Competencies Measured

Article

How Relevant Is Grit? The Importance of Social Capital in First-Generation College Students’ Academic Success

Daniel J. Almeida 1

, Andrew M. Byrne

1 , Rachel M. Smith

1 ,

and Saul Ruiz 1

Abstract

Traditional definitions of Grit have diminished the role of institutional actors in

student success. Social capital theory posits that students derive benefits like insti-

tutional resources, information, and support through their social networks to

achieve success in higher education. This study employed social network analysis

to operationalize dimensions of social capital. Using a sample of first-generation

college students (FGCSs; N ¼ 156) at a 4-year private institution, this study explored the relationship between grit and social capital, and how these concepts relate to

FGCS success. This study found that Grit and its two components—consistency of

interest and perseverance of effort—do not predict FGCS’ grade point average,

while access to social capital with faculty and staff does. Implications for practice

and future research are discussed.

Keywords

grit, social capital, retention, first generation, social network

1 School of Education, California Polytechnic State University, San Luis Obispo, CA, USA

Corresponding Author:

Daniel J. Almeida, School of Education, California Polytechnic University, 1 Grand Avenue, San Luis

Obispo, CA 93407, USA.

Email: [email protected]

Journal of College Student Retention:

Research, Theory & Practice

! The Author(s) 2019 Article reuse guidelines:

sagepub.com/journals-permissions

DOI: 10.1177/1521025119854688

journals.sagepub.com/home/csr

2021, Vol. 23(3) 539–559

None of us got where we are solely by pulling ourselves up by our bootstraps. We

got here because somebody—a parent, a teacher, an Ivy League crony or a few

nuns—bent down and helped us pick up our boots. –Thurgood Marshall

A more recent iteration of the individualistic notion of bootstrap meritocracy and success is conceptualized as grit. Defined as “perseverance and passion for long-term goals” (Duckworth, Peterson, Matthews, & Kelly, 2007, p. 1087), grit is a popular buzzword in educational discourse. Research regarding grit (Credé, Tynan, & Harms, 2017; Duckworth & Quinn, 2009; Strayhorn, 2013; Vazsonyi et al., 2019; Wolters & Hussain, 2015) has given rise to programs and support initiatives to address lower higher education completion rates among first- generation college students (FGCSs). Despite grit’s widespread use, even grit researcher Angela Duckworth agrees that the “enthusiasm is ahead of the sci- ence” (Kamenetz, 2015, p. 1). Grit’s composition relies heavily on the presence of privilege (Schreiner, 2017), which comes to light by considering how student success is related to student connections.

This study contributes to the understanding of grit and its connection with social capital. While grit may be relevant to success in challenging environments, like higher education (Duckworth & Quinn, 2009; Maddi, Matthews, Kelly, Villarreal, & White, 2012 Strayhorn, 2013; Wolters & Hussain, 2015), we sug- gest with this study that social capital is perhaps more important than grit for FGCS academic success. Kundu (2017) notes that while grit relates to individual aptitude, students’ agency to reach out to others in education’s social contexts. Unlike grit, which focuses on the individual, social capital acknowledges the role of higher education institutions and institutional actors in understanding how FGCS are successful (Bourdieu, 1986; Coleman, 1988; Lin, 2001; Stanton- Salazar & Dornbusch, 1995). The following research question guides this study: What is the relationship, if any, between FGCS grit and social capital in their academic success in college?

Grit in Higher Education

Academic success in college is often predicted using standardized tests, such as the Scholastic Aptitude Test (SAT), intended to measure cognitive ability and a limited set of academic skills (Burton & Ramist, 2001; Sternberg, Bonney, Gabora, & Merrifield, 2012). However, academic outcomes among students with comparable levels of ability and preparation vary significantly (Dweck, Walton, Cohen, Paunesku, & Yeager, 2011). Researchers, university faculty, and employers alike recognize the importance of what are commonly referred to as noncognitive factors in successful college students, including interpersonal skills, leadership, adaptability, and perseverance (Credé & Kuncel, 2008; Farruggia, Han, Watson, Moss, & Bottoms, 2018; Le, Casillas, Robbins, & Langley, 2005; Schmitt, 2012; Stemler, 2012; Sternberg et al., 2012). Grit is

540 Journal of College Student Retention: Research, Theory & Practice 23(3)

one noncognitive factor that is often used erroneously as simply a synonym for work ethic, determination, or tenacity. More precisely, grit is defined as “the capacity to sustain effort and interest [emphasis added] in projects that take months or even longer to complete” (Duckworth & Quinn, 2009, p. 166).

Assessments used to predict college success fail to measure noncognitive factors like grit (Sternberg et al., 2012). Although research suggests that stan- dardized assessments of cognitive ability provide value in projecting college grades and persistence (Daniels, Gibson, Carmack, & Smith, 2012; Farruggia et al., 2018; Geiser & Santelices, 2007), they have been found to be less accurate in forecasting success of low-income and underrepresented minority students who are often also FGCS (Burton & Ramist, 2001; Hoffman & Lowitzki, 2005; Steele, 1997; Zwick & Sklar, 2005). Including noncognitive factors in models predicting college grades reduces the differences in accuracy between White students and students of color that exist when traditional measures are used alone (Farruggia et al., 2018; Oswald, Schmitt, Kim, Ramsay, & Gillespie, 2004; Sternberg et al., 2012).

Grit is useful to augment more orthodox measures for predicting college success. The Grit Scale was developed as a 12-item self-assessment asking indi- viduals to respond to statements that fall under two categories: (a) Consistency of Interest (CI) and (b) Perseverance of Effort (PE). Responses range from very much like me to not like me at all. The score on the Grit Scale can range from a low of 1 to a high of 5 (Duckworth et al., 2007). The instrument was also offered in an eight-item short form (Duckworth & Quinn, 2009). When added to meas- ures of cognitive ability, grit scores have been shown to increase the prediction of educational attainment for adults, academic success among freshman psy- chology majors at a selective higher education institution (Duckworth & Quinn, 2009) and Black male college students attending predominantly White institu- tions (Strayhorn, 2013). In Strayhorn’s (2013) sample of Black male college students—a majority of whom were FGCS—grit appeared to matter in fore- casting grades almost as much as students’ high school grade point averages (GPAs) and standardized test scores. In a rare study which incorporated qual- itative methods to examine grit, O’Neal et al. (2016) documented examples of both undocumented and U.S.-born Latine

1,2 college students exhibiting grit to

overcome a variety of obstacles in higher education, especially financial and institutional barriers. This evidence has raised the profile of grit as a noncogni- tive trait relevant to student success.

Research on grit is relatively underdeveloped in part due to limited diversity in samples. Interviews used to construct the Grit Scale were conducted with successful individuals in a variety of professions (A. L. Duckworth et al., 2007) with relatively little focus on successful FGCS. While Strayhorn (2013) focused on Black male college students, the samples in the foundational grit studies (e.g., A. L. Duckworth et al., 2007; A. L. Duckworth & Quinn, 2009) consisted mostly of White and non-FGCS (e.g., Ivy League psychology majors,

541Almeida et al.

West Point cadets, National Spelling Bee champions). Midkiff, Langer, Demetriou, and Panter’s (2017) study examining the validity and reliability of the Grit Scale using a sample of only FGCS found that the two components of grit did not load onto a higher order construct of grit, further suggesting the current conceptualization of grit may not be as relevant to FGCS. These find- ings highlight the need for more research to further develop the theoretical construct of grit, especially within specific populations. In this study, we analyze grit as it relates to FGCS success using a social capital theoretical framework.

Social Capital

Social capital can be understood as more contextual and interpersonal than other theories of capital. Consistent with the individualistic notion of success, human capital (Becker, 1994) and cultural capital theories (Bourdieu, 1986) suggest that resources derived from both reside within an individual. Human capital refers to knowledge, skills, and abilities an individual obtains primarily through education and training that can translate to an economic advantage (Becker, 1994). Cultural capital represents cultural resources (i.e., attitudes, behaviors, appearance, style of speech) that contribute to social mobility and tend to be respected in educational contexts (Bourdieu, 1986; Lamont & Lareau, 1988). Sociologist Pierre Bourdieu (1986) theorized that society’s class hierarchy is preserved by the intergenerational transfer of cultural capital. The education system and other social structures enable this transmission by rewarding dom- inant cultural capital—mostly possessed by college-educated middle-to-upper- income individuals—rather than nondominant cultural capital—more often found in lower income areas where there are less college-educated people (Carter, 2003; Lareau, 1987).

We suggest that the individualistic manner in which grit is conceptualized involves both human capital (i.e., skills or attributes) and cultural capital (i.e., behaviors or attitudes). By emphasizing student characteristics like grit, institu- tional actors responsible for shaping student success would be absolved (Rose, 2009). Unlike human and cultural capital, social capital acknowledges the role of resources not of the individual but within an individual’s network of relation- ships (Coleman, 1988; Lin, 2001).

Coleman (1988) stated that “social capital is defined by its function” (p. 302). While Coleman outlines several forms and sources of social capital, information potential is one particularly relevant as FGCS need information about financial aid, course requirements, campus resources, and so on, to succeed in college. Information that can assist students in navigating college can be accessed through one’s network of on-campus relationships (Stanton-Salazar, 1997). Students with college-educated parents are likely to gain access to valuable information through their already established networks prior to entering higher education (Bell, Rowan-Kenyon, & Perna, 2009; Wellman, 1983).

542 Journal of College Student Retention: Research, Theory & Practice 23(3)

Less college-relevant information potential is available to FGCS, and they acquire information primarily from their campus relationships.

All students who successfully complete college likely require the support of others to overcome setbacks in college. However, for FGCS who are less likely to have college-educated individuals in their networks outside of school, social capital from relationships on-campus with other students, faculty, and staff is essential to successfully complete college. Rios-Aguilar and Deil-Amen’s (2012) analysis of the on- and off-campus social networks of first-year Latine college students suggests that while most students had established and employed social capital prior to college to gain admission, few benefited from social capital developed on campus. This study highlights the importance of not only devel- oping relationships on college campuses but also deriving useful benefits from those relationships that make a difference in students’ success in college and beyond.

Pascarella, Pierson, Wolniak, and Terenzini (2004) found that FGCS who developed social capital with peers who had college-educated parents benefited with increased motivation and intellectual development, controlling for other factors. Palmer and Gasman (2008) heard from Black college students in a qualitative study that peers were instrumental in students’ motivation to succeed in college. For example, a student reported seeking out peers who “have goals, [are] ambitious, . . . have drive, passion” and derived the benefit of a positive type of “peer pressure” to persist and succeed in college (Palmer & Gasman, 2008, p. 60). This research speaks particularly to the relationship which grit has with social capital through students’ networks of peers.

Social capital theory has been used to examine student clubs and organiza- tions (Pascarella et al., 2004; Strayhorn, 2010), many of which can be considered appropriable social organizations—a determinant of Coleman’s (1988) theory of social capital. Appropriable social organizations are created for a purpose other than generating social capital, but nonetheless have the unintended benefit of developing social capital. Students who are actively engaged in student organ- izations have been found to more likely persist in higher education than those who are not involved (Engstrom & Tinto, 2008). In these organizations which are generally created around a common student interest or background charac- teristic, FGCS not only derive the social benefits that are intentional, they also unintentionally develop skills and gain knowledge that is helpful to their success in college through their relationships with others in these organizations (Pascarella et al., 2004; Strayhorn, 2010). Although Pascarella et al. (2004) found that FGCS are less likely to be engaged in extracurricular activities, those FGCS who did participate in appropriable student organizations on campus were found to have enhanced critical thinking skills and an increased sense of control and ownership over their success in college. FGCS were also found to benefit more in these areas from their extracurricular participation than did non-FGCS. These findings highlight not only the importance of

543Almeida et al.

promoting FGCS involvement on campus but also the need of examining organ- izations to understand how they make a difference for FGCS success.

Student organizations and environments intentionally designed to generate relationship building and social capital among students, and between students

and faculty and staff, support FGCS success (Strayhorn, 2006). Mentoring programs, consisting of faculty, staff, or peer mentors, are one such type of

organization for building social capital between FGCS and institutional agents (Schwartz et al., 2018; Tinto, 2012). A review of the mentoring literature

suggests that mentoring contributes to students’ academic integration and social integration (Moschetti, Plunkett, Efrat, & Yomtov, 2018). Students also benefit from career planning, guidance on research and academics, and support with

personal matters through their mentoring relationships (Ishiyama, 2007). Mentoring relationships cited among underrepresented students as helpful are

often informal (Hagler, 2018). The benefits of faculty mentoring to students hinge upon student perceptions

of the relationship (Livingstone & Naismith, 2018). On relationships with fac- ulty, Anaya and Cole (2001) found that both academic and personal relation-

ships with faculty, as well as student perceptions of the quality of these relationships, were associated with higher grades for a sample of Latine college

students. Palmer and Gasman’s (2008) qualitative study of Black college stu- dents suggests that faculty who go “above and beyond” (p. 52) and exhibit

empathy and treat students as academically capable were effective institutional agents in promoting student success. Other research (Cole & Espinoza, 2008;

Kim, 2010; Lohfink & Paulsen, 2005; Pascarella & Terenzini, 2005) has been consistent with these findings, suggesting the importance of social capital devel-

oped through quality student–faculty interactions on campuses for both aca- demic achievement and persistence in college, especially for FGCS (Lohfink &

Paulsen, 2005). Students have also been found to receive benefits such as faculty and staff providing emotional support, mentoring, role modeling, and advocat-

ing for students (Museus & Neville, 2012; Rend�on, Jalomo, & Nora, 2000; Smith, 2007; Stanton-Salazar, 1997).

Methods

This cross-sectional survey study addressed the following research question:

What is the relationship, if any, between FGCS’ grit and social capital in their collegiate academic success?

Subjects

Study participants were FGCS who were in their junior or senior year at a private, religiously-affiliated Southwestern 4-year university and identified by

faculty and staff. Of 418 FGCS invited, 156 (37.3%) took the survey.

544 Journal of College Student Retention: Research, Theory & Practice 23(3)

Instrumentation

The online survey in this study asked about students’ employment, student

status, mentoring and support systems, GPA and standardized test results,

and demographics along with the Grit Scale (A. L. Duckworth et al., 2007)

and Social Support Scale (Russell & Cutrona, 1984).

Results

Demographics

Seventy-six percent of the 156 respondents identified as female. Race and

ethnicity among participants included Latine (44%), White (31%), Asian and

Pacific Islander (12%), Black (9%), and Native American (3%) with 17% indi-

cating overlapping racial/ethnic identities. 11% were immigrants, while 47%

and 52% of respondents’ mothers and fathers, respectively, were immigrants.

The religious affiliation of the university was Catholic, so a majority (52%) of

students reported a Catholic religious identity. Fifty-nine percent of the sample

were public high school graduates, whereas 35% were Catholic private high

school graduates and 6% had attended other private secondary schools. The

mean high school GPA was 3.71 of 4.0, with a mean SAT score of 1,532 of

2,400. Nearly a third (29%) of survey respondents were transfer students who

had attended another institution prior to this university. Identity as FGCS for this sample included students whose parents did not

graduate from any 4-year higher education institution (86%), and students who

did have parents with 4-year degrees from nations outside of the United States.

Thirty-five percent had no older sibling college graduates in their families. Over half (51%) of the survey respondents were liberal arts majors, 21%

science and engineering, 13% communications and fine arts, 5% film and tele-

vision, and less than 1% were education majors. The average cumulative college

GPA for the sample was 3.29 (standard deviation [SD] ¼ 0.35) on a 4.00 scale. Most students in the sample received financial aid and worked in jobs either

on or off campus, with 32% working both on and off campus. Over half of the

student survey respondents (55%) received federal Pell grants to help support

the cost of their higher education. Seventy-five percent earned federal work

study money for on-campus jobs. In addition to on-campus jobs, 58% had

jobs off campus. Roughly 20% of these students worked more than 20 hours

per week, while almost half (49%) worked 10 to 20 hours, and about 30% spent

10 or less hours per week working. Most students in the sample have lived on campus for part or all of their time

and were involved in student organizations on campus. Almost two thirds of the

students in the sample (65%) had never commuted from their family home to

attend college. Over 38% of student survey respondents had lived on campus for

545Almeida et al.

3 or more years, 26% for 2 years, and 13% for 1 year of their college experi-

ences. Almost three quarters (73%) of student survey respondents were involved

in student organizations on campus. Between 25% and 30% of respondents

were associated with Greek, community service, religious student, and cultural

student organizations. Smaller numbers of student respondents were involved in

intramural (15%) and varsity (7%) athletics. In addition, some students

reported participation in the university’s first-generation mentoring program

(13%), where students are paired with a mentor who was also an FGCS.

Students were also invited to participate in other activities. A smaller subset

of these students (7%) were part of a first-generation scholars cohort who took

classes together as freshman. Students involved in the first-generation mentoring

program and scholars cohort also participated in other activities designed to

build their social capital and support their academic success. Other students in

the sample took part in a variety of on-campus learning communities designed

to enhance their academic success and encourage graduate school aspirations

and preparation. In all, 23% of student respondents participated in programs or

initiatives for underrepresented students’ academic success and social capital

on campus.

Grit Scale Scores

Table 1 depicts the focal variables of this study, beginning with the Grit Scale

(Duckworth et al., 2007). The range for the overall grit score and the two

components was 1 to 5. The mean grit score of student survey respondents

was 3.61 (SD ¼ 0.52). The mean scores for PE and CI subscales were 4.10 (SD ¼ 0.56) and 3.13 (SD ¼ 0.72), respectively.

Informational Support Networks

In the survey, students answered two primary network questions, identifying up

to seven student peers and seven faculty or staff on campus from whom they

previously received informational support. The number of individuals named by

each respondent determined the social network measure of outdegree with the

respondent as the vertex. Students in the sample generally received information-

al support more frequently from peers than they did from faculty and staff. The

mean peer outdegree for survey respondents was 2.89 (SD ¼ 2.64), significantly higher (p < .01) than the mean faculty/staff outdegree of 2.23 (SD ¼ 2.20). In addition to the quantity of relationships, survey respondents also indicated

stronger ties (p < .001) to peers than to the faculty/staff from whom they had received informational support. The social network survey also captured shared

characteristics of students and their peer informational support networks (see

Table 2). For example, of the 451 peer outdegree relationships, 68% were in the

same year of college, 69% were of the same gender, and 48% were of the same

546 Journal of College Student Retention: Research, Theory & Practice 23(3)

race or ethnicity. In addition, 26% of peers identified in respondents’ support networks were also FGCS. Thirty-eight percent of the peer relationships were with students in the same student organization, while about a quarter were with students in the same major (28%), or roommates (25%).

The type of information most often shared through peer networks was about choosing or registering for classes (41%), followed by study tips (38%), career

Table 1. Focal Variables of Survey (N ¼ 156) and Interview Respondents (N ¼ 21). Variable Survey M (SD) [range] Interview M (SD) [range]

College GPA 3.29 (0.35) [0–4] 3.21 (.40) [0–4]

Grit 3.61 (0.52) [1–5] 3.50 (0.51) [1–5]

Perseverance of effort 4.10 (0.56) [1–5] 4.00 (0.46) [1–5]

Consistency of interests 3.13 (.72) [1–5] 3.03 (0.76) [1–5]

Informational support network

Peer outdegree 2.89 (2.64) [0–7] 3.90 (2.17) [0–7]

Peer strength of ties x

16.30 (6.18) [0–25] 19.45 (4.81) [0–25]

Peer strength of ties þ

7.79 (2.30) [0–10] 8.77 (1.16) [0–10]

Faculty/staff outdegree 2.23 (2.20) [0–7] 3.62 (1.83) [0–7]

Faculty/staff strength of ties x

13.05 (4.65) [0–25] 13.61 (4.65) [0–25]

Faculty/staff strength of ties þ

7.07 (1.65) [0–10] 7.30 (1.20) [0–10]

Combined outdegree 5.12 (4.10) [0–14] 7.75 (3.35) [0–14]

Combined strength of tie x

30.75 (7.20) [0–50] 33.30 (7.33) [0–50]

Combined strength of tie þ

15.45 (2.14) [0–20] 16.13 (1.87) [0–20]

No. of faculty/staff providing info support

Career advice 1.23 (1.46) [0–7] 2.24 (1.58) [0–7]

Register/select classes 1.16 (1.37) [0–7] 2.29 (1.42) [0–7]

Campus resources 1.04 (1.38) [0–7] 1.81 (1.83) [0–7]

Studying tips 0.85 (1.34) [0–7] 1.24 (1.67) [0–7]

Jobs/internships 0.84 (1.17) [0–7] 1.48 (1.36) [0–7]

Choosing major 0.62 (0.92) [0–7] 1.33 (1.11) [0–7]

No. of peers providing info support

Register/select classes 1.20 (1.45) [0–7] 1.62 (1.43) [0–7]

Studying tips 1.09 (1.52) [0–7] 2.24 (2.02) [0–7]

Career advice 0.99 (1.45) [0–7] 1.76 (1.73) [0–7]

Campus resources 0.97 (1.47) [0–7] 1.62 (1.86) [0–7]

Jobs/internships 0.73 (1.28) [0–7] 1.05 (1.40) [0–7]

Choosing major 0.40 (1.05) [0–7] 0.71 (1.65) [0–7]

Perceived Social Support Scale 2.78 (0.26) [1–4] 2.85 (0.25) [1–4]

Subscales of interest

Guidance 3.02 (0.54) [1–4] 3.21 (0.50) [1–4]

Social integration 2.28 (0.46) [1–4] 2.48 (0.31) [1–4]

Reliable alliance 2.96 (0.31) [1–4] 2.75 (0.24) [1–4]

Note. SD ¼ standard deviation; GPA ¼ grade point average.

547Almeida et al.

advice (34%), campus resources (34%), jobs and internships (25%), and choos-

ing a major (14%). Descriptive statistics in Table 1 show, on average, how many peers students credit with each type of informational support. For example,

survey respondents had 1.20 peers, on average, who had provided support in selecting and registering for classes. Of the 348 student relationships with faculty

and staff on campus (Table 2), 54% were with faculty/staff in the same field of study as the student and 52% were with faculty/staff of the same gender. Only

30% were of the same race/ethnicity and only 21% were with faculty and staff who the student survey respondents believed to be FGCS. Twenty-eight percent

of students’ relationships to faculty/staff on campus were with their assigned faculty advisors, while 46% were with faculty and staff in the same department

as students’ respective majors. Some students also received informational sup- port from faculty and staff who worked in the same on-campus office where the

student worked (15%), from an advisor to their student organizations (18%), or from a mentor (7%). Career advice (55%) was the most common type of infor-

mation shared by faculty and staff with students. Informational support regard-

ing choosing and registering for classes was second (52%), followed by campus resources (47%), study tips (38%), jobs/internships (38%), and choosing a

major (28%). Information about choosing a major was the only type of

Table 2. Faculty/Staff Informational Support Network (N ¼ 348). Percentage

Students shared characteristics with faculty/staff

Major/field of study 53.74

Gender 52.30

Race/ethnicity 29.89

First-generation status 20.69

religion 16.38

How has student accessed faculty/staff

Worked in department of student’s major 45.98

Faculty advisor 27.87

Student organization advisor 17.53

Worked in same office 14.94

Mentor 7.18

Information support from faculty/staff

Career advice 55.17

Choosing/registering for classes 52.01

Campus resources 46.84

Study tips 37.93

Jobs/internships 37.64

Choosing a major 27.87

548 Journal of College Student Retention: Research, Theory & Practice 23(3)

advice that students received more from faculty/staff than from stu- dents (p < .05).

Perceived Social Support

In addition to informational support, social support is another benefit that students may have received through their relationships with faculty, staff, and peers on campus. In the online survey, students’ perception of social support was captured by the 24-item Social Provisions Scale (Russell & Cutrona, 1984), which asked them to think about their current relationships to faculty, staff, and students on campus when answering the questions. On a scale of 1 to 4, the mean value for overall perceived social support was 2.78 (SD ¼ 0.26, see Table 1).

Missing Data

Data were missing for a number of the focal variables in this study. For instance, between 7% and 10% respondents were missing each of the 12 Grit Scale items, between 17% and 20% respondents were missing items on the Social Support Scale, 6% had missing college GPAs, and between 17% and 20% were missing one of the three SAT scores. For these variables (i.e., grit, social support, college GPA, high school GPA, SAT scores), we used mean imputation to increase the power and precision of standard error estimates which would have been biased in the default method for addressing missing data in Stata, case-wise deletion (Donders, van der Heijden, Stijnen, & Moons, 2006). For these variables, we utilized the mean of those survey respondents who did answer these questions to replace the missing values.

OLS Regression

We explored an ordinary least square (OLS) regression model predicting the dependent variable of cumulative college GPA, the measure of academic success used in this study. We investigated several models using various combinations of independent variables, including social network measures that represent access to social capital (i.e., staff outdegree, peer outdegree, peer strength of ties

xþ ,

staff strength of ties xþ ), benefits of social capital (i.e., social support and its key

determinants, and the types of informational support received from one’s social network), and grit and grit’s components (i.e., CI and PE). We used variables such as student involvement on campus, Pell grant, family education, race/eth- nicity, prior achievement (i.e., high school GPA and SAT score), and the school or college of the students’ majors as control variables. We examined various interactions between grit and social network measures as well to explore the potential relationship of grit and social capital and how the interaction of the two may be predictive of college GPA.

549Almeida et al.

Table 3 displays the results of the final OLS model (p < .0001), with the equation of

Yi ¼ ai þ bixGriti þ bixSCi þ biXdemi þ biXPA þ ei

where Yi is the outcome, cumulative college GPA. xGriti represents FGCS Grit Scale scores. xSCi indicates a measure of social capital, in this case faculty/staff outdegree. Xdemi is a vector of control dummy variables for student demo- graphics factors (i.e., transfer student, commuter, Pell grant recipient, campus involvement) and XPA is a vector for continuous variables of prior achievement (i.e., SAT scores and high school GPA). ai is the constant which represents the cumulative college GPA when all other variables are equal to 0, and ei is the error term.

Throughout more than 50 regressions run, predicting college GPA, the var- iables of grit and its two CI and PE components were not found to be significant predictors of cumulative GPA. The variables for perceived social support and its relevant determinants (i.e., reliable alliance, guidance, social integration) and the various types of informational support operationalized in the study were also not significant predictors of cumulative GPA in any of the regression models. We also explored the intersection of grit and social capital by including inter- actions between grit (and its components) and variables representing access to or benefits of social capital (e.g., grit interacted with faculty/staff outdegree, CI interacted with reliable alliance, etc.). None of the interaction terms run in the

Table 3. OLS Regression Results, Final Model.

OLS college GPA B B

Grit �0.0004 (0.0512) �0.0005 Faculty/staff outdegree 0.0317 (0.0123)* 0.1992

Involved on campus �0.0237 (0.067) �0.0607 Transfer student 0.1155 (0.0607) 0.1479

Commuter student �0.1327 (0.0568)* �0.1817 Pell recipient �0.0396 (0.0547) �0.0565 High school GPA 0.1253 (0.0788) 0.1285

SAT scores 0.0006 (0.0001)** 0.3411

_cons 2.8108 (0.3332)**

N 156

R 2

.1190

Adj. R 2

.1554

F 4.56

Note. GPA ¼ grade point average; OLS ¼ ordinary least square; SAT ¼ Scholastic Aptitude Test.

*p < .05. **p < .0001.

550 Journal of College Student Retention: Research, Theory & Practice 23(3)

regressions were significant. Furthermore, we controlled for the schools and colleges of students’ majors which did not change the results of the final regres- sion model.

The only social network measure that was consistently significant in the regression models was the size of FGCS informational support network of fac- ulty and staff, or faculty/staff outdegree. Controlling for other factors in the model, each additional faculty or staff from whom a FGCS received informa- tional support is associated with a 0.03 unit, or a 0.20 SD, increase in college GPA (p < .05). The control variables for SAT scores and commuter students were also significant in this model. Controlling for other variables in the model, with every 100-point increase in SAT score, students were predicted to have a 0.06 increase in cumulative GPA (p < .0001). Students who had ever lived at home with family and commuted during their time at the university were pro- jected to have a 0.13 lower cumulative GPA (p < .05), controlling for other factors in the model.

Discussion

This research administered an online survey to first-generation juniors and seniors at a 4-year, private university. Not only did we collect and analyze FGCS attribute data, we also employed social network analysis to include rela- tional data about FGCS relationships to faculty, staff, and students on campus. The survey consisted of the Grit Scale (A. L. Duckworth & Quinn, 2009), a Social Support Scale (Russell & Cutrona, 1984), and students’ demographics, involvement on campus, prior achievement, and cumulative college GPA. Ego- centric network data about the peers, faculty, and staff that have provided informational support that has helped the survey respondents succeed in college were also collected.

Our analysis of the study’s results suggests that grit could be less important than social capital in academic success among FGCS. Despite prior regression research suggesting grit is predictive of college students’ GPA (Duckworth et al., 2007; Strayhorn, 2013), in this study, neither grit nor its components, CI or PE, were found to be significant predictors of FGCS cumulative GPA. In this study, the mean grit score of student survey respondents of 3.61 (SD ¼ 0.52) was sig- nificantly higher (p < .001) than Duckworth et al.’s (2007) mean grit score of 3.46 (SD ¼ 0.61, n ¼ 1,545) and significantly lower (p < .001) than Strayhorn’s (2013) mean grit score of 4.08 (SD ¼ 0.88, n ¼ 140) study of Black male college students. Sixty-one percent (n ¼ 85) of the participants in Strayhorn’s study were FGCS, but their results were not isolated. The mean scores for PE and CI subscales among FGCS of 4.10 (SD ¼ 0.56) and 3.13 (SD ¼ 0.72) were both significantly higher (p < .001) than the mean values of 3.7 (SD ¼ 0.7) and 2.9 (SD ¼ 0.9) for PE and CI, respectively, in Duckworth and Quinn’s (2009) study of adults aged 25 years and older.

551Almeida et al.

Moreover, none of the correlations exploring the relationship of cumulative GPA with grit, PE, or CI produced significant results. Access to social capital, however, was a significant predictor of FGCS cumulative GPA, which was projected to increase 0.03 points for each additional faculty or staff member a student named as someone on campus who provided informational support.

The OLS regression results indicated that commuter students had an expected decrease of 0.13 in GPA, a magnitude over 4 times larger than the positive effect (0.03 points) of one additional faculty or staff member in the student’s network. These results suggested that a commuter student may have been able to make up for the negative effect of living at home with five faculty and staff in their information support network.

Only 9 of the 101 commuters in the survey sample had more than five faculty and staff in their information support network. Perhaps if FGCS were not faced with the burden of working longer hours, commuting, or navigating other chal- lenges, FGCS grit may have correlated with their overall GPA.

Although we suggest the prominence of social capital in the achievement of FGCS, we do not dismiss grit’s relevance entirely. There are several reasons why grit may not have been found to be predictive of GPA in this study. Unlike prior studies that have a more homogenous sample (e.g., Duckworth et al., 2007; Strayhorn, 2013), this study had a diverse group of FGCS with a wide variety of majors. One additional plausible explanation was the increased complexity of grit in the context of FGCS’ lives. For instance, PE had a relationship to number of hours students worked. Grittier individuals have been found to work longer hours in general (Duckworth et al., 2007), and other prior research suggested higher academic performance for college students working between 10 and 19 hours per week (Dundes & Marx, 2006). Over 20% of the FGCS in this study worked more than 20 hours per week and many added on several hours for their commutes. In addition to financial necessity, students’ grit, particularly PE, may have led them to work longer hours (i.e., over 20) at the expense of their grades, particularly those who commuted.

Although not a focal point, we also found evidence of grit’s relationship to elements of social capital in this study. For example, we found that students with above average grit scores for this sample had larger information support networks and were more likely to receive career advice from faculty and staff than students with below average grit scores. We also found that students with above average GPAs had larger peer information support networks than do students with below average GPAs.

Limitations

Some limitations are inherent in self-assessment survey research, for example, self-selection bias, leading to a sample that may not be representative of FGCS at this university. Disengaged students were also likely underrepresented as part

552 Journal of College Student Retention: Research, Theory & Practice 23(3)

of the recruitment strategy was reaching students through campus organizations and through staff and faculty nomination. Future researchers should devise a strategy that provides a better cross-section of students. Other issues with self- report assessments cited by others (Duckworth & Yeager, 2015; Shechtman et al., 2013) include participants’ inability to accurately evaluate their abilities or mindsets and their different interpretations or frames of reference for survey items. Frames of reference used to make choices on self-assessments may vary based on numerous factors including individuals’ cultural norms (Heine, Lehman, Peng, & Greenholtz, 2002).

Relying on the self-reported cumulative GPA as an outcome variable was also major limitation in this study. Although the use of self-reported GPA is cautioned due to its threat to construct validity (Kuncel, Credé, & Thomas, 2005), linking survey data to institutional data (Bowman, 2010), like student’s official GPA, was not feasible at the university. We suggest that future research- ers collect students’ transcripts which will also enable the exploration of grit’s potential relationship to grades in specific semesters and major GPA. Also, students’ cumulative GPA used in this study included many classes that were less relevant to their interests and long-term goals than the classes they have taken for their major courses of study. Furthermore, cumulative GPA included grades from freshman year, which was 2 or 3 years prior to the time of the survey. Student social network development and GPA may hold more meaning if they are tracked in parallel, over time. A longitudinal, rather than cross- sectional study might capture potential relationships with more precision. Akos and Kretchmar (2017) recommend using major GPA as the outcome which we suspect might be more likely related to grit, and particularly to CI. College completion is still another outcome which may show greater efficacy, as GPA is not always the primary reason for student attrition.

We also call for expanded use of social network analysis in studies of FGCS and provide suggestions based on our experience to strengthen future research. Instead of using the name generator technique (Burt, 1984) to collect network data, we suggest using the roster method (unavailable in this study) where respondents choose names from rosters instead of recalling names. While both methods can identify the strongest ties, the roster method importantly helps to reveal weaker ties (Scott, 2000), through which information flows to more students in a network, especially those on the periphery (Granovetter, 1973; Lin, 1999). Also, unlike in this study, future researchers may elect not to limit the number of faculty, staff, and peers that respondents can choose, thereby increasing the variability of outdegree. A limit to the number of nom- inations for social network analysis also hindered the ability to explore which on-campus structures, such as first-year experience or peer mentoring programs. A future social network analysis conducted without setting a limit on nomina- tions would help to categorize the advising and other social structures that relate to campus programming.

553Almeida et al.

Conclusion

This study sought to provide a reconceptualization of the construct of grit— perseverance and passion for long-term goals—as it relates to FGCS success at one 4-year, private university, using social capital. This study suggests that especially for FGCS, maintaining a grit mindset and employing grit to navigate college and overcome obstacles to succeed is intertwined with the use of embed- ded resources in one’s social network on campus.

In particular, institutional agents can be more engaged in three areas: (a) with students, by encouraging grit through engaging students’ interests in manifold ways; (b) with their network, to have up-to-date knowledge of the interests of network members and resources within one’s network; and (c) with the campus leadership, insofar as the institutional agent can influence the design and imple- mentation of student programs and social spaces with the intention of facilitat- ing social capital that particularly benefits FGCS and encourages their perseverance and passion for long-term goals.

By replicating this study’s findings on multiple campuses, we may come to a more thorough and nuanced understanding of FGCS success, grit, and social capital. Through the process, we can collect evidence for Thurgood Marshall’s assertion that

None of us got where we are solely by pulling ourselves up by our bootstraps. We

got here because somebody—a parent, a teacher, an Ivy League crony or a few

nuns—bent down and helped us pick up our boots.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research,

authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publi-

cation of this article.

ORCID iD

Daniel J. Almeida https://orcid.org/0000-0003-4679-7185

Notes

1. Latine is a gender-inclusive alternative to Latino/a and is more consistent with Spanish

grammar than the more popular gender neutral alternative, Latinx 2. Latine is a gender-inclusive alternative to Latino/a and is more consistent with Spanish

grammar that the also common gender neutral alternative, Latinx

554 Journal of College Student Retention: Research, Theory & Practice 23(3)

References

Akos, P., & Kretchmar, J. (2017). Investigating grit as a non-cognitive predictor of col- lege success. Review of Higher Education, 40(2), 163–186.

Anaya, G., & Cole, D. G. (2001). Latina/o student achievement: Exploring the influence of student-faculty interactions on college grades. Journal of College Student Development, 42(1), 3–14.

Becker, S. (1994). Human capital: A theoretical and empirical analysis, with special refer- ence to education (2nd ed.). Chicago, IL: University of Chicago Press.

Bell, A. D., Rowan-Kenyon, H. T., & Perna, L. W. (2009). College knowledge of 9th and 11th grade students: Variation by school and state context. The Journal of Higher Education, 80(6), 663–685.

Bourdieu, P. (1986). The forms of capital. In J. G. Richardson (Ed.), Handbook of theory and research for the sociology of education (pp. 241–258). New York, NY: Greenwood Press.

Bowman, N. A. (2010). Can first-year students accurately report their learning and devel- opment? American Educational Research Journal, 47(2), 466–496.

Burt, R. S. (1984). Network items and the general social survey. Social Networks, 6(4), 293–339.

Burton, N. W., & Ramist, L. (2001). Predicting success in college: SAT studies of classes graduating since 1980. New York, NY: College Entrance Examination Board.

Carter, P. L. (2003). “Black” cultural capital, status positioning, and schooling conflicts for low income African American youth. Social Problems, 50(1), 136–155.

Cole, D., & Espinoza, A. (2008). Examining the academic success of Latino students in science technology engineering and mathematics (STEM) majors. Journal of College Student Development, 49(4), 285–300.

Coleman, J. S. (1988). Social capital in the creation of human capital. The American Journal of Sociology, 94(S1), S95–S120.

Credé, M., & Kuncel, N. R. (2008). Study habits, skills, and attitudes: The third pillar supporting collegiate academic performance. Perspectives on Psychological Science, 3(6), 425–453.

Credé, M., Tynan, M. C., & Harms, P. D. (2017). Much ado about grit: A meta-analytic synthesis of the grit literature. Journal of Personality and Social Psychology,

113(3), 492. Daniels, L., Gibson, N., Carmack, P., & Smith, T. (2012). Predictive power of standard

variables on postsecondary achievement in Arkansas. Journal of College Student Retention: Research, Theory & Practice, 14(2), 181–193.

Donders, A. R. T., van der Heijden, G. J., Stijnen, T., & Moons, K. G. (2006). Review: A gentle introduction to imputation of missing values. Journal of Clinical Epidemiology, 59(10), 1087–1091.

Duckworth, A. L., Peterson, C., Matthews, M. D., & Kelly, D. R. (2007). Grit: Perseverance and passion for long-term goals. Journal of Personality and Social Psychology, 92, 1087–1101.

Duckworth, A. L., & Quinn, P. (2009). Development and validation of the short grit scale (Grit-S). Journal of Personality Assessment, 91, 166–174.

Duckworth, A. L., & Yeager, D. S. (2015). Measurement matters: Assessing personal qualities other than cognitive ability for educational purposes. Educational Researcher, 44(4), 237–251.

555Almeida et al.

Dundes, L., & Marx, J. (2006). Balancing work and academics in college: Why do

students working 10 to 19 hours per week excel? Journal of College Student

Retention: Research, Theory & Practice, 8(1), 107–120. Dweck, C., Walton, G. M., Cohen, G. L., Paunesku, D., & Yeager, D. (2011). Academic

tenacity: Mindset and skills that promote long-term learning. Seattle, WA: Bill &

Melinda Gates Foundation. Engstrom, C., & Tinto, V. (2008). Learning better together: The impact of learning

communities on the persistence of low-income students. Opportunity Matters:

A Journal of Research Informing Educational Opportunity Practice and Programs,

1(1), 5–21. Farruggia, S. P., Han, C., Watson, L., Moss, T. P., & Bottoms, B. L. (2018). Noncognitive

factors and college student success. Journal of College Student Retention: Research,

Theory & Practice, 20(3), 308–327. doi:10.1177/1521025116666539 Geiser, S., & Santelices, M. V. (2007). Validity of high-school grades in predicting student

success beyond the freshman year: High-school record vs. standardized tests as indica-

tors of four-year college outcomes. Berkeley, CA: Center for Studies in

Higher Education. Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78

(6), 1360–1380. Hagler, M. (2018). Processes of natural mentoring that promote underrepresented stu-

dents’ educational attainment: A theoretical model. American Journal of Community

Psychology, 62(1-2), 150–162. doi:10.1002/ajcp.12251 Heine, S. J., Lehman, D. R., Peng, K., & Greenholtz, J. (2002). What’s wrong with cross-

cultural comparisons of subjective Likert scales?: The reference-group effect. Journal

of Personality and Social Psychology, 82(6), 903–918. Hoffman, J. L., & Lowitzki, K. E. (2005). Predicting college success with high school

grades and test scores: Limitations for minority students. The Review of Higher

Education, 28(4), 455–474. Ishiyama, J. (2007). Expectations and perceptions of undergraduate research mentoring:

Comparing first generation, low income white/Caucasian and African American stu-

dents. College Student Journal, 41(3), 540–549. Kamenetz, A. (2015, May 13). A key researcher says ‘grit’ isn’t ready for high-stakes

measures [Blog post]. Retrieved from https://www.npr.org/sections/ed/2015/05/13/

405891613/a-key-researcher-says-grit-isnt-ready-for-high-stakes-measures Kim, Y. K. (2010). Racially different patterns of student-faculty interaction in college:

A focus on levels, effects, and causal directions. Journal of the Professoriate,

3(2), 161–189. Kuncel, N. R., Credé, M., & Thomas, L. L. (2005). The validity of self-reported grade

point averages, class ranks, and test scores: A meta-analysis and review of the liter-

ature. Review of Educational Research, 75(1), 63–82. Kundu, A. (2017). Grit and agency: A framework for helping students in poverty to

achieve academic greatness. National Youth At-Risk Journal, 2(2), 69. doi:10.20429/

nyarj.2017.020205 Lamont, M., & Lareau, A. (1988). Cultural capital: Allusions, gaps and glissandos in

recent theoretical developments. Sociological Theory, 6(2), 153–168. Lareau, A. (1987). Social class differences in family-school relationships: The importance

of cultural capital. Sociology of Education, 60(2), 73–85.

556 Journal of College Student Retention: Research, Theory & Practice 23(3)

Le, H., Casillas, A., Robbins, S. B., & Langley, R. (2005). Motivational and skills,

social, and self-management predictors of college outcomes: Constructing the

Student Readiness Inventory. Educational and Psychological Measurement,

65(3), 482–508. Lin, N. (1999). Building a network theory of social capital. Connections, 22(1), 28–51. Lin, N. (2001). Social capital: A theory of social structure and action. New York, NY:

Cambridge University Press. Livingstone, N., & Naismith, N. (2018). Faculty and undergraduate student perceptions

of an integrated mentoring approach. Active Learning in Higher Education, 19(1),

77–92. doi:10.1177/1469787417723233 Lohfink, M., & Paulsen, M. B. (2005). Comparing the determinants of persistence for

first generation and continuing-generation students. Journal of College Student

Development, 46, 409–428. Maddi, S. R., Matthews, M. D., Kelly, D. R., Villarreal, B., & White, M. (2012). The role

of hardiness and grit in predicting performance and retention of USMA cadets.

Military Psychology, 24(1), 19–28. Midkiff, B., Langer, M., Demetriou, C., Panter, A. T. (2017). Measuring grit among first-

generation college students: A psychometric analysis. In W. -C. Wang., & M, Wiberg,

S. A. Culpepper, J. A. Douglas, & L. A. van der Ark (Eds.), Quantitative psychology—

81st annual meeting of the psychometric society, 2016 (196) (pp. 407–420). New York:

Springer New York LLC. doi:10.1007/978-3-319-56294-0_35 Moschetti, R. V., Plunkett, S. W., Efrat, R., & Yomtov, D. (2018). Peer mentoring as

social capital for Latina/o college students at a Hispanic-serving institution. Journal of

Hispanic Higher Education, 17(4), 375–392. doi:10.1177/1538192717702949 Museus, S. D., & Neville, K. M. (2012). Delineating the ways that key institutional agents

provide racial minority students with access to social capital in college. Journal of

College Student Development, 53(3), 436–452. O’Neal, C. R., Espino, M. M., Goldthrite, A., Morin, M. F., Weston, L., Hernandez,

P., & Fuhrmann, A. (2016). Grit under duress: Stress, strengths, and academic

success among non-citizen and citizen Latina/o first-generation college students.

Hispanic Journal of Behavioral Sciences, 38(4), 446–466. doi:10.1177/

0739986316660775 Oswald, F. L., Schmitt, N., Kim, B. H., Ramsay, L. J., & Gillespie, M. A. (2004).

Developing a biodata measure and situational judgment inventory as predictors of

college student performance. Journal of Applied Psychology, 89(2), 187–207. Palmer, R., & Gasman, M. (2008). “It takes a village to raise a child”: The role of social

capital in promoting academic success for African American men at a Black college.

Journal of College Student Development, 49(1), 52–70. Pascarella, E. T., Pierson, C. T., Wolniak, G. C., & Terenzini, P. T. (2004). First-

generation college students: Additional evidence on college experiences and outcomes.

The Journal of Higher Education, 3, 249–284. Pascarella, E. T., & Terenzini, P. T. (2005). How college affects students: A third decade of

research. San Francisco, CA: Jossey-Bass. Rend�on, L. I., Jalomo, R. E., & Nora, A. (2000). Theoretical considerations in the study

of minority student retention in higher education. In J. M. Braxton (Ed.), Reworking

the student departure puzzle (pp. 127–156). Nashville, TN: Vanderbilt University.

557Almeida et al.

Rios-Aguilar, C., & Deil-Amen, R. (2012). Beyond getting in and fitting in an examina- tion of social networks and professionally relevant social capital among Latina/o university students. Journal of Hispanic Higher Education, 11(2), 179–196.

Rose, M. A. (2009). Why school?: Reclaiming education for all of us. New York, NY: The

New Press. Russell, D. W., & Cutrona, C. E. (1984). Social provisions scale. Ames: Iowa

State University. Schmitt, N. (2012). Development of rationale and measures of noncognitive college stu-

dent potential. Educational Psychologist, 47(1), 18–29. Schreiner, L. A. (2017). The privilege of grit. About Campus, 22, 11–20.

doi:10.1002/abc.21303 Schwartz, S. E., Kanchewa, S. S., Rhodes, J. E., Gowdy, G., Stark, A. M., Horn, J. P., . . .

Spencer, R. (2018). I’m having a little struggle with this, can you help me out?”: Examining impacts and processes of a social capital intervention for first-generation college students. American Journal of Community Psychology, 61(1-2), 166–178.

Scott, J. (2000). Social network analysis: A handbook (2nd ed.) Thousand Oaks, CA: Sage. Shechtman, N., DeBarger, A., Dornsife, C., Rosier, S., & Yarnall, L, & U.S. Department

of Education, Office of Technology. (2013). Promoting grit, tenacity, and perseverance: Critical factors for success in the 21st century. Menlo Park, CA: SRI International, Center for Technology in Learning.

Smith, B. (2007). Accessing social capital through the academic mentoring process. Equity & Excellence in Education, 40(1), 36–46.

Stanton-Salazar, R. D. (1997). A social capital framework for understanding the social- ization of racial minority children and youths. Harvard Educational Review, 67(1), 1–41.

Stanton-Salazar, R. D., & Dornbusch, S. M. (1995). Social capital and the reproduction of inequality: Information networks among Mexican-origin high school students. Sociology of Education, 68(2), 116–135.

Steele, C. M. (1997). A threat in the air: How stereotypes shape intellectual identity and performance. American Psychologist, 52(6), 613.

Stemler, S. E. (2012). What should university admissions tests predict? Educational Psychologist, 47(1), 5–17.

Sternberg, R. J., Bonney, C. R., Gabora, L., & Merrifield, M. (2012). WICS: A model for college and university admissions. Educational Psychologist, 47(1), 30–41.

Strayhorn, T. L. (2006). Factors influencing the academic achievement of first-generation college students. Journal of Student Affairs Research and Practice, 43, 1278–1307.

Strayhorn, T. L. (2010). When race and gender collide: Social and cultural capital’s

influence on the academic achievement of African American and Latino males. The Review of Higher Education, 33(3), 307–332. doi:10.1353/rhe.0.0147

Strayhorn, T. L. (2013). What role does grit play in the academic success of black male collegians at predominantly white institutions? Journal of African American Studies, 18(1), 1–10.

Tinto, V. (2012). Completing college: Rethinking institutional action. Chicago, IL: University of Chicago Press.

558 Journal of College Student Retention: Research, Theory & Practice 23(3)

Vazsonyi, A. T., Ksinan, A. J., Jiskrova, G. K., Miku�ska, G. J., Javakhishvili, M., & Cui, G. (2019). To grit or not to grit, that is the question!. Journal of Research in Personality, 78, 215–226. doi:10.1016/j.jrp.2018.12.006

Wellman, B. (1983). Network analysis: Some basic principles. Sociological Theory, 1, 155–200.

Wolters, C. A., & Hussain, M. (2015). Investigating grit and its relations with college students’ self-regulated learning and academic achievement. Metacognition and Learning, 10(3), 293–311.

Zwick, R., & Sklar, J. C. (2005). Predicting college grades and degree completion using high school grades and SAT scores: The role of student ethnicity and first language. American Educational Research Journal, 42(3), 439–464.

Author Biographies

Daniel J. Almeida is an assistant professor of education at California Polytechnic State University – San Luis Obispo, where he coordinates the MS program in Higher Education Counseling/Student Affairs.

Andrew M. Byrne is an assistant professor of education at California Polytechnic State University – San Luis Obispo, and teaches in the MS program in Higher Education Counseling/Student Affairs.

Rachel M. Smith has an MA in Education, Counseling and Guidance special- ization from California Polytechnic State University – San Luis Obispo where she is a Coordinator of Student Development.

Saul Ruiz is a student in the MS program in Higher Education Counseling/ Student Affairs at California Polytechnic State University – San Luis Obispo.

559Almeida et al.