Examining Data Driven Decision Making via Formative Assessment : A Confluence of Technology , Data Interpretation Heuristics and Curricular Policy

Gerry Swan, Joan Mazur

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Although the term data-driven decision making (DDDM) is relatively new (Moss, 2007), the underlying concept of DDDM is not. For example, the practices of formative assessment and computer-managed instruction have historically involved the use of student performance data to guide what happens next in the instructional sequence (Morrison, Kemp, & Ross, 2001). Like many of its sister fields, such as knowledge management, DDDM implementation is reliant on technology, but requires many other components to be successful. This article reports on an exploratory study of preservice teachers' use of a web-based online tool designed to collect and display student level data. A primary purpose of the data displayed is to facilitate just-in-time formative assessment for instructional decision-making. Findings illuminate the barriers to implementing DDDM in actual classroom practice: a confluence of curricular policy as well as technology and teacher heuristics that result in variations in data interpretation that involve issues with both skill and perspective-taking on the data sets. Recommendations for school leaders and teacher educators alike include the need for the coherent alignment of pedagogy, policy, and supports. (Contains 6 figures and 3 tables.) (As Provided)
Original languageAmerican English
Title of host publicationContemporary Issues in Technology and Teacher Education
Pages205-222
Number of pages18
StatePublished - 2011

Publication series

NameContemporary Issues in Technology and Teacher Education
Volume11

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