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원문정보

Predicting Model of Students Leaving Their Majors Using Data Mining Technique

임영문, 유창현

피인용수 : 0(자료제공 : 네이버학술정보)

초록

영어

Nowadays most colleges are confronting with a serious problem because many students have left their majors at the colleges. In order to make a countermeasure for reducing major separation rate, many universities are trying to find a proper solution. As a similar endeavor, the objective of this paper Is to find a predicting model of students leaving their majors. The sample for this study was chosen from a university in Kangwon-Do during seven years(2000.3.1 2006. 6.30). In this study, the ratio of training sample versus testing sample among partition data was controlled as 50% : 50% for a validation test of data division. Also, this study provides values about accuracy, sensitivity, specificity about three kinds of algorithms including CHAID, CART and C4.5. In addition, ROC chart and gains chart were used for classification of students leaving their majors. The analysis results were very informative since those enable us to know the most important factors such as semester taking a course, grade on cultural subjects, scholarship, grade on majors, and total completion of courses which can affect students leaving their majors.

목차

Abstract
 1. 서론
 2. 연구내용 및 방법
 3. 분석결과
  3.1 변수선택
  3.2 모델별 결과 비교
  3.3 최적 예측 모형
 4. 결론 및 추후 연구사항
 5. 참고문헌

저자정보

  • 임영문 Leem Young Moon. 강릉대학교 산업공학과 교수
  • 유창현 Ryu Chang Hyun. 강릉대학교 산업공학과 석사과정

참고문헌

자료제공 : 네이버학술정보

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