A clustering algorithm for university admissions
Reed, Naomi Beth
Tapia, Richard A.
Master of Arts
In 2003 The Supreme Court declared that all government funded universities, which choose to consider race in their admissions processes, must utilize a holistic process. A holistic process includes a thorough evaluation of all aspects of each applicant. For larger universities this type of admissions process would be very taxing. A computer scientist from Auburn University created an algorithm, Applications Quest, to handle large quantities of applications in a way that would evaluate applicants holistically with a computational tool. Applications Quest utilizes the Euclidean distance measure, Similarity matrices, Divisive Clustering, and Random Selection. This algorithm produces a diverse admittance class for a university. In this research we simulate this algorithm and run tests with hypothetical Rice University data. Ultimately, we are left with the following question: Can a computational use of arbitrary difference account for human qualities that define certain social phenomena, such as underrepresentation in higher education?