Improving, Sustaining, and Scaling Up Teachers' Data-Based Decision Making in Reading

This session is from the NASP 2022 Annual Convention

  • PMD: 1,5
  • Skill Level: Intermediate

Learner Objectives

This session will help participants…

  1. understand the challenges elementary schools encounter when trying to engage teachers in databased decision making to inform literacy instruction.
  2. develop an understanding of how a protocol and tools used in a statewide reading reform guided teachers to synthesize literacy data and inform instruction.
  3. describe how an on-line application has the potential to scale and sustain databased decision making to inform literacy instruction in elementary schools.
  4. explain the usability, feasibility, and reliability of an on-line application designed to support databased decision making.


Data-based decision making (DBDM) is widely accepted as sound educational practice, but schools struggle to synthesize data to improve reading instruction. Tools employed in a state-wide reading reform initiative to support DBDM and efforts to scale up and sustain these tools within an online application will be showcased. We will share research on how reliably teachers assign an instructional focus using this application, along with usability, feasibility, and user satisfaction survey results.



Cynthia Pirani-McGurl, HILL for Literacy
Keith Smolkowski, PhD, Oregon Research Institute
Darci Burns, PhD, HILL for Literacy
Diana Malkin, HILL for Literacy


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