Do growth mindset interventions improve academic achievement?

Teaching students that abilities can develop is not a dependable way to produce large academic gains. The strongest case is narrower: some interventions have produced small improvements for particular students in particular settings. In the 2019 National Study of Learning Mindsets, a brief online intervention raised the grades of lower-achieving students in U.S. public high schools by about one tenth of a grade-point-average point. Other careful studies and reviews find little or no benefit.

That is a reason to be skeptical of broad promises, not a reason to tell students they cannot learn. The belief that improvement is possible, the claim that people with that belief do better, and the claim that a lesson about the belief raises grades are three different ideas.

For a teacher or school deciding where to spend time and money, the third idea is the one that counts. Encouraging language may be appealing. But whether a specific program improves learning enough to justify its cost is a question for evidence.

What a growth mindset intervention tries to change

A growth mindset is a belief that an ability can be developed rather than remaining fixed. Interventions generally try to change how students interpret difficulty: struggling with a problem need not mean that they lack the ability to learn it.

An influential 2007 paper by Lisa Blackwell, Kali Trzesniewski, and Carol Dweck combined a longitudinal study of students' beliefs with a smaller intervention study. It helped establish the argument that beliefs about intelligence could shape motivation and academic trajectories.

Those two kinds of evidence answer different questions. If students with different beliefs have different grades, the beliefs might contribute to that difference. But earlier success, instruction, and other characteristics might also influence both. Randomly assigning a lesson and measuring later outcomes asks a more direct question: did this intervention produce an improvement?

Even then, an intervention can change what students say they believe without changing what they learn. Changing how students answer a questionnaire is not yet an educational benefit.

A major national experiment found a small, targeted benefit

The 2019 National Study of Learning Mindsets, led by David Yeager and colleagues, tested a brief online intervention in U.S. public high schools. Its preregistered analysis found improved grades among lower-achieving students. The estimated benefit was about one tenth of a grade-point-average point, a standardized effect of d=.11. That figure expresses the group difference in standard-deviation units, which allows comparisons across different achievement measures.

That is a small effect, not a transformation in achievement. It is also evidence that a blanket claim of “no benefits anywhere” goes too far.

The result applied to lower-achieving students. It is not a claim that every student gains the same amount. The researchers also examined how results varied with school context. Those differences are informative, but school context itself was not randomly assigned. They do not provide a proven recipe for making the intervention work in any school.

The study also reported a favorable result for advanced mathematics enrollment in tenth grade. In an analysis of 6,690 students from 41 schools, including both lower- and higher-achieving students, enrollment was 36 percent in the intervention group versus 33 percent in the control group. This analysis was exploratory and had not been preregistered. It concerns a different outcome and a broader student group than the primary GPA result. Treat it as promising evidence that needs confirmation. Course-enrollment analysis.

A targeted benefit is still a benefit worth examining. The decision turns on its reliability, size, cost, and relevance to the students a school intends to serve.

Why two reviews reached different conclusions

In a 2023 systematic review and meta-analysis, Brooke Macnamara and Alexander Burgoyne examined achievement effects and the quality of the evidence. The overall estimate was d=.05. Several adjustments for possible publication bias reduced it further and made it statistically indistinguishable from zero. A set of six studies meeting their highest-quality criteria produced d=.02, with a confidence interval from −.06 to .10.

Publication bias is the possibility that the studies available to read are an uneven sample: encouraging results may be more likely to appear than disappointing ones. Statistical adjustments do not reveal every missing study, but they help test whether a conclusion depends on assumptions about the available evidence. This review gives strong reasons to doubt large, general academic benefits.

A separate review by Jeni Burnette and colleagues, also published in a 2023 issue, emphasized differences among interventions. For academic achievement, its model combining targeted student groups with high implementation fidelity estimated d=.14. That is a conditional estimate for selected circumstances, not an overall effect for all students. Its prediction interval ran from −.08 to .35, which leaves substantial uncertainty about what a future intervention would achieve.

Do not count these reviews as two votes. They made different choices about which results to combine, and they answer different questions. “What is the overall benefit in stronger studies?” and “What benefit might occur in targeted groups with high-quality delivery?” can produce different estimates without either estimate applying universally.

The same journal issue carried the next round of the argument. In an exploratory reanalysis, Elizabeth Tipton and colleagues, including David Yeager, who led the 2019 national study, used every effect size in Macnamara and Burgoyne's studies rather than one average per study. They estimated a mean effect of 0.09 standard deviations, and 0.15 for students they classified as at risk. Their central criticism was methodological: when effects really vary, a meta-analysis should model where they occur instead of asking whether one overall effect exists. Tipton and colleagues, 2023.

Macnamara and Burgoyne replied that the reanalysis had changed effect sizes, the coding of moderators and which studies and subsamples were included, often without explanation. When they applied the multilevel approach Tipton and colleagues recommended to their own coding, they estimated 0.07 overall and essentially zero (d=−.003) among studies that changed students' mindsets and met the most best-practice criteria. Macnamara and Burgoyne's reply.

Both reanalyses put the average effect below a tenth of a standard deviation. The live disagreement is whether the larger effects reported for targeted groups are dependable or reflect weaker designs and selective reporting. That is the question a school needs answered for its own students before adopting a program.

What the newer review changes

A 2025 structured review by Carolina Gazmuri provides another skeptical assessment. Its strongest included evaluations showed tiny or zero academic effects, which adds to the case against spending substantial resources on the assumption that a mindset program reliably raises achievement.

It is not, however, a direct retest of every positive subgroup finding. Its rules on how full-sample and subgroup results were reported led it to exclude several prominent trials, including the 2019 national experiment, and the review was not preregistered. Nor does it settle every claim about learning, motivation, or whether abilities change.

A useful message is not automatically a useful program

Imagine a student who is struggling with fractions. Telling the student that learning is possible does not identify which step they misunderstand. A mindset exercise could change how they interpret the difficulty while leaving the difficulty itself unresolved.

That example does not prove that beliefs are irrelevant. It shows why an academic intervention needs an academic outcome. A school should know whether students learned more, not only whether they gave more encouraging answers afterward.

Small effects can matter when an intervention is inexpensive and reaches many people. The benefits may also be too small to justify training costs and classroom time, especially when delivery is weak. Neither “it costs very little” nor “the average effect is small” settles that calculation without a concrete program and a realistic comparison.

If you are considering a program for a school, ask for evidence on that program, with similar students and the outcome the school wants to improve. Look for a credible comparison group and an analysis specified before the researchers saw the data. A testimonial or a general citation to mindset theory does not answer those questions.

The practical position is modest: do not build an educational strategy around a promise that changing beliefs will produce large achievement gains. Treat a specific mindset intervention as something that must earn its place alongside the other demands on students' and teachers' time.

For a different approach to the learning question, see the evidence on retrieval practice. That research tests what changes when learners try to recall material, and it has its own limits on subjects, comparison activities, and later performance.