Psychosocial Keys to African American Achievement? Examining the Relationship Between Achievement and Psychosocial Variables in High Achieving African Americans

Abstract

Grit, growth mindset, ethnic identity, and other group orientation are four psychosocial variables that have been associated with academic achievement in adolescent populations. In a sample of 105 high achieving African American high school students (cumulative grade point average [GPA] > 3.0), we examined whether these four psychosocial variables contributed to the achievement of high achieving African Americans beyond the contribution of socioeconomic status (SES) and other demographic variables. Results indicated that the psychosocial variables were not significant predictors of academic achievement for the high achieving African American students in this sample. However, SES was a significant predictor of the academic achievement with a medium effect size. These findings suggest that interventions focused on grit, growth mindset, ethnic identity, and other group orientation may not be as effective as hypothesized.

Keywords

academic achievement ethnic identity future orientation grit growth mindset other group orientation

The academic achievement gap between minority and majority students is by far one of the most urgent issues in American education (Paige & Witty, 2010). This issue persists despite the best efforts of many scholars and policy makers (Cohen, Steele, & Ross, 1999; Exec. Order No. 13621, 2012; No Child Left Behind, 2003; Yeager & Walton, 2011). However, a burgeoning body of literature has suggested that psychosocial variables—that is, individuals’ thoughts, beliefs, or feelings that affect their actions in or interpretations of the world—might be the key to closing the gap (Cohen et al., 1999; Duckworth, 2016; Yeager & Walton, 2011). An example of this viewpoint is captured in an assertion by Dweck, Walton, and Cohen (2014):

In our pursuit of educational reform, something essential has been missing: the psychology of the student. Psychological factors—often called motivational or non-cognitive factors—can matter even more than cognitive factors for students’ academic performance. These may include students’ beliefs about themselves, their feelings about school, or their habits of self-control . . . These factors also offer promising levers for raising the achievement of underprivileged children and, ultimately, closing achievement gaps based on race and income. (p. 2)

Despite promising recent studies examining this assertion (e.g., Claro, Paunesku, & Dweck, 2016; Dixson, Worrell, Olszewski-Kubilius, & Subotnik, 2016; Robbins et al., 2004; Strayhorn, 2013; Walton & Cohen, 2011), no studies appear to have examined whether psychosocial variables, either singularly or in combination, actually contribute to the achievement of high achieving minority students. In this study, we examined to what extent four psychosocial variables—grit, ethnic identity, other group orientation, and growth mindset—that have been associated with the academic achievement of minority students (Blackwell, Trzesniewski, & Dweck, 2007; Strayhorn, 2013; Worrell, 2007; Yeager & Dweck, 2012), contribute to the achievement of high achieving African Americans students. The goal of the current study is to better understand how much African Americans can benefit from interventions targeting these psychosocial variables.

Two of these four variables—grit and growth mindset—were chosen because they are some of the more popular psychosocial constructs that have been asserted to have ramifications for the achievement gap (see Duckworth, 2016; Yeager & Walton, 2011). The two identity variables (ethnic identity and other group orientation) were chosen on the basis of empirical findings with academically talented African American students (Worrell, 2007; Worrell & White, 2009), which are in keeping with theoretical models implicating cultural identities in the academic performance of students underrepresented in gifted and talented education programs (see Worrell, 2015, for an overview). We begin by introducing each of the psychosocial variables, discussing how they are related to academic achievement, and reviewing the studies that assert that they could increase the academic achievement of African American students. Then, we discuss socioeconomic status (SES) and its relationship to academic achievement, as any contribution of the four psychosocial variables should be beyond the contribution of this important demographic marker, which is also associated with academic outcomes (Sirin, 2005).

Grit

The first variable of interest is grit. Grit is one’s perseverance and passion for accomplishing long-term goals (Duckworth, Peterson, Matthews, & Kelly, 2007). Duckworth et al. (2007) argued that grit is made up of two interrelated subfactors: consistency of interests and perseverance of effort. Consistency of interests refers to how stable one’s interests are over time and perseverance of effort refers to how long and hard one is willing to work toward one’s goals even when setbacks occur (Duckworth et al., 2007). Although grit is usually measured using either the Grit Scale (Duckworth et al., 2007) or the Short Grit Scale (Grit-S; Duckworth & Quinn, 2009), recent research suggests that there is not strong psychometric evidence for measuring grit as a hierarchical construct and that grit should instead be measured using its two subfactors (Credé, Tynan, & Harms, 2016). Studies have shown that grit is associated with success in stressful competitions (Duckworth et al., 2007; Duckworth & Quinn, 2009), educational attainment and academic success (Duckworth et al., 2007; Duckworth & Quinn, 2009), retention in the United States Military Academy (Duckworth et al., 2007), emotional stability (Credé et al., 2016), teacher effectiveness (Duckworth, Quinn, & Seligman, 2009), success in life (Duckworth & Gross, 2014), and conscientiousness (Duckworth et al., 2007; Duckworth & Quinn, 2009).

Grit and Academic Achievement

Several studies have been conducted on grit and academic achievement. Duckworth et al. (2007) found that students with more grit obtained higher grade point averages (GPAs) than students with less grit (r = .25, p < .01), with a modest increase in the relationship when ability is controlled for (r = .34, p < .001). In addition, Duckworth et al. (2007) found that adults with more grit reported higher educational attainment than adults with less grit, even after age was controlled for, F(5, 1535) = 15.48, p < .001, although the effect size was quite low, η² = 0.05. Duckworth and Quinn (2009) conducted two assessments of the relationship between grit and GPA and found that the correlations between grit and GPA, controlling for age, was .30 and .32, respectively.

However, the hypothesized association between grit and academic achievement is not uncontested. Credé et al. (2016) conducted a meta-analysis that included an assessment of the association between grit and academic achievement. In their meta-analysis of 37 studies, including over 12,000 students, the researchers found that the average correlation between the total grit score and GPA was .17, the average correlation between the perseverance of effort subfactor and GPA was .26, and the average correlation between the consistency of interests subfactor and GPA was .10. They concluded that the total grit score added less than 1% incremental variance after controlling for conscientiousness, effort added about 9% to high school GPA and 2% to college GPA, and interests added no unique variance. Credé et al. also hypothesized that the negative coefficients for interests might be indicative of a suppressor effect on the effort factor.

Grit and the Academic Achievement of African American Students

Several studies have indicated that grit may be a pathway to increase African American achievement (Alan, Boneva, & Ertac, 2016; Shechtman, DeBarger, Dornsife, Rosier, & Yarnall, 2013; Strayhorn, 2013). For example, in a large-scale randomized experiment, Alan et al. (2016) found that elementary school students who were trained on the importance of sustained effort toward accomplishing one’s goals and forming a constructive interpretation of setbacks were about 10% more likely to (a) persist in attempting challenging academic tasks, (b) prefer challenging academic tasks even after failure, and (c) succeed and collect higher payoffs than those students not trained. Furthermore, these authors argued that their results lay the foundation for minority and disadvantaged youth to succeed in school settings as their success in school could be accomplished through sustained grit.

In support of this interpretation, Strayhorn (2013) found that grit was about as predictive of college grades as high school achievement and performance on the American College Test (ACT) in a sample of 140 African American college students (β_grit = .24, p < .01; β_ACT = .28, p < .05; β_HS-GPA = .31, p < .01). In addition, he found that grit added to the variance explained in college grades beyond high school achievement, educational aspirations, and ACT scores (β_grit = .24, p < .01). Collectively, these studies indicate that grit plays a major role in the academic achievement of African American adolescents and may be a pathway to close the achievement gap.

Growth Mindset

The second variable of interest is growth mindset. Dweck (2002) identified two sets of beliefs that people have about their own intelligence, a fixed mindset and a growth mindset. A fixed mindset can be defined as the belief that intelligence is a static trait. Individuals with this mindset believe that one is either born with a high or low level of intelligence and that there is very little that can be done to change one’s intelligence. In contrast, individuals with a growth mindset believe intelligence can be developed over time in various ways, such as through effort, practice, and instruction (Dweck, 2007). Essentially, an individual with a growth mindset believes the brain is similar to a muscle: The more you use it, the stronger it becomes. The two mindsets—fixed and growth—represent opposite ends of the mindset spectrum. A growth mindset has been found to be associated with high standards (Chan, 2012; Dweck, 2002), high life satisfaction (Chan, 2012), high levels of happiness (Chan, 2012), increased persistence and effort in school related activities (Dweck, 2002; O’Rourke, Haimovitz, Ballweber, Dweck, & Popović, 2014), and increased self-esteem (Murphy & Thomas, 2008). In addition, several education interventions have been developed based on growth mindset (e.g., Brainology; Ramsden et al., 2011).

Growth Mindset and Academic Achievement

In the academic domain, growth mindset has been associated with achievement in several studies (e.g., Blackwell et al., 2007; Good, Aronson, & Inzlicht, 2003). Mueller and Dweck (1998) found that a growth mindset was associated with students perceiving academic setbacks as an indication of a lack of effort and was associated with increased persistence on academic tasks after difficulty (d = 2.13 for differences between effort praise group vs. intelligence praise group). In addition, Mueller and Dweck found that after experiencing difficulty, a growth mindset was associated with either equal or increased academic performance after controlling for ability (d = 1.11 for differences between intelligence praise and effort praise groups).

In a different study, Grant and Dweck (2003) found in a year-long longitudinal study of college students that having a learning goal (implying a growth mindset) was associated with sustained intrinsic motivation (r = .39, p < .001), sustained effort and time commitment (r = .40, p < .001), active coping (β = .38, p < .01), higher academic achievement in the course overall (β = .20, p < .05), and improvement in exam grades after difficulty (β = .25, p < .01). In contrast, an ability goal (fixed mindset) predicted a loss of motivation (r = −.40, p < .001) and lower academic achievement in the face of a challenge. Taken together, these studies suggest that having a growth mindset increases academic achievement through increasing motivation and effort (Blackwell et al., 2007; Dweck, 2002).

Recently, studies have called into question growth mindset’s impact on academic performance (e.g., Duval, 2015; Li & Bates, 2017). For example, Li and Bates (2017) conducted three studies examining to what extent growth mindset interventions affect cognitive ability, grades, and performance in three Chinese samples of early adolescent students attending school in Heilongjiang Province, China (N = 624). They found that (a) those that were praised for effort did not have significantly higher scores than those praised for ability post-challenge (β = −.24, p = .064), (b) growth mindset did not predict student academic achievement over the course of two semesters (β = −.01, p = .829; β = .03, p = .723, respectively), (c) growth mindset did not predict cognitive ability for easy reasoning tasks (β = .12, p = .085) or difficult reasoning tasks (β = .12, p = .082), and (d) growth mindset did not predict enhanced learning over time (β = .03, p = .514). However, the studies calling growth mindset into question have not been conducted within the United States (Li & Bates, 2017) or are unpublished manuscripts (Duval, 2015).

Growth Mindset and the Academic Achievement of African American Students

Several researchers have asserted that growth mindset may be a pathway to close the achievement gap and increase the achievement of African American students. Blackwell et al. (2007) explored a growth mindset intervention among a mostly African American sample of middle school students. Upon finding evidence to support the assertion that growth mindset is a significant predictor of middle school student grades (β = .53, p < .05, controlling for previous achievement), they also found that eight 25-min periods of learning about the brain and how it was malleable led to increased classroom motivation (χ² = 4.72, odds ratio = 3.26, p < .05) and higher achievement (β = .53, p < .05, compared with a control group).

In another intervention study, Good et al. (2003) studied a sample of mostly Hispanic and African American middle school students. They found that those who received weekly emails about having a growth mindset throughout the year performed better on state achievement tests (d = .52) compared with the control group. The effect was particularly large for the math achievement of girls (experimental group girls’ math achievement scores were more than 1 SD higher than the control group) for whom negative stereotypes exist within the domain of math (e.g., Spencer, Steele, & Quinn, 1999). Yeager and Dweck (2012) argued that interventions like Blackwell et al.’s (2007) and Good et al.’s (2003) provide a way for adolescent students who face academic and social challenges, like many African American students do (e.g., Solorzano, Ceja, & Yosso, 2000), to achieve despite their disadvantages. This argument is based on the premise that encouraging a student to have a growth mindset will result in that student reacting to even negative environments in ways that are more conducive to academic success.

Ethnic Identity

The third variable is ethnic identity. Tajfel (1981) defined ethnic identity as an individual’s “knowledge of his membership [in] a social group” as well as “the value and emotional significance attached to that membership” (p. 225). In Phinney’s (1992) framework, ethnic identity consists of how much individuals have sought to understand their own ethnic identity, engaged in experiences common to their ethnic group, and developed a sense of belonging to their ethnic group. Ethnic identity is particularly salient in contexts with multiple ethnic groups as it highlights that one is more similar to one group over others.

Identity development is an important psychological process and a central task during the adolescent years (Erikson, 1968; Marcia, 1980), and ethnic identity may be important for ethnic minority adolescents in developing their sense of self (Erikson, 1950, 1968). Research suggests that ethnic identity attitudes have implications for positive learning, developmental, and psychological outcomes (Huang & Stormshak, 2011). In addition, several studies indicate that higher ethnic identity scores (i.e., students who have a stronger connection and commitment to their own ethnic identity) are meaningfully correlated with self-esteem (r = .49, p < .01; Phinney & Chavira, 1992), hopefulness (rs = .42, p < .01 and .35, p < .01; Adelabu, 2008), and overall psychological adjustment (r = .23, p < .001; Roberts et al., 1999).

Ethnic Identity and Achievement

In general, empirical research has suggested that ethnic identity is not related to academic achievement (Worrell, 2007). However, very few studies have examined the relationship between ethnic identity and academic achievement in African American adolescents specifically. Worrell (2007) examined ethnic identity and academic achievement in a sample of 319 academically talented adolescents attending a summer program for the academically gifted and talented. He found that for academically talented African American students, ethnic identity predicted school GPA (β = −.42; controlling for school and program rank), but did not predict summer program achievement for this group (β = .19), suggesting that context matters. In a different study, Worrell and White (2009) also examined the relationship between ethnic identity and achievement in a sample of 252 ninth- and tenth-grade students. They also reported that ethnic identity contributed negatively to school GPA for African American students (β = −.41).

However, Kerpelman, Eryigit, and Stephens (2008) found that ethnic identity was a positive predictor of grades in a sample of 354 adolescents, albeit with a small effect size (r = .20, p < .01), and Yasui, Dorham, and Dishion (2004) found that ethnic identity was a meaningful predictor of GPA within a sample of 82 African American adolescents (r = .57, p < .05); these results contradict the findings of Worrell (2007) and Worrell and White (2009). Thus, it is not yet clear what the true nature of the association is between ethnic identity and school achievement for African Americans.

Other Group Orientation

The next variable of interest is other group orientation (Phinney, 1992). Other group orientation is defined as “the general responses that members of one ethnic group have toward groups other than their own” (Worrell, Conyers, Mpofu, & Vandiver, 2006, p. 37). More specifically, it consists of one’s feelings about, willingness to engage with, and acceptance of other ethnic groups (Phinney, 1992). Studies have shown that positive other group orientation scores (i.e., students who have positive feelings about and enjoy engaging with those of other ethnic groups) predict higher self-esteem (β = .32, p < .05; Lee, 2003), social connectedness (β = .44, p < .05; Lee, 2003), sense of community (β = .30, p < .05; Lee, 2003), and academic self-concept (r = .37, p < .001; Cokley & Chapman, 2008). Studies have also indicated that other group orientation is inversely related to depression (r = −.13; Juang, Nguyen, & Lin, 2006), devaluing academic success (r = −.30, p < .001; Cokley & Chapman, 2008), and ethnic behaviors (r = −.17; Phinney, 1992).

Other Group Orientation and Academic Achievement

There are very few studies on other group orientation and academic achievement. In addition to examining the relationship between ethnic identity and achievement, Worrell (2007) also examined the relationship between other group orientation and achievement. Counter to what he found with ethnic identity, he found other group orientation to be a positive predictor of the African American students’ GPAs at their regular schools (β = .41), controlling for school and summer program rank, but it was not associated with summer program GPA (β = .12). In a closely related study, Cokley and Chapman (2008) also found that other group orientation was a statistically significant predictor of academic achievement in a sample of 274 African American college students, but with a small effect size (r = .17, p < .01). Finally, Worrell and White (2009) found within a high school sample of 252 students that other group orientation was a significant positive predictor of academic achievement for African American (β = .43) and Hispanic (β = .40) students and a significant negative predictor of achievement for Asian Americans (β = −.32). These findings suggest a positive relationship in some contexts between other group orientation and academic achievement.

SES

The major demographic variable of interest in this study is SES. Although age and gender do contribute to academic achievement, the correlations of these variables to achievement are very low (d = .08 for gender and .04 for age; Hattie, Masters, & Birch, 2015). SES is defined generally as the amount of resources at an individual’s disposal. SES is measured in many ways, such as family income, parental education, qualifying for a free or reduced lunch, or the neighborhood in which an individual resides (Sirin, 2005). In this study, we used mother’s education to operationalize SES. Mother’s educational level has been used as an indicator of a family’s SES in many adolescent studies (see Aarø et al., 2009) and has been found to have a similar relationship to academic achievement as family income (r = .29 for income; r = .30 for parental education; see Sirin’s, 2005, meta-analysis). In addition, Davis-Kean (2005) found that parental education was comparable with family income in predicting academic achievement (r = .38 vs. .33, respectively). Higher levels of SES have been associated with better overall health (Hayward, Miles, Crimmins, & Yang, 2000), less mental health problems (Hudson, 2005), lower drop-out rates (Cairns, Cairns, & Neckerman, 1989), increased life satisfaction (Louis & Zhao, 2002), and increased academic development throughout childhood (Hart & Risley, 2003).

SES and Academic Achievement

Several studies have focused on the relationship between SES and academic achievement. Sirin (2005) conducted a meta-analysis consisting of 79 effect sizes gathered from 74 independent samples that included over 100,000 students, and found that the average correlation between SES and GPA was .32, a medium effect size. Similar findings were reported by Hattie (2008), who conducted a meta meta-analysis of the relationship between academic achievement and SES. His meta-analysis of 499 studies included over 176,000 people and 957 effect sizes. He also found that the average effect size between academic achievement and SES was in the medium range (d = .57).

Studies focused on African American adolescents mirror these findings. Jeynes (2005) found in a nationally representative sample of 2,260 African American adolescents that the higher a student’s SES (as measured by a composite of both parents’ education, occupation, and income), the higher the contribution of SES to academic achievement (.19 ≤ β ≤ .94). In a different study, Irving and Hudley (2008) found within a sample of 115 high school African Americans students that SES again predicted GPA (r = .29). Altogether, these studies indicate that a meaningful relationship between SES and academic achievement exists for students in general as well as for African American students specifically.

The Current Study

In the current study, we explored the associations between four psychosocial variables—grit, growth mindset, ethnic identity, and other group orientation—and academic achievement in a sample of high performing African American adolescents, to ascertain how much variance beyond SES these variables contribute to the academic achievement of these students. The following research questions guided this study. First, are grit, ethnic identity, other group orientation, and growth mindset meaningfully correlated with academic achievement in this sample? Second, are these variables meaningful predictors of academic achievement in this sample? Third, do they contribute incremental variance to academic achievement beyond the contribution of SES?

We had several hypotheses. First, in keeping with previous research (Blackwell et al., 2007; Credé et al., 2016; Mueller & Dweck, 1998), we hypothesized that growth mindset and the effort subfactor of grit would have positive and statistically significant relationships with academic achievement. Second, we hypothesized that the interests subfactor of grit would not be related to academic achievement, and we examined the model with and without interests to see if it were suppressing the contribution of effort as Credé et al. speculated. With regard to ethnic identity and other group orientation, the limited literature on high achieving African American students (e.g., Worrell, 2007; Worrell & White 2009) suggested that these variables have moderate relationships with school achievement, and we hypothesized that we would find associations with a moderate effect size. Finally, it was hypothesized that the psychosocial variables in combination would add incremental variance to the prediction of academic achievement beyond the contribution of SES.

Method

Participants and Procedure

The sample consisted of 105 (59% female) African American high school students aged 14 to 18 (M_age = 16.15, SD = 1.08; M_grade = 10.78, SD = 0.98) with a GPA of a 3.0 or higher (M_GPA = 3.55, SD = 0.31). All students attended the same diverse high school in a Western state. Parental education of the participants ranged widely: 3.8% did not graduate from high school, 3.8% were high school graduates, 28.6% had some college, 20% were college graduates, and 31.4% had graduate degrees. The education level of the remaining 12.4% was not provided. Missing data were imputed using the expectation maximization algorithm (25 iterations). Amount of imputed data ranged from 0% to 12.4% for included variables.

Data used in this study are a subset of data collected via a school-administered survey that focused on student perceptions about schoolwide climate and improvement. Teachers administered and collected surveys within their classes. The larger sample consisted of 1,110 students (47.9% female) aged 14 to 18 (M_age = 16.17, SD = 1.06) with a diverse ethnic makeup (18.4% African American, 38.6% European American, 9.5% Asian American, 22% Hispanic American, and 11.5% more than one race/Other). The school as a whole consisted of about 3,150 students attending ninth through 12th grade. The ethnic makeup of the school was 38% European American, 21% African American, 21% Hispanic American, 9% Asian American, and 12% more than one race/Other. Thirty percent of the student population qualified for a free or reduced lunch at the beginning of the school year and about 75% of the senior class took the SAT over the course of the school year. Average SAT scores were 558 for critical reading, 557 for math, and 551 for writing. Limiting the study to high achieving African Americans mirrors previous studies conducted on similar variables with students attending programs for gifted and talented students (e.g., Dixson et al., 2016; Worrell, 2007).

Measures

Academic achievement consisted of students’ cumulative GPA, measured on a 0 to 4 scale, taken from school records. All other variables were measured with scales, except for SES, which was measured with a single item.

Grit

Grit was measured using the Grit-S (Duckworth & Quinn, 2009). The Grit-S measure is an eight-item scale that measures trait perseverance and passion for long-term goals (Duckworth & Quinn, 2009). Grit-S is made up of two factors, four items that measure consistency of interests (e.g., “I finish whatever I begin”) and four items that measure perseverance of effort (e.g., “I have been obsessed with a certain idea or project for a short time but later lost interest”). Response options range from 1 (very much like me) to 5 (not like me at all). Higher scores are indicative of more grit, and scores on the perseverance of effort factor have to be reverse-coded. Grit scores have been found to be valid and reliable in adolescent populations with alpha estimates ranging from .73 to .83 (Duckworth & Quinn, 2009).

Growth mindset

Growth mindset was measured using the Theories of Intelligence Scale (TIS; Dweck, 2000). The TIS is an eight-item scale that measures how much individuals believe that their intelligence is fixed or malleable. Four items on the scale assess the belief that intelligence is malleable (e.g., “You can always substantially change how intelligent you are”) and four items assess the belief that intelligence is fixed (“You have a certain amount of intelligence, and you really can’t do much to change it”). Response options range from 1 (strongly disagree) to 6 (strongly agree). Fixed intelligence items are reverse-coded and higher scores are indicative of having more of a growth mindset. The TIS has been used in previous research and TIS scores have been found to be internally consistent, with alphas ranging from .78 to .92 (Blackwell et al., 2007; Jones, Bryant, Snyder, & Malone, 2012).

Ethnic identity

Ethnic Identity was measured using the revised Multigroup Ethnic Identity Measure (MEIM-R; Phinney & Ong, 2007). This six-item scale measures one’s ethnic identity. The MEIM-R has two components: exploration (e.g., “I have spent time trying to find out more about my ethnic group, such as its history, traditions, and customs”) and commitment (e.g., “I have a strong sense of belonging to my own ethnic group”). Response options range from 1 (strongly disagree) to 4 (strongly agree). Total scores on the MEIM-R have been found to be internally consistent in other adolescent populations with alpha estimates ranging from .81 to .89 (Phinney & Ong, 2007; Yoon, 2011).

Other group orientation

Other group orientation was measured using six items from the original Multigroup Ethnic Identity Measure (MEIM-O; Phinney, 1992). This six-item scale measures how much students engage with and value experiences with people from other ethnic groups (e.g., “I like meeting and getting to know people from other ethnic groups”). Response options range from 1 (strongly disagree) to 4 (strongly agree), with higher scores indicating the more a student is willing to engage with other groups (Phinney, 1992). Other group orientation scores have been found to be valid and internally consistent in adolescent populations with alphas ranging from .71 to .74 (Phinney, 1992; Worrell, 2000).

SES

SES was measured via a single item that asks students what their mother’s level of education is. Response options are not a high school graduate, high school graduate, some college, college graduate, and graduate school/postgraduate. Parental education has been used as an effective indicator of SES in previous research consisting of adolescent samples (e.g., Aarø et al., 2009; Sirin, 2005).

Results

Preliminary Analyses

Means, standard deviations, and intercorrelations among the variables are reported in Table 1. As can be seen in Table 1, most of the psychosocial variables were not statistically or meaningfully correlated with each other. The three correlations among the psychosocial variables that were meaningful were between (a) Grit-S effort and growth mindset, (b) other group orientation and growth mindset, and (c) ethnic identity and other group orientation.

Table 1.

Descriptive Statistics.

Variable	1	2	3	4	5	6	7	M	SD
1. GPA (0-4)	1.00							3.55	0.31
2. Grit-S Effort (1-5)	−0.07	1.00						3.33	0.83
3. Grit-S Interests (1-5)	−0.11	0.18	1.00					3.65	0.83
4. Ethnic Identity (1-4)	−0.17	0.22	0.21	1.00				3.05	0.74
5. Other Group Or. (1-4)	−0.07	0.17	0.24	0.64*	1.00			3.36	0.63
6. SES (1-5)	0.44*	−0.15	−0.10	−0.05	−0.08	1.00		3.81	1.11
7. Growth Mindset (1-6)	−0.05	0.39*	0.20	0.13	0.31*	0.02	1.00	4.49	1.01

Note. Skew and kurtosis values ranging from −1.07 to −.15 and −.44 to 1.17, respectively. GPA = grade point average; Grit-S = Short Grit Scale; Other Group Or. = Other Group Orientation; SES = socioeconomic status.

p < .0017.

In keeping with best practice, the psychometric properties of scores on the scales were examined in this sample prior to use (American Educational Research Association, American Psychological Association, & National Council on Measurement in Education, 2014). The results of the exploratory factor analyses (principal axis extraction) are presented in Table 2. As can be seen, scores on grit, growth mindset, ethnic identity, and other group orientation generally showed sound psychometric properties. More specifically, factor coefficients were > .40, and internal consistency estimates for subscale scores were above .70, although the percent of variance accounted for on some scales was low, especially for Grit-S effort scores.

Table 2.

Psychometric Properties of Measures.

Variable (no. of items)	α	Communalities	Factor coefficients	% variance explained
Grit-S Effort (4)	.75	.18-.72	.44-.85	27.2
Grit-S Interests (4)	.71	.23-.34	.52-.69	43.0
Growth Mindset (8)	.85	.29-.57	.54-.75	43.1
Ethnic Identity (6)	.91	.44-.81	.66-.91	63.7
Other Group Orientation (6)	.89	.40-.80	.63-.89	61.3

Note. Grit-S = Short Grit Scale.

Psychosocial Variables and Academic Achievement

Associations among psychosocial variables and academic achievement were assessed using bivariate correlations. As can be seen in Table 1, the only variable in this study that had a significant and meaningful correlation with GPA was SES. Although each of the psychosocial variables had a trivial relationship with GPA, linear regression was used to see if their combined effect contributed meaningfully to academic achievement, after controlling for sex and age. As can be seen in Tables 3 and 4, the psychosocial variables were not significant predictors of GPA in this sample, individually or collectively, and with or without grit’s interests subfactor. There was no evidence of the Grit-S interests factor resulting in a suppressor effect. In contrast, SES explained about 17% of the variance in GPA (see Table 5). When psychosocial variables were added after SES, they reduced the predictive value of the model by about 1%.

Table 3.

Hierarchical Regressions Predicting GPA.

Variable (no. of items)	sr ²	B	β	Adjusted R²	ΔR²
Block 1
Sex	.035	.019	.030
Age	−.241	−.069	−.241	.042	.042
Block 2
Grit-S Effort	−.035	−.015	−.040
Grit-S Interests	−.054	−.022	−.058
Ethnic Identity	−.130	−.072	−.174
Other Group Orientation	.080	.055	.111
Growth Mindset	−.041	−.014	−.047	.025	−.017

Note. GPA = grade point average; Grit-S = Short Grit Scale.

p < .001.

Table 4.

Hierarchical Regressions Predicting GPA.

Variable (no. of items)	sr ²	B	β	Adjusted R²	ΔR²
Block 1
Sex	.041	.019	.030
Age	−.228	−.069	−.241	.042	.042
Block 2
Grit-S Effort	−.045	−.020	−.051
Ethnic Identity	−.132	−.073	−.177
Other Group Orientation	.076	.052	.106
Growth Mindset	−.048	−.017	−.055	.032	−.010

Note. GPA = grade point average; Grit-S = Short Grit Scale.

p < .001.

Table 5.

Hierarchical Regressions Predicting GPA.

Variable (no. of items)	sr ²	B	β	Adjusted R²	ΔR²
Block 1
Sex	−.031	.019	.030
Age	−.186	−.069*	−.241	.042	.042
Block 2
Socioeconomic Status	.413	.118*	.423	.211	.169
Block 3
Grit-S Effort	.033	.015	.039
Grit-S Interests	−.025	−.010	−.027
Ethnic Identity	−.145	−.081	−.195
Other Group Orientation	.099	.068	.138
Growth Mindset	−.087	−.030	−.100	.200	−.011

Note. GPA = grade point average; Grit-S = Short Grit Scale.

p < .001.

Discussion

In this study, we examined whether four psychosocial variables—grit, growth mindset, ethnic identity, and other group orientation—were meaningfully associated with academic achievement, as indicated by several studies (Mueller & Dweck, 1998; Strayhorn, 2013; Worrell, 2007). Results indicated that grit, growth mindset, ethnic identity, and other group orientation were not related to academic achievement in this sample of high achieving African Americans adolescent students.

Psychosocial Variables’ Contribution to Academic Achievement

It was hypothesized that the psychosocial variables would correlate significantly and meaningfully with academic achievement. There was no support for this hypothesis. Grit, growth mindset, ethnic identity, and other group orientation all had trivial correlations with academic achievement and, in combination, they did not predict any of academic achievement’s variance after controlling for age and gender, with or without the interests subfactor of grit (they actually reduced the predictability of the model by 1-2%). These findings indicate that consistency of interests may not suppress perseverance of effort in predicting academic achievement and that these four psychosocial variables may play less of a role in the achievement of adolescent African American students than hypothesized. This finding is surprising given that several studies have found that these psychosocial factors relate considerably to academic achievement in diverse samples (Blackwell et al., 2007; Strayhorn, 2013; Worrell, 2007) and underscores the need for research in specific population subgroups as Worrell (2014) suggested.

Before addressing the four factors directly, it is important to discuss a potential confounding factor in this study, that is, restriction of range in GPA. It would be easy to conclude that the failure to find meaningful relationships is due to the fact that only students with GPAs greater than 3.0 were included in the study. However, this hypothesis is contradicted by the results reported by Worrell (2007) and the data in the current study. In the Worrell (2007) study, the high achieving African American students had a GPA of 3.6 (SD = .33) on a 4-point scale, which is quite similar to achievement level in the current study and he found meaningful associations with both ethnic identity and other group orientation. In the current study, the low correlations between GPA and the two cultural constructs (measured on a 1-4 scale) were comparable with the correlations with the two motivation constructs (measured on a 1-5 scale), whereas the correlation with SES (measured on a 1-5 scale) was substantial. Thus, based on previous research with a similar sample and the pattern of results in this sample, restriction of range does not provide an explanation for our results.

Grit

It is much more likely that the hypotheses based on previous research are overstated. Consider the case of grit. As Credé et al. (2016) found in their meta-analytic study, the association between grit and academic achievement is much more modest than one would anticipate, given other claims in the literature, and the incremental variance beyond conscientiousness is small. Grit’s failure to predict achievement in a high achieving sample is also in keeping with findings in a recently published study on a diverse sample of academically talented students, in which Dixson et al. (2016) found that the two Grit-S factors contributed little incremental variance beyond gender, SES, age, and perceived ability, with coefficients very similar to the ones found in this study (see Rimfeld, Kovas, Dale, & Plomin, 2016, for similar findings in a sample of adolescents in the United Kingdom). In short, despite the hype, grit, at least as measured by the Short Grit Scale, does not seem to be a meaningful predictor of academic achievement once other variables are controlled for.

Growth mindset

A similar explanation comes to mind with regard to growth mindset. Although growth mindset had a moderate association with Grit-S effort in the current study, like the effort variable, it was not associated with achievement. In many of the studies that have shown that growth mindset is correlated with achievement, other variables have not been controlled for, as SES was in this study. Also, many of the studies have been intervention studies intended to increase the growth mindset of students who were low- or average-achieving. It is possible that the high achieving students in this study already are near to their ceiling on growth mindset (notwithstanding the mean) and that this variable’s impact on achievement has already been accounted for.

Alternatively, the impact of growth mindset on achievement may also be exaggerated. As previously mentioned, Li and Bates (2017) found no evidence that having a growth mindset was beneficial to academic performance in a Chinese sample of over 600 students across three studies. Mirroring those findings, Duval (2015) examined the association between growth mindset and academic achievement in a sample of 310 ninth- and tenth-grade students attending a diverse high school. After controlling for gender and SES, Duval found that an incremental growth mindset had negligible to low associations with achievement in African American (β = .07), Asian American (β = .27), European American (β = −.17), and Hispanic American (β = .002) students.

Ethnic identity and other group orientation

As noted in the Introduction, the majority of studies have not yielded a meaningful association between ethnic identity and achievement, and one of the studies that did find this relationship (i.e., Worrell, 2007) did not find it consistently. The same pattern was found for other group orientation—the association was present in the home school context and not in the summer program—and Worrell (2007) noted that “we do not fully understand how these [cultural] variables contribute to student outcomes across groups and settings” (p. 34). The findings of this study lead to the same conclusion.

Summary

Many researchers assert that various psychosocial factors that have been found to be related to academic achievement in a study can help African American students become high achievers (e.g., Strayhorn, 2013; Yeager & Walton, 2011). However, these studies do not typically consist of exclusively high achieving samples. Therefore, it is not clear if (a) the findings from previous studies do not generalize to high achievers, (b) the psychosocial variables used in this study do not contribute as much variance as some of the initial studies suggest, or (c) the psychosocial variables do not contribute incremental variance after demographic and other factors are controlled for. It is worth noting that Dixson et al. (2016) found that academic self-efficacy and hope predicted academic achievement in an academically talented sample, although Grit-S interest and effort did not, leading Dixson et al. (2016) to conclude that “all psychosocial variables are not created equal” (p. 74).

On the contrary, SES explained about 17% of the variance in academic achievement. Given that SES has a well-established relationship with academic achievement (Sirin, 2005) and is very difficult to change (Mazur, Malkowska-Szkutnik, & Tabak, 2013), future studies should focus on assessing whether psychosocial variables contribute to academic achievement beyond the contributions of demographic variables such as SES, so that interventions can focus on the variables that are most likely to have a meaningful impact on achievement.

Limitations and Conclusion

The current study had several limitations. First, this current study’s participants were selected from a very limited range of GPA. Given the restricted range of GPAs within this sample, the findings from this study may not be generalizable to students outside the range. Second, the study was cross-sectional and conducted within just one high school, also limiting its generalizability. The study needs to be replicated with larger samples including multiple high schools and districts. It would also be useful to study the associations of these variables longitudinally. Given the popularity of the psychosocial constructs and the resources being invested in interventions based on these constructs, the current findings warrant follow-up research.

The achievement gap is a huge problem and high achieving African American students may provide unique insights into African American achievement. Substantial claims have been made about many psychosocial variables and their potential contributions to the academic success of African Americans. However, the current study indicates that some psychosocial variables may not be the keys to African American achievement as suggested. In addition, the current study highlights the role of SES in achievement outcomes and the importance of examining psychosocial variables alongside SES. Although some psychosocial variables are likely to be important for the success of high achieving African Americans, more research needs to be conducted to determine which psychosocial factors matter. Research that identifies psychosocial factors that can reliably distinguish between high achieving and low achieving African American students will contribute greatly toward developing interventions with the goal of closing the achievement gap.

Footnotes

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) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by the African American Success Foundation’s Lydia Donaldson Tutt-Jones Memorial Research Grant.

About the Authors

Dante D. Dixson is an assistant professor of School Psychology in the College of Education at Wayne State University. His areas of expertise include hope, the achievement gap, African American achievement, talent development/gifted education, positive psychology, and how psychosocial variables relate to and can improve academic achievement.

Cyrell C. B. Roberson is a doctoral student within the School Psychology program at the University of California (UC), Berkeley. His current research interests focus on identifying the positive, psychosocial variables that enable high achieving, low-income, ethnic minority students to overcome adversity and excel in academics.

Frank C. Worrell is a professor of School Psychology at UC Berkeley’s Graduate School of Education. His areas of expertise include talent development/gifted education, at-risk youth, cultural identities, scale development and validation, teacher effectiveness, and the translation of psychological research findings into practice.

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