Giving Compass' Take:
- Here are six guiding questions to think about when analyzing education data to understand what programs and models are serving all students.
- Why is disaggregated demographic information necessary for understanding education data? How can donors help schools improve equitable data collection processes?
- Learn why education equity requires more than access.
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Data is critical to addressing inequities in education. However, too often data is misused, interpreted to fit a particular agenda or misread in ways that perpetuate an inaccurate story. Data that’s not broken down properly can hide gaps between different groups of students. Facts out of context can lead to superficial conclusions.
For example, a 2019 Minnesota Department of Education Report highlights that between 2016 and 2018, Advanced Placement exam participation for Black students increased by 29 percent, the largest jump for any student group. But Black students still accounted for just 4 percent of AP test takers, and the pass rate was only 41 percent — significantly lower than the statewide average. None of this appears anywhere in the report, which also fails to mention ongoing racial disparities in AP and dual-enrollment access and success in the state.
This is just one example of how data can create a deceptive narrative. In this case, the goal was to celebrate success. But while this is important, it is also essential to be honest when there is work to be done to effectively serve all kids. Below are six guiding questions that I ask myself (and that I hope will be helpful for you) when I am consuming data.
- Is it representative?
- Is it disaggregated?
- What is the sample size?
- What are the limitations?
- What is it measuring?
- How can you put the data in context?
Read the full article about education data by Krista Kaput at The 74.