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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...
Language Development01:22

Language Development

Children master language quickly and with relative ease, supported by both biological predisposition and reinforcement. B. F. Skinner (1957) proposed that language is learned through reinforcement, while Noam Chomsky (1965) argued that language acquisition mechanisms are biologically determined.
The critical period for language acquisition suggests that the ability to acquire language is at its peak early in life. As people age, this proficiency decreases. Language development begins very...
Components of Language01:24

Components of Language

Language, whether spoken, signed, or written, consists of specific components: lexicon and grammar. The lexicon is the vocabulary of a language, comprising its words. Grammar is the set of rules used to convey meaning through the lexicon. For example, English grammar adds “-ed” to most verbs to indicate past tense. Words are formed by combining phonemes, which are the basic sound units of a language. Different languages have different sets of phonemes (e.g., “ah” vs. “eh”). Phonemes combine to...
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...
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...
Steps in the Modeling Process01:14

Steps in the Modeling Process

Albert Bandura's theory of observational learning identifies four critical processes: attention, retention, motor reproduction, and reinforcement or motivation.
Attention is the first necessary component for observational learning. It involves focusing on what the model is doing and saying. For example, if you decide to take a drawing class to enhance your skills, you need to pay close attention to the instructor's words and hand movements. The characteristics of the model significantly...

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Related Experiment Video

Updated: Jun 19, 2026

Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning
05:33

Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning

Published on: January 29, 2020

Individual strategies in artificial grammar learning.

Ingmar Visser1, Maartje E J Raijmakers, Emmanuel M Pothos

  • 1Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands. i.visser@uva.nl

The American Journal of Psychology
|October 16, 2009
PubMed
Summary

Analyzing individual strategies in artificial grammar learning (AGL) is crucial. A new latent class regression model reveals distinct participant groups focusing on grammaticality versus fragment overlap for learning.

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Transcranial Direct Current Stimulation (tDCS) of Wernicke's and Broca's Areas in Studies of Language Learning and Word Acquisition
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Transcranial Direct Current Stimulation (tDCS) of Wernicke's and Broca's Areas in Studies of Language Learning and Word Acquisition

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Related Experiment Videos

Last Updated: Jun 19, 2026

Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning
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Experimental Paradigm for Measuring the Effect of Induced Emotion on Grammar Learning

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Transcranial Direct Current Stimulation (tDCS) of Wernicke's and Broca's Areas in Studies of Language Learning and Word Acquisition
12:49

Transcranial Direct Current Stimulation (tDCS) of Wernicke's and Broca's Areas in Studies of Language Learning and Word Acquisition

Published on: July 13, 2019

Area of Science:

  • Cognitive Psychology
  • Computational Linguistics
  • Statistical Modeling

Background:

  • Artificial grammar learning (AGL) is a key paradigm for studying human learning processes.
  • Understanding individual differences in AGL strategies is essential for robust theoretical conclusions.
  • Existing methods may not fully capture the heterogeneity in participant responses.

Purpose of the Study:

  • To introduce a novel statistical method for analyzing individual strategies in AGL.
  • To apply latent class regression models to identify distinct learning strategies.
  • To investigate the roles of grammaticality and fragment overlap in AGL.

Main Methods:

  • Development and application of latent class regression models.
  • Modeling heterogeneity in participant responses within AGL studies.
  • Analysis of intercept and regression coefficient variations across latent groups.

Main Results:

  • Identification of distinct latent groups representing different strategic reliance on learning cues.
  • Demonstration that grammaticality and fragment overlap function as separable learning aspects.
  • Evidence of participant groups predominantly adopting either grammaticality or fragment overlap strategies.

Conclusions:

  • Latent class regression models effectively capture individual strategy differences in AGL.
  • Grammaticality and fragment overlap represent distinct dimensions of learning performance.
  • This method enhances the analysis of learning theories by accounting for strategic heterogeneity.