Real-time cognitive-affective dynamics of failure feedback in a technology-based learning task.

As technology-based learning environments increasingly employ automated feedback, understanding how learners process feedback in real time is essential. This study examined how automated cognitive and metacognitive failure feedback delivered by a humanoid robot affected performance and how effects w...

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Detalles Bibliográficos
Publicado en:Communications Psychology Vol. 4; no. 1; pp. 1 - 15
Autores principales: Ackermann, Helene, Lange, Anna L., Dumont, Hanna, Hafner, Verena V., Lazarides, Rebecca
Formato: research tables/charts Journal Article
Publicado: Springer Nature 6/12/2026
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 6/12/2026
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      pub: Springer Nature
      place: New York, New York
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        10.1038/s44271-026-00487-8
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        atl: Real-time cognitive-affective dynamics of failure feedback in a technology-based learning task.
      aug:
        au:
          Ackermann, Helene
          Lange, Anna L.
          Dumont, Hanna
          Hafner, Verena V.
          Lazarides, Rebecca
        affil: https://ror.org/03bnmw459 Department of Educational Sciences, Universität Potsdam, Potsdam, Germany
      sug:
        subj:
          Technology
          Learning Methods
          Automation
          Feedback
          Cognition Disorders
          Task Performance and Analysis
          Robotics
          Human
          Male
          Female
          Adolescence
          Adult
          Middle Age
          Vocabulary
          Experimental Studies
          Outcome Assessment
          Data Analysis Software
          Descriptive Statistics
          Intelligence Tests
          Funding Source
          Adolescent: 13-18 years
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Male
          Female
      ab: As technology-based learning environments increasingly employ automated feedback, understanding how learners process feedback in real time is essential. This study examined how automated cognitive and metacognitive failure feedback delivered by a humanoid robot affected performance and how effects were moderated by feedback characteristics and learner characteristics. Ninety adults (18-59 years, Mage = 29.53, 61 female, 27 male, 2 diverse) completed a learning task in three conditions: (1) fixed guidance condition with fixed-frequency and content-generic feedback, (2) basic-adaptive condition with frequency-adaptive but content-generic feedback, or (3) personalized-adaptive condition with frequency-adaptive and content-personalized feedback adjusting content to learners specific errors and prior steps. A three-level generalized path model (trials nested within time blocks within learners) was estimated to investigate effects of failure feedback on immediate task performance and cross-level moderation effects. Results showed that cognitive and metacognitive failure feedback increased the likelihood of a correct subsequent response across conditions. Relative to fixed guidance (condition 1), the implemented form of frequency-adaptive feedback (condition 2) did not show statistically significant moderation to these effects. Content-personalized feedback (condition 3) reduced effectiveness of cognitive failure feedback on immediate performance but improved overall performance as compared to content-generic feedback (condition 2). Across conditions, learners with higher cognitive ability benefited less, while those reporting higher momentary on-task boredom benefited more from cognitive feedback. These findings highlight that the effectiveness of automated failure feedback depends on both its design and learners' situational cognitive and emotional states, illustrating how a situational, temporally sensitive approach can help open the "black box" of feedback effectiveness. This study examines how automated failure feedback influences performance in a technology-based learning task. Trial level analyses show that effectiveness depends on feedback design and learners' situational emotional and cognitive characteristics.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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