Distributing Leadership for Collective Teacher Learning to Effect Student Learning Outcomes: A Singapore Case

• In Event: The Relationship Between Distributed Leadership and Student Learning

Abstract

The objective of the study is to investigate the direct and indirect influences of distributed leadership on student learning outcomes via teacher leadership and teacher collective learning.

The study is premised on the assumption that effectiveness of distributed leadership to enhance instruction is dependent on how well instructional leadership is distributed through teacher leadership enroute to improvements on teaching and learning. While the distribution on instruction from senior leadership to middle leadership has been well established in terms of practice, the distribution to teacher leaders is much less so. Furthermore, what teacher leaders do, in their formal and informal roles, and especially in collective learning spaces (e.g., professional learning communities), to improve teaching and learning also still need greater empirical attention. The link between leadership and collective learning (Hairon & Goh, 2015) is closely related to the idea of ‘leadership for learning’ (MacBeath et al., 2008), specifically the importance of leadership in creating and sustaining a school-wide focus on learning (Hallinger & Heck, 2010).
Methods and Sources of Data
The study employs a survey design consisting of two parts. Part 1 involves three Grade 5 mathematical problem-solving tests spread over a 1-year period to determine. Part 2 involves a questionnaire for primary school educators at the end of the 1-year period. The questionnaire contains rating scales on the dimensions of distributed leadership, teacher leadership and collective learning. The dimensions of distributed leadership (DL) include empowerment, shared leadership, shared decision and collective engagement. The dimensions of teacher leadership (TL) include collegial collaborative relations, teacher learning and development, and teachers’ teaching practices. The dimensions of collective learning (CL) include sharing knowledge, reflecting knowledge, interrogating knowledge, applying knowledge, innovating knowledge.


Rasch analysis was used to not only calibrate and validate the test items, but also equate Test 1, 2 and 3. The dimensions of the three key constructs of distributed leadership, teacher leadership and collective learning were also derived from Rasch analysis. A multi-level SEM analysis was used to aid in estimating the predictive pathways between the dependent variables of distributed leadership, teacher leadership and collective learning through regression to the outcome variable of student growth (Test 3 minus Test 1), albeit in a nested or hierarchical manner. The multilevel path analysis gives a parsimonious frame to understand the direct and indirect effects of how the dimensions of distributed leadership, teacher leadership and collective learning on student learning growth. It shows that school leaders’ empowerment is critical insofar as it promotes the development of teacher leadership practices; specifically, enabling change in teachers’ teaching practices – that is, teacher leaders’ effort at impacting their colleagues’ teaching practices. This practice then impacts teachers’ collective learning by bringing their teaching practices to their collective learning spaces, followed by teachers’ collective practices of applying what they have learned in their collective learning spaces back to their respective classroom teaching contexts.

This study has provided evidence that distributed leadership practice on empowerment impacts on student learning outcomes, albeit through teacher leadership leading collective teacher learning that intimately connects teacher teaching and learning spaces together.

Authors

• Salleh Hairon, National Institute of Education, Nanyang Technological University

• Jonathan Goh, National Institute of Education - Nanyang Technological University