Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Inflow and outflow analysis of double majors using social network analysis

사회 연결망 분석을 이용한 복수전공 유입 및 유출 분석

  • Cho, Jang-Sik (Department of Informational Statistics, Kyungsung University)
  • 조장식 (경성대학교 정보통계학과)
  • Received : 2012.05.30
  • Accepted : 2012.07.02
  • Published : 2012.07.31
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Abstract

Recently, the number of students who get double majors has tended to increase in many universities. As results, many problems occur because immoderate inflow of double-major students is concentrated in a specific popular department. In this paper, we study the characteristic of inflow and outflow of double majors using social network analysis and decision tree analysis. According to the results, SAT score affected the inflow of double majors the most. Additionally, department category, course evaluation score, employment rate also affected the inflow of double majors in the order named. On the other hand, department category affected the outflow of double majors the most. Additionally, SAT score, employment rate, course evaluation score also affected the outflow of double majors in the order named.

각 대학마다 복수전공에 대한 선택의 폭이 넓어짐에 따라 학과별 복수전공자의 유입과 유출에 심한 편중현상이 나타나고 있다. 이런 현상의 결과로 특정 학과에서는 과도한 복수전공자의 유입(유출)으로 여러 가지 문제가 발생하고 있다. 따라서 본 논문에서는 사회연결망 분석과 의사결정나무 분석을 이용하여 학과별 복수전공자들의 유입과 유출에 대한 특성을 분석하였다. 분석방법으로 데이터 마이닝의 한 기법인 의사결정나무 모형을 활용하였으며, 분석결과에 대한 적절한 함의를 찾기 위해서 이지분리를 하는 CART 알고리즘을 사용하였다. 분석결과에 따르면, 복수전공 유입에 영향을 미치는 특성으로는 학과별 수능성적이 가장 많은 영향을 미치며, 그 다음으로 계열, 강의평가점수, 취업률의 순서로 나타났다. 한편 복수전공 유출에 영향을 미치는 특성으로는 계열이 가장 많은 영향을 미치며, 그 다음으로 수능성적, 취업률, 강의평가점수의 순서로 나타났다.

Keywords

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