmer, Kuh, and Hannah (2006) found that student-athletes across Divisions and institutional types did not differ from their peers on involvement in effective educational prac-tices, such as academic challenge, interaction with faculty, and par-ticipation in active and collaborative learning. However, Simons et al. (2007) indicated that African American student-athletes reported a much higher degree of negative perceptions from faculty than their teammates of different races. Gayles and Hu (2009) suggest that the “influence of student engagement on cognitive outcomes is conditional on the type of sport student athletes participate in, suggesting differential effects for student athletes in different sport types” (p. 329).

Research further suggests that when a student-athlete becomes completely engulfed in his or her athletic role, his/her academic per-formance may be affected (Brewer et al., 1993; Lally & Kerr, 2005).

For example, in a national survey of over 10,000 student-athletes, 20% reported that their athletic participation prohibited them from studying their field of choice (Wolverton, 2007).

Student-Athlete Athletic Success

There is very little research available that examines how individual student-athletes perceive their athletic success. Most of the research focuses on athletic program success and economic issues including alumni giving (Cohen, Whisenant, & Walsh, 2011), tuition rates (Alex-ander & Kern, 2010), and state appropriations (Alexander & Kern, 2010), or on how student-athletes perceive their athletic experience (Potuto & O’Hanlon, 2006).

Dilley-Knoles, Burnett, and Peak (2010) examined the role of aca-demic support programs. They found that women sports teams had sig-nificantly higher grade point averages than their men counterparts but there was no relationship to the athletic success of the teams. Another study conducted by Rishe (2003) suggested that neither the graduation rate for student-athletes nor the graduation rate for all other undergradu-ates is sensitive to the level of a school’s athletic success.

Other research focuses on how coaches assist student-athletes to maximize their success on the playing field through various modali-ties (Hyllegard, Radlo, & Early, 2001), mental skills (Frey, Laguna, & Ravizza, 2003), or psychological factors (Spieler et al., 2007). There are very few studies that examine how student-athletes perceive their ath-letic success. In one example, Catina and Iso-Ahola (2004) determined that positive illusion (how an athlete perceived his abilities) has both direct and indirect effects (through expectation for success) on actual success in competition. However, actual athletic success was measured using only a single item representing the student-athletes’ highest total pounds ever lifted in competition. Additional work is needed on iden-tifying measures of student-athletes’ perceptions of athletic success, in addition to their academic success and athletic identity.

Summary

There is a growing body of literature examining student-athletes and campus climate, with a nascent focus on student-athlete identity, aca-demic success, and athletic success. When examining the literature com-prehensively there are gaps which necessitate a more comprehensive examination of student-athletes. Most of the aforementioned studies uti-lized qualitative inquiries to produce robust narratives about perceptions of discrimination and hostility towards student-athletes. Other scholars have paid attention to athletes’ social identities, with most concentrating on constructs of race/ethnicity and gender. Few studies have examined

the intersections of student-athletes identities, and of those, none have fully captured the complicated relationships between student-athlete outcomes (i.e., identity, academic success, and athletic success). A com-prehensive and intersectional model is needed that wholly examines student-athlete experiences and outcomes while also controlling for student characteristics and institutional environments. SACS creates a framework to examine this holistic understanding of student-athlete suc-cess through the lens of campus climate and with consideration of stu-dents’ inputs and college/university contexts.

Methodology

Conceptual Framework

The conceptual framework for SACS was derived through a review of relevant literature, consultation with student-athletes and coaches, and findings from a pilot study of six institutions. The framework fol-lows Astin’s (1984) Inputs-Environments-Outcomes model and includes characteristics (demographics, student-athlete inputs), climate (faculty-student interaction, institutional actions), and outcomes (academic suc-cess, athletic success, and athletic identity). The top-level elements of the conceptual framework are depicted in Figure 1. Because of the proj-ect’s national scope, data from SACS provide a comprehensive picture

Figure 1. SACS Conceptual Framework

of the student-athlete experience. This framework was used to inform survey construction and subsequent analyses.

Survey Instrument

The 2008 pilot survey was constructed using questions from Rankin’s (2003) Campus Climate Survey as well as from “It takes a team! Survey on Student-Athlete’s Perspectives on Lesbian and Gay Teammates and Coaches” (Griffin, Perrotti, Priest, & Muska, 2002). Based on further review of the literature, consultation with experts in the fields of inter-collegiate athletics and higher education, and analysis of pilot data, the research team further refined the instrument. The final instrument was reviewed by several student-athletes who offered additional revisions to assist in the survey’s readability for student-athletes.

Data Source/Sample

All 1,281 NCAA member institutions were invited to participate in SACS. Participation was solicited via e-mails to each Athletic Direc-tor and Senior Woman Administrator, whose contact information was provided by the NCAA. In addition, each conference commissioner was asked to encourage their respective institutions’ participation.

Each institution’s Athletic Director designated a liaison to work with the SACS research team. The institutional liaison submitted a demographic profile of the institution’s student-athlete population and recruited student-athletes’ participation. The institutional liaison received three separate e-mail templates for recruitment purposes. Other recruitment strategies included encouragement from coaches, academic support center staff, the student-athlete council, and athletic directors.

One hundred sixty-four of the 1,281 NCAA member institutions par-ticipated in the anonymous web-based survey that was distributed in 2010. Of the 56,965 student-athletes at those institutions, 8,481 partici-pated in the project, representing institutions from all NCAA Divisions and all 23 NCAA Championship Sports (Table 1). Ratio estimation (Brick & Kalton, 1996) was used to develop weight adjustments on the characteristics of gender, race, academic class standing, and NCAA Division so as to make the data as representative as possible of the total sample, resulting in a weighted dataset of 8,018. To account for item nonresponse, the dataset was imputed using the maximum likeli-hood estimation-based Expectation-Maximization (EM) data imputation method (Allison, 2003; Garson, 2009; Graham, 2009; Musil, Warner, Yobas, & Jones, 2002). Because the software used to conduct the struc-tural equation modeling (SEM) analysis does not allow sample weights

when using maximum likelihood as the estimator (Muthen & Muthen, 2010), unweighted imputed data were used for the SEM analysis.

Measures

The individual and institutional characteristics included in the analy-sis were gender identity, race (collapsed to Student-Athlete of Color or White), sexual identity (collapsed to LGBQ or Heterosexual), participa-tion in a “featured” or “non-featured sport,” and the institution’s NCAA Division (I—FBS, I—FCS, I—non-football, II, and III). All variables were dichotomous.

TABLE 1NCAA Aggregate Student-Athlete Population and Sample Respondents

Population1 Sample2 Response Rate

Characteristic Subgroup N % N % %

Gendera Man 32,014 56.2 3,138 37.0 9.8

Woman 24,951 43.8 5,336 62.9 21.4

Transgender — — 7 0.1 —

Race/Ethnicityb,3 American Indian/Alaskan Native 357 0.6 117 1.4 32.8

Asian/Pacific Islander 1,361 2.4 237 2.8 17.4

Black, non-Hispanic 7,695 13.6 642 7.6 8.3

Hispanic 2,733 4.8 389 4.6 14.2

White, non-Hispanic 44,516 78.6 7,446 87.8 16.7

Unknown 2,677 — — — —

Class Standingc First Year 18,423 32.4 2,621 30.9 14.2

Second Year 14,470 24.6 2,088 24.6 14.4

Third Year 11,958 21.1 2,033 24.0 17.0

Fourth + Year 11,931 21.0 1,739 20.5 14.6

Unknown 2,590 — — — —

Divisiond Division I - FBS 13,104 22.1 1,703 20.1 13.0

Division I - FCS 13,537 22.8 1,926 22.7 14.2

Division I - non-football 5,080 8.6 985 11.6 19.4

Division II 10,939 18.4 1,421 16.8 13.0

Division III 16,680 28.1 2,451 28.9 14.7

Note. Percentages may not sum to 100% due to rounding.1 Population refers to the population of student-athletes at participating institutions.2 Sample was collected during the spring of 2010.3 Respondents were instructed to indicate all racial/ethnic categories that apply.a χ2 (1, N = 8,474) = 1,245, p < 0.001 (Transgender respondents not included.)b χ2 (4, N = 8,481) = 1,686, p < 0.001(Unknown respondents not included.)c χ2 (3, N = 8,481) = 38, p < 0.001 (Unknown respondents not included.)d χ2 (4, N = 8,481) =123, p < 0.001.

Climate was measured by seven factors that gauge student-athletes’ (a) perceptions of respect, (b) perceptions of climate, (c) personal com-fort with teammate diversity, (d) interactions with faculty members, (e) interactions with athletic personnel, (f) sense of diversity leadership from athletic personnel related to diversity, and (g) perceived extent to which the athletic department addresses discrimination.

The three student outcomes were based on the following scales. Aca-demic Success was measured using Pascarella and Terenzini’s (1980) Academic and Intellectual Development subscale of their Institutional Integration Scale, which focuses on students’ academic development due to their collegiate experiences. The Institutional Integration Scale or its subscales have been used in a variety of studies examining under-graduate student persistence (Berger, 1997; Pascarella, 1985; Pascarella & Chapman, 1983). No single scale has been developed to measure student-athletes’ Athletic Success, so the research team members used their experience in athletic participation, coaching, and administration to develop a scale based on “maximizing one’s athletic potential.” Ath-letic identity was measured using the Athletic Identity Measurement Scale (AIMS), developed by Brewer and colleagues (1993). The valid-ity of this scale was examined in studies that explored the correlation of AIMS with the Marlow-Crowne Social Desirability Scale (Crowne & Marlowe, 1960), Fox’s (1987) Perceived Importance Profile, Fox and Corbin’s (1986) Physical Self-Perception Profile, Curry and Weiss’ (1989) Self-Role Scale, Gill and Deeter’s (1988) Sport Orientation Questionnaire, and the Rosenberg (1965) Self-Esteem Scale.

The research team employed two phases of scale development to construct the scales used to measure climate and student outcomes: (1) exploratory factor analysis (EFA) of the constructs under investiga-tion (DeVellis, 2003), and (2) SEM based confirmatory factor analysis (CFA) (Kline, 2011). The EFA was used to explore the latent theoretical constructs indicated by the items in each of the ten scales. The CFA was used to confirm the factor structure and to provide accurate factor scores to be used in the SEM analysis. Each climate and outcome factor was analyzed separately in the CFA. See Table 2 for CFA results including fit statistics. A full description of the scale development process, a list-ing of all of the items that compose each of the seven climate and three outcome scales, and initial validity evidence for the use of scales for research purposes are detailed in Merson and Rankin (2010), Merson, Sorgen, and Rankin (2011), and Rankin et al. (2011).

Reliability and Validity. Goodness-of-fit statistics are reported for each CFA as well as the path models. Based on recommendations from Hu

and Bentler (1999) four indexes are provided (chi-square, root mean square error of approximation [RMSEA], comparative fit index [CFI], and standardized root mean residual [SRMR]). The chi-square was sig-nificant for each of the factors in the CFA, although the other fit statis-tics indicated the model accurately fit the data. Researchers recognize that the chi-square test may be unsatisfactory due to its sensitivity to large sample size (Thompson & Daniel, 1996). As a result, Hu and Bentler (1999) recommend using multiple indexes to asses goodness-of-fit and suggest the following thresholds: RMSEA < 0.06, CFI > 0.95, and SRMR < 0.08. Acceptable values for indexes are bolded in Table 2.

The joint standards regarding validity for educational and psycho-logical testing (American Educational Research Association, Ameri-can Psychological Association, & National Council on Measurement in Education, 2014) suggest providing evidence for the appropriateness of the scores obtained from a scale or instrument for a particular pur-pose. The evidence can be provided in one or more of the following five areas: test content, response processes, internal structure, relations to other variables, and potential consequences. For the SACS project, a team of educational and athletic experts identified the content of each scale, based on the academic literature, previous research, and their professional experience. As mentioned above, the Athletic Identity and Academic and Intellectual Development scales have been extensively

TABLE 2Confirmatory Factor Analysis Model Fit Indices for Latent Variables Scale (# of items) Variance RMSEA CFI SRMR Chi Square DF

Student-Athlete Outcomes

Academic Success (8) .897 .047 .998 .024 334.805*** 17

Athletic Identity (10) .741 .082 .979 .041 1,583.563*** 7

Athletic Success (4) .827 .056 .876 .033 83.575*** 3

Measures of Climate

Perceptions of Climate (12) .770 .091 .960 .043 41,4666.971*** 586

Perceptions of Respect (10) .933 .071 .986 .045 15,190.510*** 345

Personal Comfort with Team Diversity (5) .970 .072 1.00 .002 88.852*** 2

Faculty Student Interaction (6) .897 .050 .999 .007 134.983*** 6

Athletic Personnel Interaction (5) .462 .030 .999 .046 25.657*** 3

Diversity Leadership from Athletic Personnel (6) .826 .055 .997 .017 3,504.750*** 113

Athletic Department Addresses Discrimination (11) .903 .055 .997 .017 3,504.750*** 113

***p < .001.

examined by other researchers. A pilot study was conducted to exam-ine the response processes, establish initial information about the scales, and examine their relationships with other variables. The information provided above about the EFA and CFA pertains to the internal structure of the instrument. In addition, the authors have detailed this and other initial validity evidence for some of our scales in prior papers (Merson & Rankin, 2010; Merson, Sorgen, & Rankin, 2011; Rankin et al., 2011).

Analysis

SEM analysis was used to determine the unique effect of each demo-graphic characteristic on the student outcomes, as mediated by each of the seven measures of campus climate (Kline, 2011).

The authors created factor scores from the CFA procedures, provid-ing continuous metrics for estimating the path models (Kline, 2011; Rankin et al., 2011). Estimated using diagonally weighted least squares these are deviation scores with a mean of zero and a standard deviation of one. Participants are assigned a value based on how their responses deviate from the average. When computing the factor scores, the speci-fied factor structure and error correlations are considered, increasing the precision of CFA factor scores. These factor scores were saved and then used as continuous variables for the path model.

Because the factor scale scores are continuous and normally distrib-uted, maximum likelihood was selected as the estimation method for the path model (Kline, 2011). The residual variances of endogenous vari-ables were permitted to correlate based on theory and information from the modification indices. All exogenous variables in the path model were correlated with each other. Based on the literature we believed that the demographics were not independent from one another, so we included them as latent variables rather than treating them as covariates and testing demographic groups (Kline, 2011). Path models were esti-mated, tested, and modified as appropriate.

Mediation and Indirect Effects. Mediation examines how predictor variables affect the outcome when traveling through intervening vari-ables (Baron & Kenny, 1986). In simple mediator models, an indirect effect is the product of the two direct regression coefficients on either side of the mediating variable (Baron & Kenny, 1986). In SEM, it is more complex because all paths in the model are being tested simultane-ously. However, that same basic procedure is used in SEM to represent the ability of the mediator to account for the effects of the predictor on the outcome conditional on the inclusion of all other mediators in the model (Preacher & Hayes, 2008). The total indirect effect is the sum of all of the specific indirect effects.

Two models were constructed to compare the mediation effects of climate. Our general approach was more of exploration than of model testing. Therefore, we chose a model generating approach to develop-ing the path model such that it met the three commonly used criteria of making theoretical sense, being reasonably parsimonious, and cor-responding acceptably close to the data (Jöreskog, 1993; Kline, 2011). We used a nested approach to model specification, utilizing sequential chi-square difference tests (Anderson & Gerbing, 1988). We included all possible regression paths and correlations based on the initial con-ceptual framework. Iteratively, we removed the most insignificant path or correlation and re-ran the model until all remaining correlations and regression coefficients were statistically significant at p < 0.001. We chose the more rigorous significance level of 0.001 to provide more confidence that the results were not simply due to the large sample size. The mediation model required 72 iterations. The second model included the mediation model as well as all possible direct effects. Fourteen itera-tions were needed to create the model with direct effects.

The model shown in Figure 3 is considered the nested or mediator model in this analysis. The results of the fit indices indicate adequate model fit. Due to the large sample size and the degrees of freedom, the chi-square was statistically significant (χ2

(86) = 620.761, p < 0.001). However, the other three fit indices show that this model fit the data well. The RMSEA was 0.027, the CFI was 0.097, and the SRMR was 0.021. Indirect effects were also calculated and reported to the left side of the exogenous variables in the figure. A second model was created to test the direct effects of the exogenous variables to the outcomes (Figure 2). When studying indirect effects, not estimating the direct effects may potentially bias other path coefficients in a way that spuri-ously inflates estimates of indirect effects (Preacher & Hayes, 2008). Therefore, the coefficients of the indirect effects are reported from the non-nested model. Figure 2 highlights the direct effects, but can be interpreted as being superimposed on the mediation model (Figure 3). We chose to use two separate figures to help distinguish the influence of climate, but conceptually they are not mutually exclusive. Figure 2 also includes total effects, or the combination of direct and indirect effects, denoted by TE on the regression lines. The model-fit statistics suggest an acceptable fit, validating our specifications of these causal relationships. Again, because of the large sample size and the degrees of freedom, the chi-square was statistically significant (χ2

(79) = 209.938, p < 0.001). However, the other three fit indices show good model fit (RMSEA = 0.014, CFI = 0.094, and SRMR = 0.012). Since paths and correlations in the models are tested simultaneously, the results indicate

Figure 2. Direct (γ), Relevant Total Indirect (Left Column), and Total Effects (TE) of Individual and Institutional Characteristics on Student-Athlete Outcomes

Figure 3. Significant Paths Indicating How Climate Influences Student-Athlete Outcomes

that the influences of all other variables are controlled. In other words, the coefficients are reported holding all other variables constant. Sig-nificant path coefficients, total indirect effects, and total effects are pre-sented in Tables 3 and 4.

Limitations

A limitation of this study is the relatively poor measurement of ath-letic success. No scale previously existed to measure student-athletes’ athletic success. The research team consulted athletic and NCAA administrators and chose to focus on maximizing athletic potential as a proxy for athletic success. The EFA produced one factor representing two of the four original survey items with low internal consistency reli-ability (α = 0.42). However, the CFA indicated that the construct, with one item fixed to zero, explained 82.7% of the variance in the four items and two of four fit statistics indicated good model fit, so we decided to include the four-item measure in the SEM path analysis (Merson et al., 2011). We recommend that future research build on this first step in measuring student-athletes’ athletic success.

In addition, this construct is based on student-athletes’ perspectives. However, coaches may have a different definition of athletic success. Further research could examine how student-athletes’ and coaches’ defi-nitions of athletic success differ, and how the former may influence the latter.

Although the authors recognize the vastly different experiences of people of various racial identities (e.g., Chicano versus African Ameri-can or Latino(a) versus Asian American), and those experiences within these identity categories, we collapsed these categories into Student-Athletes of Color and White, non-Hispanic for many of the analyses due to the small numbers in individual categories.

Results

Sample Characteristics

The 8,018 respondents represent every geographic region of the United States, each of the five NCAA Divisions, all 23 NCAA sports, and all class-standings. Twenty-seven percent of the respondents (n = 2,149) participated in featured sports at their respective institutions. Forty-three percent (n = 3,480) were women and 4,531 (57%) were men. Seven respondents identified as Transgender. Student-Athletes of Color comprise 24% (n = 1,945) of the sample while White, non-His-panic student-athletes comprise 76% (n = 6,073). Ninety-five percent

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(n = 7,625) of the respondents were Heterosexual while 5% (n = 394) identified as Lesbian, Gay, Bisexual, or Questioning (LGBQ).

The Influence of Climate on Educational and Sport-Related Outcomes (Figure 3 and Table 4)

Of the seven climate variables tested, two had an influence on all three outcomes: (1) faculty-student interaction and (2) interactions with athletic personnel. However, interactions with faculty and interactions with athletic personnel did not always work in concert. Although both have a positive influence on student-athletes’ academic success (β8,4 = 0.363, and β8,5 = 0.152, respectively) and athletic success (β9,4 = 0.047, and β9,5 = 0.087, respectively), student-athletes who interacted with fac-ulty tended to report lower levels of athletic identity (β10,4 = –0.072) while those who interacted with athletic personnel reported higher lev-els of athletic identity (β10,5 = 0.087).

Five aspects of climate in total had a positive influence on student-athletes’ academic success: faculty-student interaction (β8,4 = 0.363), athletic personnel interaction (β8,5 = 0.152), perceptions of climate (β8,2 = 0.133), perceptions of respect (β8,1 = 0.039), and personal comfort with teammate diversity (β8,3 = 0.077). Of the 11 different significant rela-tionships depicted in the model, the strongest relationship is between faculty-student interaction and academic success, as indicated by the largest coefficient of 0.363. Only two aspects of climate had an influ-ence on student-athletes’ athletic success, the aforementioned athletic personnel interaction (β9,5 = 0.087) and faculty-student interaction (β9,4 = 0.047).

Four aspects of climate had an impact on student-athletes’ athletic identity. The largest influence was the extent to which student-athletes perceived that the athletic department addressed discrimination (β10,7 = 0.150). Interactions with athletic personnel also had a positive influence (β10,5 = 0.087). The more comfortable they were with teammate diver-sity, the less student-athletes’ identified with being an athlete, as indi-cated by the negative coefficient of –0.075. Similarly, student-athletes who interacted more with faculty were less likely to have a strong ath-letic identity (β10,4 = –0.072).

Findings Across Selected Constituent Groups (Tables 3 and 4). Differ-ences based on individual characteristics highlight the complexity of climate and the need to consider a range of student-athletes’ experiences and perspectives. Although some aspects of climate are salient for all student-athletes, some aspects of climate are more salient than others when considered across a range of demographic and institutional char-acteristics. The following results are based on the SEM analysis of the

direct, indirect, and total effects of individual and institutional charac-teristics on the three outcomes (Figure 2), as well as the details of the mediating effects of climate on the outcomes (Figure 3). Because the factor scores are standardized, all effects are in terms of standard devia-tion change from the average due to possessing the individual or institu-tional characteristic of interest.

Racial Identity. Student-Athletes of Color tended to report lower lev-els of academic success relative to their White student-athlete peers (γ8,1 = –0.144). However, there were no differences in regard to athletic suc-cess or athletic identity. Student-Athletes of Color reported more nega-tive perceptions of respect (γ1,1 = –0.105) and more negative perceptions of climate (γ2,1 = –0.077). In turn, for Student-Athletes of Color, the mediation effect of perceptions of respect and perceptions of climate had an additional negative indirect influence on their academic success (total indirect effect = –0.014). The total direct and indirect effect of being a Student-Athlete of Color was a reduction of academic success scores of approximately 0.16 standard deviations from the average.

Gender Identity. Women student-athletes reported greater levels of academic and athletic success (γ8,2 = 0.082 and γ9,2 = 0.155, respec-tively) and lower levels of athletic identity (γ10,2 = –0.148) compared to men student-athletes. Women also reported greater perceptions of cli-mate (γ2,2 = 0.212), perceptions of respect (γ1,2 = 0.210), faculty-student interaction (γ4,2 = 0.072), and personal comfort with teammate diversity (γ3,2 = 0.217). In combination, these four climate factors have the larg-est positive indirect influence on academic success found in the model (total indirect effect = 0.079). The mediating effect of climate also posi-tively affected their athletic success and negatively affected their ath-letic identity (total indirect effects of 0.003 and –0.021, respectively). The combination of direct and indirect effects result in total effects for academic success, athletic success, and athletic identity of 0.161, 0.158, and –0.169, respectively, meaning that the total effect of being a woman student-athlete is approximately 0.16 to 0.17 standard deviation change in each of the outcomes.

Sexual Identity. As suggested by the lack of direct effects of being LGBQ on the outcomes, sexual identity alone is not a significant predic-tor of academic success, athletic success, or athletic identity. However, LGBQ student-athletes experienced a more negative climate than their Heterosexual peers, which adversely influenced their athletic identities and academic success. They reported lower scores on four climate vari-ables: perceptions of climate (γ2,3 = –0.211), perceptions of respect (γ1,3 = –0.155), athletic department addresses discrimination (γ7, 3 = –0.247), and diversity leadership from athletic personnel (γ6,3 = –0.182).

TABLE 4Direct, Indirect, and Total Effects of Exogenous Demographic Variables and Endogenous Climate Factors on Student–Athlete Outcome Factors

Academic success Athletic success Athletic identity

Exogenous and endogenous predictors Unst. Coeff. Unst. Coeff. Unst. Coeff.

Perceptions of respect 0.039** — —

Perceptions of climate 0.133*** — —

Personal comfort with teammate diversity 0.077*** — –0.075*

Faculty-student interaction 0.363*** 0.047*** –0.072***

Athletic personnel interaction 0.152 0.087*** 0.087***

Diversity leadership from athletic personnel — — —

Athletic department addresses discrimination — — 0.150***

People of Color

Direct –0.144*** — —

Total indirect –0.014*** — —

Total –0.158 — —

Direct 0.082*** 0.155*** –0.148***

Total indirect 0.079*** 0.003** –0.021***

Total 0.161 0.158 –0.169

Direct — — —

Total indirect –0.034*** — –0.037***

Total –0.034 — –0.037

Division I

Direct — — —

Total indirect 0.007* 0.006*** —

Total 0.007 0.006 —

Division II

Direct — — —

Total indirect 0.048*** 0.006*** –0.009***

Total 0.048 0.006 –0.009

Division III

Direct — — –0.132***

Total indirect 0.054*** 0.007*** –0.011***

Total 0.054 0.007 –0.143

Featured sport

Direct — –0.113*** 0.081***

Total indirect 0.017*** 0.010*** 0.010***Total 0.017 –0.103 0.091

Notes. Unst. Coeff. = the unstandardized path coefficient. All climate and outcome factors are standardized factor scores.— Only statistically significant path coefficients are reported.Total effect is the sum of direct effect and total indirect effects.*p < .05. **p < .01. ***p < .001.

Compared to all other subgroups, climate’s influence on athletic iden-tity was most profound for LGBQ student-athletes, as indicated by the largest total indirect effect on athletic identity of –0.037. Athletic iden-tity was lower for LGBQ student-athletes as a result of their lesser ten-dency to report that the athletic department addresses discrimination. Climate had an almost equally negative influence on their academic suc-cess (total indirect effect = –0.034) due to their lower perceptions of respect and of climate.

NCAA Division. Without consideration given to climate, Division III student-athletes had a less salient athletic identity than their Divi-sion I and Division II peers (γ10,4 = –0.132). Differences between the outcomes emerge when climate is taken into consideration. Division I student-athletes reported greater levels of personal comfort with team-mate diversity (γ3,6 = 0.066) and athletic personnel interaction (γ5,6 = 0.067) than Division II and III student-athletes. However, they tended to have less positive perceptions of climate (γ2,6 = –0.060). The largest indirect effects on the outcomes related to climate were due to student-athletes’ in Division II and III having higher faculty-student interaction (γ4,5 = 0.132 and γ4,4 = 0.148, respectively), which resulted in higher aca-demic success (total indirect effects of 0.048 and 0.054, respectively). The total effect of being in Division III on athletic identity was –0.143.

Featured and Non-Featured Sports. Student-athletes who competed in featured sports reported a greater sense of athletic identity (γ10,7 = 0.081), but a lower sense of athletic success (γ9,7 = –0.113) than student-athletes in non-featured sports. There was no significant difference in regard to academic success. Interaction with athletic personnel was the only aspect of climate that mediated the effect of type of sport on the outcomes. Featured sport student-athletes’ have greater levels of inter-action with athletic personnel (γ5,7 = 0.111), which in turn, yields greater levels of academic success (β8,5 = 0.152), athletic success (β9,5 = 0.087), and athletic identity (β10,5 = 0.087). Playing in a featured sport had total direct and indirect effects on the three outcomes of academic success (0.017), athletic success (–0.103), and athletic identity (0.091).

Discussion

Our analyses suggests that, consistently, Women, White, and Hetero-sexual student-athletes, as well as those in Divisions II and III, report higher levels of academic success than their counterparts. Women student-athletes and those in non-featured sports show higher levels of athletic success. Finally, Men student-athletes and those in featured sports have higher levels of athletic identity. These results are consistent

with previous research. Research in higher education often illustrates the impact of individual and institutional characteristics on student out-comes. We found the largest magnitudes of total effect sizes to be about 0.10 to 0.17 standard deviations from the average for gender, race/eth-nicity, being in Division III, and playing in a featured sport.

In addition, it is clear that climate matters. Six of the seven climate scales influenced the outcomes, and differences in outcomes based on sexual identity, Division, and featured sport participation appeared to or became more salient when climate was taken into account. These differ-ences would have been overlooked if climate had not been examined. Positive aspects of climate led to increases in student-athlete outcomes in every relationship, with the exception of the influences on athletic identity of both personal comfort with team diversity and faculty- student interaction. The strongest impact was the influence of student-athletes’ interactions with faculty members on their academic success supporting the work of Comeaux and Harrison (2011) and Harrison et al. (2002).

The Importance of Interacting

The strongest relationship in the model was between faculty-student interaction and academic success, suggesting that if there is concern for student-athletes’ academics, interactions with faculty members may yield the largest “pay-off.” Similarly, the effect of interactions with ath-letic personnel on academic success is the second strongest relationship in the model. The profound influence of faculty interaction on student-athletes’ outcomes is of little surprise. A large body of research suggests that faculty-student interaction shapes the way students are socialized to the university and not only influences students’ academic achievement, satisfaction with college, persistence, and attrition, but also shapes their educational and career aspirations (Lamport, 1993; Pascarella & Terenzini, 1980, 2005; Tinto, 1993). However, interactions alone do not guarantee successful learning and development. Rather, the qual-ity of these interactions matters (Lamport, 1993; Pascarella & Teren-zini, 2005). Furthermore, the context in which these interactions occur may also influence their dynamics. Research suggests that the quality of faculty-student interactions may be contingent on faculty members’ interpersonal characteristics and that these interactions simultaneously shape and are shaped by the classroom atmosphere (Kuh & Hu, 2001; Pascarella & Terenzini, 2005; Sax, Bryant, & Harper, 2005). To further complicate matters, student-athletes may also have to overcome what they see as a negative stigma. For example, in one study, a third of

student-athletes said they were perceived negatively by faculty while only 15% reported that they were perceived positively (Simons et al., 2007).

Given this context and combined with the unique demands faced by student-athletes, it is also of little surprise—and is perhaps encour-aging—that interactions with athletic personnel also appear to pro-mote student-athletes’ academic success, as well as athletic success and athletic identity. The scale, Athletic Personnel Interaction, asked respondents about the quality of their relationships with athletic administrator(s), the athletic team academic advisor, their head coach, the assistant coach(s), and athletic trainer(s) or medical staff. Positive relationships with people who may be uniquely poised to understand the stresses experienced by student-athletes appear to yield positive results. Broughton and Neyer (2001) explained that academic advising of student- athletes has traditionally focused on “maintaining academic eligibility and graduation rates rather than on enhancing the academic, personal, and athletic development of the student athlete” (p. 48). In this regard, our findings are indeed encouraging. These interactions not only contribute to the academic success of student-athletes (a measure that extends the notion of academic success beyond GPA, Academic Prog-ress Rate (APR), or graduation rates), but also to their athletic success and athletic identity.

The primary takeaways from these results are encouraging because they are actionable. Athletic departments can promote the interaction of athletic personnel with student-athletes for academic in addition to athletic purposes. Student-athletes can be encouraged to interact with faculty members beyond Faculty Athletic Representatives (FARs) and faculty team advisors, such as their own professors. It may be especially helpful if those faculty members have positive perceptions of intercolle-giate athletes. Athletic departments can make new connections (perhaps through recommendations from FARs and faculty team advisors) with other faculty members who may be good resources for student-athletes, even if they are not taking their classes. All students, not only student-athletes, should be encouraged to discuss career plans or graduate work with faculty members. These may seem to be Division I centric rec-ommendations because often student-athletes naturally have more con-tact with faculty coaches in Division II and III, but these results exist after controlling for Division, so the influence of interactions with fac-ulty members and athletic personnel can be leveraged to improve out-comes for student-athletes in every Division. In addition, our results indicate that, regardless of Division, student-athletes in featured sports have more interaction with athletic personnel than those in non-featured

sports. The positive effect of athletic personnel interaction on all three outcomes provides motivation for athletic departments to re-examine the traditional inequalities between featured and non-featured sports.

Climate Change

Campus climate has a substantial impact on student-athletes’ aca-demic and athletic outcomes, impacts that would not have been evident if we had examined demographic characteristics alone. This is a power-ful finding because how student-athletes experience and perceive their climate can be influenced by university administrators. The following are general suggestions of how athletic personnel can modify the cli-mate in athletics to be more positive for both student-athletes of dif-ference and those who are members of the majority. A more detailed review of recommended initiatives may be found in the full SACS report (Rankin et al., 2011).

• Use inclusive language: Encourage athletic personnel and student-athletes to value the voices of those within their campus communities and use language that reflects their unique experiences.

• Respond to the use of derogatory language: Athletic personnel should have the tools to respond quickly to the use of derogatory language aimed at student-athletes.

• Visible and supportive presence of athletic personnel at institutional events: Demonstrates that the athletic department is knowledgeable of the issues/concerns facing their student-athletes.

• Develop inclusive policies: Demonstrates a commitment by the ath-letic department to providing an inclusive and supportive environ-ment.

• Increase awareness of issues and concerns facing student-athletes: Provide the opportunity for athletic community members to question and examine unfounded attitudes and beliefs. Acknowledging the contributions of diverse athletes/coaches in the sports arena is impor-tant to fully integrate their experiences into the athletic community.

• Respond appropriately to identity/diversity-based incidents/bias. Of-fering and consistently following clear procedures for reporting and responding to incidents of bias helps to create a climate that refuses to accept intolerance.

Future Research

The results indicate that experiences and perceptions of climate affect student-athletes’ academic success, athletic success, and athletic

identity. Given that the results suggest that some aspects of climate are more salient than others when considered across a range of demo-graphic and institutional characteristics, specifics of the experiences of student-athletes with these identities must be examined in detailed follow-up analyses. Further, given the literature indicating that multiple intersecting identities are important when considering student success in higher education (Abes & Kasch, 2007; Jones, 2009; Perez & Ceja, 2010), examining identity dimensions in isolation paints an incomplete picture of student-athletes’ experiences. Future research should examine the influence of climate on the success of student-athletes with multiple identities.

In the current project, a cross-sectional and anonymous study was used in order to obtain as many responses from student-athletes as pos-sible, especially from those who may have been reluctant to share their stories due to their identities. A longitudinal study of the effect of insti-tutionalized climate change initiatives on the experiences of student-athletes would provide valuable information to researchers and athletics departments. A positive campus climate requires ongoing care and con-tinuous improvement in the form of periodic assessment, along with visible and meaningful support for the people and resources that foster student-athletes’ positive collegiate experiences.

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Rankin, S. R., Merson, D., Garvey, J. C., Sorgen, C. H., Menon, I., Loya, K., & Oseguera, L....

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