Curriculum Learning in Humans and Neural Networks
Journal article, 2026

The sequencing of training trials can significantly influence learning outcomes in humans and neural networks. However, studies comparing the effects of training curricula between the two have typically focused on the acquisition of multiple tasks. Here, we investigate curriculum learning in a single perceptual decision-making task, examining whether the behavior of a parsimonious network trained on different curricula would be replicated in human participants (n = 200). Our results show that progressively increasing task difficulty during training facilitates learning compared to training at a fixed level of difficulty or at random. Furthermore, a sequence designed to hamper learning in a parsimonious neural network network also impaired learning in humans. As such, our findings indicate qualitative similarities between neural networks and humans in curriculum learning for perceptual decision-making, suggesting the former can serve as a viable computational model of the latter.

parsimonious neural networks

perceptual decision-making

curriculum learning

Author

Younes Strittmatter

Princeton Univ, Dept Psychol

Stefano Sarao Mannelli

Chalmers, Computer Science and Engineering (Chalmers), Data Science and AI

University of Gothenburg

Miguel Ruiz-Garcia

Complutense University

Sebastian Musslick

Brown Univ, Dept Cognit & Psychol Sci

Osnabrück University

Markus Wolfgang Hermann Spitzer

Martin-Luther-Universität Halle-Wittenberg

OPEN MIND-DISCOVERIES IN COGNITIVE SCIENCE

2470-2986 (eISSN)

Vol. 10 739-753

Subject Categories (SSIF 2025)

Computer Sciences

Psychology

Neurosciences

DOI

10.1162/OPMI.a.355

PubMed

42245993

More information

Latest update

6/11/2026