This study was conducted to identify variables that would differentiate between school dropouts and stayins, by applying the data mining on the data about individual, family-, peer-, school-, and community-related characteristics, and to construct the...
This study was conducted to identify variables that would differentiate between school dropouts and stayins, by applying the data mining on the data about individual, family-, peer-, school-, and community-related characteristics, and to construct the school dropout model that would suggest causes and processes of the school dropout phenomenon. The data were collected through paper-pencil surveys, telephone interviews, and face-to-face interviews with 291 dropouts and 374 students in Kyunggi. Under the assumption that school dropout phenomena would differ by gender and grade, the data were separately analyzed on male and female students, and on junior and senior high school students. Parental expectation of children's graduation was found to be the strongest differentiating variable in junior high school students. In addition, teachers' evaluation of friends, absences, and tardiness also differentiated dropouts from stayins. In senior high school students, the track type of the school(i.e., college-prep, vocational), smoking, helplessness, depressed mood, expectation of future career, and socioeconomic status were found to be powerful variables that differentiate between dropouts and stayins. The expectation of graduation was found to be the most powerful variable among males, whereas the quality of parent-child relations was most powerful among females. This study presents the variables that should be dealt with in early identification and intervention efforts for students at high risk of dropping out of school. The results imply that it be necessary to customize those early identification and intervention efforts on the basis of students' gender and grade level.