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    A Descriptive Statistical Analysis of the Relationships Between Socioeconomic Status, Attendance Rates, Per Pupil Expenditures, Teacher Qualifications, and On-Time Educational Attainment Rates within the State of Virginia Including a Comparative Study of the Appalachian and Non-Appalachian School Division

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    Date
    2010-04-01
    Author
    Siers, Kevin W.
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    Abstract
    PURPOSE This study had two purposes: (a) to examine the possible predicting abilities of socioeconomic status, per pupil expenditures, percentage of highly qualified teachers and attendance rates for on-time educational attainment in the state of Virginia and (b) to compare the Appalachian School Divisions of Virginia with the non-Appalachian school divisions for each of these variables. METHOD Data pertaining to socioeconomic status, per pupil expenditures, attendance rates, teacher qualifications, and on-time educational attainment were collected for the graduating cohorts of 2005, 2006, 2007, and 2008. A stepwise multiple regression analysis was conducted on these variables to address the first purpose. A general linear model repeated measures ANOVA was conducted for each variable to compare differences between the Appalachian, non-Appalachian divisions of similar size, non-Appalachian large school divisions, and the total non-Appalachian divisions to address the second purpose of the study. RESULTS Socioeconomic status and attendance rates were found to be the independent variables that were significantly able to predict on-time educational attainment rates. Socioeconomic status rates were found to be significantly higher in the Appalachian divisions than in the non-Appalachian large school divisions. Teacher qualification rates were found to be significantly higher in the Appalachian divisions than the non-Appalachian divisions of similar size. On-time educational attainment rates were found to be significantly higher in the Appalachian school divisions than in all three classifications of the non-Appalachian divisions.
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    http://hdl.handle.net/10919/26861
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    • Doctoral Dissertations [15822]

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