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Classroom Diversity and College Student Dropout: New Evidence from Panel Data and Objective Measures

Innovative Higher Education volume 47, pages 609–637 (2022)Cite this article

Abstract

To address the mounting concern about the validity of student self-reported data, this study relies on official matriculation records to gauge the effect of classroom diversity on student dropout risk. Using panel data to track the 4-year dropout risk of a cohort of new first-year students (N = 3545) at a public research university, we employ a discrete-time-to-event history model to estimate the marginal effect of classroom ethnic-racial composition while controlling for both time-variant and time-invariant student-level and classroom-level factors on demographics, precollege preparation, college academic experience, campus living arrangement, and financial aid support. The study finds: 1) The effect of classroom ethnic-racial composition during a student’s enrollment spell varies across student ethnic-racial identity, first-generation status, and level of academic preparation of classroom peers; exposure to Asian classmates is associated with a lower dropout risk for Black students, while exposure to underrepresented minority classmates (excluding Asians) is associated with lower dropout risk for Hispanic, Native American, multi-ethic, and first-generation students. 2) Semester-to-semester rise in exposure to Asian classmates is associated with a lower dropout risk for Black students. 3) Observed effects of classroom ethnic-racial composition do not vary significantly with enrollment in diversity-focused courses. 4) Estimated effect sizes of ethnic-racial classroom composition are very small in comparison to effects of student academic engagement and success. Thus, the nexus between diversity and academic persistence is moderated by a host of factors, both time variant and invariant, and is difficult to leverage operationally due to observed small effects and student discretionary behavior.

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References

  • Adelman, C. (2004). Principal Indicators of Student Academic Histories in Postsecondary Education, 1972–2000. US Department of Education.

  • Allison, P. (2012). When can you safely ignore multicollinearity? Statistical Horizons. September 10, 2012. From https://statisticalhorizons.com/multicollinearity. Accessed 2021.

  • Antonio, A. L., Chang, M. J., Hakuta, K., Kenny, D. A., Levin, S., & Milem, J. F. (2004). Effects of racial diversity on complex thinking in college students. Psychological Science, 15(8), 507–510.

    Google Scholar 

  • Arcidiacono, P., Foster, G., Goodpaster, N., & Kinsler, J. (2012). Estimating spillovers using panel data, with an application to the classroom. Quantitative Economics, 3(3), 421–470.

    Google Scholar 

  • Astin, A. (1993). What matters in college? Four critical years revisited. Jossey- Bass.

  • Banks, K. H. (2009). A qualitative investigation of white students’ perceptions of diversity. Journal of Diversity in Higher Education, 2(3), 149–155. https://doi.org/10.1037/a0016292

    Article  Google Scholar 

  • Bean, J. (1982). Conceptual models of student attrition: How theory can help the institutional researcher. New Directions for Institutional Research, 36, 17–33.

    Google Scholar 

  • Berg, G. A. (2020). Equity and diversity in the 21st century university: A literature review. Accessibility and Diversity in the 21st Century University, 1–19.

  • Bowman, N. A. (2009). College diversity courses and cognitive development among students from privileged and marginalized groups. Journal of Diversity in Higher Education, 2(3), 182.

    Google Scholar 

  • Bowman, N. A. (2010). College diversity experiences and cognitive development: A meta-analysis. Review of Educational Research, 80(1), 4–33.

    Google Scholar 

  • Bowman, N. A. (2011). Validity of college self-reported gains at diverse institutions. Educational Researcher, 40(1), 22–24.

    Google Scholar 

  • Bowman, N.A. (2013). How much diversity is enough? The curvilinear relationship between college diversity interactions and first-year student outcomes. Research in Higher Education, 54(8), 874–894.

    Google Scholar 

  • Bowman, N. A., & Park, J. J. (2015). Not all diversity interactions are created equal: Cross-racial interaction, close interracial friendship, and college student outcomes. Research in Higher Education, 56(6), 601–621.

    Google Scholar 

  • Bowman, N. A., Denson, N., & Park, J. J. (2016). Racial/cultural awareness workshops and post-college civic engagement: A propensity score matching approach. American Educational Research Journal, 53(6), 1556–1587. https://doi.org/10.3102/0002831216670510

    Article  Google Scholar 

  • Braxton, J., Milem, J., & Sullivan, A. (2000). The influence of active learning on the college student departure process: Toward a revision of Tinto’s theory. Journal of Higher Education, 71(5), 569–590.

    Google Scholar 

  • Burke, M. A., & Sass, T. R. (2013). Classroom peer effects and student achievement. Journal of Labor Economics, 31(1), 51–82.

    Google Scholar 

  • Carrell, S. E., Fullerton, R. L., & West, J. E. (2009). Does your cohort matter? Measuring peer effects in college achievement. Journal of Labor Economics, 27(3), 439–464.

    Google Scholar 

  • Chen, R., & DesJardins, S. L. (2008). Exploring the effects of financial aid on the gap in student dropout risks by income level. Research in Higher Education, 49(1), 1–18.

    Google Scholar 

  • Ciocca Eller, C., & DiPrete, T. A. (2018). The paradox of persistence: Explaining the black-white gap in bachelor’s degree completion. American Sociological Review, 83(6), 1171–1214.

    Google Scholar 

  • Clayson, D. E., & Sheffet, M. J. (2006). Personality and the student evaluation of teaching. Journal of Marketing Education, 28(2), 149–160.

    Google Scholar 

  • Cook, B. G., & Therrien, W. J. (2017). Null effects and publication bias in special education research. Behavioral Disorders, 42(4), 149–158.

    Google Scholar 

  • Cruce, T. M. (2009). A note on the calculation and interpretation of the delta-p statistic for categorical independent variables. Research in Higher Education, 50(6), 608–622.

    Google Scholar 

  • Cui, J., & Qian, G. (2007). Selection of working correlation structure and best model in GEE analyses of longitudinal data. Communications in Statistics: Simulation and Computation, 36(5), 987–996.

    Google Scholar 

  • De Oliveira, S., & Nisbett, R. E. (2018). Demographically diverse crowds are typically not much wiser than homogeneous crowds. Proceedings of the National Academy of Sciences, 115(9) 2066–2071.

    Google Scholar 

  • Denson, N., & Bowman, N. A. (2017). Do diversity courses make a difference? A critical examination of college diversity coursework and student outcomes. In Higher education: Handbook of theory and research (pp. 35–84). Springer.

    Google Scholar 

  • Denson, N., Bowman, N. A., Ovenden, G., Culver, K. C., & Holmes, J. M. (2021). Do diversity courses improve college student outcomes? A meta-analysis. Journal of Diversity in Higher Education, 14(4), 544–556.

  • Dills, A. K. (2018). Classroom diversity and academic outcomes. Economic Inquiry, 56(1), 304–316.

    Google Scholar 

  • Dong, S. (2019). The effects of first-generation status on student engagement and outcomes at liberal arts colleges. Journal of College Student Development, 60(1), 17–34.

    Google Scholar 

  • Eckles, D., & Bakshy, E. (2021). Bias and high-dimensional adjustment in observational studies of peer effects. Journal of the American Statistical Association, 116(534), 507–517.

  • Elder, A. (2021). Holistic factors related to student persistence at a large, public university. Journal of Further and Higher Education, 45(1), 65–78.

    Google Scholar 

  • Enders, C. K., & Tofighi, D. (2007). Centering predictor variables in cross-sectional multilevel models: A new look at an old issue. Psychological Methods, 12(2), 121–138.

    Google Scholar 

  • Feld, J., & Zölitz, U. (2017). Understanding peer effects: On the nature, estimation, and channels of peer effects. Journal of Labor Economics, 35(2), 387–428.

    Google Scholar 

  • Friedl, J. (1999). Needed: Documentation of how affirmative action benefits all students. Change: The Magazine of Higher Learning, 31(4), 40–45.

  • Geshekter, C. (2019). Diversity Discontent. Academic Questions, 32(2), 223–233.

    Google Scholar 

  • Gurin, P. (1999). Expert report of Patricia Gurin. Michigan Journal of Race and Law, 5(1), 363–425.

    Google Scholar 

  • Halaby, C. N. (2004). Panel models in sociological research: Theory into practice. Annual Review of Sociology, 30, 507–544.

    Google Scholar 

  • Hansen, Z., Owan, H., & Pan, J. (2006). The Impact of Group Diversity on Performance and Knowledge Spillover--An Experiment in a College Classroom (No. w12251). National Bureau of Economic Research.

    Google Scholar 

  • Herzog, S. (2007). Diversity and Educational Benefits: Moving Beyond Self-Reported Questionnaire Data. Education Working Paper Archive. ERIC Number: ED508971.

  • Herzog, S. (2010). Gauging the effect of compositional and curricular diversity on freshman success. New Directions for Institutional Research, 145, 73–97.

    Google Scholar 

  • Hong, S. C., & Lee, J. (2017). Who is sitting next to you? Peer effects inside the classroom. Quantitative Economics, 8(1), 239–275.

    Google Scholar 

  • Hornstein, H. A. (2017). Student evaluations of teaching are an inadequate assessment tool for evaluating faculty performance. Cogent Education, 4(1), 1304016.

    Google Scholar 

  • Ishitani, T.T. (2003). A longitudinal approach to assessing attrition behavior among first-generation students: Time-varying effects of pre-college characteristics. Research in Higher Education, 44(4), 433–449.

    Google Scholar 

  • Ishitani, T. T., & Snider K. G. (2006). Longitudinal effects of college preparation programs on college retention. IR Applications, Vol 9, May 3.

  • Kang, C. (2007). Classroom peer effects and academic achievement: Quasi-randomization evidence from South Korea. Journal of Urban Economics, 61(3), 458–495.

    Google Scholar 

  • Kraemer, H. C., Stice, E., Kazdin, A., Offord, D., & Kupfer, D. (2001). How do risk factors work together? Mediators, moderators, and independent, overlapping, and proxy risk factors. American Journal of Psychiatry, 158(6), 848–856.

    Google Scholar 

  • Kuh, G., Cruce, T., Shoup, R., Kinzie, J., & Gonyea, R. (2008). Unmasking the effects of student engagement on first-year college grades and persistence. Journal of Higher Education, 79(5), 540–563.

    Google Scholar 

  • Kuklinski, J. H. (2006). Review: the scientific study of campus diversity and students’ educational outcomes. Public Opinion Quarterly, 70(1), 99–120.

    Google Scholar 

  • Kuncel, N. R., Crede, M., & Thomas, L. L. (2005). The validity of self-reported grade point averages, class rank, and test scores: A meta-analysis and review of the literature. Review of Educational Research, 75(1), 63–82.

    Google Scholar 

  • Loes, C., Pascarella, E., & Umbach, P. (2012). Effects of diversity experiences on critical thinking skills: Who benefits? The Journal of Higher Education, 83(1), 1–25.

    Google Scholar 

  • Lott, J. R., Ramseyer, J. M., & Standen, J. (2011). Peer effects in affirmative action: Evidence from law student performance. International Review of Law and Economics, 31(1), 1–15.

    Google Scholar 

  • Martin, N. D., Spenner, K. I., & Mustillo, S. A. (2017). A test of leading explanations for the college racial-ethnic achievement gap: Evidence from a longitudinal case study. Research in Higher Education, 58(6), 617–645.

    Google Scholar 

  • Mayhew, M. J., Rockenbach, A. N., Bowman, N. A., Seifert, T. A., & Wolniak, G. C. (2016). How college affects students: 21st century evidence that higher education works (Vol. 1). Wiley.

    Google Scholar 

  • McNeish, D., Stapleton, L. M., & Silverman, R. D. (2017). On the unnecessary ubiquity of hierarchical linear modeling. Psychological Methods, 22(1), 114.

    Google Scholar 

  • Park, J. J. (2019). An Uneven Playing Field: The Complex Educational Experiences of Asian Americans. American Council on Education.

    Google Scholar 

  • Pascarella, E. T. (1985). Students' affective development within the college environment. The Journal of Higher Education, 56(6), 640–663.

    Google Scholar 

  • Pascarella, E. T. (2001). Using student self-reported gains to estimate college impact: A cautionary tale. Journal of College Student Development, 42(5), 488–492.

    Google Scholar 

  • Pascarella, E. T., & Terenzini, P. T. (2005). How College Affects Students: A Third Decade of Research. Volume 2. Jossey-Bass, An Imprint of Wiley.

  • Pascarella, E. T., Martin, G. L., Hanson, J. M., Trolian, T. L., Gillig, B., & Blaich, C. (2014). Effects of diversity experiences on critical thinking skills over 4 years of college. Journal of College Student Development, 55(1), 86–92.

    Google Scholar 

  • Petersen, T. (1985). A comment on presenting results for logit and probit models. American Sociological Review, 50(1), 130–131.

    Google Scholar 

  • Pike, G. (1999). The constant error of the halo in educational outcomes research. Research in Higher Education, 40(1), 61–86.

    Google Scholar 

  • Polanin, J. R., Tanner-Smith, E. E., & Hennesey, E. A. (2016). Estimating the difference between published and unpublished effect sizes: A meta-review. Review of Educational Research, 86(1), 207–236.

    Google Scholar 

  • Poon, O. A., Dizon, J. P. M., & Squire, D. (2017). Count me in!: Ethnic data disaggregation advocacy, racial mattering, and lessons for racial justice coalitions. Journal Committed to Social Change on Race and Ethnicity, 3(1), 91–124.

    Google Scholar 

  • Porter, S. R. (2011). Do college student surveys have any validity? The Review of Higher Education, 35(1), 45–76.

  • Porter, S. R. (2013). Self-reported learning gains: A theory and test of college student survey response. Research in Higher Education, 54(2), 201–226.

    Google Scholar 

  • Radunzel, J. (2021). Examining retention and transfer in relation to incoming student data for first-generation and continuing-generation students: What differences exist? Journal of College Student Retention: Research, Theory & Practice, 23(2), 214–242.

    Google Scholar 

  • Rincón, B. E. (2020). Does latinx representation matter for latinx student retention in STEM?. Journal of Hispanic Higher Education, 19(4), 437–451.

    Google Scholar 

  • Rjosk, C., Richter, D., Lüdtke, O., & Eccles, J. S. (2017). Ethnic composition and heterogeneity in the classroom: Their measurement and relationship with student outcomes. Journal of Educational Psychology, 109(8), 1188.

    Google Scholar 

  • Robbins, S. B., Lauver, K., Huy, L., Davis, D., & Langley, R. (2004). Do psychosocial and study skill factors predict college outcomes? A meta-analysis Psychological Bulletin, 130(2), 261–288.

    Google Scholar 

  • Roksa, J., Trolian, T. L., Pascarella, E. T., Kilgo, C. A., Blaich, C., & Wise, K. S. (2017a). Racial inequality in critical thinking skills: The role of academic and diversity experiences. Research in Higher Education, 58(2), 119–140.

    Google Scholar 

  • Roksa, J., Kilgo, C. A., Trolian, T. L., Pascarella, E. T., Blaich, C., & Wise, K. S. (2017b). Engaging with diversity: How positive and negative diversity interactions influence students’ cognitive outcomes. The Journal of Higher Education, 88(3), 297–322.

    Google Scholar 

  • Rosen, J. A., Porter, S. R., & Rogers, J. (2017). Understanding student self-reports of academic performance and course-taking behavior. AERA Open, 3(2). https://doi.org/10.1177/2332858417711427

  • Sacerdote, B. (2011). Peer effects in education: How might they work, how big are they and how much do we know thus far?. In Handbook of the Economics of Education (Vol. 3, pp. 249–277). Elsevier.

    Google Scholar 

  • Sass, D. A., Castro-Villarreal, F., Wilkerson, S., Guerra, N., & Sullivan, J. (2018). A structural model for predicting student retention. The Review of Higher Education, 42(1), 103–135.

    Google Scholar 

  • Shaw, E. J. (2005). Researching the Educational Benefits of Diversity (Research Report No.2005–4). The College Board.

  • Shaw, J. (2009). The diversity paradox: Does student diversity enhance or challenge excellence? Journal of Further and Higher Education, 33(4), 321–331.

    Google Scholar 

  • Sidanius, J., Levin, S., Van Laar, C., & Sears, D. O. (2008). The diversity challenge: Social identity and intergroup relations on the college campus. Russell Sage Foundation.

    Google Scholar 

  • Sommers, S. R., Warp, L S., & Mahoney, C. C. (2008). Cognitive effects of racial diversity: White individuals’ information processing in heterogeneous groups. Journal of Experimental Social Psychology, 44(4), 1129–1136.

    Google Scholar 

  • Spady, W. (1971). Dropouts from higher education: Toward an empirical model. Interchange, 2(3), 38–62.

    Google Scholar 

  • Steele, C. M., & Aronson, J. (1995). Stereotype threat and the intellectual test performance of African Americans. Journal of Personality and Social Psychology, 69(5), 797.

    Google Scholar 

  • Teranishi, R. T., Ceja M., Antonio, A. L., Allen, W. R., & McDonough, P. (2004). The college-choice process for Asian Pacific Americans: Ethnicity and socioeconomic class in context. The Review of Higher Education, 27(4), 527–551.

    Google Scholar 

  • Terenzini, P. T., Cabrera, A. F., Colbeck, C. L., Bjorklund, S. A., & Parente, J. M. (2001). Racial and ethnic diversity in the classroom: Does it promote student learning?. The Journal of Higher Education, 72(5), 509–531.

    Google Scholar 

  • Tinto, V. (1975). Dropout from higher education: A theoretical synthesis of recent research. Review of Educational Research, 45(1), 89–125.

    Google Scholar 

  • Tinto, V. (1993). Leaving College: Rethinking the Causes and Cures of Student Attrition, 2nd University of Chicago Press.

    Google Scholar 

  • Tinto, V. (1997). Classrooms as communities: Exploring the educational character of student persistence. The Journal of higher education, 68(6), 599–623.

    Google Scholar 

  • Tourangeau, R., Rips, L. J., & Rasinski, K. (2000). The psychology of survey response. Cambridge U. Press.

    Google Scholar 

  • Wang, L., & Maxwell, S. E. (2015). On disaggregating between-person and within-person effects with longitudinal data using multi-level models. Psychological Methods, 20(1), 63–83.

    Google Scholar 

  • Wang, Y., Murphy, O., Turgeon, M., Wang, Z., Bhatnagar, S. R., Schulz, J., & Moodie, E. E. M. (2015). The perils of quasi-likelihood information criteria. Stat, 4(1), 246–254.

    Google Scholar 

  • Westrick, P. A., Le, H., Robbins, S. B., Radunzel, J. M. R., & Schmidt, F. L. (2015). College performance and retention: A meta-analysis of the predictive Validities of ACT® scores, high school grades, and SES. Educational Assessment, 20(1), 23–45.

    Google Scholar 

  • Yue, H., & Fu, X. (2017). Rethinking graduation and time to degree: A fresh perspective. Research in Higher Education, 58(2), 184–213.

    Google Scholar 

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Acknowledgements

The author appreciates helpful comments by Stephen Porter and the anonymous reviewers.

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    Serge Herzog

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Herzog, S. Classroom Diversity and College Student Dropout: New Evidence from Panel Data and Objective Measures. Innov High Educ 47, 609–637 (2022). https://doi.org/10.1007/s10755-021-09591-5

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Keywords

  • Diversity
  • Student dropout
  • Classroom peers
  • Event history model
  • College retention