When examining the impact of distributed leadership, it is important to consider student outcomes. Student achievement measures capture some degree of what
schooling today seeks to produce in students, but they are by no means all-inclusive. Although what public education institutions seek to accomplish for our students cannot be narrowed only to achievement scores, they do provide one way to measure outcomes. When understanding student achievement as it relates to distributed leadership,
indirect impacts are more prevalent given the nature of leadership. A number of studies have captured this indirect impact.
Leithwood & Mascall (2008) examined 180 schools in 45 districts across nine states using random sampling procedures to identify the schools. This study used data collected through surveys by teachers and principals and the available student
achievement data. From their findings, the authors hypothesize that the performance of the employee is a function of their motivation, their capacity, and the situation in which they work. They define motivation as the employees’ beliefs about their ability to
complete a task and their beliefs concerning their particular context and whether or not it will help or hinder their ability to complete the task. Capacity involves sense making and the ability to build and develop skills, both as an individual and collectively
(Leithwood & Mascall, 2008). Finally, work setting is defined as the context in which a group works and is measured by examining the supports that are directly accessible by the individual or the group to accomplish the task (Leithwood & Mascall, 2008).
The study found that distributed leadership can have a significant relationship to student achievement (r= .34) and the three teacher variables used: teachers’ work setting (r=. 58), teacher motivation (r=. 55), and teacher capacity (r=.36) (Leithwood & Mascall, 2008). The study also found a significant correlation between student
in this study had an indirect impact on student achievement through the correlation that it has with teacher motivation and work setting (Leithwood & Mascall, 2008).
Other large studies in both England and the United States have provided similar results, reinforcing the idea that distributed leadership has a direct positive effect on improving teachers’ motivation and their working conditions (Leithwood et al., 2008). This aligns with analysis of data collected concerning the emotions teachers have that lead to their motivation (Leithwood et al., 2008). Teachers’ commitment to learning, their belief on how well they teach, their morale, their stress level, and how much they enjoy their work all impact their motivation to do the hard work of teaching (Leithwood et al., 2008). These motivations have a direct effect on student learning and are directly affected by a distributed model of leadership (Leithwood et al., 2008).
Another study sampling 110 schools found a relationship between a value-added measure of student achievement and the use of distributed leadership (Leithwood et al., 2008). Schools with the highest value-added scores showed more influence from
multiple sources of leadership; conversely, the lowest performing schools had the least amount of input from all the potential sources of leadership in the school (Leithwood et al., 2008). A major difference between these higher and lower performing schools was that those with better value-added scores distributed more leadership to teams, parents, and students (Leithwood et al., 2008). Finally, this study found that the school
administrator wielded the most leadership in all schools, whether this influence had a positive or negative effect (Leithwood et al., 2008). These findings reinforce the claims made earlier that the formal leader of a school using a distributed model remains crucial to the implementation of those distributed structures.
Two research studies conducted by Hallinger & Heck investigated the
relationship between the context of a school, that school’s leadership, and the processes evident in the school building (Hallinger & Heck, 2009; Heck & Hallinger, 2009). Over a three-year period, data for the first study were gathered in 200 elementary schools from teachers and students (Hallinger & Heck, 2009). The results suggest that state policy had an impact on the capacity of a school to distribute leadership (Hallinger & Heck, 2009). In these schools, which were in states that had policies with the intent of increasing distributed leadership, there was a significant increase in the perception that leadership was being distributed (Hallinger & Heck, 2009). The study also found that increasing the capacity to implement distributed leadership increased the capacity of school improvement, which had a small indirect effect on student’s math scores (Hallinger & Heck, 2009).
The second study by Heck & Hallinger (2009) over a four-year period examined 195 elementary schools in one state, looking to measure the link between distributive leadership, academic capacity, and student achievement. For this study, distributed leadership was measured through teacher surveys and focused on collaborative decision making, empowerment of staff and the school community, shared accountability for student learning, and encouragement of the school community to manage the instructional program (Heck & Hallinger, 2009). School academic capacity was measured by examining how much focus was on the standards and their
implementation, actions taken to continually improve, student support available at the school, and the professional development supports at the school (Heck & Hallinger, 2009). The results found that positive changes in distribution of leadership led to
impact in the distribution of leadership (Heck & Hallinger, 2009). The study also found that these two variables had a positive impact on student math achievement (Heck & Hallinger, 2009).
The research in these studies showed that distributing leadership had a direct effect on school improvement, teachers’ motivation, teaching capacity, a school’s capacity, and teacher working conditions. These five effects thus positively influenced student outcomes. These studies, while not noting a direct link between distributed leadership and student performance, do suggest that distributed leadership is a critical part of improving a school’s outcomes (Harris, 2014).
Summary
This literature review reveals that distributed leadership shows three major components: empowerment, shared decision making, and building leadership capacity with a recent study including collective engagement. These dimensions are present in the leadership functions of vision setting, building people, redesigning the organization, and managing the instructional program. Undergirding both these components and functions, schools with an effective distributed model have high levels of reciprocal trust. This trust is multidirectional between formal leaders and other staff, between informal leaders and their colleagues, and between the staff as a whole and the school. With this foundation of trust, these schools are able to build collective capacity often through a PLC model that completes complex tasks through interdependence and a disciplined approach and that manages the instructional program. The distributed model in these schools is phased in over time, beginning with building trust and capacity, then distributing leadership functions to many in the building, and finally focusing on deepening a curriculum by adding creativity and enjoyment for staff and
students. Lastly, schools in distributed environments identify key staff to lead based on their expertise and their personality traits. Research identified in this literature shows how distributive leadership differs from a traditional approach, but it also indicates that it has a direct effect on school improvement, teachers’ motivation, teaching capacity, and teacher working conditions. Through influencing these teacher beliefs, distributed leadership indirectly impacts student achievement. Overall, distributed leadership presents leadership activities that are measurably different than schools with a more traditional approach, and this difference has a positive indirect impact on student outcomes.
Based on this literature review, I have identified key factors of distributed leadership in specific questions from the North Carolina Teacher Working Conditions survey that reveal teacher perceptions of either areas necessary in a school for a distributed leadership model to work or actual evidence that a distributed model is in place. I used these questions to determine that empirically there is an underlying factor of distributed leadership, and with this information created two distribute leadership measures for each non-charter public school that participated in the North Carolina Teacher Working Conditions Survey.
CHAPTER III: METHODOLOGY (QUANTITATIVE)