Examining the Relationship between Math Anxiety, Effort, and Learning Outcomes Using Latent Class Analysis

Math anxiety has been found to negatively correlate with math achievement, affecting students’ choices to take fewer math classes and avoid math educational opportunities. Educational technology tools can ameliorate some of the negative effects of math anxiety. We examined students’ math anxiety, effort in an educational technology platform, and their relationship with students’ math achievement. Multilevel latent class analysis was used to identify student profiles of math anxiety. Regression analysis was used to examine how students of different profiles interacted with MathSpring, an adaptive intelligent tutor that provides affective supports to students during math problem-solving. The student's math achievement was measured by a standardized test. Our analysis indicated heterogeneity in math anxiety, and students could fall into one of three groups: Highly Anxious, Performance Anxious, and Calm. Highly Anxious students tended to give up more often when solving questions in MathSpring and had the lowest math achievement outcomes. For these students, using hints to solve problems in MathSpring was significantly associated with increased math outcomes. These findings have implications for the field's understanding of how students of different math anxiety profiles can demonstrate varying efforts in math educational technology platforms, and different math learning outcomes.