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  • 标题:Clustering students into groups according to their learning style
  • 本地全文:下载
  • 作者:Irene Pasina ; Goze Bayram ; Wafa Labib
  • 期刊名称:MethodsX
  • 印刷版ISSN:2215-0161
  • 电子版ISSN:2215-0161
  • 出版年度:2019
  • 卷号:6
  • 页码:2189-2197
  • DOI:10.1016/j.mex.2019.09.026
  • 语种:English
  • 出版社:Elsevier
  • 摘要:Graphical abstractDisplay OmittedAbstractThis method article aims to use group technology to classify engineering students at classroom level into clusters according to their learning style preferences. The Felder and Silverman’s Index Learning Style (ILS) was used to evaluate students’ learning style preferences. Students were then grouped into clusters based on the similarities of their learning styles preferences by using clustering algorithms, such as complete clustering.•Prior research on Learning Styles preferences in engineering education is limited in Saudi Arabia.•Students’ learning style preferences allows instructors to adopt suitable teaching approach. Students having same learning styles can work together in group assignments.•Grouping students into clusters, we find that outlier students who having different learning styles than the rest may allow instructors to deal with them accordingly.
  • 关键词:Learning style;Group technology;Felder and Silverman;Teaching style
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