The Probability of Identifying Potential Sophomore High School Dropouts From Elements in Their Cumulative Records

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Authors

Murray, Dan L.

Issue Date

1983-06

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Thesis

Language

en_US

Keywords

School attendance , Education, Secondary

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Abstract

The problem. Are there similarities or characteristics in the cumulative records that would identify students as potential dropouts? Procedure. Six items of information were selected from the cumulative records: IQ level, grade point average, absences, extra-curricular activities, disciplinary actions and form of guardianship. Data was obtained from the records of the thirty-two sophomores who dropped out of the 1980 class at Des Moines Lincoln High School. The same data was taken from an equal number of students in the same class who completed the year. This group was selected by means of a random sample. A Multiple Regression Analysis was used to determine if significant differences exist between the two groups on the first five items. A Chi Square Test was used to determine the significance of the last variable, form of guardianship. Findings. The Multiple Regression Analysis identified three variables; GPA, attendance and disciplinary actions, as very significant predictors of potential dropouts. Two other elements, IQ level and extra-curricular activities, were found to be insignificant. The Chi Square Test indicated a very strong relationship between the type of guardianship and the tendency for a student to drop out of school. Conclusions. Grade point average, absences and disciplinary actions are important predictors of potential dropouts. When used in conjunction with the form of guardianship of the student it becomes a very useful tool for administrators and guidance counselors. Recommendations. Based on the information found in this study it is recommended that: (1) a computer program be developed to facilitate the use of the information by administrators and counselors, (2) the resulting computer program be made available to educational personnel, and (3) additional studies be conducted to determine if there are other elements that would be significant predictors.

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iv, 48 leaves. Advisor: Richard Lampshire.

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Drake University

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