Analyzing Student Success Outcome Variables in Higher Education Utilizing the Chi-Square Test of Independence

Jim Kenneth Rost

International Journal of Higher Education, 2024, vol. 13, issue 2, 100

Abstract: For the past two decades student success measures such as student persistence, retention, and graduation rates have been a point of emphasis in higher education. These measures are often directly related to funding formulas for state public colleges and universities. Therefore, analyses of these data have become more critical to evaluating student success initiatives for faculty and administration at many institutions. However, while these data are often widely available there is very little higher education research on how they should be analyzed to assess student success initiatives, program evaluations, or teaching effectiveness at the institutional level.As student success outcome variables are categorical in nature, linear analyses of these data may prove rather difficult as a dependent variable without a significant amount of transformation. Therefore, the purpose of this article is to provide practitioners with a simple, yet powerful option for analyzing student success outcome variables utilizing the Chi-square test of independence. A case study approach was taken to illustrate how Chi-square can be used to specifically analyze the association between an experiential learning high impact practice and graduation rates among undergraduate students. This case was based on a results and interpretation perspective, rather than step-by-step instruction on how to perform the analysis itself.

Date: 2024
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