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Friday, June 16, 2017

Equity Algorithms

We tend to use simple algorithms for comparison. Each year schools with the highest standardized test scores are listed at the top while schools with lower standardized test scores are listed at the bottom. Yet is using scores alone to rate teachers or schools a fair analysis?

As I thought of this today, I thought about the factors that could be figured into a more equitable analysis of good work and growth with students--factors such as the following:

  • How many students arrived at school having had a good night's sleep and breakfast?
  • How many students in the class are at the poverty level?
  • How many students in the class face daily disruption due to illness, violence, and other disharmony?
  • How many students are labeled as special education students?
  • How many students face issues of chronic absenteeism?
  • How many face language barriers?
  • How many have physical, emotional, or psychological disabilities that get in the way of learning?
  • How many have access to technology at home?
  • How many face prejudice due to gender, body size, race, culture or religion?
  • How many children are in the class?
There are so many factors that affect learning and teaching, and the longer we are satisfied with simple comparisons, the less we'll be able to grow in ways that matter to all students.

Who is working on these better algorithms for good analysis when it comes to good service, teaching, and learning for all children, and how will these algorithms help us to teach and learn better.