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Intervention, Evaluation, and Policy Studies

Reducing Inequality in Academic Success for Incoming College Students: A Randomized Trial of Growth Mindset and Belonging Interventions

ORCID Icon, , , , &
Pages 317-338 | Received 09 Mar 2017, Accepted 05 Jan 2018, Published online: 09 Apr 2018
 

ABSTRACT

Light-touch social psychological interventions have gained considerable attention for their potential to improve academic outcomes for underrepresented and/or disadvantaged students in postsecondary education. While findings from previous interventions have demonstrated positive effects for racial and ethnic minority and first-generation students in small samples, few interventions have been implemented at a larger scale with more heterogeneous student populations. To address this research gap, 7,686 students, representing more than 90% of incoming first-year students at a large Midwestern public university, were randomly assigned to an online growth mindset intervention, social belonging intervention, or a comparison group. Results suggest that after the fall semester, the growth mindset intervention significantly improved grade point averages for Latino/a students by about .40 points. This represents a 72% reduction in the GPA gap between White and Latino/a students. Further, this effect was replicated for both spring semester GPA and cumulative GPA. These findings indicate that light-touch interventions may be a minimally invasive approach to improving academic outcomes for underrepresented students. Our findings also highlight the complexity of implementing customized belonging interventions in heterogeneous contexts.

Notes

1 The official institutional designation for Latino/a students is “Hispanic (all races).” We use Latino/a throughout this paper in an effort to use a more inclusive group identifier.

2 Although not the primary focus of this paper, which examines the impact of these interventions on underrepresented students, for reference, we also present results for the main effect of each intervention in the full sample, which includes students from all racial/ethnic groups.

3 This approach was used after confirming the unidimensionality of the data using principal components analysis (PCA). Results from the PCA confirmed that the four items in the scale loaded onto one primary factor, and that the scale scores (weights) for each item were roughly equivalent. The same process was used for the calculation of the pre-measure for growth mindset.

4 The sample referenced here is the analytic sample, which includes all students who completed courses in the fall semester. No differences were also found between intervention and control groups for the original (pre-attrition) sample. These estimates are available from the author.

5 In this approach, indicator variables are used to denote observations with missing values on given variables, and the missing values are imputed to 0. This provides an adjustment for coefficient estimates for variables with observed vs. missing data. While this approach is not recommended in a nonrandomized research design, simulations by Puma et al. (Citation2009) demonstrated that the dummy variable approach performs equally well as compared to other missing data methods, such as multiple imputation, when analyzing data in a randomized intervention.

6 Full estimates are available from the author upon request. While it is possible that in some cases a nonsignificant main effect may be driven by significant subgroup moderation in different directions, that was not the case here. All moderators tested were nonsignificant (all p values > .05) for all outcomes in all subgroups, except for pre-intervention levels of belonging, which were a significant and negative moderator (B = −0.41, p = .03) of the relationship between belonging treatment and spring GPA in the Latino/a treatment group.

7 The impact of the growth mindset pre-measure was 0.009 according to Frank's (Citation2000) approach to quantifying variable impact.

8 For high school GPA, Latino/a = 3.55, African American = 3.34, t = 7.17, d = .57. For ACT scores, Latino/a = 23.90, African American = 20.98, t = 11.28, d = .86.

9 Latino/a = 4.89, African American = 5.19, t = −4.83, d = −.36.

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