Examining Data Driven Decision Making via Formative Assessment: A Confluence of Technology, Data Interpretation Heuristics and Curricular Policy
Gerry Swan, Joan Mazur, University of Kentucky, United States
CITE Journal Volume 11, Number 2, ISSN 1528-5804 Publisher: Society for Information Technology & Teacher Education, Waynesville, NC USA
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.
Swan, G. & Mazur, J. (2011). Examining Data Driven Decision Making via Formative Assessment: A Confluence of Technology, Data Interpretation Heuristics and Curricular Policy. Contemporary Issues in Technology and Teacher Education, 11(2), 205-222. Waynesville, NC USA: Society for Information Technology & Teacher Education.
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