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Data‐Based Decision‐Making: Developing a Method for Capturing Teachers’ Understanding of CBM Graphs
Author(s) -
Espin Christine A.,
Wayman Miya Miura,
Deno Stanley L.,
McMaster Kristen L.,
Rooij Mark
Publication year - 2017
Publication title -
learning disabilities research and practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.018
H-Index - 21
eISSN - 1540-5826
pISSN - 0938-8982
DOI - 10.1111/ldrp.12123
Subject(s) - interpretation (philosophy) , curriculum , exploratory research , coherence (philosophical gambling strategy) , computer science , psychology , focus (optics) , mathematics education , management science , data science , pedagogy , physics , sociology , anthropology , optics , economics , programming language , quantum mechanics
In this special issue, we explore the decision‐making aspect of data‐based decision‐making . The articles in the issue address a wide range of research questions, designs, methods, and analyses, but all focus on data‐based decision‐making for students with learning difficulties. In this first article, we introduce the topic of data‐based decision‐making and provide an overview of the special issue. We then describe a small, exploratory study designed to develop a method for studying teachers’ understanding and interpretation of Curriculum‐Based Measurement (CBM) graphs. Specifically, we examine whether think‐alouds scored for coherence, specificity, reflectivity, and accuracy differentiate teachers with more or less understanding of CBM data. We conclude the article by discussing the importance of, and the need for, research on teachers’ understanding, interpretation, and use of data for instructional decision‐making.