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Related Concept Videos

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...
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...
Classical Conditioning01:18

Classical Conditioning

Associative learning, a core principle in behavioral psychology, involves forming connections between events and facilitating learned responses. This concept is vividly illustrated by classical conditioning, a process extensively studied by the Russian physiologist Ivan Pavlov. Pavlov's pioneering research on dogs' digestive systems led to the discovery that behaviors can be learned through association, laying the groundwork for classical conditioning.
Ivan Pavlov observed that dogs salivated...
Higher Mental Functions of Brain: Learning and Memory01:26

Higher Mental Functions of Brain: Learning and Memory

Memory is one of the most vital higher mental functions of the brain. Memory is closely related to learning because it enables us to retain information and experiences from our past to use them in our present life. It also helps us to remember facts, events, and skills, such as riding a bike or swimming. There are two types of memory — declarative memory, which involves memorizing facts or events, and procedural memory, which enables us to remember how to do something like writing or playing an...

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Related Experiment Video

Updated: Jul 3, 2026

Drosophila Passive Avoidance Behavior as a New Paradigm to Study Associative Aversive Learning
06:20

Drosophila Passive Avoidance Behavior as a New Paradigm to Study Associative Aversive Learning

Published on: October 15, 2021

Bayesian approaches to associative learning: from passive to active learning.

John K Kruschke1

  • 1Department of Psychological and Brain Sciences, Indiana University, Bloomington, Indiana 47405-7007, USA. kruschke@indiana.edu

Learning & Behavior
|August 8, 2008
PubMed
Summary
This summary is machine-generated.

Bayesian models offer a more nuanced view of learning than traditional associationist models, enabling active exploration for optimal knowledge acquisition. New research shows these models make distinct predictions, with some experimental evidence contradicting Kalman filter models.

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Appetitive Associative Olfactory Learning in Drosophila Larvae
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Last Updated: Jul 3, 2026

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

  • Cognitive Science
  • Computational Neuroscience
  • Machine Learning

Background:

  • Traditional associationist models use single association strengths, assuming passive learners.
  • Bayesian models represent knowledge as belief distributions, allowing for active learning.

Purpose of the Study:

  • Review Bayesian accounts of backward blocking, a challenge for traditional theories.
  • Analyze two formalizations of optimal active learning: maximizing information gain or probability gain.

Main Methods:

  • Review of existing Bayesian models for backward blocking.
  • Analysis of active learning strategies using Kalman filter and noisy-logic gate models.

Main Results:

  • Bayesian models provide an alternative to traditional associationist accounts.
  • Kalman filter and noisy-logic gate models yield different predictions for active learning.
  • Experimental data disconfirms Kalman filter predictions in at least one scenario.

Conclusions:

  • Bayesian frameworks offer a powerful approach to understanding learning and knowledge representation.
  • Active learning strategies in Bayesian models have testable implications.
  • Further research is needed to refine active learning models based on empirical findings.