Data Teams in Teacher Preparation: Improving Data-Based Instruction in Reading

Abstract

Data-based instruction (DBI) is a process of collecting and using student progress data to guide decision-making related to intervention intensity and individualization for students with learning disabilities (LD). However, effective DBI requires that teachers have a range of knowledge and skills across multiple domains. Past research has shown that data teams can improve teachers’ use of data for instructional decision-making. This article describes the use of simulated data teams to build capacity for DBI among pre-service teachers in an undergraduate-level course focused on intensive reading intervention. Three components are described for each weekly data team meeting: mini professional development session (e.g., instruction led by course instructor focused on key DBI knowledge and skills), data chat (e.g., review and discussion of student data), and completion of a weekly team activity and submission. The structure and implementation of this five-week, multi-component professional learning tool are detailed.

Authors 3

1. Jessica R. Toste corresponding

   The University of Texas at Austin

   Affiliation as printed

   The Meadows Center for Preventing Educational Risk

   The University of Texas at Austin, Department of Special Education

   University Station, D5300, Austin, TX 78712

2. Marissa J. Filderman

   University of Alabama

   Affiliation as printed

   University of Alabama, Department of Special Education and Multiple Abilities

3. Christine A. Espin Aachen

   Leiden University

   Affiliation as printed

   Leiden University, The Netherlands