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.

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