Abstract
Higher education is in a moment of pause, facing an opportunity to transform or continue to perpetuate the status quo. The COVID-19 pandemic, coupled with the recognition of racial violence, has created an opportunity for institutions to question their own policies and practices. The purpose of this inquiry is to question the science behind established statistical practices. Specifically, the question guiding this investigation is: How can higher education quantitative scholars (students and faculty) identify and be critical of statistical practices that perpetuate inequity, forms of oppression, and White supremacy? Using a QuantCrit framework, five examples are presented that illustrate multiple forms of oppression, subjectivity, and bias including: (a) comparing across groups, (b) eliminating outliers, (c) addressing non-response bias, (d) small sample sizes, and (e) theory development. Two recommendations are discussed that could help transform higher educational quantitative research and training into a more inclusive, equitable, and anti-racist educational environment.
Subject
Public Administration,Developmental and Educational Psychology,Education,Computer Science Applications,Computer Science (miscellaneous),Physical Therapy, Sports Therapy and Rehabilitation
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