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Change one can believe in: Adding learning to computational models of self-regulation

Authors
Journal
Organizational Behavior and Human Decision Processes
0749-5978
Publisher
Elsevier
Volume
124
Issue
1
Identifiers
DOI: 10.1016/j.obhdp.2013.12.002
Keywords
  • Computational Model
  • Motivation
  • Dynamics
  • Learning

Abstract

Abstract Theories of self-regulation describe motivation as a dynamic process of goal choice and goal striving. To facilitate those processes, individuals learn about themselves and their environment, which is an internal dynamic process. However, the precise nature of the relationship between these learning and motivational processes is not well specified. This article integrates formal models of learning, goal choice, and goal striving using a single information processing structure found in self-regulatory models of motivation. Results from two published studies (DeShon & Rench, 2009; Schmidt & DeShon, 2007) validate the model. In both cases, the integrated model accounts for findings that previous theories of self-regulation could not explain. Discussion focuses on additional tests to validate the model and on the value of incorporating formal models from the cognitive, learning, and motivational literatures to account for behavior in complex settings and over time.

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