Learning Value Perceptions in Visual Pattern Recognition
Year: 2025
Type: preprint
Abstract: This project examines how Learning Value Perceptions (LVP)—the extent to which individuals perceive success and failure as informative for learning—shape how people learn from experience and feedback. Specifically, the study investigates whether valuing learning from success and failure predicts learning rate, performance accuracy, reaction time, and expectancy accuracy during a visual pattern recognition task. In addition, the study explores how LVP relates to attitudes toward success and failure and how self-efficacy contributes to the accuracy of performance expectancies. Participants completed a matrix-based pattern recognition task designed to capture learning through repeated exposure, with half receiving trial-by-trial feedback and half learning without feedback. This design allows for the examination of both experiential learning (pattern recognition over time) and feedback-based learning, as well as how individuals calibrate their expectations of success as they accumulate evidence from repeated successes and failures. By focusing on expectancy accuracy, performance progression, and response timing, this study extends prior work on learning value perceptions beyond self-reported learning value perceptions to observable learning behavior. The findings aim to clarify the cognitive mechanisms through which valuing learning from success and failure supports adaptive learning, more accurate self-evaluation, and improved performance across repeated experiences.
Institution: Duke University
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7131253150