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Abstract Socioeconomic disparities in academic progress have persisted throughout the history of the United States, and growth mindset interventions—which shift beliefs about the malleability of intelligence—have shown promise in reducing these disparities. Both the study of such disparities and how to remedy them can benefit from taking the “long view” on adolescent development, following the tradition of John Schulenberg. To do so, this study focuses on the role of growth mindsets in short‐term academic progress during the transition to high school as a contributor to longer‐term educational attainment. Guided by the Mindset × Context perspective, we analyzed new follow‐up data to a one‐year nationally representative study of ninth graders (National Study of Learning Mindsets,n = 10,013; 50% female; 53% white; 63% from lower‐SES backgrounds). A conservative Bayesian analysis revealed that adolescents' growth mindset beliefs at the beginning of ninth grade predicted their enrollment in college 4 years later. These patterns were stronger for adolescents from lower‐SES backgrounds, and there was some evidence that the ninth‐grade math teacher's support for the growth mindset moderated student mindset effects. Thus, a time‐specific combination of student and teacher might alter long‐term trajectories by enabling adolescents to develop and use beliefs at a critical transition point that supports a cumulative pathway of course‐taking and achievement into college. Notably, growth mindset became less predictive of college enrollment after the onset of the COVID‐19 pandemic, which occurred in the second year of college and introduced structural barriers to college persistence. 

Group-based educational disparities are smaller in classrooms where teachers express a belief that students can improve their abilities. However, a scalable method for motivating teachers to adopt such growth mindset–supportive teaching practices has remained elusive. In part, this is because teachers often already face overwhelming demands on their time and attention and have reason to be skeptical of the professional development advice they receive from researchers and other experts. We designed an intervention that overcame these obstacles and successfully motivated high-school teachers to adopt specific practices that support students’ growth mindsets. The intervention used the values-alignment approach. This approach motivates behavioral change by framing a desired behavior as aligned with a core value—one that is an important criterion for status and admiration in the relevant social reference group. First, using qualitative interviews and a nationally representative survey of teachers, we identified a relevant core value: inspiring students’ enthusiastic engagement with learning. Next, we designed a ~45-min, self-administered, online intervention that persuaded teachers to view growth mindset–supportive practices as a way to foster such student engagement and thus live up to that value. We randomly assigned 155 teachers (5,393 students) to receive the intervention and 164 teachers (6,167 students) to receive a control module. The growth mindset–supportive teaching intervention successfully promoted teachers’ adoption of the suggested practices, overcoming major barriers to changing teachers’ classroom practices that other scalable approaches have failed to surmount. The intervention also substantially improved student achievement in socioeconomically disadvantaged classes, reducing inequality in educational outcomes. 

Behavioral science interventions have the potential to address longstanding policy problems, but their effects are typically heterogeneous across contexts (e.g., teachers, schools, and geographic regions). This contextual heterogeneity is poorly understood, however, which reduces the field’s impact and its understanding of mechanisms. Here, we present an efficient way to interrogate heterogeneity and address these gaps in knowledge. This method a) presents scenarios that vividly represent different moderating contexts, b) measures a short-term behavioral outcome (e.g., an academic choice) that is known to relate to typical intervention outcomes (e.g., academic achievement), and c) assesses the causal effect of the moderating context on the link between the psychological variable typically targeted by interventions and this short-term outcome. We illustrated the utility of this approach across four experiments (total n = 3,235) that directly tested contextual moderators of the links between growth mindset, which is the belief that ability can be developed, and students’ academic choices. The present results showed that teachers’ growth mindset-supportive messages and the structural opportunities they provide moderated the link between students’ mindsets and their choices (studies 1 to 3). This pattern was replicated in a nationally representative sample of adolescents and did not vary across demographic subgroups (study 2), nor was this pattern the result of several possible confounds (studies 3 to 4). Discussion centers on how this method of interrogating contextual heterogeneity can be applied to other behavioral science interventions and broaden their impact in other policy domains. 

Mindset interventions, which shift students’ beliefs about classroom experiences, have shown promise for promoting diversity in science, technology, engineering, and mathematics (STEM). Psychologists have emphasized the importance of customizing these interventions to specific courses, but there is not yet a protocol for doing so. We developed a protocol for creating customized “peer-modeled” mindset interventions that elicit advice from former students in videotaped interviews. In intervention activities, clips from these interviews, in which the former students’ stories model the changes in thinking about challenge and struggle that helped them succeed in a specific course, are provided to incoming life sciences students. Using this protocol, we developed a customized intervention for three sections of Introductory Biology I at a large university and tested it in a randomized controlled trial ( N = 917). The intervention shifted students’ attributions for struggle in the class away from a lack of potential to succeed and toward the need to develop a better approach to studying. The intervention also improved students’ approaches to studying and sense of belonging and had promising effects on performance and persistence in biology. Effects were pronounced among first-generation college students and underrepresented racial/ethnic minority students, who have been historically underrepresented in the STEM fields. 

Abstract Social-evaluative stressors—experiences in which people feel they could be judged negatively—pose a major threat to adolescent mental health 1–3 and can cause young people to disengage from stressful pursuits, resulting in missed opportunities to acquire valuable skills. Here we show that replicable benefits for the stress responses of adolescents can be achieved with a short (around 30-min), scalable 'synergistic mindsets' intervention. This intervention, which is a self-administered online training module, synergistically targets both growth mindsets 4 (the idea that intelligence can be developed) and stress-can-be-enhancing mindsets 5 (the idea that one’s physiological stress response can fuel optimal performance). In six double-blind, randomized, controlled experiments that were conducted with secondary and post-secondary students in the United States, the synergistic mindsets intervention improved stress-related cognitions (study 1, n  = 2,717; study 2, n  = 755), cardiovascular reactivity (study 3, n  = 160; study 4, n  = 200), daily cortisol levels (study 5, n  = 118 students, n  = 1,213 observations), psychological well-being (studies 4 and 5), academic success (study 5) and anxiety symptoms during the 2020 COVID-19 lockdowns (study 6, n  = 341). Heterogeneity analyses (studies 3, 5 and 6) and a four-cell experiment (study 4) showed that the benefits of the intervention depended on addressing both mindsets—growth and stress—synergistically. Confidence in these conclusions comes from a conservative, Bayesian machine-learning statistical method for detecting heterogeneous effects 6 . Thus, our research has identified a treatment for adolescent stress that could, in principle, be scaled nationally at low cost.