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

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...
Generalization, Discrimination, and Extinction01:24

Generalization, Discrimination, and Extinction

Generalization, discrimination, and extinction are key concepts in operant conditioning that influence how behaviors are learned and maintained.
Generalization occurs when a behavior reinforced in one context is performed in similar situations. For instance, a student who studies diligently for calculus and receives excellent grades might apply the same study habits to psychology and history, expecting similar results. Generalization shows how learning in one setting can influence behavior in...
Criteria for Causality: Bradford Hill Criteria - II01:28

Criteria for Causality: Bradford Hill Criteria - II

The Bradford Hill criteria serve as guidelines for establishing causative links in epidemiological research. Beyond Strength, Consistency, Specificity, and Temporality, key criteria also include Biological Gradient, Plausibility, Coherence, Experiment, and Analogy. These principles assist scientists in assessing the likelihood of causation in complex biological contexts. Below is a summary of these concepts:
Fundamental Attribution Error01:14

Fundamental Attribution Error

According to some social psychologists, people tend to overemphasize internal factors as explanations—or attributions—for the behavior of other people. They tend to assume that the behavior of another person is a trait of that person, and to underestimate the power of the situation on the behavior of others. They tend to fail to recognize when the behavior of another is due to situational variables, and thus to the person’s state. This erroneous assumption is called the fundamental attribution...
Cause and Effect01:53

Cause and Effect

While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable, is actually causing the systematic movement in our variables of interest. For instance, as sales in ice cream increase, so does the overall rate of crime. Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone?
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 from inductive reasoning. It uses a general principle or law to predict specific results. From these general principles, a scientist can predict specific results that remain valid as long as the general principles are correct.For example, a researcher can make specific predictions from the hypothesis "butterflies are attracted...

You might also read

Related Articles

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

Sort by
Same author

Turkish preschoolers show an advantage in their understanding of their own representational change over others' false belief.

The British journal of developmental psychology·2026
Same author

Longitudinal Relations Among Theory of Mind, Advanced Theory of Mind, and Executive Function From Ages Four to Seven.

Developmental science·2026
Same author

Children's decision to challenge themselves on a novel task relates to their metacognitive monitoring of their ability.

Child development·2026
Same author

Origins of understanding fair resource collection.

Cognition·2026
Same author

Examining Baseline Relations Between Parent-Child Interactions and STEM Engagement and Learning.

Developmental science·2025
Same author

Distinct Inhibitory-Control Processes Underlie Children's Judgments of Fairness.

Psychological science·2024

Related Experiment Video

Updated: Jun 25, 2026

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms
07:31

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms

Published on: February 8, 2019

Domain generality and specificity in children's causal inference about ambiguous data.

David M Sobel1, Sarah E Munro

  • 1Department of Cognitive and Linguistic Sciences, Box 1978, Brown University, Providence, RI 02912, USA. Dave_Sobel@brown.edu

Developmental Psychology
|March 11, 2009
PubMed
Summary

Three-year-olds understand causal mechanisms, differentiating between machines and agents. They use this knowledge, alongside base rate information, to make inferences about object properties and agent intentions.

More Related Videos

Experience is Instrumental in Tuning a Link Between Language and Cognition: Evidence from 6- to 7- Month-Old Infants' Object Categorization
05:35

Experience is Instrumental in Tuning a Link Between Language and Cognition: Evidence from 6- to 7- Month-Old Infants' Object Categorization

Published on: April 19, 2017

Exploring the Role of Deontic Reasoning and World Knowledge in Wason´s Selection Task
06:08

Exploring the Role of Deontic Reasoning and World Knowledge in Wason´s Selection Task

Published on: July 22, 2025

Related Experiment Videos

Last Updated: Jun 25, 2026

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms
07:31

Defining the Role Of Language in Infants' Object Categorization with Eye-tracking Paradigms

Published on: February 8, 2019

Experience is Instrumental in Tuning a Link Between Language and Cognition: Evidence from 6- to 7- Month-Old Infants' Object Categorization
05:35

Experience is Instrumental in Tuning a Link Between Language and Cognition: Evidence from 6- to 7- Month-Old Infants' Object Categorization

Published on: April 19, 2017

Exploring the Role of Deontic Reasoning and World Knowledge in Wason´s Selection Task
06:08

Exploring the Role of Deontic Reasoning and World Knowledge in Wason´s Selection Task

Published on: July 22, 2025

Area of Science:

  • Cognitive Development
  • Developmental Psychology
  • Causal Inference

Background:

  • Children's understanding of causality is crucial for learning.
  • Investigating how children integrate mechanism knowledge with statistical data is key.

Purpose of the Study:

  • To examine 3-year-olds' causal reasoning about mechanisms and base rates.
  • To determine if children differentiate between agents and machines in causal understanding.
  • To explore how children integrate domain-specific knowledge into causal inference.

Main Methods:

  • Five experiments were conducted with 3-year-old children.
  • Children's interpretations of object activation by machines versus agents were assessed.
  • Reasoning about ambiguous data using base rate information was analyzed.

Main Results:

  • Children distinguish between machines and agents, attributing internal properties to agents.
  • Three-year-olds utilize mechanistic knowledge to interpret ambiguous data with base rates.
  • Inferences are based on domain-specific knowledge integration, not solely on desires.

Conclusions:

  • Children's causal inference integrates domain-specific mechanism knowledge with general statistical learning.
  • A Bayesian inference model may describe how children combine mechanism understanding and covariation data.
  • This research sheds light on the sophisticated nature of early causal reasoning.