Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Purposive Learning01:22

Purposive Learning

E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a bonus...
Cognitive Learning01:21

Cognitive Learning

Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
Associative Learning01:27

Associative Learning

Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
Causality in Epidemiology01:21

Causality in Epidemiology

Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
Introduction to Learning01:18

Introduction to Learning

Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
Observational Learning01:12

Observational Learning

Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning because...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Lossy encoding of distributions in judgment under uncertainty.

Cognitive psychology·2025
Same author

Embodied large language models enable robots to complete complex tasks in unpredictable environments.

Nature machine intelligence·2025
Same author

Automating the practice of science: Opportunities, challenges, and implications.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

Beyond discrete-choice options.

Trends in cognitive sciences·2024
Same author

Designing optimal behavioral experiments using machine learning.

eLife·2024
Same author

Naïve information aggregation in human social learning.

Cognition·2023

Related Experiment Videos

Actively Learning to Learn Causal Relationships.

Chentian Jiang1, Christopher G Lucas1

  • 1School of Informatics, University of Edinburgh, Edinburgh, UK.

Computational Brain & Behavior
|July 16, 2026
PubMed
Summary

People actively learn by seeking information not just about specific causal relationships but also about abstract overhypotheses. This strategy facilitates long-term learning and knowledge transfer across similar situations.

Keywords:
Active learningCausal learningGeneralizationOverhypothesesTransfer learning

Related Experiment Videos

Area of Science:

  • Cognitive Science
  • Psychology
  • Machine Learning

Background:

  • Understanding active learning is crucial for explaining how humans acquire knowledge efficiently.
  • Previous models often focus on learning specific causal links, neglecting abstract knowledge acquisition.

Purpose of the Study:

  • To investigate how individuals actively seek information for long-term learning.
  • To explore the role of abstract beliefs (overhypotheses) in active causal learning.

Main Methods:

  • Proposed a hierarchical Bayesian model to predict information-seeking behavior.
  • Conducted two active "blicket detector" experiments with 14 between-subjects manipulations.

Main Results:

  • The proposed model accurately predicted human behavior in active causal learning tasks.
  • Participants learned and transferred abstract overhypotheses when problems shared similarities.
  • Overhypotheses were exploited to enhance long-term active learning.

Conclusions:

  • Humans actively learn by acquiring both specific causal knowledge and abstract overhypotheses.
  • Abstract beliefs play a key role in facilitating efficient and transferable learning across diverse situations.