Exploring the influence of collaborative data-based decision making among teachers in professional learning communities on teaching practice

Abstract

Educational policies such as the No Child Left Behind Act in 2001 and Every Student Succeeds Act in 2015 have emphasized the need for hard evidence such as standardized test data to make educational decisions. Therefore, teachers have been expected to use student assessment data to make informed curricular decisions and adjustments in teaching practice. This has led school districts to turn to data-based decision-making (DBDM) to create an effective process of student assessment data analysis, and reflection during professional learning communities (PLCs). The study explored teachers’ collaboration on the DBDM when teachers were analyzing student assessment data from common, district, and state assessments, as well as its influence on their instructional decisions. Participating teachers’ department and PLC meetings were recorded, and individual teachers’ classrooms were also observed. Teacher interview data and their lesson plans were also included and analyzed qualitatively. Results revealed that the purpose of collaboration determined types of data used, modes of analysis, and the impact on their teaching. Furthermore, teachers used varied assessment data to plan and adjust their instruction. Their motivation to enhance their teaching practices was also increased by exchanging ideas and insights rooted in the data.