IDEAS home Printed from https://ideas.repec.org/p/aut/wpaper/201403.html
   My bibliography  Save this paper

Using Predictive Modelling to Identify Students at Risk of Poor University Outcomes

Author

Listed:
  • Pengfei Jia

    (Department of Economics, Faculty of Business and Law, Auckland University of Technology)

  • Tim Maloney

    (Department of Economics, Faculty of Business and Law, Auckland University of Technology)

Abstract

We use predictive modelling to identify students at risk of not completing their first-year courses and not returning to university in the second year. Our aim is two-fold. Firstly, we want to understand the pathways that lead to unsuccessful first-year experiences at university. Secondly, we want to develop simple, low-cost tools that would allow universities to identify and intervene on vulnerable students when they first arrive on campus. This is why we base our analysis on administrative data routinely collected as part of the enrolment process from a New Zealand university. We assess the ‘target effectiveness’ of our model from a number of perspectives. This approach is found to be substantially more predictive than a previously developed risk tool at this university. Students in the top decile of risk scores account for over 29% of first-year course non-completions and more than 23% of second-year student non-retentions at this university

Suggested Citation

  • 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.
    • Handle: RePEc:aut:wpaper:201403
    as

    Download full text from publisher

    File URL: https://www.aut.ac.nz/__data/assets/pdf_file/0008/122021/Economics-WP-2014-03.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bai Juhong & Tim Maloney, 2006. "Ethnicity and academic success at university," New Zealand Economic Papers, Taylor & Francis Journals, vol. 40(2), pages 181-213.
    2. Alan B. Krueger, 1999. "Experimental Estimates of Education Production Functions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(2), pages 497-532.
    3. Todd Stinebrickner & Ralph Stinebrickner, 2012. "Learning about Academic Ability and the College Dropout Decision," Journal of Labor Economics, University of Chicago Press, vol. 30(4), pages 707-748.
    4. Simone Dobbelsteen & Jesse Levin & Hessel Oosterbeek, 2002. "The causal effect of class size on scholastic achievement: distinguishing the pure class size effect from the effect of changes in class composition," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(1), pages 17-38, February.
    5. Grubb, W. Norton, 1989. "Dropouts, spells of time, and credits in postsecondary education: Evidence from longitudinal surveys," Economics of Education Review, Elsevier, vol. 8(1), pages 49-67, February.
    6. Altonji, Joseph G, 1993. "The Demand for and Return to Education When Education Outcomes Are Uncertain," Journal of Labor Economics, University of Chicago Press, vol. 11(1), pages 48-83, January.
    7. Julian R. Betts & Darlene Morell, 1999. "The Determinants of Undergraduate Grade Point Average: The Relative Importance of Family Background, High School Resources, and Peer Group Effects," Journal of Human Resources, University of Wisconsin Press, vol. 34(2), pages 268-293.
    8. Stampen, Jacob O. & Cabrera, Alberto F., 1988. "The targeting and packaging of student aid and its effect on attrition," Economics of Education Review, Elsevier, vol. 7(1), pages 29-46, February.
    9. Caroline M. Hoxby, 2000. "The Effects of Class Size on Student Achievement: New Evidence from Population Variation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(4), pages 1239-1285.
    10. Cyrenne, Philippe & Chan, Alan, 2012. "High school grades and university performance: A case study," Economics of Education Review, Elsevier, vol. 31(5), pages 524-542.
    11. Cohn, Elchanan & Cohn, Sharon & Balch, Donald C. & Bradley, James Jr., 2004. "Determinants of undergraduate GPAs: SAT scores, high-school GPA and high-school rank," Economics of Education Review, Elsevier, vol. 23(6), pages 577-586, December.
    12. Ficano, Carlena Cochi, 2012. "Peer effects in college academic outcomes – Gender matters!," Economics of Education Review, Elsevier, vol. 31(6), pages 1102-1115.
    13. 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.
    14. Claude Montmarquette & Nathalie Viennot-Briot & Marcel Dagenais, 2007. "Dropout, School Performance, and Working while in School," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 752-760, November.
    15. Montmarquette, Claude & Mahseredjian, Sophie & Houle, Rachel, 2001. "The determinants of university dropouts: a bivariate probability model with sample selection," Economics of Education Review, Elsevier, vol. 20(5), pages 475-484, October.
    16. Ost, Ben, 2010. "The role of peers and grades in determining major persistence in the sciences," Economics of Education Review, Elsevier, vol. 29(6), pages 923-934, December.
    17. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Aina, Carmen & Baici, Eliana & Casalone, Giorgia & Pastore, Francesco, 2022. "The determinants of university dropout: A review of the socio-economic literature," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).
    2. Carmen Aina & Chiara Mussida & Gabriele Lombardi, 2023. "Are Business and Economics Alike?," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 9(2), pages 557-585, July.
    3. Ma, Lingjie & Koenker, Roger, 2006. "Quantile regression methods for recursive structural equation models," Journal of Econometrics, Elsevier, vol. 134(2), pages 471-506, October.
    4. Giacomo De Giorgi & Michele Pellizzari & William Gui Woolston, 2012. "Class Size And Class Heterogeneity," Journal of the European Economic Association, European Economic Association, vol. 10(4), pages 795-830, August.
    5. Ralph Stinebrickner & Todd R. Stinebrickner, 2014. "A Major in Science? Initial Beliefs and Final Outcomes for College Major and Dropout," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 81(1), pages 426-472.
    6. Black, Sandra E. & Lincove, Jane & Cullinane, Jennifer & Veron, Rachel, 2015. "Can you leave high school behind?," Economics of Education Review, Elsevier, vol. 46(C), pages 52-63.
    7. Aina, Carmen & Baici, Eliana & Casalone, Giorgia & Pastore, Francesco, 2018. "The Economics of University Dropouts and Delayed Graduation: A Survey," IZA Discussion Papers 11421, Institute of Labor Economics (IZA).
    8. By Vincenzo Carrieri & Marcello D’Amato & Roberto Zotti, 2015. "On the causal effects of selective admission policies on students’ performances: evidence from a quasi-experiment in a large Italian university," Oxford Economic Papers, Oxford University Press, vol. 67(4), pages 1034-1056.
    9. Joshua D. Angrist & Erich Battistin & Daniela Vuri, 2017. "In a Small Moment: Class Size and Moral Hazard in the Italian Mezzogiorno," American Economic Journal: Applied Economics, American Economic Association, vol. 9(4), pages 216-249, October.
    10. Christopher Jepsen, 2015. "Class size: Does it matter for student achievement?," IZA World of Labor, Institute of Labor Economics (IZA), pages 190-190, September.
    11. Cyrenne, Philippe & Chan, Alan, 2012. "High school grades and university performance: A case study," Economics of Education Review, Elsevier, vol. 31(5), pages 524-542.
    12. Reiling, Rune Borgan, 2016. "Does size matter? Educational attainment and cohort size," Journal of Urban Economics, Elsevier, vol. 94(C), pages 73-89.
    13. Ludger Wößmann, 2003. "European education production functions: what makes a difference for student achievement in Europe?," European Economy - Economic Papers 2008 - 2015 190, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    14. West, Martin R. & Woessmann, Ludger, 2006. "Which school systems sort weaker students into smaller classes? International evidence," European Journal of Political Economy, Elsevier, vol. 22(4), pages 944-968, December.
    15. Argaw, Bethlehem A. & Puhani, Patrick A., 2018. "Does class size matter for school tracking outcomes after elementary school? Quasi-experimental evidence using administrative panel data from Germany," Economics of Education Review, Elsevier, vol. 65(C), pages 48-57.
    16. Gary-Bobo, Robert J. & Mahjoub, Mohamed Badrane, 2006. "Estimation of Class-Size Effects, Using 'Maimonides' Rule': The Case of French Junior High Schools," CEPR Discussion Papers 5754, C.E.P.R. Discussion Papers.
    17. Mikael Lindahl, 2005. "Home versus School Learning: A New Approach to Estimating the Effect of Class Size on Achievement," Scandinavian Journal of Economics, Wiley Blackwell, vol. 107(2), pages 375-394, June.
    18. Kedagni, Desire & Krishna, Kala & Megalokonomou, Rigissa & Zhao, Yingyan, 2021. "Does class size matter? How, and at what cost?," European Economic Review, Elsevier, vol. 133(C).
    19. Maximilian Bach & Stephan Sievert, 2019. "Birth Cohort Size Variation and the Estimation of Class Size Effects," Discussion Papers of DIW Berlin 1817, DIW Berlin, German Institute for Economic Research.
    20. Philippe Cyrenne & Alan Chan, 2019. "The Determinants of Student Success in University: A Generalized Ordered Logit Approach," Departmental Working Papers 2019-03, The University of Winnipeg, Department of Economics.

    More about this item

    Keywords

    Predictive Risk Modelling; University Failure and Dropout Behaviour; and New Zealand;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aut:wpaper:201403. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Gail Pacheco (email available below). General contact details of provider: https://edirc.repec.org/data/fbautnz.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.