Integrating Critical Approaches into Quantitative STEM Equity Work

Abstract

A primer of reflective questions to assist researchers with framing, analysis, and interpretation of student-level data frequently used to identify disparities and assess course-level and programmatic interventions is provided to support the scientific community with enhancing how we understand and address systemic inequity in STEM fields.

Students who prefer face-to-face tests outperform their online peers in organic chemistry

“…While students who attend high schools with less academic resources are just as capable, they are on average less academically prepared for introductory classes (Ferguson et al, 2007;Aikens and Barbarin, 2008). We emphasize this is not a student deficit, but a shortcoming of classrooms that do not provide opportunities for all students to excel, regardless of their academic background (Cotner and Ballen, 2017;Pearson et al, 2022). While we observed a relationship between incoming preparation and performance, we did not observe a relationship between testing mode and incoming preparation that would explain performance gaps between online and face-to-face examinations.…”

Engineering graduate students’ mental health: A scoping literature review

“…Future work should include details of the intersections of variables that are known to impact one another as they relate to desired outcomes. Although Table 11 focuses on individualistic traits, when studying mental health, it is equally important to consider what and how current systematic structures can impact individuals' mental health (Garcia et al, 2017; Pearson et al, 2022). For example, how would an institution's size or culture impact students' comfort with reporting experiences of assault or seeking help in those situations?…”

“…Similarly, regardless of method choice (i.e., qualitative, quantitative, mixed methods), researchers should first consider their positionalities and biases that can impact the work, as not doing so can raise serious validity concerns for the findings (Garcia et al, 2017; Hampton et al, 2021; Pearson et al, 2022; Secules et al, 2021). It is equally important to elect methods that adequately answer the research question(s) posed.…”

Career Self-Efficacy Disparities in Underrepresented Biomedical Scientist Trainees

“…Scholars contend that interest in science, technology, engineering, mathematics (STEM; see Supplemental Information S1 for list of acronyms) is developed over the years through socialization and educational experiences (e.g., starting from K-12 experiences, through undergraduate, and graduate education), and that a lack of participation of racial/ethnic and gender minorities in STEM careers starts early (13)(14)(15). For example, in a longitudinal study that tracked students' transition from high school to postsecondary careers, higher math self-efficacy during high school increased the likelihood of choosing STEM fields for White students but not for students from underrepresented groups (15) (note that White is capitalized throughout to indicate that it is a racial category as well, and to decenter Whiteness; (12)). Such sorting into different professions exemplifies the early loss of students from underrepresented backgrounds at various points along their education and career advancement, resulting in relatively few URs holding senior-level positions in STEM.…”