D3: Data, Discovery, Dialogue Session 1 Equity: The Water We Swim in

1. D3: Data, Discovery, DialogueSession 1 Equity: The Water We Swim in Dr. Bridget Herrin Associate Dean, Research & Planning

2. “Inquiry is a change strategy, become a researcher of your own practice” -Estela Bensimon

3. “If the ladder of educational opportunity rises high at the doors of some youth and scarcely rises at the doors of others, while at the same time formal education is made a prerequisite to occupational and social advance, then education may become the means, not of eliminating race and class distinctions but of deepening and solidifying them” -Harry S. Truman (Commission on Higher Education Report, 1947)

4. Session Learning Outcomes • To examine the question of why equity should fundamentally be understood in terms of race rather than other factors such as income or some other variable. • To explore data around student experiences in access, success/retention and completion with an equity lens • To increase confidence in using publicly available data tools • To be able to make meaning out of data and consider action https://cue.usc.edu/files/2016/01/CUE_WhyRace_2013.pdf

6. Assumptions/Background • All students should have equal opportunities for success • We want to serve ALL students well • There are no inherent differences across groups (race, gender, etc.) that reasonably explain gaps • Higher Education was built on white middle class values

7. Talking about race “Offending someone” (43) “Being politically correct” (43) received the “lack of knowledge or understanding—one’s own (36) or co-workers (37) “motives questioned” (37)

8. Talking about race “Talking about race is still a touchy subject”

9. Why Race? (why not low income?) • Race is visible • Racial and ethnic minorities have been legally prohibited from attending universities • Unlike financial aid policies (which remove barriers for low income students) no policies exist to remove barriers for people of color • Many SES-based policies favor white students over students of color • Racial gaps are more prominent and persist regardless of income Ching, C.D. (2013). Why race? Understanding the importance of foregrounding race and ethnicity in achieving equity on college campuses. Los Angeles, CA: Center for Urban Education, Rossier School of Education, University of Southern California.

10. Measuring Equity • How might we capture equity data and/or where can we find it? • How do we measure equity? • What metrics are we using? • How do we determine if a group is experiencing inequities?

11. Peeling back the layers Uncover, understand, and predict • Often aggregate measures provide little actionable info • Even when we disaggregate by a single dimension, we may be missing significant pieces of the story • Don’t stop at the symptoms, try and get to the root

12. Effectively Evaluating Our Programs • Is it serving who we intended it to serve? • Is it having the results we intended it to have? • Are there other results we did not anticipate?

13. Using the tools • SD Mesa Data Dashboards • http://www.sdmesa.edu/about-mesa/institutional-effectiveness/institutional-research/data-warehouse/index.shtml

14. How do you know if something is equity minded? Equity Advancing Evidence Based Race Conscious Institutionally Focused Systemically Aware

15. Practical Strategies for Modeling Equity Mindedness • Develop your framework, inform yourself • Know the data and trends • Understand how data/metrics are connected • Reframe conversations: Focus on institutional barriers • Develop ground rules for discussion • Acknowledge our own biases and levels of privilege

16. Resources • http://scorecard.cccco.edu/scorecard.aspx • https://cue.usc.edu/files/2016/02/Developing-a-Practice-of-Equity-Mindedness.pdf • https://cue.usc.edu/files/2016/01/CUE_WhyRace_2013.pdf • http://www.whatsrace.org/pages/questions.htm • https://cue.usc.edu/tools/the-equity-scorecard/ • https://cue.usc.edu/tools/data/

17. Questions