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Published on: March 2, 2015
Curriculum Learning in Humans and Neural Networks.
Younes Strittmatter1, Stefano Sarao Mannelli2,3, Miguel Ruiz-Garcia4,5
1Department of Psychology, Princeton University, Princeton, NJ, USA.
Open Mind : Discoveries in Cognitive Science
|June 5, 2026
Summary
Curriculum learning, or the sequencing of training trials, significantly impacts learning in both humans and neural networks. Findings show humans and neural networks exhibit similar learning patterns in perceptual decision-making tasks.
Area of Science:
- Cognitive Science
- Computational Neuroscience
- Machine Learning
Background:
- Training trial sequencing influences learning outcomes in humans and artificial neural networks.
- Previous research primarily focused on multi-task learning, leaving single-task curriculum learning under-explored.
- Understanding these similarities can validate neural networks as models for human learning.
Purpose of the Study:
- To investigate curriculum learning in a single perceptual decision-making task.
- To compare learning outcomes in humans and a parsimonious neural network under varied training curricula.
- To determine if neural network behavior under curriculum learning is replicable in human participants.
Main Methods:
- Human participants (n=200) and a parsimonious neural network were trained on a perceptual decision-making task.
- Training curricula involved progressively increasing difficulty, fixed difficulty, and random difficulty.
- Learning performance was assessed across different curriculum conditions.
Main Results:
- Progressively increasing task difficulty during training significantly facilitated learning in both humans and the neural network.
- A curriculum designed to impede neural network learning also impaired human learning.
- Qualitative similarities in learning patterns were observed between humans and the neural network.
Conclusions:
- Humans and neural networks exhibit comparable responses to curriculum learning in single perceptual decision-making tasks.
- The findings support the use of neural networks as computational models for human perceptual learning.
- Curriculum design is a critical factor influencing learning efficiency in both biological and artificial systems.
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