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

Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...
Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.
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...
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...
Survival Tree01:19

Survival Tree

Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a survival tree begins...
Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...

You might also read

Related Articles

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

Sort by
Same author

Language models do not yet achieve explanatory adequacy because language is more than incremental prediction.

The Behavioral and brain sciences·2026
Same author

Learning from the Input: A Corpus-Based Investigation of Chinese Classifiers in Children's Books and Child-Directed Speech.

Journal of child language·2026
Same author

Effects of Explicit Phonetic Instruction in Shaping Second-Language Perceptual Cue Weighting: Evidence From English /iː/-/ɪ/.

Journal of speech, language, and hearing research : JSLHR·2026
Same author

Domain-general categorisation explains constrained cross-linguistic variation in noun classification.

Cognition·2026
Same author

Predictive Structure Emerges During the Generalisation of Kin Terms to New Referents.

Open mind : discoveries in cognitive science·2025
Same author

Communicative pressures shape language during communication (not learning): Evidence from case-marking in artificial languages.

Cognition·2025
Same journal

Corrigendum to 'Consonant, vowel, and tone cues in early wordform recognition: Evidence from Cantonese-learning infants' [Cognition 275 (2026) 106624].

Cognition·2026
Same journal

Identifying distinct sources of whole number interference in children's decimal comparison: the role of numerical magnitude and inhibitory control.

Cognition·2026
Same journal

Evidence for abstract spatial concept learning in young animals.

Cognition·2026
Same journal

Blurred lines or clear boundaries? Synchrony and social dominance shape domain-specific self-other processing.

Cognition·2026
Same journal

Knowability predicts curiosity and learning.

Cognition·2026
Same journal

Throwing good effort after bad: Evidence for a sunk-cost effect in cognitive effort-based decision-making.

Cognition·2026
See all related articles

Related Experiment Videos

Eliminating unpredictable variation through iterated learning.

Kenny Smith1, Elizabeth Wonnacott

  • 1Cognition and Communication Research Centre, Department of Psychology, Northumbria University, Northumberland Building, Northumberland Road, Newcastle upon Tyne NE18ST, UK. kenny.smith@northumbria.ac.uk

Cognition
|July 10, 2010
PubMed
Summary
This summary is machine-generated.

Population-level learning processes, not just individual acquisition, can shape human languages. Repeated learning in diffusion chains increased language predictability, suggesting a mechanism for linguistic regularity.

Related Experiment Videos

Area of Science:

  • Cognitive Science
  • Linguistics
  • Evolutionary Psychology

Background:

  • Human language evolution is influenced by both individual language acquisition and population-level learning.
  • Natural languages tend to exhibit regularity and avoid unpredictable variation.

Purpose of the Study:

  • To investigate whether iterated learning in adult diffusion chains can lead to increased linguistic predictability.
  • To explore population-level processes as a source of language regularity.

Main Methods:

  • Utilized an iterated artificial language learning methodology.
  • Organized participants into diffusion chains where each learner was exposed to the language produced by the previous learner.
  • Introduced an artificial language with unpredictable plural marking to the first learner in each chain.

Main Results:

  • Diffusion chains, unlike isolate learners, demonstrated a cumulative increase in the predictability of plural marking.
  • Learners in diffusion chains lexicalized the choice of plural marker, leading to greater regularity.
  • This suggests that gradual, cumulative population-level learning drives linguistic regularization.

Conclusions:

  • Population-level learning processes, such as iterated learning in diffusion chains, can foster linguistic regularity.
  • These findings provide a potential explanation for the prevalence of predictable patterns in natural languages.
  • The study highlights the role of social transmission in shaping language structure.