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Factors affecting student retention probabilities: A case study

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  • James Wetzel
  • Dennis O’Toole
  • Steven Peterson

Abstract

A comprehensive model of retention based on Tinto’s goal commitment and institutional commitment combined with financial considerations is evaluated for the case of an urban public university enrolling large numbers of non-traditional students. The model was evaluated using data from all freshman and sophomore students over the years 1989–1992. White and minority students were also analyzed separately to determine if there were different sensitivities to various enrollment factors. Academic and social integration factors were found to be the most significant factors in persistence in these years. Financial considerations were of less importance in the persistence decision. Copyright Springer 1999

Suggested Citation

  • James Wetzel & Dennis O’Toole & Steven Peterson, 1999. "Factors affecting student retention probabilities: A case study," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 23(1), pages 45-55, March.
    • Handle: RePEc:spr:jecfin:v:23:y:1999:i:1:p:45-55
    DOI: 10.1007/BF02752686
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    References listed on IDEAS

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    1. John H. Bishop, 1996. "Is the market for college graduates headed for a bust? Demand and supply responses to rising college wage premiums," New England Economic Review, Federal Reserve Bank of Boston, issue May, pages 115-138.
    2. McPherson, Michael S & Schapiro, Morton Owen, 1991. "Does Student Aid Affect College Enrollment? New Evidence on a Persistent Controversy," American Economic Review, American Economic Association, vol. 81(1), pages 309-318, March.
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    Cited by:

    1. Singell, Larry Jr., 2004. "Come and stay a while: does financial aid effect retention conditioned on enrollment at a large public university?," Economics of Education Review, Elsevier, vol. 23(5), pages 459-471, October.
    2. Fabio Vinicius de Macedo Bergamo & Antônio Carlos Giuliani & Lesley Carina do Lago Attadia Galli, 2011. "Students’ loyalty and retention pattern for higher education institutions: a theoretical study based on the relationship marketing," Brazilian Business Review, Fucape Business School, vol. 8(2), pages 42-65, April.
    3. Huang, Wei & Li, Fan & Liao, Xiaowei & Hu, Pingping, 2018. "More money, better performance? The effects of student loans and need-based grants in China's higher education," China Economic Review, Elsevier, vol. 51(C), pages 208-227.
    4. Patron, Rossana, 2005. "Enhancing the public provision of education," IOB Working Papers 2005.03, Universiteit Antwerpen, Institute of Development Policy (IOB).
    5. Angela Boatman & Bridget Terry Long, 2016. "Does Financial Aid Impact College Student Engagement?," Research in Higher Education, Springer;Association for Institutional Research, vol. 57(6), pages 653-681, September.
    6. Holmgren, Mark & McCracken, Vicki A., 2010. "Identifying Student Success at a Land Grant Institution," 2010 Annual Meeting, July 25-27, 2010, Denver, Colorado 61701, Agricultural and Applied Economics Association.
    7. Adam GUERRERO, 2023. "Student Retention Analytics: Modeling the Effect of Poverty on College Student Retention," RAIS Journal for Social Sciences, Research Association for Interdisciplinary Studies, vol. 7(1), pages 1-9, June.
    8. Fábio Vinicius de Macedo Bergamo & Antonio Carlos Giuliani & Silvia Helena Carvalho Ramos Valladao de Camargo & Felipe Zambaldi & Mateus Canniatti Ponchio, 2012. "Student loyalty based on relationship quality: an analysis on higher," Brazilian Business Review, Fucape Business School, vol. 9(2), pages 26-46, April.
    9. Zhaoyi Cao & Tim Maloney, 2017. "Decomposing Ethnic Differences in University Academic Achievement in New Zealand," Working Papers 2017-02, Auckland University of Technology, Department of Economics.
    10. Kerkvliet, Joe & Nowell, Clifford, 2005. "Does one size fit all? University differences in the influence of wages, financial aid, and integration on student retention," Economics of Education Review, Elsevier, vol. 24(1), pages 85-95, February.
    11. Pengfei Jia & Tim Maloney, 2014. "Using Predictive Modelling to Identify Students at Risk of Poor University Outcomes," Working Papers 2014-03, Auckland University of Technology, Department of Economics.

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