School of Education
Doctor of Education (EdD)
Primary Subject Area
Education, General; Education, Tests and Measurements; Education, Administration
Academics, At Risk, Economically Disadvantaged, Family Structure, Mobility, Predictive Regression Model
Student mobility can be described as movement from one school to another for any reason beyond grade promotion. Student mobility affects many areas of student learning. The causes of student mobility include disadvantages within the family unit, student behavior issues, and complicated school district initiatives. Research shows that student mobility issues affect all demographical areas; however, low-socioeconomic, urban areas have the highest percentage rate of movement. Student mobility negatively impacts student achievement in the areas of academics, social adjustment, and psychological well being. Although there is no overall solution to the mobility crisis, there are many strategies that can be implemented that will help decrease the number of transient students. The purpose of this study is create and utilize a predictive regression model in order to predict Criterion Reference Competency Test (CRCT) reading scores for at risk mobile students. Intense analysis of a valid prediction model by concentrated stakeholder collaboration can start a school district on a more successful path of addressing student mobility.