The advent of COVID-19 highlighted widespread misconceptions regarding people’s accuracy in interpreting quantitative health information. How do people judge whether they accurately answered health-related math problems? Which individual differences predict these item-by-item metacognitive monitoring judgments? How does a brief intervention targeting math skills—which increased problem-solving accuracy—affect people’s monitoring judgments? We investigated these pre-registered questions in a secondary analysis of data from a large Qualtrics panel of adults (N = 1,297). Pretest performance accuracy, math self-efficacy, gender, and math anxiety were associated with pretest item-level monitoring judgments. Participants randomly assigned to the intervention condition, relative to the control condition, made higher monitoring judgments post intervention. That is, these participants believed they were more accurate when answering problems. Regardless of experimental condition, those who actually were correct on health-related math problems made higher monitoring judgments than those who answered incorrectly. Finally, consistent with prior research, math anxiety explained additional variance in monitoring judgments beyond trait anxiety. Together, findings indicated the importance of considering both objective (e.g., problem accuracy) and subjective factors (e.g., math self-efficacy, math anxiety) to better understand adults’ metacognitive monitoring.
|Number of pages||35|
|Journal||Metacognition and Learning|
|State||Published - Dec 2022|
Bibliographical noteFunding Information:
This research was supported in part by the U.S. Department of Education Institute of Education Sciences Grants R305A160295 and R305U200004 to C. A. Thompson at Kent State University.
© 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
- Math anxiety
- Math cognition
- Math self-efficacy
- Monitoring judgments
ASJC Scopus subject areas