Purpose – The purpose of this paper is to use an extreme case to identify and describe the nature of routines that might support processes and outcomes of data use, drawing from a framework developed by Coburn and Turner (2012a). Design/methodology/approach – The author conducted a four‐month case study (Stake, 1995) of an elementary school in a large urban school district that had implemented balanced score cards. The author identified a school that had strong qualities to support data use, including leadership and information systems. Findings – Two school‐level organizational routines facilitated teachers’ data use: collaborative teams and processes of inquiry. These routines stored knowledge about the types of data teachers ought to notice, and to a lesser extent, how they ought to interpret data and construct implications for practice. These routines also provided opportunities for single and double‐loop learning (Argyris and Schön, 1996) and might contribute to improvements in student learning. This case provides an example of how a school negotiated external performance management pressures, and maintained their professional autonomy, focussing on internally initiated assessments. Originality/value – Relatively little research has described what organizational routines support data use among practitioners. In addition to describing two routines, this case also demonstrated the need to frame these routines as organizational routines for learning. To further develop these routines, the author drew on the notion of the knowledge‐creating company (Nonaka and Takeuchi, 1995) to explain how the school used their organizational routines to share tacit knowledge (socialization), and to convert tacit knowledge to explicit knowledge (externalization), which supported instructional innovations.
Journal of Educational Administration – Emerald Publishing
Published: Jul 1, 2014
Keywords: Performance management; Decision making; Assessment; Organizational learning; Organizational routines; Data use; Evidence‐based decision making; Data‐based decision making
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