Date of Award

Spring 2000

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Program/Concentration

Urban Services - Urban Education

Committee Director

Edward Carter

Committee Member

Denny Wolfe

Committee Member

Rebecca Bowers

Abstract

This study developed a school site-based dropout identification and prescription process for student placement in alternative education programs in a school system with diverse residential environments—urban, rural, and suburban. The dropout performance-based and measurable predictor variables selected through discriminate function analysis were total retentions, yearly average of absences, total out-of-school suspensions, the state competency tests passed on time, total administrative hearings, and yearly average of poor grades. The combination and nature of these variables allow for early detection of potential dropouts.

While subtle differences existed between the urban, suburban, and rural prediction formulas, the variables selected produced prediction formulas with accuracy rates of 88.1% overall, 85.7% for urban, 94.2% for suburban, and 97.7% for rural students. Total retentions and passing the competency tests on time had the largest unstandardized canonical discriminate function coefficients in the overall, rural, and urban prediction formulas. Administrative hearings and passing the state competency tests on time variables were found to have positive impacts on students staying in school.

The significant events that the research suggested should trigger the identification process include: (1) Retention for the second time, (2) Average school absences of 15 days or more, (3) Failing two or more subjects, (4) Five or more cumulative out-of-school suspensions, (5) An administrative hearing, (6) Failing the state competency tests, (7) Averaging two or more family generated school transfers.

The researcher's policy recommendations are that once activated by triggering events, the screening process should be by a site-based early intervention team which can use the research generated discriminated function formulas to evaluate the severity of dropout risk, prescribe the appropriate type of education program from a continuum of services, and develop individualized alternative education plans with long term, short term, and exit goals.

With dropouts failing to pass the state competency tests on time at a rate five times that of non-dropouts and the increased pressure on schools that their students perform well on mandated competency testing will amplify the demand for early detection of potential dropouts with additional, diverse, and more individualized dropout prevention programs.

DOI

10.25777/e57t-hx68

ISBN

9780599754638

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