Using an Intelligent Tutor and Math Fluency Training to Improve Math Performance

نویسندگان

  • Ivon Arroyo
  • James M. Royer
  • Beverly Park Woolf
چکیده

This article integrates research in intelligent tutors with studies of basic student competencies, e.g., problem solving strategies and math fluency (the speed needed to retrieve or calculate answers). It describes the impact of computer software designed to improve either strategic behavior or math fluency. Both competencies are key to improved performance and both help decrease the load on working memory as students mature from using physical representations (e.g., counting with fingers) to using cognitive representations. This research evaluated software interventions to improve strategies and fluency and tested their relative magnitude on math post-tutor performance. We discovered that both interventions combined impact math performance and suggest that training in both provide an advantage due to more available memory capacity. Mathematics fluency has an impact on students’ cognitive resources that are needed for more difficult (computationally intensive) problems. We suggest that intelligent tutors can be enhanced with math fluidity training activities that help students to make calculations automatically with minimal memory load.

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عنوان ژورنال:
  • I. J. Artificial Intelligence in Education

دوره 21  شماره 

صفحات  -

تاریخ انتشار 2011