Session Details

Kelly Wahl

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(CAIR Best Presentation) Data Mining to Identify Grading Practices

  • Date:Wednesday, May 31
  • Time:2:30 PM - 3:15 PM
  • Room:Mint
  • Session Type:Affiliated Organization Best Presentation
  • Program Book Abstract:To enhance student success and to build inclusive classrooms, researchers have used technical tools and expertise to yield insight into problems many undergraduate students experience in higher education. A collaborative research effort explored how k-means cluster analysis can reveal contrasting patterns in the distribution of letter grades among large course offerings. Consistent with previous studies, our findings showed that norm-referenced grading practices exacerbate an existing achievement gap, while a criterion-referenced grading approach enhances student learning and overall success in school. This session will provide a hands-on opportunity for attendees to learn statistical techniques using SPSS, with datasets and syntax available during the session for data mining skills development.