Too Much Grit to Quit? An Examination of Grit in Two Separate Within-Institution Contexts

Abstract

Although the grit narrative—the idea that individual success is as much a product of passion and perseverance as it is a result of intelligence and talent—has captured the public’s imagination, much of the empirical literature has focused almost exclusively on traditional-age college students attending more selective residential universities. The current investigation leveraged two distinct samples of students to explore the association between grit and a wide range of educational outcomes for location-bound and online adult college students. Regression results indicated that the perseverance subscale of grit tended to be a better predictor of persistence and graduation intentions, and social and academic integration, particularly for location-bound adult students, while the passion subscale was a better predictor of actual persistence. The results also suggest that the predictive utility of grit is weaker for online adult college students.

Keywords

grit persistence nontraditional students adult students

Researchers have long argued that college persistence reflects individual decisions and psychological processes (Bean & Eaton, 2001). More recently, empirical studies have exhibited the value of including noncognitive factors as predictors of college success. In the recent decade, studies of grit—broadly defined as perseverance and passion for long-term goals (Duckworth et al., 2007)—have attracted much attention from researchers and college administrators interested in college student success (Akos & Kretchmar, 2017; Bowman et al., 2015; Credé et al., 2017; Fosnacht et al., 2018). The vast majority of these studies have focused almost exclusively on academic performance or persistence intentions—as opposed to actual persistence—of traditional-age, high-achieving students, attending more selective residential institutions. The preponderance of the extant research has failed to examine the association between grit and many other well-established factors through which grit might operate. In light of these shortcomings, it is unclear whether grit predicts actual persistence, as well as other outcomes, such as academic and social integration, in less traditional academic contexts.

Such a focus on the heterogeneous academic settings that now collectively constitute higher education is certainly warranted. In the United States in particular, the past 50 years have witnessed an enormous transformation in the higher educational landscape: What was once a smaller educational system that provided education to a relatively small group of homogeneous students grew into to a multitiered, highly diversified postsecondary system that serves an increasingly diverse group of students (Thelin, 2013). This period of time also witnessed concomitant growth in the proportion of entering college students bearing one or more nontraditional characteristics—older than 24, employed, enrolled part-time, financially independent, commute from off-campus, or have dependent children (Deil-Amen, 2011). From 2000 to 2016, growth in adult student enrollment outpaced growth in traditional-age student enrollment (Hussar & Bailey, 2019), and according to the Lumina Foundation (2019), adult students account for 37% of all college students. Importantly, traditional higher education institutions have adapted to these demographic shifts by decentralizing (e.g., expanding via satellite campuses and education centers) and diversifying the means of educational delivery (e.g., expanding to online education), allowing institutions to effectively segment the market, while also diversifying their resource base (Marginson, 2006; Rossi & Goglio, 2020). Despite these changes, much of the extant empirical literature—including the most recent studies of grit—continues to examine college student persistence through a lens focused narrowly on traditional students attending residential college campuses.

Based on these shortcomings, this study builds on the grit literature to examine the influence of grit on a broad range of educational outcomes and process indicators related to student success, focusing specifically on nonresidential adult college students. Three research questions guided the current investigation:

To what extent does grit predict students’ academic persistence (graduation intentions and persistence behaviors)?

What is the association between grit and process indicators of success (e.g., students’ sense of belonging, academic engagement and disengagement, faculty–student interactions)?

Does grit’s association with these outcomes differ depending on the academic context?

We examined separate samples of incoming students from two distinct operations within a single private, not-for-profit university in the Southeastern region of the United States: Adult students enrolled strictly at a satellite campus of a residential university, and adult students attending this same institution’s separate online campus. This strategy ultimately allowed us to statistically test, using regression models, whether grit operates similarly across two academic contexts that are reflective of the aforementioned decentralization and diversification strategies employed by institutions. Importantly, in light of current research demonstrating the malleability of grit (Eskreis-Winkler, 2015), understanding the relationship between grit and these outcomes could prove vital for planning and aligning targeted retention interventions.

The next section of this article discusses the broader grit literature that informed this study. Following this review is an overview of the methodology employed, a summary presentation of the statistical results, and a discussion of the findings to help situate the current study within the grit literature.

Literature and Theoretical Underpinnings

Grit is defined as a personality trait that reflects individuals’ capacity to sustain both effort and interest in undertakings that take substantial time and commitment to complete (Duckworth & Quinn, 2009). It is comprised of two lower-order dimensions: Perseverance of effort (hereafter, GPE), which reflects individuals’ inclination to sustain effort in the face of setbacks and challenges, and consistency of interest (hereafter GCI), which reflects individuals’ inclination to pursue the same goal over a prolonged period of time. The earliest proponents of the concept argued that grit can provide the key to understanding high achievement in a way that other closely related personality traits, such as conscientiousness, could not, primarily because grit emphasizes long-term stamina, as opposed to short-term intensity (Duckworth & Quinn, 2009), and it embodies consistent goals and interests (Duckworth et al., 2007). The first empirical study of grit found a positive association between grit and educational attainment in adults age 25 years or older, even after controlling for the conscientiousness (Duckworth & Quinn, 2009; Duckworth et al., 2007). That is, there is evidence of incremental predictive validity of grit for education, above and beyond the effect of conscientiousness, for adults. In the studies that followed, individuals with more grit were found to be less likely to shirk their commitments, change their careers less frequently, divorce at lower rates, stay with their employers longer, and demonstrate higher commitment in the military (Duckworth & Quinn, 2009; Duckworth et al., 2007; Eskreis-Winkler et al., 2014; Robertson-Kraft & Duckworth, 2014; Suzuki et al., 2015). Collectively, these early studies lend support to the argument that adults that are higher on grit are more likely to stay the course. For the current study, grit is particularly appealing given that adult and nontraditional students tend to experience additional obstacles related to their roles as parents and workers (Markle, 2015).

Grit and College Student Success

The earliest empirical studies of college student success and grit focus almost exclusively on high-achieving students. For example, a handful of studies have shown that grit predicts achievement at United States Military Academy (West Point), including completion of a rigorous summer training program (Duckworth & Quinn, 2009; Duckworth et al., 2007), cumulative academic performance (Kelly et al., 2014), retention through various specific courses (Eskreis-Winkler et al., 2014; Kelly et al., 2014), and graduation (Kelly et al., 2014). Grit has also been shown to predict academic performance, even after controlling for cognitive ability, as measured by the SAT, for students at an Ivy League University (Duckworth et al., 2007). In a study of first-year, traditional-age college students from a highly selective private university in the Southern region of the United States, Chang (2014) found that the perseverance subscale of grit was predictive of first-year GPA.

Grit's relationship with college success has been examined in nonelite college contexts as well, with the vast majority of this published scholarship focusing specifically on grit’s relationship with academic performance—a more proximal outcome, rather than persistence or degree completion—more distal outcomes. This focus stems from the argument that noncognitive attributes, like grit, have an indirect effect on longer-term outcomes, such as persistence, through academic performance (Farrington et al., 2012; Richardson et al., 2012). A growing number of studies of traditional-age college students at public universities have found a consistent relationship between grit and GPA (Bowman et al., 2015; Cooper, 2014; Strayhorn, 2014). For example, Bowman et al.’s (2015) multiinstitution study found that GPE had a moderate-size positive effect on college GPA; however, they did not find a statistically significant relationship between GCI and college GPA. In a recent multiinstitution study of first-year and senior-year college students, both GPE and GCI were found to have a positive association with college GPA (Fosnacht et al., 2018). Despite the disproportionate number of studies focusing on traditional, residential college students, the paucity of studies that include college persistence (e.g., fall-to-fall persistence) as an outcome measure makes it difficult to conclude whether grit affects the likelihood of actually persisting or graduating from college.

There is some evidence—though limited to a small handful of studies—that suggests that grit operates similarly for nontraditional students. This strand of research has focused on an exceedingly unique or small student population. For example, examining a very small sample of nontraditional students at a for-profit institution, Ryan (2015) found that students who reported higher levels of grit were more likely to persist. In a study of nontraditional doctoral students at a midsize private institution in Southwest United States, Cross (2013) found that grit predicts academic performance in students’ program of study. In their study of older, female, nontraditional students (mean age of 37 years) at an open-enrollment university in South Korea, Hwang et al. (2018) found that GPE had a positive indirect effect on academic performance, as measured by students’ current GPA; GCI, on the other hand, did not have a significant effect on students’ GPA. And finally, studying both traditional and nontraditional students, Warden and Myers (2017) found that grit predicts academic performance of younger college students (24 years of age or younger), but does not predict performance for older students.

At best, it can be argued that this small body of research lends some evidence that grit's association with college success might not be context dependent. However, these studies fail to account for many of the factors known to be important to student persistence and academic performance, making their findings difficult to leverage in practice. A smaller body of empirical research focusing on traditional-age college students demonstrates the potential value of considering how grit relates to processes that contribute to student success.

Grit and Process Indicators of Success

Higher education scholars have long noted the importance of students’ academic and social integration to success in college, for both traditional and nontraditional students (e.g., Bean & Metzner, 1985; Pascarella & Terenzini, 1980; Tinto, 1993). Academic integration, including broader engagement and disengagement behaviors, as well as student interactions with faculty inside and outside the classroom, has been shown to be predictive of retention for nontraditional college students (Bean & Metzner, 1985; Chen & Hossler, 2017; Wolf-Wendel et al., 2009). Numerous scholars have also emphasized that students’ sense of belonging, a measure students’ social integration, is also critically important to student retention (Hoffman et al., 2002; Hurtado & Carter, 1997). Researchers have only recently begun to examine grit’s association with these process indicators of college success, such as academic engagement, sense of belonging, and faculty–student interaction, as well as more intermediate outcomes, such as students’ intent to persist and graduate (Bowman et al., 2015; Cooper, 2014). For scholars and college administrators interested in better understanding the potential mechanisms through which grit influences longer-term student outcomes (e.g., persistence, graduation, etc.), this new area of research is perhaps the most promising avenue.

Although few in number, several studies demonstrate an association between grit and process indicators of success. In their analysis of 395 Australian university students, Hodge et al. (2018) found that both facets of grit were predictive of academic engagement. In a larger multiinstitution study, Fosnacht et al. (2018) found that GPE was significantly and positively associated with academic engagement behaviors, such as allocating time to prepare for classes; GCI, on the other hand, was found to have a weaker, yet positive, association for first-year students, but no meaningful association with engagement for senior-year students. This same study also found that GPE was positively, and GCI was negatively, related to faculty–student interactions, supporting similar findings from earlier studies (e.g., Bowman et al., 2015). While sense of belonging has been well established by the higher education scholarship, to date, only one empirical study has examined the relationship between grit and students’ sense of belonging. Bowman et al. (2015) found that sense of belonging was not statistically associated with GCI, but was positively associated with GPE. This same study—one of only a couple that examines grit’s relationship with persistence intentions—also found that GPE was predictive of intent to persist in college.

Despite these incremental steps forward, this review reveals serious limitations in the grit research, particularly for scholars and practitioners interested in less traditional student populations. Very few studies have examined the association between grit and college success for adult or nontraditional college students—a population that is especially vulnerable to the risks associated with early departure from college. This dearth of empirical research makes it difficult to assert strong conclusions about the predictive validity of grit for this understudied population.

Data and Methods

Data Source

The current investigation leveraged survey data collected as part of a larger, multiinstitution study, focusing on nontraditional adult students and longer-term persistence and graduation. The current study’s data were drawn from a single private, not-for-profit university in the Southeastern region of the United States. Students of this institution were enrolled either at this institution’s traditional residential campus, which primarily serves traditional-age first-time in college (FTIC) students; at one of its satellite (nonresidential) campuses; or strictly online via the institution’s dedicated online campus. Almost 95% of the students enrolled at the satellite and online campuses were categorized by the institution as nontraditional, adult, non-FTIC students. For this reason, given the purpose of this study, the satellite and online campuses were selected for the current investigation. It is important to note that while age has been used as a proxy for nontraditional status, scholars of adult education typically define nontraditional status in a more nuanced manner, taking into account social roles (e.g., Messemer & Valentine, 2004), whether a student commutes or attends a nonresidential campus (e.g., Bean & Metzner, 1985), or the presence of one or more risk factors associated with nontraditional students, such as delayed enrollment, part-time attendance, employment status, the presence of dependents, or being a single parent (Deil-Amen, 2011). Thus, while 18-year-old students constituted a small percentage of enrollments at the satellite and online campuses of this institution, they were included in this study—and are referred to as nontraditional adult students—based on the fact that they were all nonresidential students.

Surveys were administered to students who enrolled for the first time at one of the three large satellite campuses, all within the Southeastern part of the United States, or at this institution’s dedicated online campus, during the fall 2018 or fall 2019 semesters. An online survey was administered at the midpoint of the semester to 1,500 undergraduate students—half were students enrolled at the online campus—randomly drawn from a larger pool of new, degree-seeking adult students who fit the eligibility requirements. Of these students, approximately 54% of the online students and 67% of the satellite campus students responded to the survey; and of these responses, 91% and 87% were complete across all items used in the analyses, leaving a final sample of N = 368 and N = 439, respectively.

Sample

The satellite campus sample was typical of students enrolled at these off-campus locations, in terms of age (M = 35.8 years), gender (76% female), employment while enrolled (66% employed full time, 18% employed part time), and the percentage who were the primary caretaker of a dependent child (52%). The online campus sample was also reflective of the typical students enrolled exclusively at the online campus, in terms of age (M = 36.2 years), gender (76% female), employment while enrolled (73% employed full time, 13% employed part time), and the percentage who were the primary caretaker of a dependent child (50%). Aside from slight differences in employment status, these two samples were remarkably similar to each other.

Measures

Grit

Grit was assessed with the previously validated short grit scale (Duckworth & Quinn, 2009), an eight-item self-report questionnaire used widely in both higher education and other social science research (Credé et al., 2017). The scale assesses two separate facets of grit: GPE (e.g., “I finish whatever I begin”) and GCI (e.g., “I often set a goal but later choose to pursue a different one”), with items presented on a five-point response scale, ranging from (1) “not at all like me” to (5) “very much like me.” After reverse scoring responses to the GCI items, subscale scores were computed as an average across all items, with higher subscale scores indicating higher levels of grit. To confirm that items were measuring the same latent construct in this study, each scale’s internal consistency was assessed using Crobnbach’s alpha—a measure of scale reliability—given its wide acceptance for this purpose (Nunnally & Bernstein, 1994). This additional step was taken for each of the scales in this study due to the fact that a scale’s reliability is a characteristic of the responses and the underlying sample, as opposed to the question items themselves (Streiner, 2003). A minimum alpha of 0.70 is commonly considered an acceptable threshold for scale reliability (Lance et al., 2006). Additionally, an item-rest correlation was calculated to identify how well each item correlated with a scale computed from all of the other related indicators; this step tests for convergent and divergent properties for each item, and provided grounds for excluding poor-fitting items from the scales that were created in this study. Finally, given that outliers can inflate the estimates of Cronbach’s alpha (Liu et al., 2010), all items were analyzed for the presence of outliers; analyses revealed that outliers were not problematic for the scales used in this study. Of the four original items, only three were retained for the GPE subscale (satellite: α = 0.74, M = 4.36; online: α = 0.79, M = 4.42), due to poor a very low item-rest correlation for one item (“Setbacks don’t discourage me”). All four items were retained for GCI (satellite: α = 0.79, M = 3.52; online: α = 0.79, M = 3.61). Given the recent finding that combining the GPE and GCI scores into an overall grit score (here, α = 0.80) deteriorates the ability to predict outcomes (Credé et al., 2017, p. 502), and taking into account recent findings that most of the predictive power of grit is concentrated in the former (Fosnacht et al., 2018), this study opted to include the separate facets rather than the overall grit score.

Dependent Variables

Following recent studies of traditional college students (Bowman et al., 2015), the current investigation included two outcome measures related to student intentions: intent to persist and intent to graduate. Each of these outcomes were measured by single question items, respectively, using a 6-point ordinal scale (1 = very uncertain to 6 = very certain). While persistence intentions have certainly been shown to be predictive of actual persistence (Cabrera et al., 1992), we have long known that intentions can sometimes have no statistical association with actual persistence (see, e.g., Perry et al., 1999), and thus intent to persist has always been a second-best alternative when data on actual persistence are unavailable. Fortunately, unlike previous grit research, the current study also collected data related to actual persistence decisions, measured here as a dichotomous variable (where 1 = persisted to the second term).

Several additional outcomes were included in order to examine the association between grit and process indicators that reflect social and academic integration; many of these scales were drawn from the deep well of integration research. One scale was included to capture social integration: An 8-item sense of belonging scale (Hurtado & Carter, 1997), which taps into perceptions of integration into the university community (e.g., “I see myself as a part of the university community,” 1 = strongly disagree to 5 = strongly agree; α = 0.95 for satellite students; α = 0.93 for online students). Three scales were included in this study to reflect students’ academic integration: A 3-item academic engagement scale designed to capture frequency of behaviors that are supportive of academic success (e.g., “Interacted with faculty during classes,” 1 = never to 5 = very often; α = 0.83 for satellite students; α = 0.72 for online students); a 4-item academic disengagement scale to measure behaviors that are counterproductive to academic success (e.g., “Did not attend a scheduled class,” 1 = never to 5 = very often; α = 0.73 for satellite students; α = 0.76 for online students); and a commonly-used 5-item faculty–student interaction scale (Nora & Cabrera, 1996), which captures perceptions of informal interaction with faculty (e.g., “I am satisfied with the opportunities to engage with faculty outside the classroom,” 1 = strongly disagree to 5 = strongly agree; α = 0.76 for satellite students; α = 0.83 for online students).

Control Variables

Although not a central focus of this study, given that prior research has shown that students’ background characteristics are associated with success in college (Bean & Metzner, 1985), this study also controlled for the effects of age, gender, race/ethnicity, self-reported family income, and cognitive ability. For the latter, due to the length of time since high school graduation for many of the study participants, and given the importance of cognitive ability to success, the current investigation included a measure of verbal intelligence, Wordsum, measured using a 10-item battery of questions.¹

Statistical Analyses

In the current study, hierarchical multiple regression models were employed to assess the extent to which grit predicts unique variance in the seven distinct outcomes, controlling for the effects of the demographic control variables. The first step was to regress each outcome on a block of demographic characteristics, including age, gender, race/ethnicity, self-reported family income, and cognitive ability. The second step added both grit subscales to the initial model. Although not shown in the tables, Akaike’s information criteria and Bayesian information criterion (BIC) were used to adjudicate between the initial model and the full model with both grit subscales (Raftery, 1995). Ordinary least squares (OLS) regression models were used for all continuous outcomes (sense of belonging, academic engagement and disengagement, and faculty–student interactions), ordinal logit regression models were employed for single-item ordinal outcomes (intent to persist and intent to graduate), and logit regression analysis was used for the binary outcome persistence. Because changes in logits are not intuitive, odds ratios (e^logits) were reported for a more straightforward interpretation. Additionally, we reported coefficients of determination (Adjusted R²) for each model, and changes in Adjusted R² (△R²), to demonstrate the incremental increase in the variance accounted for when grit is added to each model (i.e., the second step).

Results

Grit, Persistence, and Intentions

Results from the logistic regression models conducted separately for the satellite and online student samples revealed that grit operates differently for the satellite campus students, compared to the online students. As shown in Table 1, after controlling for other variables in the ordered logistic regression models, GPE was positively associated with persistence intentions (OR = 3.04, p < .001) and graduation intentions (OR = 3.57, p < .001), but only for the students attending the satellite campuses. GPE was not predictive of actual fall-to-spring term persistence. GCI, on the other hand, was found to have a statistically significant association with actual persistence (OR = 1.64, p < .01), but only for the satellite campus students. For online students, GCI was associated with graduation intentions (OR = 1.46, p < .01).

Table 1.

Odds Ratios for Grit Predicting Persistence and Intentions Outcomes.

	Satellite campus students						Online campus students
	Perseverance of effort		Consistency of interest				Perseverance of effort		Consistency of interest
Dependent variable	OR	SE	OR	SE	R ²	△R²	OR	SE	OR	SE	R ²	△R²
Persistence: fall-to-spring	1.03	0.30	1.64**	0.30	0.11	0.04	1.2	0.30	0.95	0.30	0.05	0.01
Persistence intentions	3.04***	0.82	1.13	0.21	0.13	0.10	1.17	0.82	1.15	0.21	0.10	0.01
Graduation intentions	3.57***	0.91	1.14	0.20	0.18	0.13	1.1	0.91	1.46**	0.20	0.09	0.02

Note. OR = odds ratio; SE = standard error.

*p < .05; **p < .01; ***p < .001. All hierarchical logistic regression models were conducted with all control variables (age, gender, race/ethnicity, WORDSUM, and self-reported family income) entered in the first step, followed by the inclusion of both grit variables in the second step. Adjusted R² are reported for the full models; △R² are reported to show the difference between the adjusted R² for the initial versus final models, for each outcome.

It is worth pointing out that the model fit statistics for the online regression models showed weak justification for the inclusion of grit, compared to the more parsimonious model with only control variables. In the graduation intentions analysis, the BIC for the model with grit (861) was higher than the BIC for the more parsimonious model (858). The BIC statistic penalizes for the addition of each variable to the model; given that one of the two additional parameters was not statistically significant, this small difference is understandable. An alternative specification that leaves out GPE, but includes GCI, results in a slightly lower BIC (855), reflecting an improved fit of the data over a model without grit; however, there is no theoretical justification for measuring one subscale absent of the other. With this caveat in place, the inclusion of measures of grit appears to be justified, even if weakly, for online model of graduation intentions. Nevertheless, it is clear that grit does a much better job of explaining the persistence, persistence intentions, and graduation intentions, for the satellite campus students.

Grit and Process Indicators of Success

Based on the results from the regression models, grit was found to be predictive of the process indicator outcomes that reflect students’ social and academic integration. For both samples of adult students, as shown in Table 2, GPE was positively associated with students’ sense of belonging (β = 0.33, p < .001 for satellite students; β = 0.14, p < .01 for online students) and academic engagement behaviors (β = 0.33, p < .001 for satellite students; β = 0.25, p < .001 for online students), after controlling for other variables in the OLS regression models. GPE was also positively associated with faculty–student interactions, but only for the students taking their courses at the satellite campus (β = 0.16, p < .05). Across both samples, GPE was negatively associated with behaviors related to academic disengagement (β = −0.20, p < .01 for satellite students; β = −0.11, p < .05 for online students), as was GCI (β = −0.32, p < .001 for satellite students; β = −0.24, p < .001 for online students). Perhaps surprisingly, given the findings of the extant research, GCI was also found to be predictive of students’ sense of belonging (β = 0.11, p < .05) and academic engagement (β = 0.11, p < .05), but only for online students.

Table 2.

Regression Coefficients for Grit Predicting Social and Academic Integration Outcomes.

	Satellite campus students						Online campus students
	Perseverance of effort		Consistency of interest				Perseverance of effort		Consistency of interest
Dependent variable	β	SE	β	SE	R ²	△R²	β	SE	β	SE	R ²	△ R²
Sense of belonging	0.33***	0.09	0.04	0.06	0.17	0.12	0.14**	0.06	0.11*	0.05	0.13	0.04
Academic engagement	0.33***	0.10	0.07	0.06	0.19	0.12	0.25***	0.07	0.11*	0.05	0.13	0.09
Academic disengagement	−0.20**	0.09	−0.32***	0.06	0.24	0.18	−0.11*	0.05	−0.24***	0.04	0.11	0.08
Faculty–student interaction	0.16*	0.14	0.08	0.09	0.12	0.04	0.06	0.10	0.06	0.08	0.08	0.01

Note. SE = standard error.

*p < .05; **p < .01; ***p < .001. All hierarchical ordinary least squares regression models were conducted with all control variables (age, gender, race/ethnicity, WORDSUM, and self-reported family income) entered in the first step, followed by the inclusion of both grit variables in the second step. Adjusted R² are reported for the full models; △R² are reported to show the difference between the adjusted R² for the initial versus final models, for each outcome.

Discussion

The current investigation sought to expand upon the extant literature by examining grit’s association with a broader set of outcomes related to, and reflective of, success in college, across two different college contexts that represent understudied, yet increasingly common corners of higher education, with a special focus on adult students. Three research questions guided this study: (a) To what extent does grit predict students’ academic persistence? (b) What is the association between grit and process indicators of success?, and (3) Does grit’s association with these outcomes differ depending on the academic context?

Addressing the first research question, this study found that grit was a statistically significant predictor of both proximal and distal persistence measures. Specifically, this study found that GPE was predictive of persistence intentions for satellite campus students, and graduation intentions for both satellite campus and online students. Scholars of student success have long known that students’ intent to persist to graduation serves as an intermediate step in the eventual persistence/attrition decision process (Cabrera et al., 1993), making it particularly appealing for college administrators. Perhaps one of the most important contributions of this study is the finding that GCI was predictive of actual persistence for satellite campus students. This association might best be understood by considering the original conceptualization of GCI as the “passion” aspect of grit (Duckworth et al., 2007). The foundational literature on passion (e.g., Vallerand et al., 2003) suggests that individuals with more passion for an activity are more likely to invest the time and energy needed to take part in it, because the activity itself has become a part of the individual’s identity, its importance has been internalized, and time and energy are viewed as a meaningful investment. More recently, Schmidt et al. (2020) argued that GCI represents an “ability to adhere to a given goal over longer periods of time more explicitly” (p. 17). Thus, it is possible that college students with higher levels of passion are more inclined to understand the importance of completing college and are in turn more likely to make the necessary time investments that are important to college persistence. Nevertheless, the finding that grit was not associated with the actual persistence of online college students suggests that there is still much to be learned about this group of students.

Regarding the second research question, the findings of current study parallel the extant grit research on traditional college students. The finding that GPE was generally predictive of process indicators of success lends further support to Bowman et al.’s (2015) conclusion that grittier students are more likely to take advantage of and benefit from the opportunities that exist in college. Specifically, the positive relationship between grit and academic engagement, and negative association between grit and academic disengagement, observed for both samples studied in this paper, aligns with the findings from previous studies (Fosnacht et al., 2018; Hodge et al., 2018). This finding also lends support to a growing body of empirical research demonstrating an association between grit and more general engagement behaviors for noncollege populations (Datu et al., 2016; Von Culin et al., 2014). Furthermore, the current investigation found that the perseverance aspect of grit was predictive of faculty–student interactions, a finding that supports recent research (Bowman et al., 2015; Fosnacht et al., 2018). While these previous studies found a significant negative association between GCI and faculty–student interactions, the current study did not find a statistically significant association. This departure might be attributable to the different student populations. And finally, the current study provides perhaps the earliest empirical evidence that grit predicts students’ sense of belonging for adult students, a finding that aligns with the previous research at traditional residential universities (Bowman et al., 2015). Taken altogether these findings demonstrate a connection between grit and academic and social integration—two critical components of college success that have been the focal points of a long history of college persistence literature (e.g., Pascarella & Terenzini, 1980; Tinto, 1993).

Regarding the third research question, despite strong similarities between the online and satellite student samples, the findings suggest that grit might operate differently for students pursuing their education completely online. For example, factoring grit into the persistence and intention models added very little explanatory power to the models for online campus students. Additionally, while the findings of this study support the inclusion of grit into the process indicator models, grit tended to account for less variability in these outcomes for the online student models compared to the satellite campus student models. For example, comparing the satellite student and online student models, grit accounted for 12% versus 4% of the variability in sense of belonging, and 18% versus 8% of the variability in academic disengagement behaviors, respectively. The findings suggest that some of the underlying factors that distinguish online students from satellite campus students might mediate the relationship between grit and the outcomes examined in this study. Consequently, it is important that future studies examine these student populations separately, rather than as a monolithic group.

The findings from this study could prove useful for practitioners interested in adult college student success, particularly in light of recent studies showing that grit can be augmented through interventions (Eskreis-Winkler, 2015; Murray et al., 2019). Institutions could replicate this study at very low cost; for institutions that observe similar findings, administrators could examine how grit interventions might be used to cultivate grit as a means to bolstering students’ academic and social integration, and ultimately, their persistence in college. For example, interventions aimed at helping college students identify their personal signature strengths (e.g., Peterson & Seligman, 2004) have been shown to increase students’ passion (Forest et al., 2012). Passion-strengthening interventions could help students understand the importance and relevance of college-related activities to degree completion, and help students understand time and energy allocated to academic activities as a meaningful investment. Another group that might benefit from the results of this study consists of admissions professionals. Taken together with the findings from recent studies (e.g., Fosnacht, et al., 2018), the findings from this study support using grit in conjunction with traditional data to help admissions personnel identify students who might otherwise be turned away based on existing criteria.

As with all studies, the current investigation has several limitations that should guide future grit research. First, although study participants were enrolled at various locations within one university’s campus system, the fact that all students were from the same university in the United States limits the generalizability of the findings. Future studies should extend these findings to other contexts. Second, while access to institutional data helped address limitations of the extant literature via the inclusion of a measure of actual persistence, many of the other outcome variables reflect intentions (e.g., intent to graduate) or perceptions, rather than observed behaviors or outcomes. Longitudinal data could be used to examine whether grit predicts longer-term outcomes, such as college graduation. If long-term success is associated with grit, as proponents argue, graduation is an ideally suited outcome measure for future studies.

Despite these limitations, the findings from this study provide an important contribution to the grit literature, by examining how grit operates across heterogeneous academic settings that exist within even a single institution. This study is important because it provides evidence of grit’s association with important educational outcomes and processes for less traditional, adult college students, while also shedding light on an area in which we clearly still need more research—online adult college students. The two academic settings examined here are not unique to this institution; segmentation within and between institutions is a hallmark of higher education, particularly in light of increased uncertainty and competition for resources (Slaughter & Rhoades, 2004). For nonelite institutions, satellite campuses and online learning options reflect a strategy of place-filling and expansion that has been underway for decades (Marginson, 2006). For these institutions, the findings from this study have potential implications for administrators interested in bolstering student success.

Footnotes

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

William Hamilton

Notes

Author Biography

William Hamilton is the Chief Assessment and Institutional Research Officer at Saint Leo University, where he also teaches courses in sociology. He received his Ed.D. from the University of Florida, and graduate degrees from the University of Arizona (sociology) and Georgia State University (economics). His research uses a sociological lens to examine higher education issues, including student success, organizational leadership, and the experiences of nontraditional students in college.

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