본문 바로가기
  • Home

Development of the Drop-outs Prediction Model for Intelligent Drop-outs Prevention System

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2017, 22(10), pp.9-17
  • DOI : 10.9708/jksci.2017.22.10.009
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : September 22, 2017
  • Accepted : October 19, 2017
  • Published : October 31, 2017

Mi-Young Song 1

1수원여자대학교

Accredited

ABSTRACT

The student dropout prediction is an indispensable for many intelligent systems to measure the educational system and success rate of all university. Therefore, in this paper, we propose an intelligent dropout prediction system that minimizes the situation by adopting the proactive process through an effective model that predicts the students who are at risk of dropout. In this paper, the main data sets for students dropout predictions was used as questionnaires and university information. The questionnaire was constructed based on theoretical and empirical grounds about factor affecting student’s performance and causes of dropout. University Information included student grade, interviews, attendance in university life. Through these data sets, the proposed dropout prediction model techniques was classified into the risk group and the normal group using statistical methods and Naive Bays algorithm. And the intelligence dropout prediction system was constructed by applying the proposed dropout prediction model. We expect the proposed study would be used effectively to reduce the students dropout in university.

Citation status

* References for papers published after 2022 are currently being built.