“How School Leadership Influences Student Learning A Test of “The Four Paths Model”

Assignment 2: 143400 Seminar on Dissertation

 

Nutthakarn O.

“How School Leadership Influences Student Learning A Test of “The Four Paths Model”

Kenneth Leithwood University of Toronto kenneth.leithwood@utoronto.ca Jingping Sun University of Alabama jsun22@ua.edu Randall Schumacker University of Alabama rschumacker@ua.edu Paper to be presented at the annual conference of the American Education and Research Association, New York, April 2018

 

This paper is a quantitative research study that examines the indirect contributions of school leadership to student learning. The study uses a partial replication approach to generalize the results from Ontario to Texas schools. The authors propose a Four Paths Model that identifies four key areas of school leadership that indirectly influence student learning: Rational Path, Family Path, Developmental Path, and Teacher Path. The study finds that the Rational Path and Family Path have the strongest indirect effects on student learning, while the Teacher Path has the weakest. The study also provides insights into the specific leadership practices that contribute to student learning in each of the four paths. The authors conclude that school leaders can have a significant impact on student learning through their indirect contributions, and that future research should aim to include data from a larger sample of schools.

Type of Research

    This study is quantitative research as it involves statistical analysis of data collected from surveys and standardized tests

Variables in the Research

    The research identifies 12 variables that are grouped into four paths in the Four Paths Model. These variables are:

1. Rational Path: Academic Press (AP), Developmental Curriculum (DC), and Use of Instructional Time (UIT)

2. Family Path: Parental Involvement (PI), Home Environment (HE), and Student Mobility (SM)

3. Developmental Path: Student Self-Concept (SSC), Teacher Expectations (TE), and Teacher-Student Relationships (TSR)

4. Teacher Path: Teacher Professionalism (TP), Teacher Collaboration (TC), and Teacher Efficacy (TEF)

 

These variables are used to measure the indirect effects of school leadership on student learning through the Four Paths Model

 

Sampling Design

The study used a smaller survey sample size of 81 schools, and the unit of analysis for the analyses was the school. The sample of teachers providing data for the study was quite large (1779). The authors suggest that future research on the Four Paths model should aim to include data from at least 100 schools

 

Measurement Design

The paper uses a quantitative research design to measure the indirect effects of school leadership on student learning through the Four Paths Model. The study uses a partial replication approach to generalize the results from Ontario to Texas schools. The authors collected data from surveys completed by teachers and principals in 81 schools in Texas. The study uses multiple regression analysis to test the relationships between the Four Paths variables and student achievement, while controlling for student socio-economic status (SES). The study also uses reliability analysis to test the internal consistency of the scales used to measure the Four Paths variables.

 

Statistical Design

The study uses a mixed-methods research design that combines quantitative and qualitative data. The quantitative data were collected through surveys completed by teachers and principals in 81 schools in Texas. The study uses multiple regression analysis to test the relationships between the Four Paths variables and student achievement, while controlling for student socio-economic status (SES). The study also uses reliability analysis to test the internal consistency of the scales used to measure the Four Paths variables. The qualitative data were collected through interviews with principals and teachers in a subset of the schools.

 

Internal and External Validity of the Research

The internal validity of the research refers to the extent to which the study's findings are accurate and can be attributed to the variables being studied. The study uses a mixed-methods research design that combines quantitative and qualitative data to test the relationships between school leadership and student learning. The study uses multiple regression analysis to test the relationships between the Four Paths variables and student achievement, while controlling for student socio-economic status (SES). The study also uses reliability analysis to test the internal consistency of the scales used to measure the Four Paths variables. The study's internal validity is strengthened by the use of these statistical tests and the careful selection of variables to be studied 

The external validity of the research refers to the extent to which the study's findings can be generalized to other populations and settings. The study uses a partial replication approach to generalize the results from Ontario to Texas schools. The authors collected data from surveys completed by teachers and principals in 81 schools in Texas. While the sample size is relatively small, the study's external validity is strengthened by the use of a mixed-methods research design that combines quantitative and qualitative data and the careful selection of variables to be studied.

 

Limitation

The study has several limitations that should be considered when interpreting the findings. First, the study uses self-reported data from teachers and principals, which may be subject to social desirability bias. Second, the study's sample size is relatively small, which may limit the generalizability of the findings to other populations and settings. Third, the study focuses on the Four Paths model of school leadership, which may limit the generalizability of the findings to other models of school leadership. Finally, the study's cross-sectional design does not allow for causal inferences to be made about the relationships between school leadership and student learning.

Future research can address the limitations of this study by using larger sample sizes and more diverse populations to increase the generalizability of the findings. Researchers can also use more objective measures of school leadership and student learning to reduce the potential for bias in the data. Longitudinal designs can also be used to establish causal relationships between school leadership and student learning. Finally, future research can explore the relationships between school leadership and other outcomes, such as teacher retention and job satisfaction, to provide a more comprehensive understanding of the impact of school leadership on schools.