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dc.contributor.authorCollins, David Bishop
dc.date.accessioned2014-03-04T18:21:30Z
dc.date.available2014-03-04T18:21:30Z
dc.date.issued2009-12
dc.identifier.othercollins_david_b_200912_edd
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/collins_david_b_200912_edd
dc.identifier.urihttp://hdl.handle.net/10724/26023
dc.description.abstractThis dissertation investigated the variables associated with high-school dropout rates in a large metropolitan area in the southeastern United States. Data from 143 high schools with a combined population of 269,290 students was included. Variables included ethnicity, gender, school size, school location, special education status, limited English Proficiency status, and socioeconomic status. Multiple regression analysis was used to answer the following research questions. 1. Which variables—ethnicity, gender, school size, school location, special education status, socioeconomic status, and limited English proficiency status—are more likely to predict higher dropout rates among students who attend school in the large metropolitan area studied? 2. Which variables — ethnicity, gender, school size, school location, special education status, socioeconomic status, and limited English proficiency status —have the greatest impact on dropout rates? Results from the multiple regression analysis revealed the variables gender, ethnicity, and school size are more likely to predict dropout rates. Furthermore, the variables having the greatest impact on dropout rates in the school districts included in this study were, in rank order, gender (male), ethnicity (Black and Hispanic), and school size (medium). Since the results of this quantitative research study provide a means to predict dropout rates, legislators and school system personnel can use the regression formula to predict school dropout rates in order to prioritize the allocation of resources and focus on intervention efforts. Additionally, education specialists, practitioners, and school system personnel will have a better understanding of which student groups have the greatest impact on dropout rates and can tailor intervention strategies designed to help reduce the dropout rate.
dc.languageeng
dc.publisheruga
dc.rightspublic
dc.subjectDropout
dc.subjectAt risk
dc.subjectUrban
dc.subjectSuburban
dc.subjectRural
dc.subjectMetropolitan Statistical Area
dc.subjectWorkforce Education
dc.subjectIntervention strategies
dc.subjectHigh School
dc.titleVariables that impact high-school dropout rates in a large metropolitan area
dc.typeDissertation
dc.description.degreeEdD
dc.description.departmentWorkforce Education, Leadership, and Social Foundations
dc.description.majorOccupational Studies
dc.description.advisorJohn Schell
dc.description.committeeJohn Schell
dc.description.committeeJay Rojewski
dc.description.committeeKaren Jones


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