The Education Data Issues Model : using a knowledge mobilization framework to examine teachers' engagement with large scale assessment data as a means to enhance student learning

Abstract

The purpose of this research was to examine the Education Data Issues Model (EDIM), as a useful conceptual framework through which to study teachers' engagement with large scale assessment data as a means to enhance student learning. The ED1M framework was developed by myself and was based on knowledge mobilization theory, together with educational literature on data use, it was applied to the study and was revised based on the results. Eight Grade 3 and seven Grade 6 teachers volunteered to participate in semi-structured interviews regarding their perceptions and experiences using data from large scale assessment to inform teaching practice and student learning. ATLAS.ti software was used to code and analyze the transcribed audio-recorded interviews. Analysis entailed the identification of themes and patterns across the data. The results supported the EDIM as a useful conceptual framework through which to explore teachers' engagement with data as a means of enhancing student learning. Modifications were made to the EDIM which represented the data from the interviews with teachers. Two main themes became apparent in the data: the importance of time and timing as it relates to a large-scale assessment (LSA) program and the importance of the social context in which teachers used LSA data. Implications of the findings for teachers, students and testing agencies are discussed.