Understanding Temporal Patterns of Metacognitive Monitoring and Control in 5- to 6-Year-Olds: A Latent Class Vector-Autoregression Analysis.
Efficient metacognition relies on a fine-tuned interplay between monitoring and control. However, these temporal dynamics between monitoring and control are still poorly understood, which limits our understanding of why some children succeed and other children struggle with metacognition. We assesse...
| Publicado en: | Developmental Psychology Vol. 62; no. 4; pp. 753 - 765 |
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| Autores principales: | , |
| Formato: | Artículo |
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American Psychological Association
Apr2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=192413304&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 192413304 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00121649 DPS jtl: Developmental Psychology issn: 00121649 maglogo: N pubinfo: dt: Apr2026 vid: 62 iid: 4 pid: 34 pub: American Psychological Association artinfo: ui: 192413304 10.1037/dev0002071 ppf: 753 ppct: 12 formats: tig: atl: Understanding Temporal Patterns of Metacognitive Monitoring and Control in 5- to 6-Year-Olds: A Latent Class Vector-Autoregression Analysis. aug: au: Buehler, Florian Jonas Oeri, Niamh affil: Department of Developmental Psychology, University of Bern su: Education of parents Task performance Executive function Sex distribution Age distribution Child development Child behavior Children Cognitive testing Research funding Cluster analysis (Statistics) Data analysis Scientific observation Kruskal-Wallis Test Time series analysis Structural equation modeling Descriptive statistics Intraclass correlation Statistics Data analysis software sug: subj: Education of parents Task performance Executive function Sex distribution Age distribution Child development Child behavior Children Cognitive testing Research funding Cluster analysis (Statistics) Data analysis Scientific observation Kruskal-Wallis Test Time series analysis Structural equation modeling Descriptive statistics Intraclass correlation Statistics Data analysis software keyword: latent class vector autoregression metacognitive control metacognitive monitoring off-task temporal patterns latent class vector autoregression metacognitive control metacognitive monitoring off-task temporal patterns ab: Efficient metacognition relies on a fine-tuned interplay between monitoring and control. However, these temporal dynamics between monitoring and control are still poorly understood, which limits our understanding of why some children succeed and other children struggle with metacognition. We assessed metacognitive monitoring, control, and off-task behavior in an unsolvable task in which participants built a wooden snake according to a plan. Participants were N = 123 typically developing 5- to 6-year-olds (M = 5.45 years, SD = 0.59, 52% female). We coded monitoring, control, and off-task behavior in 5-s intervals, resulting in a total of 6,150 observations. Based on children's monitoring, control, and off-task behaviors, we ran a latent class vector-autoregression analysis. We identified four latent clusters. The four clusters display distinct behavioral patterns over time, marked by varying levels of monitoring, control, and off-task behaviors. Subsequent analyses showed that younger children showed less stable metacognition than older children. Understanding differences in metacognitive dynamics is particularly important when trying to understand why children have metacognitive difficulties and may have important implications for tailoring interventions to the metacognitive needs of children. Public Significance Statement: The study suggests that the temporal dynamics between metacognitive behaviors can be reliably observed in 5- to 6-year-olds. Based on the behavior children show during a problem-solving task, four different subgroups could be identified. The subgroups differed in the temporal associations of monitoring, control, and off-task behavior. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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