Abstract
This special issue explores the complexity and interconnectedness of the many components of data-based decision making. The selection of papers represents many countries (i.e., Belgium, The Netherlands, New Zealand, Norway, and the United States), theories, methods, and foci. All the papers seek to explicate how data are used at the different level of the system, ranging from students, teachers, schools, and districts. Together these papers offer a view of the current data-based decision making landscape, including in- and pre-service professional development, district and school organizational capacity, the data use process (from goal setting to collaborative instructional decision making), and effects on student achievement. The intent of the special issue is to stimulate future work in terms of impact on research, theory, policy, and practice.
Highlights
This special issue is grounded in recent sessions on data-based decision making held at the annual conferences of the American Educational Research Association (AERA) and the International Congress for School Improvement and Effectiveness (ICSEI) as well as critical publications
Still many misconceptions and criticism exist in the field and have become apparent in the sessions organized by ICSEI and AERA
Common misconceptions include that data can only be used for accountability purposes; data use does not lead to increased student learning and achievement; data equals test results; and data literacy equals assessment literacy
Summary
This special issue is grounded in recent sessions on data-based decision making held at the annual conferences of the American Educational Research Association (AERA) and the International Congress for School Improvement and Effectiveness (ICSEI) as well as critical publications. Common misconceptions include that data can only be used for accountability purposes; data use does not lead to increased student learning and achievement; data equals test results; and data literacy equals assessment literacy These are some of the misconceptions that formed the starting point for this special issue, and which will be addressed in the various papers. We have provided a unique and broad perspective of the international landscape around data-based decision making (DBDM), and we address some of the existing misconceptions and criticism This special issue demonstrates how complex the field of DBDM is, and why it is so difficult to achieve definitive outcomes about the impact of data use on classroom practice and student performance. A parallel intention for the special issue is to engage young scholars and those who heretofore have not worked in the data field
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