Year

2025

Season

Spring

Paper Type

Master's Thesis

College

College of Arts and Sciences

Degree Name

Master of Science in Psychological Science (MSPS)

Department

Psychological and Brain Sciences

NACO controlled Corporate Body

University of North Florida. Department of Psychological and Brain Sciences

Committee Chairperson

Dr. Charles Fitzsimmons

Second Advisor

Dr. Sara Davis

Department Chair

Dr. Lori Lange

College Dean

Kaveri Subrahmanyam

Abstract

Metacognitive monitoring, the awareness of one’s own knowledge, is important because it can inform control decisions like help-seeking. The goal of the current study was to examine whether and why math anxiety is related to metacognitive monitoring and control during an arithmetic task. In two studies, we expected judgments to be more accurate (i.e., more aligned with fraction arithmetic performance) when made retrospectively (i.e., after the task) compared to prospectively (i.e., before the task), but that this difference would be smaller among those with higher math anxiety. This prediction was based on the hypothesis that higher math anxiety would be related to more accurate prospective judgments. Overall, adults were underconfident in their fraction arithmetic performance and overconfident in their decimal arithmetic performance, but their judgments were more accurate retrospectively compared to prospectively. Additionally, math anxiety was negatively related to metacognitive bias and this relation may have been a reflection of math self-concept’s relation to monitoring (i.e., suggesting math-anxious adults may reflect on their math self-concept when making monitoring judgments). Consistent with self-regulated learning theories, adults were more likely to request hints when they had lower levels of confidence. Although math-anxious individuals asked for help more often than non-anxious adults in general, they asked for help less frequently when they had low confidence. These findings suggest that math anxiety may hinder people’s ability to accurately predict their performance in some cases and therefore may be related to suboptimal self-regulatory decisions like help seeking.

Available for download on Sunday, April 21, 2030

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