Dropping out of high school among language minority students: Multiple regression and discriminant analysis of variables
Abstract
The present study investigated the correlates of dropping out of high school among language minority students. Correlates included were academic achievement, type of school program, socioeconomic status, employment, level of English language usage in the home; level of English language usage outside the home, bilingual program participation, special program participation, length of U.S. residence of the parents and the student, and ethnic origin. Subjects were drawn from those who participated in the survey known as High School and Beyond, conducted for the National Center for Educational Statistics in 1980 and followed-up in 1982. The total sample included 459 dropouts and 4268 subjects who were still in school. Stepwise and forced entry regression analyses were performed to determine how the variables contributed to the prediction of dropping out. The analyses indicated that academic achievement was the strongest predictor, followed by employment, level of English usage outside the home, and special program participation, respectively. The four variables were significant at the.05 level. Discriminant analysis was performed to determine if the variables discriminated language minority students who dropped out from those who remained in school. The analysis resulted in a correct classification rate of 68.66%, significant at the.01 level. Results are discussed in terms of the specific correlates as well as programs which may be implemented at various grade levels in schools. Recommendations are made for further research.
Subject Area
Secondary education|Minority & ethnic groups|Sociology|Educational psychology
Recommended Citation
Berezny, Patricia Marmo, "Dropping out of high school among language minority students: Multiple regression and discriminant analysis of variables" (1989). ETD Collection for Fordham University. AAI9007170.
https://research.library.fordham.edu/dissertations/AAI9007170
