A computational model of self-efficacy's various effects on performance: Moving the debate forward

Area of Science:

• Psychology
• Cognitive Science
• Computational Modeling

Background:

• Self-efficacy, or belief in one's capabilities, demonstrates complex effects on effort and performance, sparking debate between social-cognitive and perceptual control theories.
• Existing models primarily explain positive self-efficacy effects, leaving the negative and null effects less understood within a unified framework.

Purpose of the Study:

• To develop a computational model that integrates multiple processes to explain the varied effects of self-efficacy on performance.
• To reconcile theoretical discrepancies between social-cognitive and perceptual control theories regarding self-regulation.

Main Methods:

• Building upon an existing goal choice model, a symbolic processing structure for goal striving was added to simulate self-efficacy effects.
• The enhanced computational model was used to replicate findings from a study on feedback ambiguity's influence on the self-efficacy-performance relationship.

Main Results:

• The computational model successfully reproduced positive, negative, and null effects of self-efficacy on performance.
• The model's symbolic processing component accounts for negative self-efficacy effects observed in recent research.

Conclusions:

• The computational model offers a unified explanation for diverse self-efficacy effects, bridging social-cognitive and control theory perspectives.
• This modeling approach demonstrates the utility of computational methods in resolving theoretical disputes in self-regulation research.