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  • 标题:Contributions from Data Mining to Study Academic Performance of Students of a Tertiary Institute
  • 本地全文:下载
  • 作者:David L. la Red Martínez ; Carlos E. Podestá Gómez
  • 期刊名称:American Journal of Educational Research
  • 印刷版ISSN:2327-6126
  • 电子版ISSN:2327-6150
  • 出版年度:2014
  • 卷号:2
  • 期号:9
  • 页码:713-726
  • DOI:10.12691/education-2-9-3
  • 语种:English
  • 出版社:Science and Education Publishing
  • 摘要:Education-oriented data mining allows to predict determined type of factor or characteristic of a case, phenomenon or situation. In this article the mining models used are described and the main results are discussed. Mining models of clustering, classification and association are considered especially. In all cases seeks to determine patterns of academic success and failure for students, thus predicting the likelihood of dropping them or having poor academic performance, with the advantage of being able to do it early, allowing addressing action to reverse this situation. This work was done in 2013 with information on the years 2009 to 2013, students of the subject Operating Systems tertiary career Superior Technical Analyst (TSAP) Higher Institute of Curuzú Cuatiá (ISCC), Corrientes, Argentina.
  • 关键词: academic performance; data mining; profiling students
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