Skip to main content
SpringerLink
Log in

The Postsecondary Resource Trinity Model: Exploring the Interaction Between Socioeconomic, Academic, and Institutional Resources

  • Published:
Research in Higher Education Aims and scope Submit manuscript

Abstract

The purpose of this study is to revisit the widely held assumption that the impact of socioeconomic background declines steadily across educational transitions, particularly at the postsecondary level. Sequential logit modeling, a staple methodological approach for estimating the relative impact of SES across educational stages, is applied to a nationally representative cohort of high school sophomores drawn from the National Center for Education Statistics’ Education Longitudinal Study of 2002. However, the study extends the traditional sequential logit approach by examining how socioeconomic background interacts with students’ academic ability and postsecondary institutional selectivity and how the nature of these interactions varies across postsecondary stages. Analyzing the interactions between these three resources (socioeconomic, academic, and institutional) reveals the need for a more nuanced understanding of how SES influences students’ postsecondary outcomes. This new approach is termed the Postsecondary Resource Trinity Model. The empirical results and conceptual model have important implications for the way in which policymakers and higher education practitioners promote the postsecondary success of disadvantaged students, as well as for how scholars of higher education and social mobility study the relationship between socioeconomic background and postsecondary outcomes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Adelman, C. (1999). Answers in the tool box: Academic intensity, attendance patterns, and bachelor’s degree attainment. Washington, DC: National Center for Education Statistics.

    Google Scholar 

  • Adelman, C. (2006). The toolbox revisited: Paths to degree completion from high school through college. Washington, DC: U.S. Department of Education.

    Google Scholar 

  • Agresti, A. (2002). Categorical data analysis (2nd ed.). Hoboken, NJ: Wiley-Interscience.

    Book  Google Scholar 

  • Aries, E., & Seider, M. (2005). The interactive relationship between class identity and the college experience: The case of lower income students. Qualitative Sociology, 28(4), 419–443.

    Article  Google Scholar 

  • Aries, E., & Seider, M. (2007). The role of social class in the formation of identity: A study of public and elite private college students. The Journal of Social Psychology, 147(2), 137–157.

    Article  Google Scholar 

  • Bastedo, M. N., & Jaquette, O. (2011). Running in place: Low-income students and the dynamics of higher education stratification. Educational Evaluation and Policy Analysis, 33(3), 318–339.

    Article  Google Scholar 

  • Baum, S., & Lapovsky, L. (2006). Tuition discounting: Not just a private college practice. New York, NY: College Board.

    Google Scholar 

  • Bowen, W. G., Chingos, M. M., & McPherson, M. S. (2009). Crossing the finish line: Completing college at America’s public universities. Princeton, NJ: Princeton University Press.

    Google Scholar 

  • Breen, R., & Jonsson, J. O. (2000). Analyzing educational careers: A multinomial transition model. American Sociological Review, 65(5), 754–772.

    Article  Google Scholar 

  • Cabrera, A. F., Burkum, K. R., & La Nasa, S. M. (2005). Pathways to a four-year degree: Determinants of transfer and degree completion. In A. Seidman (Ed.), College student retention: Formula for student success (pp. 155–213). Washington, DC: American Council on Education.

    Google Scholar 

  • Cabrera, A. F., & La Nasa, S. M. (2000). Understanding the college-choice process. New Directions for Institutional Research, 107, 5–22.

    Article  Google Scholar 

  • Cabrera, A. F., & La Nasa, S. M. (2001). On the path to college: Three critical tasks facing America’s disadvantaged. Research in Higher Education, 42(2), 119–149.

    Article  Google Scholar 

  • Cameron, S. V., & Heckman, J. J. (1998). Life cycle schooling and dynamic selection bias: Models and evidence for five cohorts of American males. The Journal of Political Economy, 106(2), 262–333.

  • Carnevale, A. P., & Rose, S. J. (2003). Socioeconomic status, race/ethnicity, and selective college admissions. New York, NY: The Century Foundation.

    Google Scholar 

  • Castleman, B. L., Arnold, K., & Wartman, K. L. (2012). Stemming the tide of summer melt: An experimental study of the effects of post-high school summer intervention on low-income students’ college enrollment. Journal of Research on Educational Effectiveness, 5(1), 1–17.

    Article  Google Scholar 

  • Choy, S. P. (2001). Students whose parents did not go to college: Postsecondary access, persistence, and attainment. Washington, DC: National Center for Education Statistics. Retrieved from http://nces.ed.gov/pubs2001/2001126.pdf.

  • Corrigan, M. E. (2003). Beyond access: Persistence challenges and the diversity of low-income students. New Directions for Higher Education, 121, 25–34.

    Article  Google Scholar 

  • Doyle, W. R. (2006). Adoption of merit-based student grant programs: An event history analysis. Educational Evaluation and Policy Analysis, 28(3), 259–285.

    Article  Google Scholar 

  • Dynarski, S., & Scott-Clayton, J. (2013). Financial aid policy: Lessons from research. Future of Children, 23(1), 67–91.

    Article  Google Scholar 

  • Engle, J., & Tinto, V. (2008). Moving beyond access: College success for low-income, first-generation students. Washington, DC: The Pell Institute for the Study of Opportunity in Higher Education.

    Google Scholar 

  • Goldrick-Rab, S. (2006). Following their every move: An investigation of social-class differences in college pathways. Sociology of Education, 79(1), 61–79.

    Article  Google Scholar 

  • Granfield, R. (1991). Making it by faking it: Working-class students in an elite academic environment. Journal of Contemporary Ethnography, 20, 331–351.

    Article  Google Scholar 

  • Guo, G., & Zhao, H. (2000). Multilevel modeling for binary data. Annual Review of Sociology, 26, 441–462.

    Article  Google Scholar 

  • Hauser, R. M., & Andrew, M. (2006). Another look at the stratification of educational transitions: The logistic response model with partial proportionality constraints. Sociological Methodology, 36(1), 1–26.

    Article  Google Scholar 

  • Haveman, R., & Smeeding, T. (2006). The role of higher education in social mobility. The Future of Children, 16(2), 125–150.

    Article  Google Scholar 

  • Hoxby, C. M., & Avery, C. (2012). The missing “one-offs”: The hidden supply of high-achieving, low-income students. Working Paper #18586: National Bureau of Economic Research.

  • 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.

    Article  Google Scholar 

  • Ishitani, T. T. (2006). Attrition and degree completion behavior among first-generation college students in the United States. The Journal of Higher Education, 77(5), 861–885.

    Article  Google Scholar 

  • Kim, D. (2004). The effect of financial aid on students’ college choice: Differences by racial groups. Research in Higher Education, 45(1), 43–70.

    Article  Google Scholar 

  • Kuriloff, P., & Reichert, M. C. (2003). Boys of class, boys of color: Negotiating the academic and social geography of an elite independent school. Journal of Social Issues, 4, 751–769.

    Article  Google Scholar 

  • Maddala, G. (1983). Limited dependent and qualitative variables in econometrics. Cambridge, UK: Cambridge University Press.

    Book  Google Scholar 

  • Mare, R. D. (1980). Social background and school continuation decisions. Journal of the American Statistical Association, 75(370), 295–305.

    Article  Google Scholar 

  • Mare, R. D. (1981). Change and stability in educational stratification. American Sociological Review, 46(1), 72–87.

    Article  Google Scholar 

  • Mare, R. D. (2006). Response: Statistical models of educational stratification—Hauser and Andrew’s models for school transitions. Sociological Methodology, 11, 27–37.

    Article  Google Scholar 

  • McPherson, M. S., & Shapiro, M. O. (1998). The student aid game: Meeting need and rewarding talent in American higher education. Princeton, NJ: Princeton University Press.

    Google Scholar 

  • Mortenson, T. G. (2010). Family income and educational attainment 1970 to 2009. Postsecondary Education Opportunity, 221, 1–16.

    Google Scholar 

  • National Center for Education Statistics. (2013). The Condition of Education, 2012. Washington, DC: Author.

    Google Scholar 

  • Oliff, P., Palacios, V., Johnson, I., & Leachman, M. (2013). Recent deep state higher education cuts may harm students and the economy for years. Washington, DC: Center on Budget and Policy Priorities.

  • Ostrove, J. M. (2003). Belonging and wanting: Meanings of social class background for women’s constructions of their college experiences. Journal of Social Issues, 59(4), 771–784.

    Article  Google Scholar 

  • Pascarella, E. T., & Chapman, D. W. (1983). A multiinstitutional, path analytic validation of Tinto’s model of college withdrawal. American Educational Research Journal, 20(1), 87–102.

    Article  Google Scholar 

  • Pascarella, E. T., Pierson, C. T., Wolniak, G. C., & Terenzini, P. T. (2004). First-generation college students: Additional evidence on college experiences and outcomes. The Journal of Higher Education, 75(3), 249–284.

    Article  Google Scholar 

  • Paulsen, M. B., & St. John, E. P. (2002). Social class and college costs: Examining the financial nexus between college choice and persistence. The Journal of Higher Education, 73(2), 189–236.

    Article  Google Scholar 

  • Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods (2nd ed.). Thousand Oaks, CA: Sage Publications Inc.

    Google Scholar 

  • Reardon, S. F. (2011). The widening academic achievement gap between the rich and the poor: New evidence and possible explanations. In G. J. Duncan & R. J. Murnane (Eds.), Whither opportunity? Rising inequality, schools, and children’s life chances. New York, NY: Russell Sage Foundation.

    Google Scholar 

  • Reed, M., & Cochrane, D. (2013). Student debt and the class of 2012. Washington, DC: The Institute for College Access and Success.

    Google Scholar 

  • Roderick, M., Nagaoka, J., Coca, V., Moeller, E., Roddie, K., Gilliam, J., & Patton, D. (2008). From high school to the future: Potholes on the fold to college. Chicago, IL: Consortium on Chicago School Research at the University of Chicago.

    Google Scholar 

  • Savage, M., & Egerton, M. (1997). Social mobility, individual ability and the inheritance of class inequality. Sociology, 31(4), 645–672.

    Article  Google Scholar 

  • Shavit, Y., Arum, R., & Gamoran, A. (2007). Stratification in higher education: A comparative study. Stanford, CA: Stanford University Press.

    Google Scholar 

  • Shavit, Y., & Blossfield, H. (1993). Persistent inequality: Changing educational attainment in thirteen countries. Boulder, CO: Westview Press.

    Google Scholar 

  • Smith, J., Pender, M., & Howell, J. (2012). The full extent of student-college academic undermatch. Economics of Education Review, 32, 247–261.

    Article  Google Scholar 

  • State Higher Education Executive Officers. (2014). State Higher Education Finance, FY 2013. Boulder, CO: Author.

    Google Scholar 

  • Stolzenberg, R. M. (1994). Educational continuation by college graduates. American Journal of Sociology, 99(4), 1042–1077.

    Article  Google Scholar 

  • Terenzini, P. T., Cabrera, A. F., & Bernal, E. M. (2001). Swimming against the tide: The poor in American higher education. College Board Research Report No. 2001-1. New York, NY: The College Board.

  • The College Board. (2009). Trends in Student Aid, 2009. New York, NY: Author. Retrieved from http://www.trends-collegeboard.com/student_aid/pdf/2009_Trends_Student_Aid.pdf

  • Tutz, G. (1991). Sequential models in categorical regression. Computational Statistics and Data Analysis, 11(3), 275–295.

    Article  Google Scholar 

  • United States Department of Education. (2006). A test of leadership: Charting the future of U.S. higher education. Washington, DC: Author.

  • Woo, J. H., & Choy, S. P. (2011). Merit aid for undergraduates: Trends from 1995–1996 to 2007–2008. Washington, DC: National Center for Education Statistics.

    Google Scholar 

Download references

Acknowledgments

This material is based upon work supported by the Association for Institutional Research, the National Science Foundation, the National Center for Education Statistics, and the National Postsecondary Education Cooperative under Association for Institutional Research Grant Number DG13-32. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the Association for Institutional Research, the National Science Foundation, the National Center for Education Statistics or the National Postsecondary Education Cooperative.

Author information

Authors and Affiliations

  1. Office of Community College Research and Leadership, University of Illinois at Urbana-Champaign, 51 Gerty Drive, 129 CRC, Champaign, IL, 61820, USA

    Matt S. Giani

Authors
  1. Matt S. Giani
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Matt S. Giani.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Giani, M.S. The Postsecondary Resource Trinity Model: Exploring the Interaction Between Socioeconomic, Academic, and Institutional Resources. Res High Educ 56, 105–126 (2015). https://doi.org/10.1007/s11162-014-9357-4

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11162-014-9357-4

Keywords

Search

Navigation