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Leveraging cognitive theory to create large-scale learning tools
22nd Annual Conference on Research in Undergraduate Mathematics Education (2019)
  • Darryl Chamberlain, Jr., University of Florida
  • Russell Jeter, Emory University
Abstract
At the 21st Annual Conference on Research in Undergraduate Mathematics Education, Ed Dubinsky highlighted the disparity between what the research community knows and what is actually used by practicing instructors. One of the heaviest burdens on instructors is the continual assessment of student understanding as it develops. This theoretical paper proposes to address this practical issue by describing how to dynamically construct multiple-choice items that assess student knowledge as it progresses throughout a course. By utilizing Automated Item Generation in conjunction with already-published results or any theoretical foundation that describes how students may develop understanding of a concept, the research community can develop and disseminate theoretically grounded and easy-to-use assessments that can track student understanding over the course of a
semester.
Keywords
  • Assessment,
  • Automated Item Generation,
  • Technology in Mathematics Education
Publication Date
February 28, 2019
Citation Information
Darryl Chamberlain and Russell Jeter. "Leveraging cognitive theory to create large-scale learning tools" 22nd Annual Conference on Research in Undergraduate Mathematics Education (2019)
Available at: http://works.bepress.com/darryl-chamberlain/11/