Advancing Self-Determination Theory via computational modelling: the case of competence and optimal challenge
File(s)
Published version
Author(s)
Deterding, Sebastian
Guckelsberger, Christian
Lintunen, Erik M
Ady, Nadia M
Type
Journal Article
Abstract
Computational modelling is a powerful tool to specify psychological theories and conduct model-based empirical research. Yet it has seen little use in Self-Determination Theory (SDT), one of the most successful theories of human motivation. Here, we use two basic SDT constructs, competence and optimal challenge, to demonstrate how computational modelling can benefit theory building and practical application for SDT. Drawing on conceptual analysis and a toy model, we identify three plausible intensional facets of verbal competence definitions that unevenly align with operationalisations and propositions on optimal challenge. We then show how computational modelling, inspired by the AI field of computational intrinsic motivation, can help inform the refinement of these and other constructs, provide point-precise predictions, complement cognition-level mechanistic accounts of competence, refine practical guidance, and support implementation in digital task and goal-setting applications.
Date Issued
2026-02-01
Date Acceptance
2025-07-16
Citation
Motivation and Emotion, 2026, 50 (1), pp.80-99
ISSN
0146-7239
Publisher
Springer
Start Page
80
End Page
99
Journal / Book Title
Motivation and Emotion
Volume
50
Issue
1
Copyright Statement
© The Author(s) 2025, modified publication 2025 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
License URL
Subjects
AUTONOMY
Competence
Computational modelling
DIFFICULTY
EXPLANATION
EXPLORATION
HIERARCHICAL MODEL
INCENTIVES
INTRINSIC MOTIVATION
MECHANISMS
Optimal challenge
PERFORMANCE
Psychology
PSYCHOLOGY
Psychology, Experimental
Psychology, Social
Self-Determination Theory
Social Sciences
Theory crisis
Publication Status
Published
Date Publish Online
2025-09-26