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 x 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.

BackgroundSingle-session interventions have the potential to address young people's mental health needs at scale, but their effects are heterogeneous. We tested whether the mindset + supportive context hypothesis could help explain when intervention effects persist or fade over time. The hypothesis posits that interventions are more effective in environments that support the intervention message. We tested this hypothesis using the synergistic mindsets intervention, a preventative treatment for stress-related mental health symptoms that helps students appraise stress as a potential asset in the classroom (e.g., increasing oxygenated blood flow) rather than debilitating. In an introductory college course, we examined whether intervention-consistent messages from instructors sustained changes in appraisals over time, as well as impacts on students' predisposition to try demanding academic tasks that could enhance learning.MethodsWe randomly assigned 1675 students in the course to receive the synergistic mindsets intervention (or a control activity) at the beginning of the semester, and subsequently, to receive intervention-supportive messages from their instructor (or neutral messages) four times throughout the term. We collected weekly measures of students' appraisals of stress in the course and their predisposition to take on academic challenges. Trial-registration: OSF.io; DOI: 10.17605/osf.io/fchyn.ResultsA conservative Bayesian analysis indicated that receiving both the intervention and supportive messages led to the greatest increases in positive stress appraisals (0.35 SD; 1.00 posterior probability) and challenge-seeking predisposition (2.33 percentage points; 0.94 posterior probability), averaged over the course of the semester. In addition, intervention effects grew larger throughout the semester when complemented by supportive instructor messages, whereas without these messages, intervention effects shrank somewhat over time.ConclusionsThis study shows, for the first time, that supportive cues in local contexts can be the difference in whether a single-session intervention's effects fade over time or persist and even amplify. Single-session interventions hold promise as scalable treatments for young people, but their effects sometimes persist and sometimes fade out. We found that an established single-session intervention's effects could be sustained and amplified over time in an introductory college course (n = 1675) by providing brief messages from instructors that supported the intervention message. This study provides evidence for a framework that can explain and predict heterogeneity in the effects of single-session interventions, which will help future researchers and practitioners to shape local environments to sustain the beneficial effects of interventions over time. image

In this study, we identified multidimensional profiles in students' math anxiety, math self-concept, and math interest using data from a large generalizable sample of 16,547 9th grade students in the United States who participated in the National Study of Learning Mindsets. We also analyzed the extent that students' profile memberships are associated with related measures such as prior mathematics achievement, academic stress, and challenge-seeking behavior. Five multidimensional profiles were identified: two profiles which demonstrated relatively high levels of interest and self-concept, along with low math anxiety, in line with the tenets of the control-value theory of academic emotions (C-VTAE); two profiles which demonstrated relatively low levels of interest and self-concept, and high levels of math anxiety (again in accordance with C-VTAE); and one profile, comprising more than 37% of the total sample, which demonstrated medium levels of interest, high levels of self-concept, and medium levels of anxiety. All five profiles varied significantly from one another in their association with the distal variables of challenge seeking behavior, prior mathematics achievement, and academic stress. This study contributes to the literature on math anxiety, self-concept, and interest by identifying and validating student profiles that mainly align with the control-value theory of academic emotions in a large, generalizable sample.

Group-based educational disparities are smaller in classrooms where teachers express a belief that students can improve their abilities. However, a scalable method for motivatthat 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 similar to 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.

Educators increasingly recognize the importance of students' learning orientations, but relatively little is known about how these mindsets vary across and potentially shape educational settings. We use nationally representative data to document contextual variation in mathematics orientations in U.S. high schools. We find systematic variation in orientations between differentiated course levels within school, suggesting orientations are more a feature of proximate instructional contexts than general school climate. Between-course variation in orientations is comparable to analogous sorting on demographic characteristics and not primarily explained by prior achievement. Measures of individual learning orientations at scale hold promise for understanding collective educational contexts.

When do adolescents' dreams of promising journeys through high school translate into academic success? This monograph reports the results of a collaborative effort among sociologists and psychologists to systematically examine the role of schools and classrooms in disrupting or facilitating the link between adolescents' expectations for success in math and their subsequent progress in the early high school math curriculum. Our primary focus was on gendered patterns of socioeconomic inequality in math and how they are tethered to the school's peer culture and to students' perceptions of gender stereotyping in the classroom. To do this, this monograph advances Mindset x Context Theory. This orients research on educational equity to the reciprocal influence between students' psychological motivations and their school-based opportunities to enact those motivations. Mindset x Context Theory predicts that a student's mindset will be more strongly linked to developmental outcomes among groups of students who are at risk for poor outcomes, but only in a school or classroom context where there is sufficient need and support for the mindset. Our application of this theory centers on expectations for success in high school math as a foundational belief for students' math progress early in high school. We examine how this mindset varies across interpersonal and cultural dynamics in schools and classrooms. Following this perspective, we ask: 1. Which gender and socioeconomic identity groups showed the weakest or strongest links between expectations for success in math and progress through the math curriculum? 2. How did the school's peer culture shape the links between student expectations for success in math and math progress across gender and socioeconomic identity groups? 3. How did perceptions of classroom gender stereotyping shape the links between student expectations for success in math and math progress across gender and socioeconomic identity groups? We used nationally representative data from about 10,000 U.S. public school 9th graders in the National Study of Learning Mindsets (NSLM) collected in 2015-2016-the most recent, national, longitudinal study of adolescents' mindsets in U.S. public schools. The sample was representative with respect to a large number of observable characteristics, such as gender, race, ethnicity, English Language Learners (ELLs), free or reduced price lunch, poverty, food stamps, neighborhood income and labor market participation, and school curricular opportunities. This allowed for generalization to the U.S. public school population and for the systematic investigation of school- and classroom-level contextual factors. The NSLM's complete sampling of students within schools also allowed for a comparison of students from different gender and socioeconomic groups with the same expectations in the same educational contexts. To analyze these data, we used the Bayesian Causal Forest (BCF) algorithm, a best-in-class machine-learning method for discovering complex, replicable interaction effects. Chapter IV examined the interplay of expectations, gender, and socioeconomic status (SES; operationalized with maternal educational attainment). Adolescents' expectations for success in math were meaningful predictors of their early math progress, even when controlling for other psychological factors, prior achievement in math, and racial and ethnic identities. Boys from low-SES families were the most vulnerable identity group. They were over three times more likely to not make adequate progress in math from 9th to 10th grade relative to girls from high-SES families. Boys from low-SES families also benefited the most from their expectations for success in math. Overall, these results were consistent with Mindset x Context Theory's predictions. Chapters V and VI examined the moderating role of school-level and classroom-level factors in the patterns reported in Chapter IV. Expectations were least predictive of math progress in the highest-achieving schools and schools with the most academically oriented peer norms, that is, schools with the most formal and informal resources. School resources appeared to compensate for lower levels of expectations. Conversely, expectations most strongly predicted math progress in the low/medium-achieving schools with less academically oriented peers, especially for boys from low-SES families. This chapter aligns with aspects of Mindset x Context Theory. A context that was not already optimally supporting student success was where outcomes for vulnerable students depended the most on student expectations. Finally, perceptions of classroom stereotyping mattered. Perceptions of gender stereotyping predicted less progress in math, but expectations for success in math more strongly predicted progress in classrooms with high perceived stereotyping. Gender stereotyping interactions emerged for all sociodemographic groups except for boys from high-SES families. The findings across these three analytical chapters demonstrate the value of integrating psychological and sociological perspectives to capture multiple levels of schooling. It also drew on the contextual variability afforded by representative sampling and explored the interplay of lab-tested psychological processes (expectations) with field-developed levers of policy intervention (school contexts). This monograph also leverages developmental and ecological insights to identify which groups of students might profit from different efforts to improve educational equity, such as interventions to increase expectations for success in math, or school programs that improve the school or classroom cultures.

Meta-analysts often ask a yes-or-no question: Is there an intervention effect or not? This traditional, all-or-nothing thinking stands in contrast with current best practice in meta-analysis, which calls for a heterogeneity-attuned approach (i.e., focused on the extent to which effects vary across procedures, participant groups, or contexts). This heterogeneity-attuned approach allows researchers to understand where effects are weaker or stronger and reveals mechanisms. The current article builds on a rare opportunity to compare two recent meta-analyses that examined the same literature (growth mindset interventions) but used different methods and reached different conclusions. One meta-analysis used a traditional approach (Macnamara & Burgoyne, 2023), which aggregated effect sizes for each study before combining them and examined moderators one-by-one by splitting the data into small subgroups. The second meta-analysis (Burnette et al., 2023) modeled the variation of effects within studies-across subgroups and outcomes-and applied modern, multilevel metaregression methods. The former concluded that growth mindset effects are biased, but the latter yielded nuanced conclusions consistent with theoretical predictions. We explain why the practices followed by the latter meta-analysis were more in line with best practices for analyzing large and heterogeneous literatures. Further, an exploratory re-analysis of the data showed that applying the modern, heterogeneity-attuned methods from Burnette et al. (2023) to the data set employed by Macnamara and Burgoyne (2023) confirmed Burnette et al.'s conclusions; namely, that there was a meaningful, significant effect of growth mindset in focal (at-risk) groups. This article concludes that heterogeneity-attuned meta-analysis is important both for advancing theory and for avoiding the boom-or-bust cycle that plagues too much of psychological science.

Large language models (LLMs), such as OpenAI's GPT-4, Google's Bard or Meta's LLaMa, have created unprecedented opportunities for analysing and generating language data on a massive scale. Because language data have a central role in all areas of psychology, this new technology has the potential to transform the field. In this Perspective, we review the foundations of LLMs. We then explain how the way that LLMs are constructed enables them to effectively generate human-like linguistic output without the ability to think or feel like a human. We argue that although LLMs have the potential to advance psychological measurement, experimentation and practice, they are not yet ready for many of the most transformative psychological applications - but further research and development may enable such use. Next, we examine four major concerns about the application of LLMs to psychology, and how each might be overcome. Finally, we conclude with recommendations for investments that could help to address these concerns: field-initiated 'keystone' datasets; increased standardization of performance benchmarks; and shared computing and analysis infrastructure to ensure that the future of LLM-powered research is equitable. Large language models (LLMs), which can generate and score text in human-like ways, have the potential to advance psychological measurement, experimentation and practice. In this Perspective, Demszky and colleagues describe how LLMs work, concerns about using them for psychological purposes, and how these concerns might be addressed.

Educational outcomes remain highly unequal within and across nations. Students' mindsets-their beliefs about whether intellectual abilities can be developed-have been identified as a potential lever for making adolescents' academic outcomes more equitable. Recent research, however, suggests that intervention programs aimed at changing students' mindsets should be supplemented by programs aimed at the changing the mindset culture, which is defined as the shared set of beliefs about learning in a school or classroom. This paper reviews the theoretical and empirical origin of the mindset culture and examines its potential to reduce group-based inequalities in education. In particular, experiments have identified two broad ways the mindset culture is communicated by teachers: via informal messages about growth (e.g., that all students will be helped to learn and succeed), and formal opportunities to improve (e.g., learning-focused grading policies and opportunities to revise and earn credit). New field experiments, applying techniques from behavioral science, have also revealed effective ways to influence teachers' culture-creating behaviors. This paper describes recent breakthroughs in the U.S. educational context and discusses how lessons from these studies might be applied in future, global collaborations with researchers and practitioners.