Related Experiment Video
Updated: Jun 14, 2026

A Computerized Functional Skills Assessment and Training Program Targeting Technology Based Everyday Functional Skills
Published on: February 13, 2020
Real-time cognitive-affective dynamics of failure feedback in a technology-based learning task
Helene Ackermann1,2, Anna L Lange3,4, Hanna Dumont5
1Department of Educational Sciences, Universität Potsdam, Potsdam, Germany. helene.ackermann@uni-potsdam.de.
Abstract:
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.
Related Concept Videos
Avoidance Learning and Learned Helplessness
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...
Negative and Positive Feedback
Effects of feedback
Feedback significantly modifies the gain of a control system. The gain of a system without feedback is altered by a factor of one plus GH, where G represents...
Cognitive Learning
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
Self-Evaluation Maintenance Model
Hindsight Biases
