Ch 3, Using and Communicating Data as a Tool to Advance Equity, of “From Equity Talk to Equity Walk” (ET2EW) posits that disaggregating data by race is an important first step in being equity-minded and addressing inequities because it allows practitioners to “see” differences in student outcomes.
Questions to ponder:
Does your institution collect/share data on retention and completion? How do they disaggregate data? For example: by race, by gender, by socioeconomic status, or first-generation status? Do they use the problematic URM (underrepresented minority) designation? How do they share this information?
Equity-Minded Sensemaking
Data is not “self-acting” - the value of data depends on how it is used. The Center for Urban Education (CUE) describes Equity-Minded Sensemaking as
The process of critical reflection, contextualization, and meaning-making
And says that it
Goes beyond examining data and noticing equity gaps in outcomes
And involves
Interpreting equity gaps as a signal that practics and not working as intended and asking equity-minded questions about how and why current practices are failing to serve students experiencing inequities
Questions to ponder:
Do you agree with the idea of equity-minded sensemaking? Have you used data to start to process of examing practices at your institution?
Take a look at pages 60-62 of ET2EW for more information on Equity-Minded Sensemaking
Not being part of an institution and also not having the ET2EW book, just as an interested observer I am curious to hear responses to the question.
Based on the phrasing, it seems hard to argue against “equity-minded sensemaking”-- it’s the how we go about this that we hope we can get create some useful discussion here.
I was curious about the Center for Urban Education, so that leads me to looking it up! For those here in the EDI mix, it’s probably well known. Their Racial Equity Tools look very useful in bringing more colleagues to a place of sensemaking (and are CC licensed, yay).
As a librarian working for a college serving residents with ethnic and socioeconomic diversity in the greater Boston area, I have found that my Roxbury Community College has been using “an equity-minded campus culture” for our students, faculty, and staff. The college has been using the disaggregated data of the student profile based on the ethnicity (Black, Latinx, others), gender, age, and neighborhood districts. College Facts
Using these data is beneficial for student recruitment and staff employment.
It is great to hear that Roxbury is disaggregating data to better understand its students’ needs and community and for staff employment. My favorite OER research disaggregated by student demographic compares outcomes from OER classes to traditional classes at the University of Georgia (2018). We definitely need more research in this area for OER. See you tomorrow!!
I find the more disaggregation the better. The most helpful data doesn’t simply classify students as either white and non-white. Lumping all URM (underrepresented minorities - as identified in the book) of different genders into one group doesn’t give the full picture.