Policymakers and institutional leaders in higher education too often make decisions based on descriptive data analyses or even anecdote when better analysis options could produce more nuanced and more valuable results. Employing the setting of higher education program evaluation at a midwestern regional public university, for this study we compared analysis approaches using basic descriptive analyses, regression, standard propensity score matching (PSM), and a mixture of PSM with continuous variables, coarsened exact matching, and exact matching on categorical variables. We used three examples of program evaluations: a freshman seminar, an upper division general education program intended to improve cultural awareness and respect for diverse groups, and multiple living learning communities. We describe how these evaluations were conducted, compare the different results for each type of method employed, and discuss the strengths and weaknesses of each in the context of program evaluation.

高等教育中的政策制定者和机构领导者常常会基于描述性数据分析来做出决策，甚至在更好的分析选项可以产生更细微差别和更有价值的结果时也会轶事。利用中西部地区性公立大学的高等教育课程评估设置，在本研究中，我们比较了使用基本描述性分析，回归，标准倾向得分匹配（PSM）以及带有连续变量的PSM，粗化的精确匹配的混合分析方法，以及类别变量的精确匹配。我们使用了三个项目评估示例：新生研讨会，旨在提高文化意识和对不同群体的尊重的高年级普通教育计划，以及多个生活学习社区。我们描述了如何进行这些评估，