Theses and Dissertations

Date of Award


Document Type


Degree Name

Doctor of Education (EdD)


Educational Leadership

First Advisor

Dr. Marie Simonsson

Second Advisor

Dr. Karen Watt

Third Advisor

Dr. Roberto Zamora


This study analyzes the relationship between student mobility, reading and math scores, gender, ethnicity, socioeconomic status (SES), and the number of moves by students during their academic years. Data were taken from four different high schools during the 2015-2016, 2016-2017, and 2017-2018 school years. The purpose of this study was to determine if student mobility when considering gender, ethnicity, SES, and number of moves impact a student’s reading and math scores. The study will provide educational leaders, community, and parents with valuable data to make informed decisions with regards to instructional adjustments and school changes for mobile students. The null hypothesis for this study was tested with an F distribution with an alpha level of .05.

Since the establishment of the Federal No Child Left Behind Act of 2001 (NCLB), and the accountability system that schools are continually being evaluated on; school administrators and district leaders have tried to adjust instruction to meet all student’s needs. With this study the researcher attempts to identify the implications that student mobility based on gender, ethnicity, socioeconomic status, and frequency of mobility had on student’s academic performance in reading and math. In this quantitative correlational research study, the research consisted of correlational research, which was conducted by using SPSS software program, PEIMS data and STAAR EOC state assessment results to determine how mobility impacted a student’s academic performance when compared to nonmobile students. The research analyzes the data to determine if mobile students are more prone to struggle when comparing success on state assessment in reading and math. The research was conducted by collecting data from four different high schools in a school district along the Rio Grande Valley of Texas that was identified as having higher than state average mobility rates. The data will be collected from the Texas Education Agency (TEA) and district PEIMS school records.


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