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August 5, 2026Journal of IntelligenceOpen Access

Explaining Individual Differences in Metacognitive Monitoring: A Multilevel Analysis of Person-Level Predictors Across Academic Assessments

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Authors

JCJinjushang ChenBeijing Normal UniversityQZQian ZhangSpencer FoundationYYYue YinShenyang Medical College

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Implication

Multilevel analysis reveals how learning attributes predict metacognitive monitoring in sixth-grade students, suggesting important implications for education.

Key Points

  • This study aims to explore how learning-related attributes influence metacognitive monitoring in students.
  • Conducted multilevel analyses with data from 3946 Chinese sixth-grade students.
  • Students provided performance estimates and completed questionnaires on learning attributes.
  • Examined cognitive and demographic variables alongside learning attributes as predictors.
  • General confidence was significantly predicted by learning-related attributes, improving marginal R2.
  • Resolution had a weaker association with learning attributes compared to general confidence.
  • Findings suggest a separation between cognitive ability and certain non-cognitive learning attributes.

Cite This Study

Chen et al. (2026) studied this question.

synapsesocial.com/papers/6a72e85b226790f370658316https://doi.org/10.3390/jintelligence14080178
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Also Consider

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  1. 1Self-evaluation of decision-making: A general Bayesian framework for metacognitive computation.2016 · 639 citations
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  3. 3A better lemon squeezer? Maximum-likelihood regression with beta-distributed dependent variables.2006 · 1,836 citations