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Race, academic achievement and the issue of inequitable motivational payoff


As racial inequities continue to pervade school systems around the world, further research is necessary to understand the factors undergirding this pressing issue. Here across three studies conducted in the United States (N = 8,293), we provide evidence that race-based differences in student achievement do not stem from a lack of motivation among Black, Latinx and Indigenous (BLI) students, but a lack of equitable motivational payoff. Even when BLI and non-BLI students have the same levels of motivation, BLI students still receive maths grades that are an average of 9% lower than those of their non-BLI peers (95% confidence interval 7 to 11%). This pattern was not explained by differences in students’ aptitude, effort or prior achievement but was instead linked to teachers’ diminished expectations for their BLI students’ academic futures. We conclude by discussing statistical power limitations and the implications of the current findings for how researchers consider the sources of, and solutions for, educational inequity.

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Fig. 1: Motivation profile results for studies 1–3.
Fig. 2: Results from models predicting maths grade from BLI background within each motivational profile for studies.
Fig. 3: SEM results demonstrating mediating role of teachers’ expectations for students’ academic futures in the negative relationship between BLI background and grade within each motivational profile in study 3.

Data availability

Per the ethics board agreement, the complete datasets for studies 1 and 2 will be made available upon request pending approval from the University System of Georgia. The datasets provided will be limited to the variables relevant to the current analyses. The complete dataset for study 3 is publicly available on the National Center for Education Statistics website:

Code availability

The complete analytic code for each study may be found here:


  1. Elliot, A. J., Dweck, C. S. & Yeager, D. S. (eds) Handbook of Competence and Motivation: Theory and Application (Guilford Publications, 2017).

  2. Guo, J., Parker, P. D., Marsh, H. W. & Morin, A. J. Achievement, motivation, and educational choices: a longitudinal study of expectancy and value using a multiplicative perspective. Dev. Psychol. 51, 1163–1176 (2015).

    Article  PubMed  Google Scholar 

  3. Hong, W., Bernacki, M. L. & Perera, H. N. A latent profile analysis of undergraduates’ achievement motivations and metacognitive behaviors, and their relations to achievement in science. J. Educ. Psychol. 112, 1409–1430 (2020).

    Article  Google Scholar 

  4. Jiang, S., Simpkins, S. D. & Eccles, J. S. Individuals’ math and science motivation and their subsequent STEM choices and achievement in high school and college: a longitudinal study of gender and college generation status differences. Dev. Psychol. 56, 2137–2151 (2020).

    Article  PubMed  Google Scholar 

  5. DeVoe, J. F. & Darling-Churchill, K. E. Status and Trends in the Education of American Indians and Alaska Natives: 2008. NCES 2008-084 (National Center for Education Statistics, 2008).

  6. Hardin, T. L. A Comparative Study of Native American Student Academic Achievement in Public and Bureau of Indian Education Schools. Doctoral dissertation, Ball State Univ. (2012).

  7. Hemphill, F. C. & Vanneman, A. Achievement Gaps: How Hispanic and White Students in Public Schools Perform in Mathematics and Reading on the National Assessment of Educational Progress. Statistical Analysis Report. NCES 2011-459 (National Center for Education Statistics, 2011).

  8. Reardon, S. F., Kalogrides, D. & Shores, K. The geography of racial/ethnic test score gaps. Am. J. Sociol. 124, 1164–1221 (2019).

    Article  Google Scholar 

  9. Walton, G. M., Spencer, S. J. & Erman, S. Affirmative meritocracy. Soc. Issues Policy Rev. 7, 1–35 (2013).

    Article  Google Scholar 

  10. Broda, M. et al. Reducing inequality in academic success for incoming college students: a randomized trial of growth mindset and belonging interventions. J. Res. Educ. Eff. 11, 317–338 (2018).

    Google Scholar 

  11. Harackiewicz, J. M., Canning, E. A., Tibbetts, Y., Priniski, S. J. & Hyde, J. S. Closing achievement gaps with a utility-value intervention: disentangling race and social class. J. Personal. Soc. Psychol. 111, 745–765 (2016).

    Article  Google Scholar 

  12. Roksa, J. & Whitley, S. E. Fostering academic success of first-year students: exploring the roles of motivation, race, and faculty. J. Coll. Stud. Dev. 58, 333–348 (2017).

    Article  Google Scholar 

  13. Shernoff, D. J. & Schmidt, J. A. Further evidence of an engagement–achievement paradox among US high school students. J. Youth Adolesc. 37, 564–580 (2008).

    Article  Google Scholar 

  14. Chen, X. & Weko, T. Students Who Study Science, Technology, Engineering, and Mathematics (STEM) in Postsecondary Education (US Department of Education, National Center for Education Statistics, 2009).

  15. Griffith, A. L. Persistence of women and minorities in STEM field majors: is it the school that matters? Econ. Educ. Rev. 29, 911–922 (2010).

    Article  Google Scholar 

  16. Oyserman, D., Johnson, E. & James, L. Seeing the destination but not the path: effects of socioeconomic disadvantage on school-focused possible self content and linked behavioral strategies. Self Identity 10, 474–492 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Priest, N. et al. Stereotyping across intersections of race and age: racial stereotyping among white adults working with children. PLoS ONE 13, e0201696 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Destin, M., Hanselman, P., Buontempo, J., Tipton, E. & Yeager, D. S. Do student mindsets differ by socioeconomic status and explain disparities in academic achievement in the United States? AERA Open 5, 1–12 (2019).

    Article  Google Scholar 

  19. Eccles, J. et al. in Achievement and Achievement Motives (ed. Spence, J. T.) pp. 73–146 (W. H. Freeman, 1983).

  20. Dweck, C. S. Self-Theories: Their Role in Motivation, Personality and Development (Taylor and Francis/Psychology Press, 1999).

  21. Oyserman, D. & Lewis Jr, N. A. Seeing the destination AND the path: using identity‐based motivation to understand and reduce racial disparities in academic achievement. Soc. Issues Policy Rev. 11, 159–194 (2017).

    Article  Google Scholar 

  22. Lavrijsen, J., Vansteenkiste, M., Boncquet, M. & Verschueren, K. Does motivation predict changes in academic achievement beyond intelligence and personality? A multitheoretical perspective. J. Educ. Psychol. 114, 772–790 (2021).

    Article  Google Scholar 

  23. Harvey, K. E., Suizzo, M. A. & Jackson, K. M. Predicting the grades of low-income–ethnic-minority students from teacher-student discrepancies in reported motivation. J. Exp. Educ. 84, 510–528 (2016).

    Article  Google Scholar 

  24. Mickelson, R. A. The attitude-achievement paradox among Black adolescents. Sociol. Educ. 63, 44–61 (1990).

    Article  Google Scholar 

  25. Mickelson, R. A. in Minority Status, Oppositional Culture, & Schooling (ed. Ogbu, J. U.) pp. 348–373 (Routledge, 2008).

  26. Downey, D. B., Ainsworth, J. W. & Qian, Z. Rethinking the attitude-achievement paradox among blacks. Sociol. Educ. 82, 1–19 (2009).

    Article  Google Scholar 

  27. Ladson-Billings, G. & Tate, W. F. in Critical Race Theory in Education (eds Dixson, A. D., Rousseau Anderson, C. K. & Donnor, J. K.) pp. 10–31 (Routledge, 2016).

  28. Vaught, S. E. & Castagno, A. E. “I don’t think I’m a racist”: critical race theory, teacher attitudes, and structural racism. Race Ethn. Educ. 11, 95–113 (2008).

    Article  Google Scholar 

  29. Mello, Z. R., Mallett, R. K., Andretta, J. R. & Worrell, F. C. Stereotype threat and school belonging in adolescents from diverse racial/ethnic backgrounds. J. Risk Issues 17, 9–14 (2012).

    Google Scholar 

  30. Steele, C. M. & Aronson, J. in The Black–White Test Score Gap (eds Jencks, C. & Phillips, M.) pp. 401–427 (Brookings Institution Press, 1998).

  31. Walton, G. M. & Cohen, G. L. A question of belonging: race, social fit, and achievement. J. Personal. Soc. Psychol. 92, 82–96 (2007).

    Article  Google Scholar 

  32. Smalls, C., White, R., Chavous, T. & Sellers, R. Racial ideological beliefs and racial discrimination experiences as predictors of academic engagement among African American adolescents. J. Black Psychol. 33, 299–330 (2007).

    Article  Google Scholar 

  33. McGee, E. & Spencer, M. B. Black parents as advocates, motivators, and teachers of mathematics. J. Negro Educ. 84, 473–490 (2015).

    Article  Google Scholar 

  34. Baker, B. & Cotto, R. Jr The under-funding of Latinx-serving school districts. Phi Delta Kappan 101, 40–46 (2020).

    Article  Google Scholar 

  35. Simeone, T. The Harvard Project on American Indian economic development: findings and considerations. Ottawa: Parliamentary Information and Research Service. Library of Parliament (2007).

  36. Boser, U., Wilhelm, M. & Hanna, R. The Power of the Pygmalion Effect: Teachers’ Expectations Strongly Predict College Completion (Center for American Progress, 2014).

  37. Riley, T. & Ungerleider, C. Self-fulfilling prophecy: how teachers’ attributions, expectations, and stereotypes influence the learning opportunities afforded Aboriginal students. Can. J. Educ. 35, 303–333 (2012).

    Google Scholar 

  38. Sorhagen, N. S. Early teacher expectations disproportionately affect poor children’s high school performance. J. Educ. Psychol. 105, 465–477 (2013).

    Article  Google Scholar 

  39. Woolley, M. E., Strutchens, M., Gilbert, M. C. & Martin, W. G. Mathematics success of Black middle school students: direct and indirect effects of teacher expectations and reform practices. Negro Educ. Rev. 61, 41–59 (2010).

    Google Scholar 

  40. Pit-ten Cate, I. M. & Glock, S. Teachers’ implicit attitudes toward students from different social groups: a meta-analysis. Front. Psychol. 10, 1–18 (2019).

    Article  Google Scholar 

  41. Quinn, D. M. Racial attitudes of preK–12 and postsecondary educators: descriptive evidence from nationally representative data. Educ. Res. 6, 397–411 (2017).

    Article  Google Scholar 

  42. Rosenthal, R. & Jacobson, L. Pygmalion in the classroom. Urban Rev. 3, 16–20 (1968).

    Article  Google Scholar 

  43. Jussim, L. & Harber, K. D. Teacher expectations and self-fulfilling prophecies: knowns and unknowns, resolved and unresolved controversies. Personal. Soc. Psychol. Rev. 9, 131–155 (2005).

    Article  Google Scholar 

  44. Turetsky, K. M., Sinclair, S., Starck, J. G. & Shelton, J. N. Beyond students: how teacher psychology shapes educational inequality. Trends Cogn. Sci. 25, 697–709 (2021).

    Article  PubMed  Google Scholar 

  45. Gershenson, S. & Papageorge, N. The power of teacher expectations: how racial bias hinders student attainment. Education 18, 64–71 (2018).

    Google Scholar 

  46. Cronin, M. R. et al. Anti-racist interventions to transform ecology, evolution and conservation biology departments. Nat. Ecol. Evol. 5, 1213–1223 (2021).

    Article  PubMed  Google Scholar 

  47. Destin, M. Identity research that engages contextual forces to reduce socioeconomic disparities in education. Curr. Dir. Psychol. Sci. 29, 161–166 (2020).

    Article  Google Scholar 

  48. Destin, M., Silverman, D. M. & Rogers, L. O. Expanding the social psychological study of educators through humanizing principles. Soc. Personal. Psychol. Compass 16, e12668 (2022).

    Article  Google Scholar 

  49. Silverman, D. M., Hernandez, I. A., & Destin M. Educators’ beliefs about students’ socioeconomic backgrounds as an avenue for supporting motivation. Personal. Soc. Psychol. Bull. 49, 215–232 (2023).

  50. National Science Board. Science & Engineering Indicators, 2018 (National Science Board, 2018).

  51. Ma, J., Pender, M. & Welch, M. Education Pays 2016: The Benefits of Higher Education for Individuals and Society. Trends in Higher Education Series (College Board, 2016).

  52. de Brey, C. et al. Status and Trends in the Education of Racial and Ethnic Groups 2018 (National Center for Education Statistics, 2019).

  53. McGrady, P. B. & Reynolds, J. R. Racial mismatch in the classroom: beyond Black–white differences. Sociol. Educ. 86, 3–17 (2013).

    Article  Google Scholar 

  54. Reardon, S. F., Robinson-Cimpian, J. P. & Weathers, E. S. in Handbook of Research in Education Finance and Policy (eds Ladd, H. F. & Goertz, M. E.) pp. 507–525 (Routledge, 2014).

  55. Lee, S. J. Unraveling the “Model Minority” Stereotype: Listening to Asian American Youth (Teachers College Press, 2015).

  56. Barron, K. E. & Hulleman, C. S. in International Encyclopedia of Social and Behavioral Sciences, 2nd Edition: Motivational Psychology (eds Eccles, J. S. & Samelo-Aro, K.) (Elsevier, 2015).

  57. Dweck, C. S. Mindset: The New Psychology of Success (Random House, 2008).

  58. Collins, L. M. & Lanza, S. T. Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Sciences (John Wiley & Sons, 2009).

  59. Bergman, L. R., Magnusson, D., & El Khouri, B. Studying Individual Development in an Interindividual Context: A Person-Oriented Approach (Lawrence Erlbaum Associates, 2003).

  60. Perez, T. et al. Science expectancy, value, and cost profiles and their proximal and distal relations to undergraduate science, technology, engineering, and math persistence. Sci. Educ. 103, 264–286 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  61. Meredith, W. Measurement invariance, factor analysis and factorial invariance. Psychometrika 58, 525–543 (1993).

    Article  Google Scholar 

  62. González, A., Paoloni, V., Donolo, D. & Rinaudo, C. Motivational and emotional profiles in university undergraduates: a self-determination theory perspective. Span. J. Psychol. 15, 1069–1080 (2012).

    Article  PubMed  Google Scholar 

  63. Xie, K., Vongkulluksn, V. W., Lu, L. & Cheng, S. A person-centered approach to examining high-school students’ motivation, engagement and academic performance. Contemp. Educ. Psychol. 62, 1–13 (2020).

    Article  Google Scholar 

  64. Soland, J. The achievement gap or the engagement gap? Investigating the sensitivity of gaps estimates to test motivation. Appl. Meas. Educ. 31, 312–323 (2018).

    Article  Google Scholar 

  65. Entwisle, D. R., Alexander, K. L. & Olson, L. S. First grade and educational attainment by age 22: a new story. Am. J. Sociol. 110, 1458–1502 (2005).

    Article  Google Scholar 

  66. McKown, C. & Weinstein, R. S. Teacher expectations, classroom context, and the achievement gap. J. Sch. Psychol. 46, 235–261 (2008).

    Article  PubMed  Google Scholar 

  67. McDermott, R. & Vossoughi, S. Beyond the culture of poverty, again. Diaspora Indig. Minor. Educ. 14, 60–69 (2020).

  68. Sherman, D. K. et al. Deflecting the trajectory and changing the narrative: how self-affirmation affects academic performance and motivation under identity threat. J. Personal. Soc. Psychol. 104, 591–618 (2013).

    Article  Google Scholar 

  69. Okonofua, J. A., Perez, A. D. & Darling-Hammond, S. When policy and psychology meet: mitigating the consequences of bias in schools. Sci. Adv. 6, eaba9479 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  70. Griffiths, C. M. Feed Forward: How Feedback Shapes Teachers’ Beliefs about Student Potential and Student Beliefs about Teachers. Dissertation, Stanford Univ. (2021).

  71. Ladson-Billings, G. I’m here for the hard re-set: post pandemic pedagogy to preserve our culture. Equity Excell. Educ. 54, 68–78 (2021).

    Article  Google Scholar 

  72. Canning, E. A., Muenks, K., Green, D. J. & Murphy, M. C. STEM faculty who believe ability is fixed have larger racial achievement gaps and inspire less student motivation in their classes. Sci. Adv. 5, eaau4734 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  73. Hornstra, L., Stroet, K., van Eijden, E., Goudsblom, J. & Roskamp, C. Teacher expectation effects on need-supportive teaching, student motivation, and engagement: a self-determination perspective. Educ. Res. Eval. 24, 324–345 (2018).

    Article  Google Scholar 

  74. Rattan, A., Good, C. & Dweck, C. S. “It’s ok—not everyone can be good at math”: instructors with an entity theory comfort (and demotivate) students. J. Exp. Soc. Psychol. 48, 731–737 (2012).

    Article  Google Scholar 

  75. Guay, F., Marsh, H. W. & Boivin, M. Academic self-concept and academic achievement: developmental perspectives on their causal ordering. J. Educ. Psychol. 95, 124–136 (2003).

    Article  Google Scholar 

  76. Major, B. & O’brien, L. T. The social psychology of stigma. Annu. Rev. Psychol. 56, 393–421 (2005).

    Article  PubMed  Google Scholar 

  77. Cadinu, M., Maass, A., Frigerio, S., Impagliazzo, L. & Latinotti, S. Stereotype threat: the effect of expectancy on performance. Eur. J. Soc. Psychol. 33, 267–285 (2003).

    Article  Google Scholar 

  78. Aronson, J., Fried, C. B. & Good, C. Reducing the effects of stereotype threat on African American college students by shaping theories of intelligence. J. Exp. Soc. Psychol. 38, 113–125 (2002).

    Article  Google Scholar 

  79. Yeager, D. S. et al. A national experiment reveals where a growth mindset improves achievement. Nature 573, 364–369 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Walton, G. M. & Yeager, D. S. Seed and soil: psychological affordances in contexts help to explain where wise interventions succeed or fail. Curr. Dir. Psychol. Sci. 29, 219–226 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  81. National Center for Education Statistics. Educational Longitudinal Study (ELS), 2002 (United States Department of Education, 2002).

  82. Kosovich, J. J., Hulleman, C. S., Phelps, J. & Lee, M. Improving algebra success with a utility-value intervention. J. Dev. Educ. 42, 2–10 (2019).

    Google Scholar 

  83. Pintrich, P. R., Smith, D., Garcia, T. & McKeachie, W. A Manual for the Use of the Motivated Strategies for Learning Questionnaire (MSLQ) (The University of Michigan, 1991).

  84. Ingels, S. J., Pratt, D. J., Rogers, J. E., Siegel, P. H. & Stutts, E. S. Education Longitudinal Study of 2002: Base-Year to First Follow-Up Data File Documentation (National Center for Education Statistics, 2005).

  85. Blackwell, L. S., Trzesniewski, K. H. & Dweck, C. S. Implicit theories of intelligence predict achievement across an adolescent transition: a longitudinal study and an intervention. Child Dev. 78, 246–263 (2007).

    Article  PubMed  Google Scholar 

  86. Kraus, M. W., Piff, P. K. & Keltner, D. Social class, sense of control, and social explanation. J. Personal. Soc. Psychol. 97, 992–1004 (2009).

    Article  Google Scholar 

  87. Muthén, L. K. & Muthén, B. Mplus. The Comprehensive Modelling Program for Applied Researchers: User’s Guide (Muthén & Muthén, 2018).

  88. Jorgensen, T. D. et al. semTools: Useful tools for structural equation modeling (2020).

  89. Wang, Y., Kim, E. & Yi, Z. Robustness of latent profile analysis to measurement noninvariance between profiles. Educ. Psychol. Meas. 82, 5–28 (2022).

    Article  PubMed  Google Scholar 

  90. Johnson, S. K. Latent profile transition analyses and growth mixture models: a very non‐technical guide for researchers in child and adolescent development. New Dir. Child Adolesc. Dev. 2021, 111–139 (2021).

    Article  PubMed  Google Scholar 

  91. Geiser, C. Data Analysis with Mplus (Guilford Publications, 2013).

  92. Asparouhov, T. & Muthén, B. Auxiliary variables in mixture modeling: three-step approaches using M plus. Struct. Equ. Modeling 21, 329–341 (2014).

    Article  Google Scholar 

  93. Vermunt, J. K. Latent class modeling with covariates: two improved three-step approaches. Political Anal. 18, 450–469 (2010).

    Article  Google Scholar 

  94. Ingels, S. J., Pratt, D. J., Rogers, J. E., Siegel, P. H. & Stutts, E. S. Education Longitudinal Study of 2002: Base Year Data File User’s Manual (National Center for Education Statistics, 2004).

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We would like to thank I. A. Hernandez and D. C. Molden for providing valuable feedback throughout our work on the project. This research was supported by the National Science Foundation’s Graduate Research Fellowship Program (no. DGE-1842165, D.M.S.), Joyce Foundation (grant number 16-37550, C.S.H. and Y.T.) and National Science Foundation (grant number EHR 2000507, C.S.H. and Y.T.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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D.M.S. determined the initial research question and methodological approach, conducted all analyses and wrote the manuscript. R.J.R. helped develop the research question and assisted with the manuscript writing process. S.V.W. assisted with analyses and data collection. Y.T. and C.S.H. assisted with the data collection and the writing process. M.D. helped develop the research question, advised on all analyses and assisted with the writing process.

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Correspondence to David M. Silverman.

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Silverman, D.M., Rosario, R.J., Wormington, S.V. et al. Race, academic achievement and the issue of inequitable motivational payoff. Nat Hum Behav (2023).

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