| This study's goal was to investigate the variables associated with dropout rates by analyzing secondary data gathered from one state's entire public school system.;The study population consisted of 273 public high school institutions and an individual student population of 1,544,044 during the 2003-2004 school year. School size and school location was used to gauge its affect on dropout rates. School size [<1000 small, 1000-1499 medium, ≥1500 large] and school location [rural, suburban, and urban] is greatly diverse throughout the Georgia Public School System. The diversity ranged from the inner-city urban schools found in Atlanta, to the rural farmland of Vidalia, Georgia, to the upper class suburbs of the metro-Atlanta area.;Analysis of Variance (ANOVA) was used to measure the relationship between dropout rates and the following independent variables: [Ethnicity --Black, Hispanic, White, and multiracial/other], [Gender --male, female], [School size--small (<1000), medium (1001-1499), and large (1500≤)], [School location--rural, suburban, and urban], and [prevalent subcategories--Socioeconomic status, Limited English Proficiency, and Special Education enrollment]. The relationship between dropout rates, graduation rates, and truancy rates were illustrated using a two-tailed Pearson's Correlation Matrix significant to the (.001) level. The multiple regression method of constructing a scattered do-plot allowed to follow the regression line to determine which independent variable had the highest probability of causing higher dropout rates in the future.;The study finding points toward a stronger Pearson's Correlation relationship between males and dropout rate (.970) than there was between females and dropout rate, a stronger Pearson's Correlation relationship between dropout rates and having Hispanic ethnicity (.792) than any other ethnical background, and the relationship between dropout rates and prevalent subcategories produced Special Education (.724) as the variable with the strongest relationship. The data also yielded that smaller school population (.694) had a stronger relationship with dropout rates than any of the other population variables, and that rural school location (.858) had a stronger relationship with dropout rates than any of the other location variables. This examination also produced that dropout rates and truancy rates had the strongest Pearson's correlational relationship [.341 (two-tailed)]. The profile of a typical dropout that this study revered of being (A) Male, (B) White, and (C) being enrolled in Special Education. The result of this study may assist practitioners in identifying at-risk population for drop out and provide early intervention. |
