Using archival grade distribution data, we used descriptive analytics to create equity gap tables. Using this descriptive data, we provided individual faculty assessment reports.
All full-time faculty having taught at least 200 students over the past 4 years in one of our selected courses were included. The quantitative measure to determine the gaps is whether a student who was enrolled in the class past the first week earned a grade of C or higher or not. Students are considered to have not succeeded if they earn a D or F, withdraw, or are dropped from the course. Student data are disaggregated by race (White, Black, Latino/Hispanic, Asian, Indigenous). Students who do not identify with a particular race or are mixed race are excluded from the analysis. Comparisons were made between the success rates of students by race.
Through mentoring and coaching, faculty receive guidance for how to create positive change in their classrooms. Additional digital leaning will be available in fall 2023.
Reduction of academic equity gaps through use of data to inform pedagogical decisions.
Lessons learned include:
Pulling and verifying the data were quite complicated and efforts will be made to simplify the process and make it easily repeatable.
Highly recommend speaking with Deans and Department Chairs before rolling out to faculty.
Highly recommend individualized meeting with faculty.