ArticleJournal of Intelligence2026
Exploring Latent Profiles of Metacognition and Their Impact on Computational Thinking and Mathematical Modeling Competency in High School Students.
Article in Journal of Intelligence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
As the capacity to monitor and regulate one's own cognitive processes, metacognition is considered pivotal for mathematics learning and the development of higher-order thinking skills. However, research from a person-centered perspective remains limited regarding individual differences in metacognition and their associations with mathematics-related abilities. To address this gap, the present study surveyed 512 high school students and employed Latent Profile Analysis (LPA) to identify three distinct metacognitive profiles: "High metacognition," "Medium metacognition," and "Low metacognition," accounting for 17.96%, 53.52%, and 28.52% of the sample, respectively. The BCH method revealed significant between-profile differences in computational thinking and mathematical modeling competency, with the "High metacognition" group demonstrating the strongest performance. Mediation analysis indicated that computational thinking partially mediated the relationship between metacognitive profiles and mathematical modeling competency, with the effect being most pronounced in the "High metacognition" group. These findings suggest substantial heterogeneity in students' metacognition and highlight the potential relevance of prioritizing metacognitive cultivation in mathematics education. They further suggest that fostering computational thinking may be a productive route to strengthening mathematical modeling competency.
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