Performance feedback triggers liberal detection and perceptual confidence biases in early childhood: Implications for metacognitive training.
Saved in:
| Title: | Performance feedback triggers liberal detection and perceptual confidence biases in early childhood: Implications for metacognitive training. |
|---|---|
| Authors: | Soto D; Basque Center on Cognition, Brain and Language, 69, 2nd Floor 20009, San Sebastian, Spain. d.soto@bcbl.eu.; Ikerbasque, Basque Foundation for Science, Bilbao, Spain. d.soto@bcbl.eu., Lallier M; Basque Center on Cognition, Brain and Language, 69, 2nd Floor 20009, San Sebastian, Spain.; Ikerbasque, Basque Foundation for Science, Bilbao, Spain., Desender K; Brain and Cognition, KU Leuven, Leuven, Belgium., Elosegi P; Basque Center on Cognition, Brain and Language, 69, 2nd Floor 20009, San Sebastian, Spain.; University of the Basque Country, San Sebastian, Spain. |
| Source: | Psychonomic bulletin & review [Psychon Bull Rev] 2025 Dec; Vol. 32 (6), pp. 2913-2925. Date of Electronic Publication: 2025 Jun 24. |
| Publication Type: | Journal Article |
| Language: | English |
| Journal Info: | Publisher: Springer] Country of Publication: United States NLM ID: 9502924 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1531-5320 (Electronic) Linking ISSN: 10699384 NLM ISO Abbreviation: Psychon Bull Rev Subsets: MEDLINE |
| Imprint Name(s): | Publication: <2013-> : [New York : Springer] Original Publication: Austin, TX : Psychonomic Society, Inc., c1994- |
| MeSH Terms: | Metacognition*/physiology , Judgment*/physiology , Feedback, Psychological*/physiology , Child Development*/physiology, Humans ; Child ; Male ; Female ; Learning/physiology |
| Abstract: | Competing Interests: Declarations. Conflicts of interest/Competing interests: None. Ethics approval: Ethics approval for the study was granted by the BCBL Ethics Board. Consent to participate: Participant consent was obtained from parents and children following informed consent. Consent for publication: All authors agreed on the final version of the manuscript prior to publication. Metacognition allows us to monitor our own mental processes and the quality of our decisions in order to promote adaptive behavior and learning across different domains. Despite its potential, the role of metacognition in children - who often exhibit confidence biases that hinder learning - has yet to be systematically evaluated. This study aimed to improve confidence judgments in 7-year-old children by means of performance feedback. Two groups of children performed a multi-letter array recognition task: one group received feedback during the task whereas the other group did not (N = 24 each, 832 trials per participant). Both groups of participants were matched on their reading performance and non-verbal IQ. Surprisingly, feedback led to more liberal detection criteria in the letter task, faster choice latencies, and increased confidence biases. Simulations from a drift-diffusion model showed that the confidence increase in the feedback group was best explained by a decrease in response latencies, originating from a reduction in non-decision time. Thus, providing children with performance feedback may speed up their responses, which in turn boosts their feeling of confidence. This study underscores the complexity of using performance feedback to enhance metacognitive monitoring in children. We highlight the need for nuanced protocols to train metacognition that bypass the influence of children's inherent confidence biases and discuss potential research directions in this regard. (© 2025. The Psychonomic Society, Inc.) |
| References: | Baer, C., & Odic, D. (2020). Children flexibly compare their confidence within and across perceptual domains. Developmental Psychology, 56(11), 2095. (PMID: 3291505010.1037/dev0001100) Baer, C., Gill, I. K., & Odic, D. (2018). A domain-general sense of confidence in children. Open Mind, 2(2), 86–96. (PMID: 10.1162/opmi_a_00020) Balcazar, F., Hopkins, B. L., & Suarez, Y. (1985). A critical, objective review of performance feedback. Journal of Organizational Behavior Management, 7(3–4), 65–89. (PMID: 10.1300/J075v07n03_05) Benson, P. G., & Önkal, D. (1992). The effects of feedback and training on the performance of probability forecasters. International Journal of Forecasting, 8(4), 559–573. (PMID: 10.1016/0169-2070(92)90066-I) Bosse, M. L., & Valdois, S. (2009). Influence of the visual attention span on child reading performance: A cross-sectional study. Journal of Research in Reading, 32(2), 230–253. (PMID: 10.1111/j.1467-9817.2008.01387.x) Bosse, M. L., Tainturier, M. J., & Valdois, S. (2007). Developmental dyslexia: The visual attention span deficit hypothesis. Cognition, 104(2), 198–230. (PMID: 1685966710.1016/j.cognition.2006.05.009) Buehler, F. J., Ghetti, S., & Roebers, C. M. (2023). training primary school children’s uncertainty monitoring. OSF Preprints. https://doi.org/10.31219/osf.io/yw476. Carpenter, J., Sherman, M. T., Kievit, R. A., Seth, A. K., Lau, H., & Fleming, S. M. (2019). Domain-general enhancements of metacognitive ability through adaptive training. Journal of Experimental Psychology: General, 148(1), 51. Cuetos Vega, F., Rodríguez, B., & Ruano Hernández, E. (1996). PROLEC: Batería de evaluación de los procesos lectores de los niños de educación primaria. T.E.A. Desoete, A., Roeyers, H., & De Clercq, A. (2003). Can offline metacognition enhance mathematical problem solving? Journal of Educational Psychology, 95(1), 188–200. (PMID: 10.1037/0022-0663.95.1.188) Destan, N., & Roebers, C. M. (2015). What are the metacognitive costs of young children’s overconfidence? Metacognition and Learning, 10, 347–374. (PMID: 10.1007/s11409-014-9133-z) Dunlosky, J., & Rawson, K. A. (2012). Overconfidence produces underachievement: Inaccurate self-evaluations undermine students’ learning and retention. Learning and Instruction, 22(4), 271–280. (PMID: 10.1016/j.learninstruc.2011.08.003) Elosegi, P., Rahnev, D., & Soto, D. (2024). Think twice: Re-assessing confidence improves visual metacognition. Attention, Perception, & Psychophysics, 86(2), 373–380. (PMID: 10.3758/s13414-023-02823-0) Escarti, A., & Guzman, J. F. (1999). Effects of feedback on self-efficacy, performance, and choice in an athletic task. Journal of Applied Sport Psychology, 11(1), 83–96. (PMID: 10.1080/10413209908402952) Finn, B., & Metcalfe, J. (2014). Overconfidence in children’s multi-trial judgments of learning. Learning and Instruction, 32, 1–9. (PMID: 10.1016/j.learninstruc.2014.01.001) Fleur, D. S., Bredeweg, B., & van den Bos, W. (2021). Metacognition: Ideas and insights from neuro-and educational sciences. npj Science of Learning, 6(1), 13. Gelman, A., & Rubin, D. B. (1992). Inference from iterative simulation using multiple sequences. Statistical Science, 7(4), 457–472. https://doi.org/10.1214/ss/1177011136 . Publisher: Institute of Mathematical Statistics. (PMID: 10.1214/ss/1177011136) Geurten, M., & Meulemans, T. (2017). The effect of feedback on children’s metacognitive judgments: A heuristic account. Journal of Cognitive Psychology, 29(2), 184–201. (PMID: 10.1080/20445911.2016.1229669) Ghetti, S., & Alexander, K. W. (2004). “If it happened, I would remember it”: Strategic use of event memorability in the rejection of false autobiographical events. Child Development, 75(2), 542–561. (PMID: 1505620510.1111/j.1467-8624.2004.00692.x) Guggenmos, M., Wilbertz, G., Hebart, M. N., & Sterzer, P. (2016). Mesolimbic confidence signals guide perceptual learning in the absence of external feedback. Elife, 5, e13388. Haddara, N., & Rahnev, D. (2022). The impact of feedback on perceptual decision-making and metacognition: Reduction in bias but no change in sensitivity. Psychological Science, 33(2), 259–275. (PMID: 35100069909646010.1177/09567976211032887) Hainguerlot, M., Vergnaud, J.-C., & de Gardelle, V. (2018). Metacognitive ability predicts learning cue-stimulus associations in the absence of external feedback. Scientific Reports, 8(1), 5602. (PMID: 29618809588481410.1038/s41598-018-23936-9) Herregods, S., Le Denmat, P., & Desender, K. (2023). Modelling speed-accuracy tradeoffs in the stopping rule for confidence judgments. bioRxiv. https://doi.org/10.1101/2023.02.27.530208. Kang, E., & Han, Z. (2015). The efficacy of written corrective feedback in improving L2 written accuracy: A meta-analysis. The Modern Language Journal, 99(1), 1–18. (PMID: 10.1111/modl.12189) Kaufman, A. S. (1990). Kaufman brief intelligence test: KBIT. AGS, American Guidance Service. Kiani, R., & Shadlen, M. N. (2009). Representation of confidence associated with a decision by neurons in the parietal cortex. Science, 324(5928), 759–764. Kiani, R., Corthell, L., & Shadlen, M. N. (2014). Choice certainty is informed by both evidence and decision time. Neuron, 84(6), 1329–1342. (PMID: 25521381427119110.1016/j.neuron.2014.12.015) Kluger, A. N., & DeNisi, A. (1996). The effects of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback intervention theory. Psychological Bulletin, 119(2), 254. (PMID: 10.1037/0033-2909.119.2.254) Kruschke, J. (2014). Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan (2nd ed.). Academic Press/Elsevier. Kuhn, D. (2000). Metacognitive Development. Current Directions in Psychological Science, 9(5), 178–181. (PMID: 10.1111/1467-8721.00088) Liu, T., Wang, D., Wang, C., Xiao, T., & Shi, J. (2022). The influence of reward anticipation on conflict control in children and adolescents: Evidence from hierarchical drift-diffusion model and event-related potentials. Developmental Cognitive Neuroscience, 55, 101118. (PMID: 35653919916369910.1016/j.dcn.2022.101118) Luo, T., & Liu, C. (2023). The impact of feedback on metacognition: Enhancing in easy tasks, impeding in difficult ones. Consciousness and Cognition, 116, 103601. (PMID: 3795100710.1016/j.concog.2023.103601) Lyons, K. E., & Ghetti, S. (2011). The development of uncertainty monitoring in early childhood. Child Development, 82(6), 1778–1787. (PMID: 2195487110.1111/j.1467-8624.2011.01649.x) Mamassian, P. (2020). Confidence forced-choice and other metaperceptual tasks. Perception, 49(6), 616–635. (PMID: 3255248810.1177/0301006620928010) Maniscalco, B., & Lau, H. (2012). A signal detection theoretic approach for estimating metacognitive sensitivity from confidence ratings. Consciousness and Cognition, 21(1), 422–430. (PMID: 2207126910.1016/j.concog.2011.09.021) Manning, C., Wagenmakers, E. J., Norcia, A. M., Scerif, G., & Boehm, U. (2021). Perceptual decision-making in children: Age-related differences and EEG correlates. Computational Brain & Behavior, 4, 53–69. (PMID: 10.1007/s42113-020-00087-7) Miller, T. M., & Geraci, L. (2011). Training metacognition in the classroom: The influence of incentives and feedback on exam predictions. Metacognition and Learning, 6, 303–314. (PMID: 10.1007/s11409-011-9083-7) Moritz, S., & Woodward, T. S. (2007). Metacognitive training in schizophrenia: From basic research to knowledge translation and intervention. Current Opinion in Psychiatry, 20(6), 619–625. (PMID: 1792176610.1097/YCO.0b013e3282f0b8ed) Nelson, T. O., & Narens, L. (1990). Metamemory: A theoretical framework and new findings. In G. H. Bower (Ed.), The psychology of learning and motivation (Vol. 26, pp. 125–133). Ratcliff, R., & McKoon, G. (2008). The diffusion decision model: Theory and data for two-choice decision tasks. Neural Computation, 20(4), 873–922. (PMID: 18085991247474210.1162/neco.2008.12-06-420) Ratcliff, R., & Starns, J. J. (2009). Modeling confidence and response time in recognition memory. Psychological Review, 116(1), 59. (PMID: 19159148269389910.1037/a0014086) Roebers, C. M., Schmid, C., & Roderer, T. (2009). Metacognitive monitoring and control processes involved in primary school children’s test performance. The British Journal of Educational Psychology, 79(Pt 4), 749–767. (PMID: 1934153210.1348/978185409X429842) Rouault, M., Dayan, P., & Fleming, S. M. (2019). Forming global estimates of self-performance from local confidence. Nature Communications, 10(1), 1141. (PMID: 30850612640849610.1038/s41467-019-09075-3) Rouy, M., de Gardelle, V., Reyes, G., Sackur, J., Vergnaud, J. C., Filevich, E., & Faivre, N. (2022). Metacognitive improvement: Disentangling adaptive training from experimental confounds. Journal of Experimental Psychology: General, 151(9), 2083. (PMID: 3515748110.1037/xge0001185) Schoenfeld, A. H. (2016). Learning to think mathematically: Problem solving, metacognition, and sense making in mathematics (reprint). Journal of Education, 196(2), 1–38. (PMID: 10.1177/002205741619600202) Stone, E. R., & Opel, R. B. (2000). Training to improve calibration and discrimination: The effects of performance and environmental feedback. Organizational Behavior and Human Decision Processes, 83(2), 282–309. (PMID: 1105607210.1006/obhd.2000.2910) Taouki, I., Lallier, M., & Soto, D. (2022). The role of metacognition in monitoring performance and regulating learning in early readers. Metacognition and Learning, 17(3), 921–948. (PMID: 10.1007/s11409-022-09292-0) van Den Berg, R., Anandalingam, K., Zylberberg, A., Kiani, R., Shadlen, M. N., & Wolpert, D. M. (2016). A common mechanism underlies changes of mind about decisions and confidence. Elife, 5, e12192. (PMID: 26829590479897110.7554/eLife.12192) Van Loon, M. H., & Roebers, C. M. (2020). Using feedback to improve monitoring judgment accuracy in kindergarten children. Early Childhood Research Quarterly, 53, 301–313. (PMID: 10.1016/j.ecresq.2020.05.007) Van Marcke, H., Denmat, P. L., Verguts, T., & Desender, K. (2024). Manipulating prior beliefs causally induces under-and overconfidence. Psychological Science, 35(4), 358–375. (PMID: 3842731910.1177/09567976241231572) Veenman, M. V., Kok, R., & Blöte, A. W. (2005). The relation between intellectual and metacognitive skills in early adolescence. Instructional Science, 33, 193–211. (PMID: 10.1007/s11251-004-2274-8) Wiecki, T. V., Sofer, I., & Frank, M. J. (2013). HDDM: Hierarchical Bayesian estimation of the drift-diffusion model in Python. Frontiers in Neuroinformatics, 7, 55610. (PMID: 10.3389/fninf.2013.00014) Zylberberg, A., Fetsch, C. R., & Shadlen, M. N. (2016). The influence of evidence volatility on choice, reaction time and confidence in a perceptual decision. Elife, 5, e17688. |
| Grant Information: | Severo Ochoa CEX2020-001010-S Agencia Estatal de Investigación |
| Contributed Indexing: | Keywords: Confidence; Feedback; Metacognition; Perception |
| Entry Date(s): | Date Created: 20250624 Date Completed: 20251118 Latest Revision: 20251118 |
| Update Code: | 20251118 |
| DOI: | 10.3758/s13423-025-02720-7 |
| PMID: | 40555904 |
| Database: | MEDLINE |
| Abstract: | Competing Interests: Declarations. Conflicts of interest/Competing interests: None. Ethics approval: Ethics approval for the study was granted by the BCBL Ethics Board. Consent to participate: Participant consent was obtained from parents and children following informed consent. Consent for publication: All authors agreed on the final version of the manuscript prior to publication.<br />Metacognition allows us to monitor our own mental processes and the quality of our decisions in order to promote adaptive behavior and learning across different domains. Despite its potential, the role of metacognition in children - who often exhibit confidence biases that hinder learning - has yet to be systematically evaluated. This study aimed to improve confidence judgments in 7-year-old children by means of performance feedback. Two groups of children performed a multi-letter array recognition task: one group received feedback during the task whereas the other group did not (N = 24 each, 832 trials per participant). Both groups of participants were matched on their reading performance and non-verbal IQ. Surprisingly, feedback led to more liberal detection criteria in the letter task, faster choice latencies, and increased confidence biases. Simulations from a drift-diffusion model showed that the confidence increase in the feedback group was best explained by a decrease in response latencies, originating from a reduction in non-decision time. Thus, providing children with performance feedback may speed up their responses, which in turn boosts their feeling of confidence. This study underscores the complexity of using performance feedback to enhance metacognitive monitoring in children. We highlight the need for nuanced protocols to train metacognition that bypass the influence of children's inherent confidence biases and discuss potential research directions in this regard.<br /> (© 2025. The Psychonomic Society, Inc.) |
|---|---|
| ISSN: | 1531-5320 |
| DOI: | 10.3758/s13423-025-02720-7 |
Full Text Finder
Nájsť tento článok vo Web of Science