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High school grades and university performance: A case study

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  • Cyrenne, Philippe
  • Chan, Alan

Abstract

A critical issue facing a number of colleges and universities is how to allocate first year places to incoming students. The decision to admit students is often based on a number of factors, but a key statistic is a student's high school grades. This paper reports on a case study of the subsequent performance at the University of Winnipeg of high school students from 84 Manitoba high schools. By tracking the university performance of students admitted for the years 1997–2002, we are able to estimate the likelihood of success of subsequent students based on their characteristics as well as their high school grades. In doing so, we use a number of alternative estimators including a Least Squares Dummy Variable Model and a Hierarchical Linear Model. The methodology should be of interest to admissions officers at other universities as an input into estimating the subsequent performance of first year students.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:ecoedu:v:31:y:2012:i:5:p:524-542 DOI: 10.1016/j.econedurev.2012.03.005
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    Cited by:

    1. Zhaoyi Cao & Tim Maloney, 2017. "Decomposing Ethnic Differences in University Acedemic Achievement in New Zealand," Working Papers 2017-02 Classification-I2, Auckland University of Technology, Department of Economics.
    2. Cardak, Buly A. & Vecci, Joe, 2013. "Catholic school effectiveness in Australia: A reassessment using selection on observed and unobserved variables," Economics of Education Review, Elsevier, vol. 37(C), pages 34-45.
    3. Trappey, Amy J.C. & Trappey, Charles V. & Liu, Penny H.Y. & Lin, Lee-Cheng & Ou, Jerry J.R., 2013. "A hierarchical cost learning model for developing wind energy infrastructures," International Journal of Production Economics, Elsevier, vol. 146(2), pages 386-391.
    4. 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.
    5. Sezgin Polat & Jean-Jacques Paul, 2016. "How to predict university performance: a case study from a prestigious Turkish university?," Investigaciones de Economía de la Educación volume 11,in: José Manuel Cordero Ferrera & Rosa Simancas Rodríguez (ed.), Investigaciones de Economía de la Educación 11, edition 1, volume 11, chapter 22, pages 423-434 Asociación de Economía de la Educación.
    6. Meya, Johannes & Suntheim, Katharina, 2014. "The second dividend of studying abroad: The impact of international student mobility on academic performance," Center for European, Governance and Economic Development Research Discussion Papers 215, University of Goettingen, Department of Economics.
    7. Black, Sandra E. & Cortes, Kalena E. & Lincove, Jane Arnold, 2014. "Efficacy vs. Equity: What Happens When States Tinker with College Admissions in a Race-Blind Era?," IZA Discussion Papers 8733, Institute for the Study of Labor (IZA).
    8. Danilowicz-Gösele, Kamila & Meya, Johannes & Schwager, Robert & Suntheim, Katharina, 2014. "Determinants of students' success at university," Center for European, Governance and Economic Development Research Discussion Papers 214, University of Goettingen, Department of Economics.
    9. 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.
    10. Graham Beattie & Jean-William P. Laliberté & Philip Oreopoulos, 2016. "Thrivers and Divers: Using Non-Academic Measures to Predict College Success and Failure," NBER Working Papers 22629, National Bureau of Economic Research, Inc.
    11. Liu, Vivian Y.T. & Belfield, Clive R. & Trimble, Madeline J., 2015. "The medium-term labor market returns to community college awards: Evidence from North Carolina," Economics of Education Review, Elsevier, vol. 44(C), pages 42-55.
    12. Hoffmann, Anna-Lena & Lerche, Katharina, 2016. "Class attendance and university performance," Center for European, Governance and Economic Development Research Discussion Papers 286, University of Goettingen, Department of Economics.
    13. 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.

    More about this item

    Keywords

    High school grades; University performance; HLM model;

    JEL classification:

    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
    • L2 - Industrial Organization - - Firm Objectives, Organization, and Behavior
    • L4 - Industrial Organization - - Antitrust Issues and Policies
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism
    • I2 - Health, Education, and Welfare - - Education

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