Freshman Year Dropouts: Interactions Between Student and School Characteristics and Student Dropout Status
Keith Zvoch
Abstract
Keith Zvoch
Abstract
Data from a large school district in the southwestern United States were analyzed to investigate relations between student and school characteristics and high school freshman dropout patterns. Application of a multilevel logistic regression model to student dropout data revealed evidence of school-to-school differences in student dropout rates and school-to-school differences in the relation between student characteristics and student dropout status. Investigation of the school differences revealed that school organization and schools' social context were statistically significant predictors of several of the dropout outcomes. Evidence of school context and school practice effects on student dropout outcomes suggests that school personnel may need to consider how characteristics of the school environment interact with the background characteristics of students when developing and focusing dropout prevention strategies. Implications for school policy and practice are discussed.
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Data from a large school district in the southwestern United States were analyzed to investigate relations between student and school characteristics and high school freshman dropout patterns. Application of a multilevel logistic regression model to student dropout data revealed evidence of school-to-school differences in student dropout rates and school-to-school differences in the relation between student characteristics and student dropout status. Investigation of the school differences revealed that school organization and schools' social context were statistically significant predictors of several of the dropout outcomes. Evidence of school context and school practice effects on student dropout outcomes suggests that school personnel may need to consider how characteristics of the school environment interact with the background characteristics of students when developing and focusing dropout prevention strategies. Implications for school policy and practice are discussed.
Key concepts: Dropout (neural networks), School dropout, Context (archaeology), Psychology, Logistic regression, Multilevel model, Mathematics education, At-risk students