Understanding school-level data use and analysis in the context of knowledge management.

摘要

Data use within the context of public education agencies is a key component of many high-stakes accountability initiatives intent on improving student achievement by publicly reporting school- and teacher-effectiveness. The accountability logic contends that a small and discrete number of quantifiable indicators can accurately capture student learning. This study explored the ways in which school-level actors define and collect data in their day-to-day work.;By employing a Knowledge Management framework to public education, the study examined school-level knowledge generation and management processes, and the ways in which these processes inform data production, consumption, use, and the meaning making associated with the data use and analysis. In examining the relationship between the construction and management of knowledge about student achievement at the school-level, and how it compares to knowledge about student achievement defined through centrally driven accountability mechanisms, the study finds: (a) teachers and principals rely on multiple strategies and frameworks - connected to multiple logics about what it means to teach and learn - when collecting, analyzing, and acting upon data that inform instruction; (b) individual and school-level belief systems and norms help teachers to negotiate meaning about various data elements and understand how these data elements support their definitions of success within and outside of their school communities; (c) at least three dominant logics surfaced as frameworks for understanding student learning - accountability, human element, and parallel systems of knowledge generation.;Most importantly the study reveals that teachers' use of data situates data as part of a process of meaning making whereas the accountability logic largely focuses on data as part of a set of outcome indicators for measuring student learning. The study contributes to our understanding of data use and analysis at the classroom level, and promotes an understanding that recognizes teachers' role as professionals whose use of data informs students' progression as learners.