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 Street Data: A Next-Generation Model for Equity, Pedagogy, and School Transformation

Street Data: A Next-Generation Model for Equity, Pedagogy, and School Transformation

Presented by Shane Safir, Jamila Dugan, Chris Emdin and Jal Mehta
[Recorded] Date: Monday, May 03, 2021
Duration: 60 minutes

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Street data is the qualitative and experiential data that emerges at eye level and on lower frequencies when we train our brains to discern it. Street data is asset based, building on the tenets of culturally responsive education by helping educators look for what’s right in our students, schools, and communities instead of seeking out what’s wrong. Street data embodies an ethos and a change methodology that will transform how we analyze, diagnose, and assess everything from student learning to district improvement to policy--offering us a new way to think about, gather, and make meaning of data. In this dynamic webinar, authors Shane Safir and Jamila Dugan lay out their transformational model.

Outcomes for this webinar: 

  • Get to know the authors and their deeply personal “why” for writing this book.
  • Interrogate the roots of the current educational data system through an antiracist lens.
  • Explore a next-generation model for school transformation, rooted in street-level data.

 

 

 

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