首页    期刊浏览 2025年07月26日 星期六
登录注册

文章基本信息

  • 标题:Using Data Mining Techniques in Building a Model to Determine the Factors Affecting Academic Data for Undergraduate Students
  • 本地全文:下载
  • 作者:Faisal Mohammed Nafie ; Abdelmoneim Ali Mohamed Hamed
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2021
  • 卷号:21
  • 期号:4
  • 页码:306-312
  • DOI:10.22937/IJCSNS.2021.21.4.38
  • 出版社:International Journal of Computer Science and Network Security
  • 摘要:The main goal of higher education institutions is to present a high level of quality education to its students. This study uses data mining techniques to extract educational data from cumulative databases and used them to make the right decisions. This paper also aims to find the factors affecting students' academic performance in Majmaah University, KSA, during 2010 - 2017 period. The study utilized a sample of 6,158 students enrolled from two colleges, males and females. The results showed a high percentage of stumbling and dismissed between graduate and regular students where more than 62.5% failed to follow the plan. Only 2% of students scored distinction during their study of all graduated since their grade point average, secondary level, was statistically significant, where p<0.05. Dismissed percentage was higher among males. These results promoted some recommendations in which decision-makers could take them in considerations for better improvement of academic achievements: including of specialized programs to follow-up in regards to stumbling and failure. Utilization of different communication tools are needed to activate academic advisory for dismiss and dropout evaluation.
  • 关键词:Academic performance; Data Mining; Higher education; Academic advising; Decision-making.
国家哲学社会科学文献中心版权所有