A New Approach Examining Math Anxiety: Task Difficulty and Facial Feedback

• In Event: Millennium Hotel Roundtable Session 17
  In Roundtable Session: Emotions and Attitudes in Mathematics

Abstract

Math anxiety increases physiological arousal and negatively affects students’ ability to complete mathematical problems. The aim of the present study was to use automated facial recognition technology to examine the relationship between task difficulty and students’ real-time math anxiety. Results from this study indicated that significant differences in emotional expressions of anger, confusion and frustration occur as a function of increasing task difficulty. Analysis of items that were rated high on task difficulty demonstrated that increases in these three emotions significantly correlate with increases in self-reported anxiety. The findings of this study contribute preliminary evidence to inform the use of facial recognition technology to identify the real-time emotions present in math-anxious learners.

Authors

• Matthew Moreno, University of Toronto

• Stephanie Buono, University of Toronto

• Zhenhua Xu, University of Toronto

• Earl Woodruff, OISE/University of Toronto

• Rose Schnabel, University of Toronto