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

Mathematical Induction01:29

Mathematical Induction

Mathematical induction is a structured method of proof used to confirm the truth of statements involving natural numbers. Consider the sum of the first n natural numbers:This formula describes a pattern that appears to hold true as more terms are added. To verify that it is valid for all natural numbers, mathematical induction proceeds in two essential steps. The first is the base case, where the formula is tested for the initial value, typically n = 1. Substituting into both sides confirms the...
Inductive Reasoning00:59

Inductive Reasoning

Inductive reasoning is a form of logical thinking that uses related observations to arrive at a general conclusion. It is uncertain and operates in degrees to which the conclusions are credible. As such, inductive arguments can be weak or strong, rather than valid or invalid, and conclusions can be used to formulate testable, falsifiable hypotheses.
Inductive reasoning is common in descriptive science. A life scientist makes observations and records them. This data can be qualitative or...
Trial and Error and Algorithm01:12

Trial and Error and Algorithm

A problem-solving strategy is a plan of action used to find a solution. Different strategies have distinct action plans. Trial and error involves trying different solutions until one works. For instance, to fix a broken printer, you might check ink levels, ensure the paper tray isn't jammed, and verify the printer's connection to your laptop. This method can be time-consuming but is commonly used. Thomas Edison, for example, used trial and error to find a suitable filament for the light bulb,...
Deductive Reasoning01:16

Deductive Reasoning

Deductive reasoning, or deduction, is the type of logic used in hypothesis-based science. In deductive reasoning, the pattern of thinking moves in the opposite direction as compared to inductive reasoning, which means that it uses a general principle or law to predict specific results. From those general principles, a scientist can deduce and predict the specific results that would be valid as long as the general principles are valid.
For example, a researcher can deduce specific predictions...
Piaget's Stage 3 of Cognitive Development01:17

Piaget's Stage 3 of Cognitive Development

During Piaget's concrete operational stage, from ages 7 to 11, children exhibit a marked increase in logical thinking skills, specifically in relation to tangible, real-world events. This stage is characterized by the development of several essential cognitive concepts, including conservation, reversibility, and classification, all of which support the child's evolving capacity for structured thought.
Conservation and Constancy of Quantity
A significant cognitive milestone in the concrete...
Piaget's Theory of Cognitive Development from Childhood into Adulthood01:25

Piaget's Theory of Cognitive Development from Childhood into Adulthood

Jean Piaget's theory of cognitive development emphasizes the role of thinking in a child's learning process, suggesting that children are naturally curious about their environment. His approach to development is discontinuous, proposing that cognitive abilities progress through distinct stages, each with unique characteristics. Central to Piaget's theory is schemata—mental structures that allow individuals to understand and interpret the world.
Schemata: Building Blocks of Knowledge
Schemata...

You might also read

Related Articles

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

Sort by
Same author

One Action, Two Reference Frames: Compound Cognitive Maps of Object Location.

Psychological science·2025
Same author

Do Humans Use Push-Down Stacks When Learning or Producing Center-Embedded Sequences?

Cognitive science·2025
Same author

Symbolic metaprogram search improves learning efficiency and explains rule learning in humans.

Nature communications·2024
Same author

Formalising the role of behaviour in neuroscience.

The European journal of neuroscience·2024
Same author

Response to Difficulty Drives Variation in IQ Test Performance.

Open mind : discoveries in cognitive science·2024
Same author

The algorithmic origins of counting.

Child development·2023
Same journal

Forced changes in a Tibetan lake ecosystem over the past millennium.

Nature communications·2026
Same journal

Time-Temperature Superposition Principle Serving as a Design Tool for Tailored MOF-Crystal Glass Composite Membranes.

Nature communications·2026
Same journal

Simultaneous nanoscale imaging of local conductivity and chemical potential in a quantum Hall isospin ferromagnet.

Nature communications·2026
Same journal

A family of archaeal hibernation factors that bind in tandem and protect ribosomes in dormant cells.

Nature communications·2026
Same journal

Surface energy-driven perpendicular gradient structure in flexible composite dielectrics for high-temperature capacitive energy storage.

Nature communications·2026
Same journal

Severe droughts in Senegal are linked to increased family reunification at migration destinations in Europe.

Nature communications·2026
See all related articles
  1. Home
  3. Children Use Algorithm Induction To Discover Patterns In Data.
  1. Home
  3. Children Use Algorithm Induction To Discover Patterns In Data.

Related Experiment Video

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task
11:18

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task

Published on: June 1, 2015

Children use algorithm induction to discover patterns in data.

Benjamin Pitt1,2, Elena Leib3, David O'Shaughnessy4

  • 1Department of Psychology, University of California, Berkeley, Berkeley, CA, USA. pitt@uchicago.edu.

Nature Communications
|May 30, 2026

View abstract on PubMed

Summary
This summary is machine-generated.

Children rapidly learn complex rules through program induction, a domain-general cognitive mechanism. This fast, flexible learning allows them to infer environmental structures across diverse cultures and ages.

More Related Videos

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
08:05

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Published on: June 30, 2020

Portable Intermodal Preferential Looking (IPL): Investigating Language Comprehension in Typically Developing Toddlers and Young Children with Autism
10:11

Portable Intermodal Preferential Looking (IPL): Investigating Language Comprehension in Typically Developing Toddlers and Young Children with Autism

Published on: December 14, 2012

Related Experiment Videos

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task
11:18

Quantifying Learning in Young Infants: Tracking Leg Actions During a Discovery-learning Task

Published on: June 1, 2015

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques
08:05

Measuring Statistical Learning Across Modalities and Domains in School-Aged Children Via an Online Platform and Neuroimaging Techniques

Published on: June 30, 2020

Portable Intermodal Preferential Looking (IPL): Investigating Language Comprehension in Typically Developing Toddlers and Young Children with Autism
10:11

Portable Intermodal Preferential Looking (IPL): Investigating Language Comprehension in Typically Developing Toddlers and Young Children with Autism

Published on: December 14, 2012

Area of Science:

  • Cognitive Science
  • Developmental Psychology
  • Artificial Intelligence

Background:

  • Human learning is remarkably fast and flexible, but the underlying cognitive mechanisms are not fully understood.
  • Existing theories often focus on specific learning strategies, leaving a gap in explaining domain-general learning capabilities.

Purpose of the Study:

  • To investigate program induction as a potential domain-general learning mechanism in children.
  • To explore whether program induction operates similarly across diverse cultural and age groups.

Main Methods:

  • Participants (US American and indigenous Tsimane' children) were presented with novel patterns and asked to generalize them without feedback.
  • Computational modeling was used to analyze response patterns and infer the underlying learning strategies.

Main Results:

  • Children across different cultures and ages successfully generalized novel patterns, demonstrating the ability to infer abstract structure from limited data.
  • Response patterns indicated the discovery of latent rules, consistent with program induction, rather than simpler learning heuristics.
  • This learning occurred even in children without formal schooling.

Conclusions:

  • Program induction appears to be a fundamental, domain-general learning mechanism present from early in life.
  • This mechanism enables children to rapidly acquire knowledge about diverse environments and cultural contexts.
  • The findings have implications for understanding human cognition and developing AI learning systems.