A national experiment reveals where a growth mindset improves achievement

In line with our first major prediction, lower-achieving adolescents earned higher GPAs in core classes at the end of the ninth grade when assigned to the growth mindset intervention, B = 0.10 grade points (95% confidence interval = 0.04, 0.16), s.e. = 0.03, n = 6,320, k = 65, t = 3.51, P = 0.001, standardized mean difference effect size of 0.11, relative to comparable students in the control condition. This conclusion is robust to alternative model specifications that deviate from the pre-registered model (Extended Data Fig. 1).

To map the growth mindset intervention effect onto a policy-relevant indicator of high school success, we analysed poor performance rates, defined as the percentage of adolescents who earned a GPA below 2.0 on a four-point scale (that is, a ‘D’ or an ‘F’; as described in the pre-analysis plan). Poor performance rates are relevant because recent changes in US federal laws (the Every Student Succeeds Act), have led many states to adopt reductions in the poor performance rates in the ninth grade as a key metric for school accountability. More than three million ninth-grade students attend regular US public schools each year, and half are lower-achieving according to our definition. The model estimates that 5.3% (95% confidence interval = −1.7, −9.0), s.e. = 1.8, t = 2.95, P = 0.005 of 1.5 million students in the United States per year would be prevented from being ‘off track’ for graduation by the brief and low-cost growth mindset intervention, representing a reduction from 46% to 41%, which is a relative risk reduction of 11% (that is, 0.05/0.46).

Average effects on mathematics and science GPAs

A secondary analysis focused on the outcome of GPAs in only mathematics and science (as described in the analysis plan). Mathematics and science are relevant because a popular belief in the United States links mathematics and science learning to ‘raw’ or ‘innate’ abilities—a view that the growth mindset intervention seeks to correct. In addition, success in mathematics and science strongly predicts long-term economic welfare and well-being. Analyses of outcomes for mathematics and science supported the same conclusions (B = 0.10 for mathematics and science GPAs compared to B = 0.10 for core GPAs; Extended Data Tables 1–3).

Quantifying heterogeneity

The intervention was expected to homogeneously change the mindsets of students across schools—as this would indicate high fidelity of implementation—however, it was expected to heterogeneously change lower-achieving students’ GPAs, as this would indicate potential school differences in the contextual mechanisms that sustain an initial treatment effect. As predicted, a mixed-effects model found no significant variability in the treatment effect on self-reported mindsets across schools (unstandardized τˆ=0.08, Q64 = 57.2, P = 0.714), whereas significant variability was found in the effect on GPAs among lower-achieving students across schools (unstandardized τˆ=0.09, Q64 = 85.5, P = 0.038) (Extended Data Fig. 2).