Designing an undergraduate data mining course by matching teaching strategies with student learning styles

  • Authors:
  • Ping Chen;Irene Chen;Rakesh Verma

  • Affiliations:
  • University of Houston-Downtown;University of Houston-Downtown;University of Houston

  • Venue:
  • Journal of Computing Sciences in Colleges
  • Year:
  • 2011

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Abstract

Regularly integrating emerging technology to keep the curriculum up to date is generally expected in the rapidly evolving discipline of Computer Science. Due to the explosion of data and information data mining has become a core area in undergraduate computer science curriculum. In this paper, we discuss our experience to design, teach, and improve an undergraduate data mining course by adopting the results of an Index of Learning Styles survey to assess student learning style. Based on the survey results, course instructor fine-tuned the organization and presentation of course materials and activities accordingly. Course evaluation clearly showed effectiveness of our approach.