Improving the Capacity of School System Leaders and Teachers to Design Productive Learning Environments

Abstract

In this article we report on the results of an innovative research partnership with the largest school district in one Canadian province where we are exploring how educational leadership practices and the factors that influence these practices interact to impact student learning. This article makes a clear connection between leadership and student learning and makes a significant contribution to the knowledge base regarding what we know about leadership in educational contexts, how and how much leadership matters within that context, as well as how important those effects are in designing productive learning environments that facilitate the learning of all children. Using Arbuckle's Amos 17 and maximum likelihood estimation, we employed path analysis procedures to develop a best-fitting nested model to examine the interrelationships among three primary sources of formal leadership for education found in schools, school districts, and government, and how these leaders interact with one another and with professional teachers, parents, and other community stakeholders to directly and indirectly impact the existence of a clear focus on student learning. We conclude with a discussion of the pathways in our best-fitting model as we explore in detail the interrelationships among the primary sources of leadership and discuss the direct and indirect effects of each of these leadership sources on one another and on the extent to which the factors individually and collectively impact a school's focus on student learning.

Notes

^†This article was published posthumously.

1. Even though a non-significant chi-square statistic (p > 0.05) would be a good indicator of model fit, we did not set a non-significant chi-square statistic as an essential element for our determination of a good fitting model because a large sample size such as in this study (N = 1804) almost always results in a statistically significant chi-square statistic.