IDENTIFYING SIGNIFICANT DIFFERENCES IN LEARNING AND INCLUSION FOR UNDERGRADUATE DEMOGRAPHIC GROUPS

Quantitative evidence can provide a starting point for interventions to improve the student experience with respect to justice, equity, diversity and inclusion. We surveyed students in the Texas A&M Department of Geology and Geophysics to identify the impacts of cultural climate (via perceptions of inclusion) and learning (via perceptions of learning) on undergraduate students. The research questions for this study are: 1. Do students perceive that they are included in the department?, 2. Do students perceive they are meeting the learning outcomes?, and 3. Do perceptions of learning and inclusion vary by demographic group? If yes, how do they vary? Students were surveyed both at mid-college career and at graduation over a three year period.

This project uses statistical methodologies (contingency tables, t-tests, regression modeling) to investigate interdependencies between different perceptions of learning and inclusion questions and demographic categories. We found that the overall population does feel included and confident in their learning, and that both of these effects increase over time. We tested for dependencies between demographic categories (race, gender, sexual orientation, college entry mode, and first-generation college students). We found that 6 of 17 questions had statistically significant differences between demographic categories.

Black, Indigenous and People of Color (BIPOC) students were more likely to disagree or be neutral to the statement "It is hard for people like me to feel accepted in the department" than white students (p = 0.0437, chi^2 = 11.491). BIPOC men reported the lowest levels of acceptance, followed by BIPOC women, white women, then white men (with the highest acceptance). Inclusion scores do not change between mid-career and graduation. This ties into one of the perceptions-of-learning questions, “I am confident in my ability to work in groups.” There is a significant difference between BIPOC and white students (p = 0.0253, chi^2 = 7.351). By applying statistical analyses to these survey data, we have been able to parse out specific areas of differences, which can inform interventions.