Toward a Framework for Classifying Teachers’ Use of Assessment Data
Author(s) -
Farley-Ripple Elizabeth N.,
Jennings Austin S.,
Buttram Joan
Publication year - 2019
Publication title -
aera open
Language(s) - English
Resource type - Journals
ISSN - 2332-8584
DOI - 10.1177/2332858419883571
Subject(s) - qualitative property , process (computing) , computer science , multimethodology , mathematics education , psychology , machine learning , operating system
Research consistently has found teachers’ use of assessment data for instructional purposes challenging and inconsistent. To support teachers’ use of data, we need to develop shared knowledge about how data are and can be used to advance teaching and learning. However, the literature on the specific actions teachers take is inconsistent, creating challenges for both research and practice. As part of a larger project examining data use in instructional decision making, we developed a framework to classify teachers’ instructional responses to data. Then, we used quantitative and qualitative data from educators across 5 districts and 20 schools to evaluate the utility of the framework. This article documents the process and outcomes of our multistage, mixed-methods approach to these tasks. We conclude with the potential uses of this framework for research and practice.
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