Cited by 174Memory Processes and InfluencesNeural and Behavioral Psychology StudiesVisual perception and processing mechanisms

Domain-general enhancements of metacognitive ability through adaptive training.

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Carpenter, Jason, Sherman, Maxine T., Kievit, Rogier A., Seth, Anil K., Lau, Hakwan, Fleming, Stephen M.·2019·Journal of Experimental Psychology: General

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Abstract

The metacognitive ability to introspect about self-performance varies substantially across individuals. Given that effective monitoring of performance is deemed important for effective behavioral control, intervening to improve metacognition may have widespread benefits, for example in educational and clinical settings. However, it is unknown whether and how metacognition can be systematically improved through training independently of task performance, or whether metacognitive improvements generalize across different task domains. Across 8 sessions, here we provided feedback to two groups of participants in a perceptual discrimination task: an experimental group (n = 29) received feedback on their metacognitive judgments, while an active control group (n = 32) received feedback on their decision performance only. Relative to the control group, adaptive training led to increases in metacognitive calibration (as assessed by Brier scores), which generalized both to untrained stimuli and an untrained task (recognition memory). Leveraging signal detection modeling we found that metacognitive improvements were driven both by changes in metacognitive efficiency (meta-d'/d') and confidence level, and that later increases in metacognitive efficiency were positively mediated by earlier shifts in confidence. Our results reveal a striking malleability of introspection and indicate the potential for a domain-general enhancement of metacognitive abilities. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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  • Delivering feedback to improve confidence calibration over a period of two weeks elevates metacognitive efficiency not only on the trained task but also more broadly.

    “As another example, delivering feedback to improve confidence calibration over a period of two weeks shows promise in elevating metacognitive efficiency not only on the trained task but also more broadly (Carpenter et al. 2019).”

    From Metacognition and Confidence: A Review and Synthesis (2024) · cites this paper as Carpenter et al. 2019

    The Method (Training; Participants) describes eight feedback sessions over 8–34 days, with experimental participants averaging 15.4 days. The Results (Metacognitive Efficiency and Bias) reports improved efficiency on the trained task and transfer to an untrained stimulus, but says evidence for transfer of efficiency across task domains was equivocal. Broader transfer was demonstrated for the composite calibration measure, not clearly for efficiency itself. (LLM, conf=0.90)

    Experimental — accuracy not yet measured
  • Metacognitive interventions, such as training through feedback on metacognitive performance, can increase judgment accuracy.

    “Metacognitive interventions, such as training through feedback on metacognitive performance [30], can, for example, increase judgment accuracy-the ability to distinguish between one's own correct and incorrect metacognitive processing.”

    From The Metacognitive Demands and Opportunities of Generative AI (2024) · cites this paper as [30]

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Research works printed but not linked: 2

  1. Kass R. E., & Raftery A. E. (1995). Bayes factors. Journal of the American Statistical Association, 90, 773– 795.
  2. Rosseel Y. (2012). Lavaan: An R package for structural equation modeling and more. Version 0.5-12 (BETA). Journal of Statistical Software, 48, 1– 36.

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Authors
Carpenter, J., Sherman, M. T., Kievit, R. A., Seth, A. K., Lau, H., & Fleming, S. M.
Affiliations
  • University of California, Los Angeles (US)
  • Wellcome Centre for Human Neuroimaging (GB)
  • University of Sussex (GB)
Corresponding author
Fleming, Stephen M.
Venue
Journal of Experimental Psychology: General
Published
2019-01
Volume
148
Issue
1
Pages
51-64
ISSN
  • 0096-3445 (ISSN-L)
  • 1939-2222
OpenAlex
W2953011441
Cited by
174
References
54
Citations by year
2026: 14 · 2025: 21 · 2024: 21 · 2023: 36 · 2022: 28 · 2021: 24 · 2020: 17 · 2019: 12 · 2018: 1
FWCI
8.04
Type
journal article
Language
en
Open access
Locations
  • Journal of Experimental Psychology General (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Sussex Research Online (University of Sussex) (submittedVersion, cc-by)
  • UCL Discovery (University College London) (submittedVersion)
  • Figshare (submittedVersion, cc-by)
  • Apollo (University of Cambridge) (submittedVersion, cc-by)
  • Apollo (cc-by)
Funders
  • National Institutes of Health (R01NS088628)
  • Wellcome Trust (206648/Z/17/Z)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
Keywords
metacognition, metacognitive calibration, metacognitive training, self-reflection, metacognitive efficiency, confidence, feedback, perceptual discrimination, recognition memory, signal detection theory, Brier score
MeSH terms
Metacognition, Adult, Female, Humans, Male, Middle Aged, Models, Psychological, Practice, Psychological, Task Performance and Analysis, Feedback, Psychological, Young Adult

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