What Gaze Data Reveal About Coordinating Multiple Mathematical Representations

Theodore Wills, Thomas F. Shipley, Briana L. Chang, Jennifer G. Cromley, Julie L. Booth

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

40 High school students were given a battery of paper and pencil tests, which collectively assessed a variety of spatial abilities, graph and table competencies, conceptual mastery of calculus, and achievement in common topics from typical precalculus and calculus courses. In addition, students completed a computer-presented measure of Coordinating Multiple Representations (CMR), in which they had to assess whether two mathematical representations (e.g. an equation and a graph) depicted the same underlying mathematical function. Gaze data were captured during this measure, using a Tobii T60 eye tracker. Findings suggest that good or poor performance on several paper measures is associated with distinct and specific gaze behaviors. Better achievement scores are associated with fewer fixations near the centerline of the graph, and with fewer point-plotting and function scanning behaviors. These findings are discussed in terms of differing approaches or strategies for engaging in CMR.

Original languageEnglish (US)
Title of host publicationProceedings of the 36th Annual Meeting of the Cognitive Science Society, CogSci 2014
PublisherThe Cognitive Science Society
Pages3113-3118
Number of pages6
ISBN (Electronic)9780991196708
StatePublished - 2014
Externally publishedYes
Event36th Annual Meeting of the Cognitive Science Society, CogSci 2014 - Quebec City, Canada
Duration: Jul 23 2014Jul 26 2014

Publication series

NameProceedings of the 36th Annual Meeting of the Cognitive Science Society, CogSci 2014

Conference

Conference36th Annual Meeting of the Cognitive Science Society, CogSci 2014
Country/TerritoryCanada
CityQuebec City
Period7/23/147/26/14

Keywords

  • coordinating multiple representations, graphs
  • Eye tracking

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Cognitive Neuroscience

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