The UA Campus Repository is experiencing systematic automated, high-volume traffic (bots). Temporary mitigation measures to address bot traffic have been put in place; however, this has resulted in restrictions on searching WITHIN collections or using sidebar filters WITHIN collections. You can still Browse by Title/Author/Year WITHIN collections. Also, you can still search at the top level of the repository (use the search box at the top of every page) and apply filters from that search level. Export of search results has also been restricted at this time. Please contact us at any time for assistance - email repository@u.library.arizona.edu.

Show simple item record

dc.contributor.advisorSummers, Jessicaen_US
dc.contributor.authorShealy, Linda
dc.creatorShealy, Lindaen_US
dc.date.accessioned2011-10-13T20:45:05Z
dc.date.available2011-10-13T20:45:05Z
dc.date.issued2011
dc.identifier.urihttp://hdl.handle.net/10150/145278
dc.description.abstractOver one million high school students drop out of school each year in this country. Dropping out of school is a serious problem for the student, community, and the nation. Often dropouts are unable to compete in an increasingly technological society and face numerous consequences from their decision to leave school early including higher levels of poverty, unemployment, public assistance, incarceration, and poor health. Dropping out is a gradual process of school disengagement and related to individual, family, and school factors. In the past, it has been difficult to track individual student's progress through school and to determine accurate dropout and graduation rates. In 2005, the National Governors Association made a commitment to implement a uniform method to calculate and report graduates and dropouts as well as better data collections systems.This study intended to replicate aspects of other major studies around the county to determine the best early predictors of dropping out of school in this large school district in southern Arizona and use this information to build an early warning system. Student data were obtained from the district's Research and Accountability office for a cohort of students (n=6751) who began the ninth grade in fall 2006 and graduated or should have graduated in 2010. Data collected included general demographic information, academic data, number of schools attended, and school withdrawal codes.The intent of this research was to determine if there were statistically significant differences between dropouts and graduates in the variables collected and which variables yielded the highest effect sizes and should be included in the district's early warning system.Two analyses were used to determine significance differences between dropouts and graduates. Then four analyses were performed to determine the highest-yield variables for this district. Consistent with recent research in the field, the variables of ninth grade attendance, ninth grade English and Math grades, and GPA were the strongest predictors of student dropouts.Local educators can use this early warning information to help identify potential high school dropouts as early as possible and intervene more efficiently and effectively with these students.
dc.language.isoenen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectdropoutsen_US
dc.subjectearly warning systemen_US
dc.subjectgraduationen_US
dc.subjecthigh schoolen_US
dc.subjectinterventionsen_US
dc.subjectrisk factorsen_US
dc.titleBuilding an Early Warning System to Identify Potential High School Dropoutsen_US
dc.typeElectronic Dissertationen_US
dc.typetexten_US
dc.identifier.oclc752261355
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.leveldoctoralen_US
dc.contributor.committeememberBauman, Sherien_US
dc.contributor.committeememberBurross, Heidi Leggen_US
dc.identifier.proquest11486
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineEducational Psychologyen_US
thesis.degree.namePh.D.en_US
refterms.dateFOA2018-07-14T23:27:43Z
html.description.abstractOver one million high school students drop out of school each year in this country. Dropping out of school is a serious problem for the student, community, and the nation. Often dropouts are unable to compete in an increasingly technological society and face numerous consequences from their decision to leave school early including higher levels of poverty, unemployment, public assistance, incarceration, and poor health. Dropping out is a gradual process of school disengagement and related to individual, family, and school factors. In the past, it has been difficult to track individual student's progress through school and to determine accurate dropout and graduation rates. In 2005, the National Governors Association made a commitment to implement a uniform method to calculate and report graduates and dropouts as well as better data collections systems.This study intended to replicate aspects of other major studies around the county to determine the best early predictors of dropping out of school in this large school district in southern Arizona and use this information to build an early warning system. Student data were obtained from the district's Research and Accountability office for a cohort of students (n=6751) who began the ninth grade in fall 2006 and graduated or should have graduated in 2010. Data collected included general demographic information, academic data, number of schools attended, and school withdrawal codes.The intent of this research was to determine if there were statistically significant differences between dropouts and graduates in the variables collected and which variables yielded the highest effect sizes and should be included in the district's early warning system.Two analyses were used to determine significance differences between dropouts and graduates. Then four analyses were performed to determine the highest-yield variables for this district. Consistent with recent research in the field, the variables of ninth grade attendance, ninth grade English and Math grades, and GPA were the strongest predictors of student dropouts.Local educators can use this early warning information to help identify potential high school dropouts as early as possible and intervene more efficiently and effectively with these students.


Files in this item

Thumbnail
Name:
azu_etd_11486_sip1_m.pdf
Size:
962.1Kb
Format:
PDF

This item appears in the following Collection(s)

Show simple item record