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Prediction of freshman GPA from college-admissions and high school tests

Version
1
Resource Type
Dataset
Creator
  • Koretz, Daniel (Harvard Graduate School of Education)
Publication Date
2019-01-02
Funding Reference
  • United States Department of Education. Institute of Education Sciences
    • Award Number: R305AII0420
Description
  • Abstract

    The current focus on assessing “college and career readiness” raises an empirical question: how do high-school tests compare with college-admissions tests in predicting performance in college? We explored this using data from the City University of New York and public colleges in Kentucky. These two systems differ in the choice of college-admissions test, the stakes for students on the high-school test, and demographics. We predicted freshman grade-point average (FGPA) from high-school grade-point average and both college-admissions and high-school tests in mathematics and English. In both systems, the choice of tests had only trivial effects on the aggregate prediction of FGPA. Adding either test to an equation that included the other had only trivial effects on prediction. Although the findings suggest that the choice of test might advantage or disadvantage different students, it had no substantial effect on the over- and underprediction of FGPA for students classified by race/ethnicity or poverty.




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Relations
  • Cites
    DOI: 10.1177/2332858416670601 (Text)
Publications
  • Koretz, Daniel, Carol Yu, Preeya P. Mbekeani, Meredith Langi, Tasmin Dhaliwal, and David Braslow. “Predicting Freshman Grade Point Average From College Admissions Test Scores and State High School Test Scores.” AERA Open 2, no. 4 (October 2016): 233285841667060. https://doi.org/10.1177/2332858416670601.
    • ID: 10.1177/2332858416670601 (DOI)

Update Metadata: 2019-11-21 | Issue Number: 1 | Registration Date: 2019-11-21

Koretz, Daniel (2019): Prediction of freshman GPA from college-admissions and high school tests. Version: 1. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset. https://doi.org/10.3886/E108441V1-19723