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

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...

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Bibliographic Details
Published inContemporary issues in technology and teacher education Vol. 11; no. 2; pp. 205 - 222
Main Authors Swan, Gerry, Mazur, Joan
Format Journal Article
LanguageEnglish
Published Society for Information Technology and Teacher Education 01.06.2011
Subjects
Alignment (Education)
Barriers
Computer Assisted Testing
Computer Managed Instruction
Computer Software
Computer Software Evaluation
Data
Data Interpretation
Decision Making
Educational Policy
Educational Technology
Formative Evaluation
Heuristics
Internet
Knowledge Management
Open Source Technology
Preservice Teacher Education
Preservice Teachers
Pretests Posttests
Surveys
Technology Integration
Usability
Use Studies
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Summary: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.)
ISSN:1528-5804
1528-5804