A Combinatorial Optimization Framework for Scoring Students in University Admissions.

Journal: Evaluation review
Published Date: Apr 15, 2022

Abstract

BACKGROUND AND OBJECTIVES: Selecting applications for college admission is critical for university operation and development. This paper leverages machine learning techniques to support enrollment management teams through data-informed decision-making in this otherwise laborious admissions processing.

Authors

  • Lucy Shao
    Division of Biostatistics, Herbert Wertheim School of Public Health and Human Longevity Science, 7117University of California San Diego, San Diego, CA, USA.
  • Richard A Levine
    Department of Mathematics and Statistics, 7117San Diego State University, San Diego, CA, USA.
  • Stefan Hyman
    Enrollment Student Services, 7117San Diego State University, San Diego, CA, USA.
  • Jeanne Stronach
    Analytic Studies & Institutional Research, 7117San Diego State University, San Diego, CA, USA.
  • Juanjuan Fan
    3 Department of Mathematics and Statistics, San Diego State University , San Diego, California.

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