IDEAS home Printed from https://ideas.repec.org/a/spr/reihed/v64y2023i8d10.1007_s11162-023-09743-w.html
   My bibliography  Save this article

Predicting Success: An Examination of the Predictive Validity of a Measure of Motivational-Developmental Dimensions in College Admissions

Author

Listed:
  • Joseph H. Paris

    (West Chester University)

  • Catherine Pressimone Beckowski

    (Temple University)

  • Sara Fiorot

    (Temple University)

Abstract

Amid the COVID-19 pandemic, an unprecedented number of higher education institutions adopted test-optional admissions policies. The proliferation of these policies and the criticism of standardized admissions tests as unreliable predictors of applicants’ postsecondary educational promise have prompted the reimagining of evaluative methodologies in college admissions. However, few institutions have designed and implemented new measures of applicants’ potential for success, rather opting to redistribute the weight given to other variables such as high school course grades and high school GPA. We use multiple regression to investigate the predictive validity of a measure of non-cognitive, motivational-developmental dimensions implemented as part of a test-optional admissions policy at a large urban research university in the United States. The measure, composed of four short-answer essay questions, was developed based on the social-cognitive motivational and developmental-constructivist perspectives. Our findings suggest that scores derived from the measure make a statistically significant but small contribution to the prediction of undergraduate GPA and 4-year bachelor’s degree completion. We also find that the measure does not make a statistically significant nor practical contribution to the prediction of 5-year graduation.

Suggested Citation

  • Joseph H. Paris & Catherine Pressimone Beckowski & Sara Fiorot, 2023. "Predicting Success: An Examination of the Predictive Validity of a Measure of Motivational-Developmental Dimensions in College Admissions," Research in Higher Education, Springer;Association for Institutional Research, vol. 64(8), pages 1191-1216, December.
  • Handle: RePEc:spr:reihed:v:64:y:2023:i:8:d:10.1007_s11162-023-09743-w
    DOI: 10.1007/s11162-023-09743-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11162-023-09743-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11162-023-09743-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Liuli Huang & Lahna R Roche & Eugene Kennedy & Melissa B Brocato, 2017. "Using an Integrated Persistence Model to Predict College Graduation," International Journal of Higher Education, Sciedu Press, vol. 6(3), pages 1-40, August.
    2. Rothstein, Jesse M, 2004. "College performance predictions and the SAT," Department of Economics, Working Paper Series qt59s4j4m4, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    3. Michael N. Bastedo & D’Wayne Bell & Jessica S. Howell & Julian Hsu & Michael Hurwitz & Greg Perfetto & Meredith Welch, 2022. "Admitting Students in Context: Field Experiments on Information Dashboards in College Admissions," The Journal of Higher Education, Taylor & Francis Journals, vol. 93(3), pages 327-374, April.
    4. Ralitsa Todorova, 2018. "Institutional Expectations and Students’ Responses to the College Application Essay," Social Sciences, MDPI, vol. 7(10), pages 1-15, October.
    5. Birk Diedenhofen & Jochen Musch, 2015. "cocor: A Comprehensive Solution for the Statistical Comparison of Correlations," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-12, April.
    6. Don Hossler & Emily Chung & Jihye Kwon & Jerry Lucido & Nicholas Bowman & Michael Bastedo, 2019. "A Study of the Use of Nonacademic Factors in Holistic Undergraduate Admissions Reviews," The Journal of Higher Education, Taylor & Francis Journals, vol. 90(6), pages 833-859, November.
    7. Kelly Ochs Rosinger & Karly Sarita Ford & Junghee Choi, 2021. "The Role of Selective College Admissions Criteria in Interrupting or Reproducing Racial and Economic Inequities," The Journal of Higher Education, Taylor & Francis Journals, vol. 92(1), pages 31-55, January.
    8. Richard C. Atkinson and Saul Geiser, 2009. "Reflections on a Century of College Admissions Tests," University of California at Berkeley, Center for Studies in Higher Education qt49z7127p, Center for Studies in Higher Education, UC Berkeley.
    9. Michael N. Bastedo & Nicholas A. Bowman & Kristen M. Glasener & Jandi L. Kelly, 2018. "What are We Talking About When We Talk About Holistic Review? Selective College Admissions and its Effects on Low-SES Students," The Journal of Higher Education, Taylor & Francis Journals, vol. 89(5), pages 782-805, September.
    10. Rothstein, J.M.Jesse M., 2004. "College performance predictions and the SAT," Journal of Econometrics, Elsevier, vol. 121(1-2), pages 297-317.
    11. Peter Arcidiacono & Esteban Aucejo & Ken Spenner, 2012. "What happens after enrollment? An analysis of the time path of racial differences in GPA and major choice," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 1(1), pages 1-24, December.
    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. Kamis, Rais & Pan, Jessica & Seah, Kelvin KC, 2023. "Do college admissions criteria matter? Evidence from discretionary vs. grade-based admission policies," Economics of Education Review, Elsevier, vol. 92(C).
    2. Rothstein, Jesse, 2022. "Qualitative information in undergraduate admissions: A pilot study of letters of recommendation," Economics of Education Review, Elsevier, vol. 89(C).
    3. Rajeev Darolia & Cory Koedel, 2018. "High Schools And Students' Initial Colleges And Majors," Contemporary Economic Policy, Western Economic Association International, vol. 36(4), pages 692-710, October.
    4. Debopam Bhattacharya & Shin Kanaya & Margaret Stevens, 2017. "Are University Admissions Academically Fair?," The Review of Economics and Statistics, MIT Press, vol. 99(3), pages 449-464, July.
    5. Peter Arcidiacono & Cory Koedel, 2014. "Race and College Success: Evidence from Missouri," American Economic Journal: Applied Economics, American Economic Association, vol. 6(3), pages 20-57, July.
    6. Guyonne Kalb & Sholeh A. Maani, 2007. "The Importance of Observing Early School Leaving and Usually Unobserved Background and Peer Characteristics in Analysing Academic Performance," Melbourne Institute Working Paper Series wp2007n05, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    7. 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.
    8. Jesse Rothstein, 2019. "Inequality of Educational Opportunity? Schools as Mediators of the Intergenerational Transmission of Income," Journal of Labor Economics, University of Chicago Press, vol. 37(S1), pages 85-123.
    9. Mario I. Suárez & Alan R Dabney & Hersh C Waxman & Timothy P Scott & Adrienne O Bentz, 2021. "Exploring Factors that Predict STEM Persistence at a Large, Public Research University," International Journal of Higher Education, Sciedu Press, vol. 10(4), pages 161-161, August.
    10. Dur, Robert & Glazer, Amihai, 2008. "Subsidizing Enjoyable Education," Labour Economics, Elsevier, vol. 15(5), pages 1023-1039, October.
    11. Gandil, Mikkel Høst & Leuven, Edwin, 2022. "College Admission as a Screening and Sorting Device," IZA Discussion Papers 15557, Institute of Labor Economics (IZA).
    12. Raj Chetty & John N. Friedman & Emmanuel Saez & Nicholas Turner & Danny Yagan, 2020. "The Determinants of Income Segregation and Intergenerational Mobility: Using Test Scores to Measure Undermatching," NBER Working Papers 26748, National Bureau of Economic Research, Inc.
    13. Bai, Chong-en & Chi, Wei & Qian, Xiaoye, 2014. "Do college entrance examination scores predict undergraduate GPAs? A tale of two universities," China Economic Review, Elsevier, vol. 30(C), pages 632-647.
    14. Judith Scott-Clayton & Peter M. Crosta & Clive R. Belfield, 2012. "Improving the Targeting of Treatment: Evidence from College Remediation," NBER Working Papers 18457, National Bureau of Economic Research, Inc.
    15. Вербецкий Алексей Дмитриевич & Фридман Алла Александровна, 2016. "Политика Приема В Вузы И Конкуренция Абитуриентов," Economic policy Экономическая политика, CyberLeninka;Автономная некоммерческая организация «Редакция журнала “Экономическая политика”», vol. 11(5), pages 68-91.
    16. Jensen, Elizabeth J. & Wu, Stephen, 2010. "Early decision and college performance," Economics of Education Review, Elsevier, vol. 29(4), pages 517-525, August.
    17. Wu, Binzhen & Zhong, Xiaohan, 2014. "Matching mechanisms and matching quality: Evidence from a top university in China," Games and Economic Behavior, Elsevier, vol. 84(C), pages 196-215.
    18. Bergman, Peter & Kopko, Elizabeth & Rodriguez, Julio, 2021. "Using Predictive Analytics to Track Students: Evidence from a Seven-College Experiment," IZA Discussion Papers 14500, Institute of Labor Economics (IZA).
    19. Attali, Yigal & Neeman, Zvika & Schlosser, Analia, 2011. "Rise to the Challenge or Not Give a Damn: Differential Performance in High vs. Low Stakes Tests," IZA Discussion Papers 5693, Institute of Labor Economics (IZA).
    20. Chapman, Gabrielle & Dickert-Conlin, Stacy, 2012. "Applying early decision: Student and college incentives and outcomes," Economics of Education Review, Elsevier, vol. 31(5), pages 749-763.

    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:spr:reihed:v:64:y:2023:i:8:d:10.1007_s11162-023-09743-w. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.