본 연구는 데이터마이닝 통계적 절차를 사용하여 대학생의 학교생활적응 모형을 예측하였다. 본 연구의 대상은 전국의 4년제 대학 12개교 1,380명이다. 대학생의 대학생활적응을 가장 잘 분류하는 변인은 자아정체감이다. 자아정체감의 수준에 따라서 대학생활적응에 영향을 미치는 변인들이 다름을 알 수 있었다. 자아정체감이 낮은 경우에는 사회적 지지와 친구교제가 중요하고, 자아정체감이 높은 경우에는 타인이해 및 가족지지가 중요한 예측 변인으로 작용하고 있었다. 인문계 출신 대학생은 자아정체감, 사회적지지, 친구교제, 학교시설이용, 대화의 정도 등이 중요한 변인으로 작용하였으며, 실업계 출신 대학생의 경우에는 교수지지, 컴퓨터 활용 시간, 모직업, 아르바이트 등이 예측변인으로 작용하고 있었다.

This paper studies the model of university students' adaptation to school life by data-mining analysis. The subjects of this research are 1,380 students of 12 universities in Korea. The most predictable variable in university students' adaption to school life is ego-identity. If the score of ego-identity is low, social support and friend support are more important than the other variables. If the score of ego-identity is high, other people's understanding and family support are more important. For the students who graduated from academic high schools, more predictable variables are ego-identity, social support, friend support, school equipment and level of conversation. For the students who graduated from vocational high schools, more predictable variables are professor support, time of using computer, mother-occupation and the kind of part-time job.

This paper studies the model of university students' adaptation to school life by data-mining analysis. The subjects of this research are 1,380 students of 12 universities in Korea. The most predictable variable in university students' adaption to school life is ego-identity. If the score of ego-identity is low, social support and friend support are more important than the other variables. If the score of ego-identity is high, other people's understanding and family support are more important. For the students who graduated from academic high schools, more predictable variables are ego-identity, social support, friend support, school equipment and level of conversation. For the students who graduated from vocational high schools, more predictable variables are professor support, time of using computer, mother-occupation and the kind of part-time job.

data mining, university students, school life adaptation