Data‐Based Decision‐Making: Developing a Method for Capturing Teachers' Understanding of CBM Graphs. Issue 1 (5th January 2017)

• Record Type: Journal Article
• Authors: Espin, Christine A.; Wayman, Miya Miura; Deno, Stanley L.; McMaster, Kristen L.; de Rooij, Mark
• Is Part Of: Learning disabilities research & practice. Volume 32:Issue 1(2017)
• Page Start: 8
• Page End: 21
• Publication Date: 2017-01-05
• Subjects: Learning disabilities -- Periodicals; Apprentissage, Troubles de l' -- Périodiques; 371.9
• DOI: 10.1111/ldrp.12123
• Languages: English
• ISSNs: 0938-8982

Abstract

Abstract : 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.