Related Experiment Video
Updated: Jan 31, 2026

Control of Eating Behavior Using a Novel Feedback System
Published on: May 8, 2018
Examining the impact of error estimation on the effects of self-controlled feedback
Joao A C Barros1, Zachary D Yantha2, Michael J Carter3
1Department of Kinesiology, California State University Fullerton, 800 North State College Blvd., Room KHS-121, Fullerton, CA 92834, USA.
Abstract:
Two experiments were conducted that examined the motivational and informational perspectives concerning learning advantages from self-controlled practice. Three groups were tasked with learning a novel skill; self-controlled (SC), yoked traditional (YT), and yoked with error estimation required during the acquisition phase (YE). Results from the delayed learning measures showed the YE group performed better than the SC and YT groups, for Expt. 1. A similar pattern emerged for Expt. 2, albeit, this was not significant. While there were no motivation differences across the groups in either experiment, a strong correlation in Expt. 2 was shown between error estimation capabilities, which were best for the YE group, and learning. These combined results suggest that informational processes contribute more to the self-controlled feedback learning advantage, relative to motivational contributions.
Related Concept Videos
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...
Feedback control systems
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
Fundamental Attribution Error
Feedback Inhibition
Drug Control Governance: Regulatory Bodies and Their Impact
Feedback Loops

