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09:00 - 10:30
Parallel sessions 1
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09:00 - 10:30
Room: HSZ - N4
Chair/s:
Sascha Meyen, Simge Hamaloğlu
The ability to judge one’s own confidence is a core ability of human metacognition. Giving informative confidence ratings is crucial in many situations: Humans making decisions, either individually or in groups, rely on their own estimates of uncertainty. But finding adequate measures for the quality of confidence ratings is a challenge. The two major approaches to tackle this challenge will be contrasted in this symposium: model-based and model-free. On the one hand are computational process models of the formation of confidence ratings in humans. The first speaker, Matthias Guggenmos, provides an overview and categorization of these models. One of them is the most prominent model, which is an extension of classical signal detection theory (where perceptual sensitivity, d’, is measured). This metacognitive extension analogously measures metacognitive sensitivity, meta-d’. Together with nine others, this prominent model is evaluated on a collection of 13 experimental data sets by the second speaker, Manuel Rausch. His results should concern researchers in the field: The meta-d’/d’ model does not provide satisfactory results. The third speaker, Simge Hamaloglu, drills deeper into the model's mechanisms: As in classical signal detection theory, the meta-d’/d’ model estimates (metacognitive) criteria that determine the point where low turns into high confidence. She focuses on these criteria to differentiate when a stimulus is actually perceived versus only inferred from other cues. Contrasting these model-based approaches, on the other hand, classical information theory has inspired approaches to measuring metacognitive ability in a model-free way. The fourth speaker, Sascha Meyen, introduces this idea in which metacognitive ability is measured as transmitted information (in bits). Taken together, this symposium will pinpoint the contention between model-based and model-free approaches to measuring metacognitive ability. It will highlight challenges in terms of empirical fit and interpretability, and thereby guide future development of both approaches in tandem.
Submission 528
From Experience to Insight: How Familiarity Shapes Confidence in Event Completion
SymposiumTalk-03
Presented by: Simge Hamaloğlu
Simge Hamaloğlu 1, Kevin Erens 1, Markus Huff 1, 2, Nadia Said 1
1 University of Tübingen, Germany
2 Leibniz-Institut für Wissensmedien Tübingen, Germany
Accurately judging one’s own confidence is key in metacognition and essential for understanding how people evaluate their perceptual experiences. In dynamic environments, however, perception often involves information that is not directly seen but inferred. This process, known as event completion, allows for coherent perception but also introduces uncertainty about what was actually perceived. Understanding how people evaluate their confidence in such situations offers new perspectives on metacognitive insight. In this work, we investigate how familiarity and repeated exposure influence event perception and confidence. Using soccer videos as stimuli, we examine how observers with different levels of domain knowledge perceive and evaluate partially omitted actions. Across three measurement points, participants repeatedly view the same events, allowing us to trace how event schemas develop over time and how these changes affect perceptual decisions and confidence. We present two studies that build on initial findings and extend them by examining event perception across repeated exposures in a broader population. We expect that increasing familiarity will enhance detection accuracy for causally implied continuations, reflecting a refinement of internal event representations. Confidence judgments, however, may not fully capture these changes, revealing limits in metacognitive awareness. To link these behavioral findings to broader metacognitive modeling approaches, we use hierarchical analyses to compare confidence distributions across conditions. This model-based perspective identifies whether confidence reliably tracks inferred versus directly perceived information and provides insights into how familiarity shapes the calibration of confidence in event perception.