Discussion for Ch 3: Using and Communicating Data as a Tool to Advance Equity Part 2

CCCOER EDI Book Club
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We have equity Gaps … Now What?

Chapter 3, part 2, is a continuation of our last book session where “Equity-Minded Sensemaking” was introduced. See below for Liz’s outlined definition of “Equity-Minded Sensemaking” for a refresher.

Equity Talk to Equity Walk (ET2EW) encourages us to move beyond data to identify equity gaps. “Equity-Minded Sensemaking” goes beyond examining data and noticing equity gaps in outcomes. It involves interpreting the equity gaps as a signal that practices are not working as intended.” EW2ET p. 61

The ET2EW suggests the practice of utilizing “equity-minded” questions to guide discussions regarding equity gaps in data. “Using data to generate questions is important because it underscores that equity gaps are ties to policies and practices that could be intentionally designed to support better the students who experience equity gaps.” ET2EW p. 62.

Equity- Minded questions include the following.

  • Open-Ended
  • Keeps focus on the inequity within practices rather than blaming students for inequities.
  • Encourages a “Culture of Inquiry” stead of jumping to conclusions regarding equity gaps. EW2ET
  • emphasizes if there is a need for additional data collection to close the equity gaps

Some examples of Open-Ended questions from ET2EW included from p.61

  • What patterns do you notice in the data?
  • Which racial groups are experience inequities?
  • What are your equity goals?
  • What equity-minded questions might you pursue with further inquiry?

Question: How do you or your institution “foster a culture of inquiry” while addressing equity gaps? Do you use equity-minded questions to guide your discussions regarding equity gaps? Please share your experiences.

Communicating Data to Advance Equity - This section discusses strategies institutions have employed to advance equity through the use of data. Some examples used in EW2ET include effective strategies, including Data Dashboards. One problematic strategy discussed is predictive analytics. P.75

Question: What effective and ineffective strategies have you or your institution used in the effort to advance equity?

Recap from Liz’s previous blog post referencing “Equity-Minded Sensemaking.”

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 practices and not working as intended and asking equity-minded questions about how and why current practices are failing to serve students experiencing inequities

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Here is an article in The Hechinger Report that provides a good overview of how inequity can be “baked into” predictive analytics: Predictive analytics are boosting college graduation rates, but do they also invade privacy and reinforce racial inequities? To wit: “There is historic bias in higher education, in all of our society,” said Iris Palmer of the New America Foundation. “If we use that past data to predict how students are going to perform in the future, could we be baking some of that bias in?”

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Thank you to everyone who attended the book club today! I know this was a busy week for many people because of the holidays.

If you were not able to join us today, below are some highlights from our meeting. What are your thoughts on Chapter 3?

  • Regarding equity-minded questions:
    • Data stories - stories that you tell based on the data. Examples: “If you are a black or brown man, how will you do in this class?”
    • Data can be uncomfortable for instructors because it can feel like a personal attack. Have to emphasize that data is not punitive and you’re not looking at instructors outcomes or assigning blame - data stories can help alleviate the feeling of being attacked
  • If you’re at the beginning stage of collecting and using data, how do you move past the mindset that data is punitive? Are there approaches that can be taken as an institution?
    • Hold many workshops about data, and present it in many different ways, it can take years to change the mindset
    • Lots of conversations - be honest, report data, address it, and share what steps you are taking to close equity gaps
    • Make sure discussions aren’t silo’d. Some departments may already be having these conversations, need to have an institution-wide discussion
    • Weave into the strategic plan(s)
  • Communicating Data
    • Use term equity gap instead of achievement gap
    • When presented with data, some will have a “deficit-minded thinking” ie, blame the students for not doing well. Some comments people have heard are:
      • “…not have ‘those’ students in those classes”
      • “Everyone has the same material”
      • “students can choose to be successful”
    • How to overcome this “deficit-minded thinking”?
      • Cultivate a culture of curiosity
      • Remember that data is just one step
      • Be open-minded, polite
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