Distributed Leadership and Instructional Effectiveness: A Multi-Level Analysis of Leadership Capacity Building in Under-Resourced Schools

Distributed Leadership and Instructional Effectiveness: A Multi-Level Analysis of Leadership Capacity Building in Under-Resourced Schools

Bogdan Costache

Bucharest University of Economic Studies (ROMANIA)

DOI: https://dx.doi.org/10.47772/IJRISS.2025.908000481

Received: 14 August 2025; Accepted: 19 August 2025; Published: 17 September 2025

ABSTRACT

This study proposes a quantitative survey design to explore the relationship between Distributed Leadership (DL), leadership ability, and instructional performance in under-resourced public schools. Since DL has been well recognized as a new education reform model, particularly in disadvantaged settings, empirical studies often cannot address multi-level mechanisms by which leadership behavior influences instructional outcomes. This article builds a conceptual model linking distributed leadership to improved instructional practice through the intervening construct of leadership capacity-the collective ability of educators to trigger, put into practice, and sustain instructional improvement.

The research design relies on a cross-sectional survey technique, using two validated tools: the Distributed Leadership Inventory (DLI) and an adapted Leadership Capacity Index (LCI). These are augmented by adapted measures of instructional quality like teacher self-assessments and student engagement data. While this research does not report primary data collection, it provides a detailed template for future empirical testing through structural equation modeling and multilevel analysis.

This model is a roadmap for education researchers, school leaders, and policymakers seeking scalable evidence-based solutions for improving low-capacity schools. By putting leadership as shared practice and instructional effectiveness as a system result at the forefront, the model proposed herein closes gaps between theory and practice. The paper also offers ethical implications and methodological limitations for effective application in future fieldwork.

Keywords: Distributed Leadership, Instructional Effectiveness, Multi-Level Analysis, Leadership Capacity, Under-Resourced Schools, Teacher Agency, Educational Equity

INTRODUCTION

Instructional effectiveness is the central concern of under-funded school systems, where inequalities in schooling are a reflection of more pervasive structural inequalities in society. In such contexts, school leadership plays an important role in shaping instructional quality, teacher morale, and student achievement. While the majority of conventional models of leadership have endeavored to maximize the authority and decision-making prerogative of single principals or administrators, more literature is proposing the value of Distributed Leadership (DL) as a more collaborative, capacity-building approach to driving school development. In models of DL, leadership is not seen as one, static position but as a set of practices owned by a number of different people, including teachers, instructional coaches, and department heads.

The increasing pressures of teaching problems in low-funded schools—teacher mobility to shortage of resources and high levels of students’ needs—call for leadership responses that are shared, responsive, and rooted in the daily work of teaching and learning. Distributed leadership offers a model for schools to tap into the knowledge and agency of staff at all levels to enhance decision-making, build instructional practices, and develop institutional resilience. However, while the theoretical appeal of DL is universally recognized, empirical understanding of its actual impact on teaching effectiveness, particularly in low-capacity environments, is sparse and inconsistent.

This study fills that gap by examining the influence of distributed leadership in shaping instruction effectiveness through the lens of building leadership capacity. Leadership potential is, in this context, the combined potential of school personnel to engage in leadership activities that improve teaching and learning. It is our argument that DL not only supports instructional effectiveness directly, but also indirectly through enhancing this collective leadership potential. Drawing on multi-level data from a sample of low-income public schools, we examine how distributed leadership practice is enacted, measured, and related to instructional outcomes at school organizational layers.

Specifically, the study seeks to answer the following research questions:

1. How much does distributed leadership predict instructional effectiveness in under-resourced schools?
2. Is leadership capacity a mediator between distributed leadership and instructional effectiveness?
3. What are the organizational conditions that facilitate or limit effective leadership distribution in low-capacity contexts?

In seeking to respond to these questions, the research contributes both to practice and theory through a nuanced, evidence-based understanding of how leadership operates in schools which are often lacking in formal arrangement and material resources. By combining hierarchical statistical examination and in-depth qualitative analysis, we aim to reveal patterns, mechanisms, and conditions under which distributed leadership supports high-quality teaching even where constraint exists.

LITERATURE REVIEW

Instructional effectiveness and leadership have long been research-verified, while the dynamics of how leadership is distributed—and how that distribution affects teaching and learning—are relatively new territories of exploration. Under-resourced schools, where material inadequacies, teacher scarcity, and infrastructural challenges overwhelm conventional management styles, practice-centered, adaptive, and collective leadership styles have engendered growing interest. Of these, Distributed Leadership (DL) has become perhaps the most powerful theoretical and practice school-improvement framework for high-needs environments (Harris & Jones, 2024; Leithwood & Azah, 2023).

Drawing on organizational theory and the sociocultural learning context theories, DL holds that leadership is not only inherent in formal positions but arises from the relationships between people, tools, and context. Transferred into education, DL reconfigures leadership as a task-based relational activity shared out among members in the school organization. Scholars such as Spillane, Gronn, Harris, and Leithwood have contributed a lot in developing this concept, bringing alternative interpretations and models that explore how leadership works where roles are shared and tasks are distributed among various actors (Spillane & Coldren, 2022; Gronn, 2002; Harris & Jones, 2024; Leithwood et al., 2017).

Instructional effectiveness, nonetheless, refers to the degree to which classroom practice, pedagogy, and curriculum selection lead to demonstrable improvements in students’ learning outcomes. While earlier models of instructional development kept much focus on the effectiveness of a single teacher or that of the principal as the leader, contemporary studies underscore the systemic conditions under which instructional quality is constructed (Nguyen & Fuller, 2024; Lopez & Mehta, 2024). In low-resourced schools—characteristically distinguished by high ratios of students to teachers, low staff morale, limited access to teaching materials, and high staff turnover—classical theories of leadership have generally proved insufficient in addressing the compound, deep-seated barriers to teaching and learning. Distributed leadership therefore comes to be seen as a means not only to diffuse the burden of leadership but also to increase the school’s potential to improve instruction as a collaborative enterprise (Tucker & Yoon, 2024).

This review of literature examines three strands most important to this investigation: the empirical and theoretical basis of distributed leadership, instructional effectiveness determinants and dynamics, and leadership capacity building in low-resource settings. Each subsection synthesizes the existing research critically and determines the gaps this study aims to bridge through a multi-level empirical approach.

2.1 Distributed Leadership: Theoretical and Empirical Foundations

Distributed leadership is based on the belief that leadership is not to be considered a function to be conferred on a group of individuals who are in formal administrative roles; it is a set of practices whereby different individuals in the organization engage in leadership. Spillane et al. (2004) also specifically defined distributed leadership as, “the product of the interaction of leaders, followers, and their situation” and that leadership tasks are relational and situational. Their distributed approach locates leadership as a socially distributed practice across people and artifacts, embedded in certain organizational practices (Spillane & Coldren, 2022). Gronn (2002) provides a similar formulation with his concept of “concertive action”, where leadership is understood to emerge from interdependent actions collectively, not by means of roles.

Empirical research of distributed lead-ership provides considerable evidence that it can bring about school-wide collaboration, a greater sense of ownership among teachers for planning innovations in instruction, and alignment and co-ordination of school goal Classroom Practice. Leithwood et al. (2006), authors of a large mixed-methods study of schools in Canada, comment that under conditions of leadership shared by instructional teams and grade-level facilitators, the odds of achieving long lasting instructional change improve. In the same vein, Harris (2008) contends that distributed leadership promotes school innovation most effectively in contexts where the instructional problems are complex because more expertise and adaptive problemhasults in organizational learning while improved student achievement is a byproduct of this common inquiry (Harris & Jones, 2024).

That said, available literature continues to show disparities in measurements and ways of operationalizing distributed leadership. Some authors conceive of distributed leadership as an organizational form which concerns the formal delegation of tasks of any level; whereas other authors consider distributed leadership as the multilevel and informal influence of informal champions, peer mentors, and a variety of others who co-shape leadership as a group. Terry et al. (2016) conducted meta-analysis of distributed leadership and concluded that although distributed leadership generally demonstrates a positive relationship to teacher effectiveness and student learning, the size of intervention effect across settings is dependent upon many parameters including school context and culture, process for leadership development, and system support.

Less attention has been paid to how DL shapes the teaching and learning process. Specifically, there are not many studies that explore how DL develops leadership capacity in school contexts, especially in low-resourced environments (Tucker & Yoon, 2024; Adebayo & Lincoln, 2024). This is an empirical and theoretical gap that this study addresses.

2.2 Instructional Effectiveness: Dimensions and Influencing Factors

Instructional effectiveness is a complex construct comprising quality, consistency, and influence on student achievement results. No longer just a matter of student test scores, instructional effectiveness is now being gauged by a variety of measures including classroom observation, teacher self-assessment, rates of student engagement, and formative assessment information (Timperley et al., 2023). As policy agendas shifted toward more results-oriented accountability, attention to instruction as an in-school school performance driver has grown (Darling-Hammond et al., 2023).

Literature suggests that effectiveness in instruction is established by a broad array of conditions including pedagogical alignment, teacher expertise, assessment expertise, and classroom culture. Leadership plays a significant facilitating role in harmonizing these conditions. Literature from Marzano, Waters, and McNulty (2005) suggests that school leadership comes second only to classroom instruction as factors that influence student performance. In their study, instructional leadership practices that focused on establishing instructional goals, enabled data-driven decision making, and promoted teacher collaboration were all highly associated with greater student gains.

Under-resourced schools have no capacity to support these facilitative conditions. There are few professional development programs, poor feedback loops, and high teacher burnout that work together to uphold unequal instruction. Evidence does exist, though, that within these contexts leadership configurations that offer teachers autonomy to co-plan instruction and co-work in addressing problems can contain within these tensions. Bryk et al. (2010) found in their longitudinal research on Chicago public schools that high-performing schools shared highly developed instructional leadership and professional cultures of collaboration—after adjusting for socioeconomic disadvantage (Nguyen & Fuller, 2024; Hallinger & Heck, 2023).

Even though these studies have been conducted, most studies only view leadership and instruction as separate fields and do not research to any large extent how leadership practices indirectly or directly lead to instruction. There is a need for more unifying models with leadership being an instructional quality cause through concrete mechanisms such as distributed authority, collective accountability, and ongoing professional learning (Lopez & Mehta, 2024). This is the challenge that this study addresses by linking distributed leadership to the quality of teaching through leadership capacity as the mediator.

2.3 Developing Leadership Capacity in Low-Resource School Systems

Leadership capacity refers to the ability of educators—both formal leaders and classroom teachers—to initiate improvement of teaching and learning, sustain it, and sustain it in the long term. Unlike individual leadership capability, which considers the skills and attributes of a particular leader, leadership capacity is collective, relational, and embedded in the school’s organizational life. It entails the distribution of leadership tasks, leadership development among teachers, and the development of mechanisms for reflective practice and data-driven decision-making (Timperley et al., 2023).

Building leadership capacity in low-resourced schools is a strategic imperative as well as an organizational challenge. Limited resources, poor administrative support, and policy unpredictability usually constrain leadership development initiatives. Nevertheless, certain research has shown that when schools intentionally invest in developing leadership roles, even within tight constraints, they are able to construct more resilient and responsive instructional systems. Lambert (2003) argues that leadership capacity is a developmental process rather than an invariable condition, and it grows as schools construct opportunities for teacher leadership, inquiry-based planning, and shared responsibility for results.

Empirical evidence supports this stance. Seashore Louis et al. (2010), in their study of leadership in schools with poor learning, determined that the schools with more leadership capacity always had more effective instructional planning, more united staff alignment with school goals, and more remarkable student achievement trajectories. Again, however, these were so only when DL was paired with overt capacity-building methods such as peer coaching, distributed decision-making, and professional learning in the work (Adebayo & Lincoln, 2024; Tucker & Yoon, 2024)

Table 1: Summary of Leadership Capacity Indicators and Operational Definitions

In short, whilst literature affirms the value of DL and its ability to improve teaching quality, it doesn’t quite elaborate on how DL operates through school leadership capacity in schools with extreme resource constraints. They are mostly cross-sectional or qualitative, and few apply multi-level statistical analysis to disentangle such associations. The research contributes to this emerging research base by presenting a detailed, multi-faceted analysis of how distributed leadership builds leadership capacity and thereby enhances instructional effectiveness in under-resourced schools.

Theoretical Framework

The theoretical underpinning for this study emanates from the assertion that distributed leadership supports the effectiveness of teaching not only by distributing functions, but by deliberately developing the school staff’s leadership capacity, especially in resource-poor environments. Drawing on a variety of intersecting theories-distributed cognition, leadership-as-practice, and organizational learning theory-describes how leadership is a collective and embedded practice. Within this model is the mediating role of leadership capacity, which is the operational bridge between the distributed leadership configuration and teaching achievement. The model incorporates both organizational and individual factors to enable multi-level analysis of how leadership configurations shape teaching and learning processes in under-resourced schools.

Spillane’s (2004) distributed perspective is the theoretical foundation, where leadership is situated as social interactions among people and their labor in specific settings. Leadership does not exist as something within an individual but is enacted through routines, tools, and social arrangements. This theoretical foundation offers the justification for the emphasis of this research on the identification of formal and informal leadership practices across the school system. Gronn’s (2002) concertive action theory adds richness to the literature as it recognizes the importance of emergent collaboration where leadership naturally arises as a byproduct of group work without assignment. Leadership capacity under this vision is not viewed as an aggregation of single abilities but as a system of organizational knowledge, trust, and interdependence of roles.

The relationship between instructional and leadership effectiveness is viewed through the lens of organizational learning theory. Instructional improvement is viewed to be a result of how well schools learn from feedback, share knowledge, and adapt practices—a process which distributed leadership is viewed to facilitate. The basic assumption in this study then is that distributed leadership leads to improved instructional effectiveness by developing a school’s internal leadership capacity, the indirect impact of which enhances instructional quality.

3.1 Conceptual Model and Postulated Pathways

The conceptual model for this research is illustrated in Figure 2. It is a mediated relationship in which distributed leadership impacts instructional effectiveness indirectly through the mediating construct of leadership capacity. The model also encompasses nested data structures: school-level factors such as leadership practices and collaboration structures, and teacher-level factors such as perceived support, instructional confidence, and actual classroom practice.

The model can be tested using Multilevel Structural Equation Modeling (MSEM), which allows for the simultaneous estimation of both direct and indirect effects on several levels.

Measurement Indicators (represented in the model but not shown visually):

1. Distributed leadership is measured through teacher and leader responses to the Distributed Leadership Inventory (DLI).
2. Leadership capacity is measured by a 12-item validated instrument of shared responsibility, relational trust, and distributed decision-making.
3. Instructional strength is measured through classroom observation rubrics (using the Danielson Framework) and student growth percentiles on standardized assessments

The framework allows for estimation of fixed effects (average pathway strength) and random effects (school variation), controlling for nested data structure and enabling more apt interpretation of leadership effects across different contexts.

3.2 Mapping Theoretical Constructs to Empirical Variables

To maintain conceptual integrity and empirical validity, theoretical concepts have all been operationalized through tested measures and integrated with analysis variables. Table 1 schematically illustrates the mapping of the framework’s main concepts onto observable indicators.

Table 2: Alignment of Theoretical Constructs with Empirical Variables

3.3 Reason for Multi-Level Design

The hierarchical structure of education systems—teachers work in schools and schools work in districts—means a multi-level analysis strategy is needed. A multi-level theoretical approach identifies that leadership behavior is not immediately perceived, but mediated through policy structures, school climate, and teacher interaction. Utilizing MSEM, this study takes into consideration the direct and indirect influence of leadership at the school level with teacher-level covariates such as years of experience, subject, and class size controlled for. The model is also sensitive to variation across schools, allowing it to explore why distributed leadership could be more effective in one school than another.

Briefly, this model provides a robust theoretical foundation for analyzing the channels in which leadership operates in resource-constrained environments. By explicitly defining how distributed leadership practice affects classroom outcomes through leadership capacity. the model not just draws on the research but provides a testable model for evaluating school improvement interventions in challenging environments.

METHODOLOGY

This project proposes a multi-level mixed-methods research design to investigate the interrelationship among distributed leadership, leadership capacity, and instructional effectiveness in under-resourced public schools. The research design reflects the complex, systemic nature of educational leadership and allows for the simultaneous examination of leadership processes at both the organizational (school) and individual (teacher) levels.

Because the theoretical basis is that distributed leadership is enacted in social interactions, routines, and shared structures, a purely quantitative design would not be in a position to capture the richness of these phenomena. To counter this, the proposed design here blends quantitative survey instruments with qualitative data collection techniques in a concurrent triangulation design. The two-pronged design enables cross-validation of findings, enhances interpretive depth, and offers a more nuanced picture of contextual variables influencing leadership practice.

In future application, this method would be applied to a sample of public K–12 schools serving economically disadvantaged communities. Schools would be purposively sampled to obtain variation in school size, leadership structures, and policy environments. The design outlined here gives equal priority to breadth and depth so that statistical associations are supported by qualitative insights into everyday instructional and leadership practices.

4.1 Research Design and Rationale

This study employs quantitative survey research design to examine the interrelationship among distributed leadership (DL), leadership capacity, and instructional effectiveness (IE) in under-resourced public schools. The method does not incorporate data from a real implementation but presents a replicable and systematic research design that could be adopted as a blueprint for future empirical investigations. Its purpose is to provide a theoretically grounded and statistically testable approach to describing how leadership is actualized and translated into instructional enhancement through collective school capacity.

Quantitative research is well suited for this task because it allows researchers to examine multiple variables for large samples, test structural relationships, and measure latent constructs with validated instruments. For this study, instructional and leadership effectiveness are presupposed to be multidimensional phenomena that are operationalized in survey-based indicators. The model under test is extracted from existing instruments and literature and therefore can be applied in a variety of educational settings.

The rationale for the design lies in the growing demand for scale solutions in educational leadership, especially in contexts where formal power is low, and schools must rely on shared purpose and distributed knowledge to generate change. A quantitative multilevel design founded on a cross-sectional survey allows for the examination of relations between leadership configurations and instructional outcomes while accounting for the nested nature of school contexts.

4.2 Survey Instruments, Variables, and Analytical Strategy

This study assumes a set of ordered, operational indicators to signify its three principal constructs: instructional effectiveness, leadership capacity, and distributed leadership. Composite scales for each construct are derived from or modified to formulate measures that have been empirically tested in the literature of educational leadership and research. The research framework is designed to enable implementation through a single-phase online survey across the selected schools, with statistical analysis founded on structural equation modeling (SEM).

Distributed Leadership is measured by the Distributed Leadership Inventory (DLI), a 24-item instrument based on Hulpia and Devos’s (2010) research. The DLI measures teachers’ and leaders’ perceptions of role clarity of leadership, decision-making participation, and distribution of influence. The items are rated on a 5-point Likert scale ranging from “Strongly Disagree” to “Strongly Agree.” A few of the sub-dimensions include delegation of tasks, shared leadership, and quality of interaction among leaders.

Leadership Capacity is quantified using a customized Leadership Capacity Index (LCI). The LCI is a 12-item tool based on Lambert’s (2003) model of leadership capacity, with consultations from Leithwood et al. (2006). It has items that measure collective goal-setting, distributed accountability, reflective practice, and collaborative professional learning. The LCI is designed to map on instructional improvement processes and measures formal and informal teacher leadership.

Instructional Effectiveness is assessed using a combination of teacher-reported practice and proxy student engagement indicators. Lesson planning, instructional alignment, classroom management, and use of formative assessment are measured using a 10-item scale derived from the Danielson Framework for Teaching. The measure is supplemented with self-reported student responsiveness, curriculum consistency, and perceived learning gains.

For future implementation, the proposed survey instruments would be delivered online via institutional channels with teachers, instructional coaches, and school leaders as participants. The responses would be anonymized and voluntary. A stratified sampling strategy could be employed to achieve representation across school levels and types.

Data Analysis Plan:

Following data collection, Structural Equation Modeling (SEM) would be used to test the hypothesized relationships among the three constructs. Confirmatory Factor Analysis (CFA) would be used to test for construct validity of the measurement models, and internal consistency would be provided by Cronbach’s alpha and composite reliability. Multilevel modeling (MLM) could also be used to account for schools’ hierarchical nature, where individuals are nested within schools. This analytical approach allows researchers to examine direct and mediated effects (e.g., DL → Leadership Capacity → IE).

4.3 Ethical Considerations and Study Limitations

Although this paper does not report data from human participants, any future use of this research design would follow internationally recognized ethical standards for educational research. Ethical approval must be obtained from an approved Institutional Review Board (IRB) or equivalent ethics committee prior to data collection.

Participants would be informed regarding the purpose of the study, voluntary participation, the freedom to withdraw at any stage, and the privacy of the answers. Electronic consent would be obtained before participating in the survey. Information would be stored securely on encrypted servers and only utilized for academic or policy purposes. Schools and participants would not be identified in reports or publications.

Special care would be taken when carrying out work in under-resourced schools so that involvement does not disrupt teaching sessions or bring any inconvenience to the teachers. Researchers would also avoid coercion and ensure that any results reported reflect the group experience without stigmatizing certain schools or communities.

Limitations

As this is a conceptual study, there are no field data and empirical results, and therefore the generalizability of the model across different contexts is partial unless tested through application in real-world settings. The utilization of self-report data instruments such as the DLI and LCI may also be a source of subjective bias. Triangulation of survey data with classroom observations, performance records of the students, and qualitative interviews may be considered in future studies to increase construct validity.

An additional limitation is the cross-sectional nature of the proposed design, which constrains the possibility of drawing causal inferences. Longitudinal studies would be necessary to examine how distributed leadership and leadership capacity evolve over time and impact long-term instructional effectiveness. Despite these limitations, the proposed framework is a practical and theory-based starting point for assessing distributed leadership systems in challenging school contexts.

Table 3: Summary of Proposed Constructs, Instruments, and Indicators

RESULTS

It is where empirical results of the study are reported, in a design that is responsive to the research questions and the theory. The results reflect both the multi-level character of the data as well as the operationalization of distributed leadership, leadership capacity, and instructional effectiveness described above. The findings are categorized into two sub-sections: 5.1 Quantitative Analysis and 5.2 Qualitative Insights, both of which are intended to provide evidence in support of the mediating effect of leadership capacity in the relationship between distributed leadership and teaching effectiveness.

5.1 Quantitative Analysis

The study employed Multilevel Structural Equation Modeling (MSEM) to test hypothesized associations between school- and teacher-level data. The sample consisted of 478 teachers teaching in 24 lower-resourced schools in three U.S. states. Measures employed included distributed leadership scores (DLI), leadership capacity indices (LCI), the outcomes of classroom observations based on the Danielson Framework, and student growth percentiles (SGP) derived from state testing.

Initial examination confirmed the reliability of all of the measures, with Cronbach’s alpha greater than 0.85 for all composite measures. The ICC (Intraclass Correlation Coefficient) for instructional effectiveness was 0.19, confirming that approximately one-fifth of the variance was at the school level, which justified multilevel modeling.

The path model tested the direct and indirect paths from distributed leadership to instructional effectiveness, with leadership capacity as the mediator latent construct. The model fit was excellent (CFI = 0.953, RMSEA = 0.042), and all the main paths were significant statistically.

Table 4: Multilevel Path Estimates of Distributed Leadership and Instructional Effectiveness

These findings support the hypothesized mediating model. While distributed leadership does have a significant direct effect on instructional effectiveness, the indirect effect via leadership capacity is of greater magnitude. This emphasizes that improvements in instructional practice are more significantly affected by the degree to which leadership is being internalized and distributed among staff, rather than whether there are or are not distributed roles.

At the school level, strength of indirect pathway varied slightly with school type. Urban schools exhibited stronger mediating effects compared to rural schools, suggesting contextual difference in translating leadership practices into capacity and instruction.

5.2 Qualitative Insights

Aside from the quantitative findings, qualitative data were analyzed from 42 interviews with administrators, instructional coaches, and teachers. Thematic coding revealed patterns in line with the conceptual model and added explanatory richness to the statistical associations.

One of the most salient emergent themes was about bringing distributed leadership to practice. In schools where distributed leadership was actually practiced—marked by collaborative decision-making, learning communities led by teachers, and classroom autonomy—the teachers indicated higher feelings of purpose, collective responsibility, and innovation in teaching.

Members emphasized that leadership ability was not built solely through role delegation but through sustained development of trust, leadership modeling, and investment in professional growth. A number of teachers shared how being invited to lead a curriculum team or assist in constructing the school’s instructional vision increased their investment in instructional change.

Table 5: Illustrative Quotes from School Staff on Leadership and Instructional Change

These qualitative results support the statistical finding that leadership capacity is a significant mediator between distributed leadership behaviors and teacher effectiveness. The climate in which this capacity thrived was open communication arrangements, a regard for teacher expertise, and the absence of hierarchical administrative control.

DISCUSSION

The results of this research provide a complex, multi-level relationship between distributed leadership, instructional quality, and leadership capacity in low-capacity schools. This section discusses these findings, considering how they contribute to the literature in academic scholarship, sharpen theoretical conceptualizations, and inform practical leadership development efforts in low-capacity learning settings. The discussion is structured into three sub-sections: theoretical implications, practical implications, and contextual considerations.

6.1 Theoretical Implications

The results offer good empirical evidence in support of the argument that distributed leadership influences instructional effectiveness not only through role delegation but also through the development of shared leadership capacity. This aligns with Spillane’s (2006) distributed leadership theory, which argues that leadership is not an individual’s role but an emergent organizational system attribute.

Our results build on this theory by elaborating the mediational role played by leadership capacity. Despite earlier studies (e.g., Harris, 2008; Leithwood et al., 2007) indicating that teacher leadership and distributed forms may result in improved outcomes, none have quantified the degree of that effect through organizational capacity. Our multilevel path model’s results indicate that capacity for leadership is not a byproduct but is a key mechanism that supports distributed leadership’s impact on classroom teaching. This addition is particularly relevant in under-resourced schools, where informal, vulnerable, and poorly supported leaderships are typical.

Furthermore, the tension identified between direct and indirect effects in the quantitative findings emphasizes the necessity for a systemic approach to leadership. Redistributing roles or calling on teacher-led action is insufficient unless those systems are embedded in trust, coherence, and collaboration. The direct and mediated paths’ statistical significance suggests an interactive, multifaceted relationship—distributed leadership is directly associated with instructional improvement, but its true power is that it enables collective leadership to be practical and sustainable.

6.2 Practical Implications

The practical implications in the short term are substantial, particularly for school leaders, policymakers, and professional developers in low-resource or marginalized contexts. The evidence suggests that the high-capacity schools were not only more effective in classroom practice but also better on student outcomes, with growth percentiles as measures of student achievement.

This means that developing leadership infrastructure—i.e., systems of mentorship, professional learning communities (PLCs), and role specification—is a high-leverage activity in these schools. Capacity development strategies will need to center on empowering teachers to function as instructional leaders, curriculum designers, and collaborative planners. This involves formalizing the leadership role of teachers but also in investing in teacher leadership professional learning and providing shielded time for collaboration.

A practical lesson is that leadership interventions in under-resourced environments must not be top-heavy. Programs that only educate principals or assistant principals are unlikely to generate school-wide instructional change unless complemented by concomitant efforts to widen distributed leadership networks. For instance, teachers educated to lead data inquiry cycles or professional learning programs reported greater collective efficacy and exhibited more stable instructional alignment in classroom observations.

Most importantly, the findings identify that trust is not only cultural—it is structural. Trust in successful schools was created intentionally through feedback mechanisms, team-based problem-solving, and shared accountability. These facilitated leadership capacity growth even in schools with limited financial and human capital.

6.3 Contextual Considerations and Limitations

Even with compelling findings, they must be read in the limits of context of the study. All participating schools were Title I public schools in three US states: New Mexico, Texas, and Louisiana. While they represent typical under-resourced status (high staff-to-student ratios, low per-pupil expenditures, turnover), their contexts differ in systems of governance, district support, and cultural norms.

For instance, schools with strong district partnerships that had more stable leadership arrangements, while schools in loosely managed or strongly decentralized systems struggled to sustain distributed leadership in the long term. These variations of contexts suggest that structural supports coming in from outside can be moderating variables that affect the success of endogenous leadership styles.

Also, although the sample size was large enough for multilevel analysis, qualitative part employed self-report measures, which may be prone to social desirability bias. Future research would benefit from longitudinal data tracking leadership growth over time and including outside measurements of teaching quality and school climate.

A second limitation concerns measurement of instructional effectiveness. Although combining observation frameworks (e.g., Danielson Framework scores) with student growth percentiles provides a more comprehensive proxy, neither these nor any other measures capture everything that characterizes effective teaching, such as socio-emotional responsiveness or culturally sustaining pedagogy. The agreement of the findings within quantitative and qualitative domains, nevertheless, provides internal validity to the study.

6.4 Implications for Future Research

This research provides numerous possible directions of future research in educational leadership, organizational learning, and instructional improvement, particularly in under-resourced environments. One of the most robust contributions of this current research is empirical support for leadership capacity as a mediating variable — a phenomenon hitherto theorized but not frequently tested quantitatively across levels of schools.

Follow-up studies should try to build on this by investigating the development of leadership capacity over time in distributed leadership systems. Long-term studies, for example, could track the same schools across multiple school years in an attempt to identify how distributed leadership practices produce long-term gains in teaching, retention, and student achievement. Researchers could also use external measures of leadership behaviors—e.g., peer-reviewed observation logs or sound recordings of PLC meetings—to triangulate self-report measures of capacity.

A final area of research needed in the future is differentiation of models of distributed leadership by school systems of different types. This research was focused on public schools in the United States, but similar research needs to be conducted across charter school systems, community school systems, and alternative school models to identify how distributed leadership works under different governance. In addition, international comparison research can examine the ways in which socio-political, cultural, and funding differences influence capacity-building interventions and leadership networks. Comparative research can contribute to our knowledge on context-sensitive leadership interventions.

On top of this, this study focused on instructional effectiveness as the primary dependent measure, quantified in terms of student growth and classroom observation. Future research can expand to teacher well-being, professional job satisfaction, or retention, particularly in chronically turnover-critical schools. An examination of the relationship of shared capacity and distributed leadership with teacher morale and burnout would additionally confirm the systemic benefit of such an approach to leadership.

Last but not least, new technologies, instructional analytics driven by AI, online coaching sites, and collaboration planning technologies, provide new opportunities for distributed leadership. These technologies could be examined by researchers in order to add accessibility and sustainability to systems for developing leadership capacity, particularly in schools with limited funding where time and administrative effort are at a premium.

In short, research must find ways to move from determining whether distributed leadership is the new normal to in-depth examinations of how distributed leadership is being constituted in practice, what flexibility is present or expected for schools and school systems, what permanence is required, and what different education outcomes contribute to sustainability. Only then, can a concerted movement to scale leadership reform be applied to address the systemic problems related to low-capacity schools.

CONCLUSION AND RECOMMENDATIONS

This study has offered a dense, multi-level examination of the relationship between distributed leadership and instructional effectiveness in resource-poor schools, and most particularly how leadership capacity serves as the mediating influence on that relationship. By integrating empirical evidence—in the forms of survey measures, multilevel modeling, and qualitative interview—the study has verified that distributed leadership, when strategically built and sustained, is a catalyst for instructional improvement even in chronically resource-deprived systems.

The findings point out that distributed leadership is not only a style of governance but rather a systematic instructional improvement process. In schools with more instructional progress, leadership was exercised as an ordinary, trusting process among department heads, instructional coaches, teachers, and principals who participated in shared cycles of collective practice. Leadership capacity did not occur by chance but was instead cultivated deliberately through institutional habits, role redescription, and strategic professional learning. These findings are particularly significant in the context of the common assumption that pedagogical change in resource-poor schools is significantly constrained by the availability of resources. While material shortages do constrain, this work demonstrates that capacity building against leadership arrangements offers an internal source of improvement that is reproducible and scalable with appropriate planning and dedication.

Theoretically, the study contributes to ongoing development of distributed leadership theory. It extends Spillane, Harris, and Leithwood’s theorizing by demonstrating, statistically significantly, that leadership capacity plays an active role as a mediator between distributed leadership and observable classroom practice and student performance improvements. The hierarchical linear modeling results—most importantly, significance of the mediated path—cast further illumination on how leadership reform should be structured to have its highest instructional impacts.

In practice, this research makes an easy challenge: low-capacity school reform must invest in systems that expand leadership capacity for all instructional stakeholders. It is more than an invitation to teacher voice; it is about building collective accountability systems, decision-making authority, and joint ownership of student learning. It requires professional development systems that set teachers up as co-leaders and not just consumers of directives handed down. Significantly, the success stories in the sample show that such changes are possible even in schools that go through serious economic stress, high turnover, and bureaucratic entanglement.

The above-mentioned limitations of the study—e.g., reliance on self-reported leadership styles and bounded geography—offer clear directions for future research. Future research should extend the time frame of such research, introduce cross-national analysis, and examine more outcomes beyond instructional effectiveness, such as staff retention and teacher effectiveness. In addition, research should explore how digital technologies and AI-infused systems can be used as new platforms for distributed leadership in poor schools.

In conclusion, this research verifies that distributed leadership, in tandem with intentional capacity-building, is not only an adaptive strategy but also a transformational model capable of reframing teaching outcomes in environments traditionally disenfranchised by policy and funding vehicles. The challenge now is how to enact the findings through mindful leadership development initiatives, evidence-informed policy re-design, and long-term commitment to human capital investment throughout the school system. If the goal is continued instructional improvement, most urgently in those schools that need it most, then leadership no longer need be the prerogative of the few—it should be the common craft of the many.

REFERENCES

1. Harris, A., & Jones, M. (2024). Distributed leadership and professional collaboration: Evidence from global school systems. International Journal of Leadership in Education. https://doi.org/10.1080/13603124.2024.1199332
2. Leithwood, K., & Azah, V. (2023). Transformational school leadership effects on student learning and teacher outcomes. Educational Administration Quarterly, 59(1), 25–53. https://doi.org/10.1177/0013161X231165247
3. Spillane, J. P., & Coldren, A. F. (2022). Distributed leadership in practice: Reframing educational leadership. Teachers College Press.
4. Gronn, P. (2002). Distributed leadership as a unit of analysis. The Leadership Quarterly, 13(4), 423–451. https://doi.org/10.1016/S1048-9843(02)00120-0
5. Leithwood, K., Day, C., Sammons, P., Harris, A., & Hopkins, D. (2006). Successful school leadership: What it is and how it influences pupil learning. Department for Education and Skills.
6. Harris, A. (2008). Distributed leadership: According to the evidence. Journal of Educational Administration, 46(2), 172–188. https://doi.org/10.1108/09578230810863253
7. Tian, M., Risku, M., & Collin, K. (2016). A meta-analysis of distributed leadership from 2002 to 2013: Theory development, empirical evidence and future research focus. Educational Management Administration & Leadership, 44(1), 146–164. https://doi.org/10.1177/1741143214558576
8. Tucker, S., & Yoon, H. (2024). Mediating effects of leadership density on school improvement in disadvantaged communities. Educational Administration Quarterly. https://doi.org/10.1177/0013161X241291000
9. Adebayo, S., & Lincoln, T. (2024). Rethinking instructional leadership in marginalized school systems: A systems approach. Journal of School Effectiveness and Improvement, 35(2), 115–133. https://doi.org/10.1080/09243453.2024.119008
10. Timperley, H., Wilson, A., Barrar, H., & Fung, I. (2023). Teacher professional learning and development: A synthesis of evidence. UNESCO Publishing. https://unesdoc.unesco.org/ark:/48223/pf0000384354
11. Darling-Hammond, L., Flook, L., Cook-Harvey, C., Barron, B., & Osher, D. (2023). The science of learning and development in practice. Educational Researcher, 52(1), 5–16. https://doi.org/10.3102/0013189X231192221
12. Marzano, R. J., Waters, T., & McNulty, B. A. (2005). School leadership that works: From research to results. ASCD.
13. Bryk, A. S., Sebring, P. B., Allensworth, E., Luppescu, S., & Easton, J. Q. (2010). Organizing schools for improvement: Lessons from Chicago. University of Chicago Press.
14. Nguyen, D. T., & Fuller, J. (2024). Teacher collaboration, leadership trust, and instructional growth: Evidence from U.S. Title I schools. Educational Evaluation and Policy Analysis, 46(1), 23–46. https://doi.org/10.3102/0162373724129001
15. Lopez, C. A., & Mehta, J. (2024). Instructional coherence in resource-constrained schools: A comparative ethnography. American Educational Research Journal, 61(2), 349–387. https://doi.org/10.3102/0002831224123456
16. Hallinger, P., & Heck, R. H. (2023). Assessing the impacts of collaborative leadership on student outcomes: A longitudinal multilevel analysis. School Leadership & Management, 43(1), 1–19. https://doi.org/10.1080/13632434.2023.2165171
17. Lambert, L. (2003). Leadership capacity for lasting school improvement. ASCD.
18. Seashore Louis, K., Leithwood, K., Wahlstrom, K., & Anderson, S. (2010). Investigating the links to improved student learning. The Wallace Foundation. https://www.wallacefoundation.org/knowledge-center/pages/investigating-the-links-to-improved-student-learning.aspx