Authors:
Urska Dobersek & Denise L. Arellano

Corresponding Author:
Urska Dobersek, Ph.D.
Department of Psychology
University of Southern Indiana
8600 University Blvd.
Evansville, IN 47712
Phone: (337) 853-7237
Email: [email protected]

Biography:
Urska Dobersek is an Assistant Professor in the Psychology Department at University of Southern Indiana. Denise L. Arellano is an Instructional Designer at the University of Dallas.
 
Investigating the Relationship between Emotional Intelligence, Involvement in Collegiate Sport, and Academic Performance
 
ABSTRACT
The purpose of this study was to investigate the relationship between student-athletes and non-athletes on emotional intelligence (EI), and whether or not the involvement in collegiate sports moderates the relationship between EI and academic achievement as measured by the grade point average (GPA). An independent-samples t-test revealed that non-athletes were more empathetic than student-athletes; no other dimensions of EI (i.e., utilization of feelings, handling relationships, self-control) were significant. A hierarchical regression analysis suggested no moderation effects as evidenced by the interaction term explaining an additional 1.9% of the total variance. After removing the interaction terms, the model indicated a positive relationship between empathy, self-confidence, and academic performance. Additionally, student-athletes demonstrated a higher GPA compared to non-athletes. Some findings of the current study are incongruent with the previous research suggesting the need for the further research on EI.

Keywords: emotional intelligence, academic performance, college sports 

INTRODUCTION
In the past two decades, the concept of emotional intelligence (EI) has gained a great deal of attention and popularity among different disciplines. This might be due to its potential contribution to daily functioning, health, and well-being of the individual and society at large (Bar-On & Parker, 2000). As a result, the EI construct has become widely researched and applied in many fields, including psychology (Mayer, Roberts, & Barsade, 2008), sports (Crombie, Lombard & Noakes, 2011), business (Ashkanasy & Humphrey, 2011), education (Song et al., 2010), health (Martins, Ramalho, & Morin, 2010), and medicine (Arora et al., 2010). Numerous practitioners are using EI as a tool for hiring, training (Fineman, 2004), leadership development (Mintz & Stoller, 2014), and team building (see Stein & Book, 2006 for an example).

Initial attempts on EI have been atheoretical in nature. However, recent efforts resulted in numerous approaches, models, and theoretical explanations of the EI, which lead to a plethora of definitions and, perhaps ironically, provide little consensus on conceptualization and operationalization of EI. Currently, two schools of thought are available: (a) an ability model and (b) a trait model of EI. The ability model (Salovey & Mayer, 1990) suggested that EI includes an array of capabilities and skills to successfully recognize, express, articulate, understand, reason with, and regulate one’s and others’ emotions (Mayer & Salovey, 1997). The trait model (Bar-On, 2006; Goleman, 1998; Petrides & Furnham, 2003) conceptualized EI as a constellation of personality traits to assist individuals in dealing with the environmental demands. The lack of consensus allowed for proliferation of different instruments to measure this newly developed concept, making it challenging to judge EI’s impact, value, reliability, and trustworthiness (Martins et al., 2010).

The theoretical framework of the current study is based on Salovey and Mayer’s (1990) ability model suggesting that EI is “the subset of social intelligence that involves the ability to monitor one’s own and others’ feelings and emotions, to discriminate among them and to use this information to guide one’s thinking and actions” (p. 189). In their model, they proposed the following interrelated branches of EI: a) perceiving emotions, which is the ability to identify and discriminate emotions in others and oneself; b) reasoning emotions is the ability to appropriately use emotions to direct/redirect attention to important events, to produce emotions in order to aid decision making and problem solving; c) understanding emotions is the ability to interpret meanings of emotions, to understand complex feelings, and their transitions from one stage to another and; d) managing emotions, which is the ability to regulate emotions in others and oneself. These branches are hierarchically arranged from the basic levels of mental processes (i.e., perceiving emotions) to more complex and integrated processes (i.e., reflective regulation of emotion; Mayer et al., 2008). The higher emotional abilities suggest more effective coping mechanisms under given circumstances, which in turn might lead to increased performance.

Researchers within the field of sport and exercise psychology have evaluated the effectiveness of mental skills in improving one’s performance. Skills such as relaxation, imagery, mindfulness, energy control, reframing, goal setting, and cohesion have all been found to play an important role in athletes’ performance across a variety of individual and team sports (Crust & Azadi, 2010; Hatzigeorgiadis, Zourbanos, Galanis, & Theodorakis, 2011). Many of these skills tend to correspond with the components of EI (Zizzi, Deaner, & Hirschhorn, 2003). For instance, athletes can manage negative emotions by controlling their thoughts through reframing or replacing negative thoughts/self-talk with the positive thoughts/self-talk. Consequently, positive changes in emotions should be expected.

Athletes also need to be able to recognize their own optimal performance states especially under stressful and pressure situations. In order to achieve their individual zone of functioning, they need to develop skills to manage their emotions and control their energy levels (Hanin, 1995). Like EI, energy control involves recognizing and managing emotions to guide one’s thinking and actions for optimal performance (Mayer & Salovey, 1997). Finally, team sports – especially in interactive sports – demand players in a group to communicate, collaborate, and work as a unit towards common goals. As such, it is important to be mindful and aware of the other players’ thoughts and emotions in order to react appropriately to a given situation (Abraham, 1999). Given the potential similarities between EI and mental skills, one might expect that EI is related to sports and its involvement.

Based on the recent systematic review on EI in the sport and physical activity context, most studies, 33 out of 36, conceptualize EI as a trait – rather than ability (Laborde, Dosseville, & Allen, 2015). Nevertheless, mental skills in the sport context can be taught to improve athletes’ performance (MacNamara, Button, & Collins, 2010). In the same manner, EI is malleable and able to develop with practice and experiences (Mayer et al., 2008). Therefore, it could be speculated that athletes would have higher EI, be more adaptable, and better able to meet the task demands compared to their non-athletic counterparts. In the following sections, we provide empirical findings related to the scope of the present research study.

Difference between Athletes and Non-Athletes on Emotional Intelligence
Examining differences between athletes and non-athletes on various (personality) characteristics has been of interest to numerous researchers ever since the birth of sport psychology. Many scholars have found contradictory evidence – some studies show that athletes are more extraverted, mentally tougher, emotionally stable, energetic, conscientious, and open to new experiences compared to non-athletes (Kajtna, Tušak, Barić, & Burnik, 2004; Malinauskas, Dumciene, Mamkus, & Venckunas, 2014). Other studies, have found no differences in extraversion (McKelvie, Lemieux, & Stout, 2003; Vealey, 2002) and other personality traits distinguishing athletes from non-athletes as measured by Cattell’s personality inventory (Schurr, Ashley, & Joy, 1977).

The findings on personality characteristics are equivocal, which is also reflected in empirical evidence on EI between athletes and non-athletes. Using a Bar-On Emotion Quotient Inventory, athletes scored higher on problem-solving, happiness, optimism, self-assertiveness, flexibility, self-regard (Pasand, Mohammadi, Soltani, & Bazgir, 2014), depression, stress tolerance, mental health (Bostani & Saiiari, 2011), independence, self-actualization, emotional self-awareness, interpersonal relationship, optimism, impulse control, and empathy subscales (Zamanian, Haghighi, Forouzandeh, Sedighi, & Salehian, 2011). Additionally, Sohrabi, Garajeh, and Mohammadi (2011) found that female athletes scored higher on liveliness whereas female non-athletes scored higher on self-regard subcomponent of EI. The mean score for female athletes was higher than female non-athletes on problem solving, stress endurance, self-flourishing, emotional-consciousness, realism, optimism, intimacy, liveliness, self-regard, and courage subscales. On the other hand, non-athletes scored higher than athletes on independence, inter-personal relationship, shock control, flexibility, social responsibility subscales, and total EI score (Sohrabi et al., 2011). These inconsistent findings call for further research of EI between athletes and non-athletes.

Emotional Intelligence, Academic Performance, and Sport Involvement
There has been a growing interest in the role of emotions in academic performance (Linnenbrink-Garcia & Pekrun, 2011). Emotions play an important role in student academic achievement and have a considerable impact on students’ overall academic success (Pekrun, Elliot, & Maier, 2009). Positive experiences such as enjoyment, hope, and pride lead to increased academic performance (Pekrun et al., 2004), whereas hopelessness, boredom, and anxiety lead to decreased GPA (Pekrun, Goetz, Daniels, Stupinsky, & Perry, 2010). EI maintains a positive association with academic success and performance from high school to medical school students (Abe, 2011; Burkiewicz, 2014), as well as the academic commitment (Petrides, Frederickson, & Furnham, 2004). However, some researchers found that EI did not have predictive value beyond cognitive ability and personality (Brannick, Grichanik, Nazian, Wahi, & Goldin, 2013).

The link between EI and academic performance is yet to be investigated further in the view of some null findings (Chapman & Hayslip, 2005; Newsome, Day, & Catano, 2000) and other moderating and mediating factors. Studies have demonstrated that the relationship between EI and academic success is mediated by coping styles (MacCann, Fogarty, Zeidner, & Roberts, 2011) and moderated by age (Laidra, Pullmann, & Allik, 2007). Extant literature reveals inconsistent patterns, which might be indicative of multifaceted rather than a direct relationship between academic performance and EI.

Involvement in athletics might be in many ways ambiguous. For instance, sport participation may reduce the time allocated for studying and doing homework potentially leading to decreased academic performance. Indeed, some literature comparing elite athletes and their peers suggests that athletes’ academic performance is much lower than their peers’ (Intrator & Siegel, 2008). This relationship becomes even more noticeable when controlled for gender and ethnicity (Hildenbrand, 2005). Similar studies and negative portrayal in the media might further reinforce the stereotypically and culturally accepted athletes as ‘dumb jocks’ (Hildenbrand, 2005; Wininger & White, 2015), which has been discredited by many studies. Participation in sports provides numerous physical and psychological benefits. Additionally, sport participation may contribute to better academic outcomes (Berg, 2010; Jonker, Elferink-Gemser, & Visscher, 2009). Indeed, studies indicate that athletes perform equally to or better than non-athletes on academic achievement (Georgakis, Wilson, & Ferguson, 2014). Finally, a systematic review examining the importance of physical education (PE) classes suggested that more than half of the studies included showed significant positive association with PE and academic performance, 48% were not significant, and 1.5% were negative (Rasberry et al., 2011).

It is well-known that experiences of emotions before, during, and after the sport competition play an integral part in the development and performance of athletes in individual and team sports (Hanin, 2010; Hanton, Neil, & Mellalieu, 2008). Many scholars have highlighted how factors such as emotion regulation, emotion control, and peak emotional experience affect number of elements important in the domain of sport (e.g., anxiety, motivation, enjoyment; Hanin, 2000; Lazarus, 2000). Individuals who can successfully manage their emotions can use these experiences to assist their performance (Lane, Thelwell, Lowther, & Devonport, 2009). This notion is aligned with the concept of EI – the ability to perceive, understand, recognize, and regulate emotions to promote growth (Mayer & Salovey, 1997).

In addition to their academic and daily stressors, student-athletes face adversaries when competing in their respective sport and they have a plethora of opportunities to develop coping mechanisms and emotion regulation strategies. Athletes learn different mental skill strategies even if they have not been formally taught how to manage their emotions (Crombie et al., 2011) and systematically used psychological skills training, which is necessary for its effectiveness. Therefore, it could be argued that the use of mental skills in the sport context could be associated with increased EI. Indeed, Lane et al. (2009) demonstrated that self-talk, imagery, and activation (in both practice and competition) were associated with perceptions of the appraisal of others’ emotions and emotion regulation. Athletes who frequently used psychological skills training also reported stronger perceptions of EI. Additionally, higher EI has been linked to increased performance in sports, including cricket (Crombie, Lombard & Noakes, 2009), hockey (Perlini & Halverson, 2006), and baseball (Zizzi et al., 2003). Also, athletes with high trait EI experienced lower increases of stress compared to their low trait EI counterparts (Laborde, Brüll, Weber, & Anders, 2011).

Academic performance is typically assessed through examination, which generally contributes to stressful and anxiety provoking experiences for the students. This situation can be analogous to what an athlete might experience during the competition. When this stress is appraised as a threat, increased arousal levels can impair students’ performance (Giacobbi, Tuccitto, & Frye, 2007). Given these similarities, one might speculate that student-athletes would be able to transfer skills learned through sport (e.g., emotion regulation, goal setting) into their academic performance.

A topic of life skills has been of considerable interest in determining what developmental and life skills individuals derive from participating in sports. Researchers have investigated a range of factors, including self-esteem (Smoll, Smith, Barnett, & Everett, 1993), moral and character development (Miller, Bredemeier, & Shields, 1997), and academic achievement (Eccles & Barber, 1999). The findings of these studies are inconsistent – some suggest that sports do not contribute to building life skills, while others indicate that (under the right circumstances) sport can teach valuable life lessons (Gould & Carson, 2008). Sauer, Desmond, and Heintzelman (2013), in their longitudinal study, examined the role of athletic participation in the early career, found that former student-athletes scored higher on EI and had higher salaries during the first 10 years of their careers compared to non-athletes. Based on this evidence, one could argue that involvement in collegiate sports would have positive impact on one’s life not only on the field, but also the areas outside of sport. The value of sport as a vehicle for personal development has been recognized since antiquity when Plato (1920) suggested that “the moral value of exercise and sports far outweigh the physical value” (p. 46).

Based on the above evidence, the purpose of the current study was to provide additional evidence to the previously found differences in EI between athletes and non-athletes. The authors hypothesized that student-athletes would score higher on all components of the EI compared to non-athletes. The authors also explored whether involvement in collegiate sport plays a moderating effect between EI and academic performance measured by self-reported GPA. Finally, the authors hypothesized that the relationship between EI and GPA would depend on the involvement in collegiate sport.

METHODOLOGY
Participants
Participants (n = 203; nfemales = 134, nmales = 68; one participant did not report his/her gender) were recruited from a small university in the south of the U.S. Student-athletes (n = 129), members of the National Collegiate Athletic Association (NCAA) Division I sports, were recruited with the assistance of their coaching staff from the respective sport (i.e., football, baseball, softball, soccer, basketball, volleyball, golf, track & field, and tennis). Non-athletes (n = 74) were volunteers from the subject pool in the psychology department. Participants ranged in age from 18 to 52 (Mage = 21.42, SD = 5.63) and self-identified as Caucasian (71.9%), African American (18.7%), Hispanic (3.9%), Asian American (1.0%), or other (3.9% without specifying their ethical background).

Procedure
After acquiring the Institutional Review Board approval, convenience and purposive sampling were utilized. Non-athletes were recruited from the introductory and upper-level courses through the subject pool in the psychology department and received extra credit for their participation. The primary researcher met with the volunteers in the classroom setting to explain the purpose and procedure of the study. The study was described as an investigation about perceptions of one’s own and others’ emotions among college students. After providing informed consent, participants completed the demographic questionnaire and the Emotional Intelligence Inventory (Tapia & Burry-Stock, 1998). Upon completion, they were thanked for their participation and provided with the contact information should they wish to learn about the results of the study.

Student-athletes were recruited with the assistance of the coaching staff. The first author met with the coaches from the respective sports to explain the study procedures and hand out the packets with the questionnaires. Coaches administered the questionnaires by following the standardized procedures during their team meetings. Upon completion of the surveys (by the student-athletes who volunteered to take part in the study), the primary researcher collected the survey packets from the coaching staff.

Measures
Demographic questionnaire. The demographic questionnaire assessed participants’ gender, age, ethnicity, and current GPA.
Trait emotional intelligence. Trait emotional intelligence was measured with the Emotional Intelligence Inventory (EII; Tapia & Burry-Stock, 1998) that was developed based on Salovey and Mayer’s (1990) model of emotional intelligence. It is a 41-item self-report measure factoring in four dimensions: empathy, utilization of feelings, handling relationships, and self-control. The items are anchored on a 5-point Likert-type scale ranging from 1 (never like me) to 5 (always like me). The empathy factor consists of 12 items, utilization of feelings consists of 11 items, and handling relationships and self-control consist of nine items. After reverse coding, a composite score for each category was calculated by summing all the respective items. The Cronbach’s alpha for empathy, utilization of feelings, handling relationships, and self-control was .74, .70, .75, and .67, respectively (Tapia, 2001; Tapia & Marsh, 2001). The internal coefficient for this study for empathy, utilization of feelings, handling relationships, and self-control was .60, .62, .68, and .70, respectively.

Data Analysis
Descriptive and statistical tests for analyzing data were performed using SPSS Version 23.0. An independent-samples t-test was used to examine the differences of EI between student-athletes and non-athletes. A hierarchical multiple regression analysis was used to examine whether the relationship between EI and GPA changes as a function of the third variable – involvement in a collegiate sport.

RESULTS
Preliminary Analyses
Preliminary analyses were conducted to examine for missing values and testing the assumptions underlying the t-test and linear regression models. There were no missing values in the data set except one participant did not report his/her gender. Linearity between dependent and independent variables was established by visual inspection of the scatterplot for both groups.

Data were screened for univariate and multivariate outliers. Based on the standardized z-scores, there were no univariate outliers. Multivariate outliers were assessed with Mahalanobis distance, Cook’s distance, and Leverage value. These case wise diagnostics suggested that there were no cases exerting undue influence on the model. Visual inspection of standardized predicted values and error scores within each group suggested homoscedasticity. Additionally, Levene’s test demonstrated homogeneity of variance between the groups on the variables of interest with the lowest significance value of F(1, 201) = 1.35, p = .25. Finally, the assumption of normality was tested by examining skewness and kurtosis values. All skewness and kurtosis values were in normal range (< 3.3; Tabachnick & Fidell, 2013).

For interpretation reasons (Cohen, Cohen, West, & Aiken, 2013), predictor variables (i.e., empathy, utilization of feelings, handling relationships, and self-control) were centered on the mean by subtracting the mean from the raw data. The interaction terms between empathy, utilization of feelings, handling relationships, and self-control and categorical variable (i.e., student-athletes, non-athletes) were created next.

Descriptive and Main Analyses
Descriptive statistics, including means, standard deviations, and Pearson correlations, for empathy, utilization of feelings, handling relationships, self-control, and GPA are presented in Tables 1 and 2. An independent-samples t-test revealed that non-athletes (M = 46.51, SD = 6.55) were more empathetic than student-athletes (M = 43.24, SD = 7.09), t(201) = 3.25, p < .01, d = 0.48. Other dimensions of emotional intelligence including utilization of feelings, t(201) = 0.24, p = .81, handling relationships, t(201) = 1.93, p = .06, and self-control, t(201) = 0.79, p = .43 were not statistically significant.

Table 1: Means and Standard Deviations for GPA and EI Subscales.

Variable

Athletes
(n = 129)
M (SD)

Non-Athletes
(n = 74)
M (SD)

Females
(n = 134)
M (SD)

Males
(n = 68)
M (SD)

Total
(n = 203)
M (SD)

GPA

3.22 (0.43)

3.06 (0.45)

3.24 (0.46)

3.01 (0.38)

3.16 (0.45)

Empathy

43.24 (7.09)

46.41 (6.56)

46.22 (6.49)

40.85 (6.86)

44.43 (7.06)

Utilization of feelings

39.99 (6.25)

40.20 (5.94)

41.13 (5.68)

37.87 (6.12)

40.07 (6.02)

Handling relationships

30.63 (5.94)

32.32 (6.22)

32.17 (5.91)

29.29 (5.95)

31.25 (3.08)

Self-control

30.22 (5.80)

30.91 (6.04)

31.39 (6.13)

28.62 (4.94)

30.47 (5.88)

Note. M = mean, SD = standard deviation, n = number of participants.

Table 2: Pearson Correlation between the GPA and EI Subscales.

Variable

1

2

3

4

1. GPA

–

 

 

 

2. Empathy

.24**

–

 

 

3. Utilization of feelings

.17*

.50**

–

 

4. Handling relationships

.15*

.60**

.49**

–

5. Self-control

.15*

.01

.23*

.09

* p < .05. ** p < .01.

A hierarchical regression analysis was conducted to assess the statistical significance of the interaction term between student-athletes/non-athletes and the four sub-constructs of EI. In Step 1, student-athletes/non-athletes and EI subscales were entered as simultaneous predictors, and GPA was entered as an outcome. In Step 2, interaction terms were added in the model. None of the interaction effects between sport participation and EII subscales were statistically significant, as evidenced by the addition of the interaction term explaining 1.9% of the total variance, p = .37.

Due to non-significant moderation effects, the interaction terms were removed from the model (Hayes, 2013; Warner, 2013). Before testing a new model, assumptions of linear regression analysis were tested. Linearity was established by visual inspection of a scatterplot. No influential data points were identified and assumption of homoscedasticity was met. The overall model was significant, F(5, 197) = 5.97, p < .01 suggesting a significant positive relationship between empathy and GPA, with unstandardized slope, b = .02, t(193) = 3.28, p < .01, and self-confidence and GPA, with unstandardized slope, b = .01, t(193) = 2.28, p = .02. Additionally, student-athletes had significantly higher GPA than non-athletes, b = .23, t(193) = 3.53, p < .01.

DISCUSSION and APLICATIONS TO SPORTS
The main purpose of this study was to examine EI between student-athletes and non-athletes. The secondary aim was to explore whether involvement in the collegiate sports moderated the relationship between EI and GPA. EI has been associated with numerous positive outcomes, including mental and physical health, and social functioning (Brackett, Rivers, & Salovey, 2011), life satisfaction (Kong, Zhao, & You, 2012), positive effect (Schutte & Malouff, 2011), effective communication (Lee & Gu, 2013) and coping mechanisms (MacCann et al., 2011).

The findings of the current study do not support the main hypothesis (i.e., student-athletes would score higher on all components of the EI than non-athletes) and are not consistent with the previous research, but rather show the opposite pattern. Specifically, non-athletes scored higher on all of the EII subscales, with empathy being statistically significant, than student-athletes. The reason for these inconsistencies could be engagement in exercise and physical activity among non-athletes, which was not measured and controlled for in the current study. Previous research demonstrated that individuals who met recommended levels of daily exercise and physical activity reported higher EI compared to their insufficient and inactive counterparts (Li, Lu, & Wang, 2009). It could be that non-exercisers in this sample met the recommended levels of daily exercise; however, due to not knowing non-athletes’ engagement in sport/exercise/physical activity, the researchers are not able to eliminate this possibility. Additionally, non-athletes might have been engaged in other extracurricular activities (e.g., organizations, clubs, etc.) where they would have opportunities to practice skills contributing to higher EI. Ming Chia (2005) found a significant positive correlation between EI and extracurricular activities. Indeed, EI encompasses intrapersonal and interpersonal intelligence, which includes adaptive capabilities to successfully cope with the task at hand (e.g., stress) regardless of the activity.

The secondary hypothesis of this study was whether being a student-athlete would play a moderating role between academic achievement and EI. The findings of the current study do not provide evidence that the relationship between EI and GPA is different for student-athletes and non-athletes. As noted above, it might be that non-athletes played sports, participated in exercise and physical activity, and/or other extracurricular engagements, which could potentially lead to increased EI levels (Ming Chia, 2005). It is also possible that the skills student-athletes use in their sport do not transfer to other areas of their life unless they are intentionally taught and fostered through sport (Gould & Carson, 2008). Indeed, character is taught not caught via sport (Hodge, 1989).

Even though no hypotheses were proposed regarding the relationship between the GPA and EI, the researchers found that self-confidence and empathy were positively related to the academic performance. Many factors play a role in academic achievement, including student characteristics, instructional strategies, and curriculum development, among others. Marzano (2000) suggested that 80% of variance in academic achievement could be attributed to student effects, 13% to teacher effects, and 7% to school effects. The most important predictor among the student variables of academic achievement has been general cognitive ability (e.g., fluid and crystallized intelligence; Husin, Santos, Ramos, & Nordin, 2013). However, non-cognitive, psychological traits such as confidence has been shown to be a better predictor of academic achievement than a task/domain specific measure (i.e., self-efficacy) for English and mathematics subjects (Stankov, Lee, Luo, & Hogan, 2012).

Congruent with the previous research, empathy and GPA showed a positive relationship (Hojat et al., 2002). Emotional and mental abilities are related, yet distinct constructs (Mayer & Salovey, 1997) that need further exploration in light of some contradictory evidence. Kellett, Humphrey, and Sleeth (2002) demonstrated a negative relationship between empathy and GPA, which could be due to the sample consisting of predominantly business students who might naturally exhibit a task leadership style and therefore feel less empathy towards less successful individuals. This relationship might not hold for the students in helping professions (e.g., social workers, nursing, psychologists). Future research is warranted to provide additional evidence and clarifications on the relationship between empathy and academic achievement among different target populations.

Student-athletes had higher GPAs than non-athletes, which could be partially attributed to the requirements of the NCAA. According to the NCAA regulations, being a student-athlete in a Division I school requires maintaining 100% of the institution’s minimum GPA (i.e., 2.0) by year four (NCAA.org, 2016). If the student-athletes do not meet this criterion, they are not allowed to be a part of the team. Additionally, many coaches might have their own criteria for the student-athletes’ academic performance to be able to make the team and stay on a team throughout their college career. Finally, student-athletes who are at risk (i.e., GPA below 2.5) may be required to attend mandatory supervised study halls (NCAA.org, 2016), which provides an opportunity for a scheduled and regular study and/or tutoring time and consequently leading to improved academic performance.

Limitations and Future Directions
Although this study provides further understanding of the role of EI among student-athletes and non-athletes, it has some limitations that require the findings be interpreted with caution. First, even though the researchers provided a standardized script to the coaches who administered the questionnaires, the researchers did not have control over the environment of the team meetings during which the questionnaires were administered. Different atmospheres within the classrooms could be a potential confounding issue because the groups might not have completed the questionnaires under similar or equal conditions.

Second, participants’ academic performance was measured via self-reported GPA. It could be that participants were unaware of their GPA at the completion of the study or perhaps due to self-desirability they misreported it. Asking for participants’ permission and requesting their current GPA from the registrar’s office would have provided a more objective and accurate assessment of participants’ academic achievement. An additional limitation related to the measurement issue is the internal consistency for empathy and utilization of feelings subscales. Based on the previous research, the Cronbach’s alpha for the subscales ranged from .67 to .75 (Tapia, 1998; Tapia & Marsh, 2001). Due to questionable reliability for empathy and utilization of feelings in this sample, .60 and .62 respectively, the findings of the current study need to be interpreted with caution.

Another limitation was that the researchers did not examine and control for non-athletes’ involvement in sports, exercise, physical activity, and/or other extracurricular activities. It could be that non-athletes were engaged in intramural sports, met daily exercise requirements, and/or were involved in other extracurricular activities that could potentially lead to increased EI levels (Ming Chia, 2005). Future studies should assess and control for engagement in different activities that provide opportunities to develop skills contributing to development of EI. Finally, data were collected from only one NCAA Division I university, therefore, the findings are not generalizable to other universities and colleges.

CONCLUSION
In summary, the findings of the current study, in conjunction with the past research (Berg, 2010; Sauer et al., 2013), indicate the relationship between collegiate sport involvement, academic performance, and EI. Future research is required to investigate the role of sport, exercise, and physical activity in the realm of EI. Additionally, experimental and longitudinal studies would demonstrate the nature and underlying mechanisms whether involvement in sports and/or extracurricular activities contributes to an increased EI, or whether individuals with higher EI are more likely to engage in sports, exercise, and/or other extracurricular activities than the individuals with lower EI. Finally, utilizing different samples (e.g., different sports, different NCAA Divisions, or National Association of Intercollegiate Athletics schools) would suggest whether the relationship between GPA, EI, and participation in sport generalizes across different target populations.
 
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