Our contention is that any research method can be used to advance equity
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docdrop.org docdrop.org
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By prioritizing data use for educational leaders at the program level, training on data use moves beyond the quantitative methods course and instead is emphasized throughout the curriculum. Embedding an emphasis on quantitative data in preparation does not preclude a focus
It almost sounds like this article is saying that quantitative is the ONLY kind of data. I do like much of what is being suggested here, but why no mention of the value of qualitative data? (Also, I haven't read the whole article yet, so I might be eating my words later).
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PhD or EdD programs can require students to develop quantitative data skills necessary to analyze district- or school-level data.
I think one challenge with this, in my personal situation, is that I feel like my math skills were already lacking when I took stats and quant, so it was really hard to understand some of the concepts. It makes me think that (as much as I wouldn't have liked it back then) there should be some lower level requirements to prepare for this in programs leading up to PhD or EdD programs.
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correlation and causation and discuss the conditions necessary to establish causal inferences from statistical analyses.
This is such an important thing for people to understand.
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Most importantly, the figure highlights the states that have the lowest rates of enrollment in special education.
This seems like the only piece of data that can really be used here right? Quant is not a strength for me so I could be wrong.
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The article outlines three basic metrics that stakeholders can use to identify potential noncompliance with the Individuals With Disabilities Education Act.
I appreciate that they are using data in this way, it seems like a way to work toward more equitable use of data perhaps.
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Without feedback, however, a statistical engine can continuespinning out faulty and damaging analysis while never learning from itsmistakes
This makes sense, another huge problem with using this to assess teachers.
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and then to calculatehow much of their advance or decline could be attributed to theirteachers
This just sounds like (excuse my language) BS to me. How could a computer possibly accurately calculate this??
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Bad teachers can seem good.
This line makes me angry. We can't use algorithms to replace what we are actually observing, that is ridiculous and so problematic.
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Their verdicts, even when wrong or harmful, were beyonddispute or appeal
This is dangerous.
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Acomputer program could speed through thousands of résumés or loanapplications in a second or two and sort them into neat lists, with themost promising candidates on top.
Even this would produce bias results based on whatever criteria is being used to determine what makes a "good" loan applicant or worker.
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lack people cost an average of US$1,800 less per year than the care given to white people with the same number of chronic health problems
Please someone correct me if I'm wrong, but it seems that because Black people are not receiving adequate care when they are sick, it causes them to be sicker, and as a result, it affects studies that determine how likely someone is to be sick with a certain disease or infection This leads to even more racist misconceptions, for example that Black people contract more illnesses than white people. The structural racism in the U.S. is not only present in every corner of our society, it is also cyclical and almost self sustaining. This is why naming it and intentionally taking action wherever possible is so important.
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