A review of professional learning community (PLC) instruments

Abstract

PurposeDespite the continuous growth of empirical studies exploring professional learning communities (PLCs) across different education systems, little is known about PLC instruments developed and used in existing research. This article aims to capture a full picture of existing PLC instruments developed since 1990. In so doing, the authors also pay attention to the seminal work of Karen Seashore Louis in alignment with the theme of the special issue.Design/methodology/approachBased on the authors’ searching databases, the authors identified eleven PLC instruments and 26 applied studies using the PLC instruments since 1990. Following this, the authors closely reviewed the identified studies and their relationships (i.e. which one influences which).FindingsThe authors’ review illuminates the measurement domains, conceptual origins and methodological soundness of the existing instruments and captures the impact of Louis's work on the applied studies using PLC instruments.Originality/valueGiven that PLCs are seen as a policy measure to sustain and scale up school improvement internationally, the authors’ review provides a better understanding of what and how researchers have measured the effect of PLCs on school improvement. As the first of its kind, the authors believe that their findings can give researchers valuable ideas about how to develop and use a PLC instrument.

Examining the Influence of Secondary Math and Science Teacher Preparation Programs on Graduates’ Instructional Quality and Persistence in Teaching

“…These findings suggest that the rigor seen in classroom task design and implementation is influenced by something other than the teacher preparation program. Our findings support those of Lee et al [70], who described that the past experience of preservice teachers may well be oriented to lower-demand tasks, and they may not have experienced higher-level tasks. The finding that the science teachers had higher rigor in their tasks and expectations than that of their math colleagues calls for further research into the ways that organizational/district-level structures and norms (e.g., pacing guides, required curricula, required courses, etc.)…”

“…In our work, the mode of most math tasks designed and implemented by novice graduates of teacher preparation programs was coded at the level of low rigor for the potential of the task, implementation of the task, and teacher expectations, echoing the earlier work on math preservice teachers conducted by Lee and colleagues [70]. In contrast, novice teachers who graduated from science teacher preparation programs were most often seen to design and have expectations for their students at a moderate level of rigor.…”

“…Further, teachers' decision-making around selecting tasks revealed limited attention to the intellectual engagement required by the task. Taken together, these earlier efforts with both in-service and preservice teachers suggest that both science and math teachers are more familiar with low-rigor tasks in science and math, although the findings of both Lee et al [70] and Tekkumru-Kisa et al [71] suggest that teachers do sometimes focus on the intellectual demand of tasks. Additionally, Lee and colleagues [70] advised that preservice teachers can be supported to attend to the demand of tasks used in instruction.…”

“…Taken together, these earlier efforts with both in-service and preservice teachers suggest that both science and math teachers are more familiar with low-rigor tasks in science and math, although the findings of both Lee et al [70] and Tekkumru-Kisa et al [71] suggest that teachers do sometimes focus on the intellectual demand of tasks. Additionally, Lee and colleagues [70] advised that preservice teachers can be supported to attend to the demand of tasks used in instruction. How novice math and science teachers orient themselves to and employ intellectually demanding tasks remains an open question.…”

“…In [69], through close examination of the same lesson employed across three different classrooms, we showed how a teacher's instructional practices interacted with students' intellectual engagement with a cognitively demanding task to support the rigor of instruction. Research that informs our understanding of the role of tasks in instructional core in both math and science includes that of Lee and colleagues [70], who examined the work of 54 preservice elementary teachers in identifying the cognitive demand of tasks, increasing the demand of low-demand tasks, and anticipating student responses to these modified tasks. They found that preservice teachers were more successful in identifying low-demand tasks than those of higher demand, and participants were not always successful in increasing the demand of tasks.…”