Calibrating Mathematics Vocabulary Self-Efficacy: Domain-Specific Accuracy by Mathematics-Difficulty Risk Status

Abstract

Knowledge of mathematics vocabulary is important for conceptual understanding, yet little is known about how students’ vocabulary self-efficacy corresponds to their performance or how accurately they judge their competence. This study examined relations between mathematics vocabulary self-efficacy (MVSE) and mathematics vocabulary performance (MVP) across four categories and compared calibration between students at risk for mathematics difficulties (MD) and their typically developing (TD) peers. Participants were 124 fifth-grade students. Structural equation modeling showed that each MVSE dimension was most strongly associated with its corresponding MVP domain; however, technical MVSE was also related to other domains. TD students often underestimated their competence in technical and symbolic vocabulary, whereas students at risk for MD more often overestimated their competence in subtechnical, symbolic, and general vocabulary. Calibration varied by vocabulary category and group.