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

Behavior Modification01:21

Behavior Modification

403
Behavioral approaches have often been criticized for ignoring mental processes and focusing solely on observable behavior. However, these approaches provide an optimistic perspective for individuals seeking to change their behaviors. Rather than concentrating on intrinsic personality traits, behavioral approaches suggest that even longstanding habits can be modified by changing the reward contingencies that maintain them.
A real-world application of operant conditioning principles is applied...
403
Behaviorism01:28

Behaviorism

4.0K
The field of behaviorism was pioneered by figures such as Ivan Pavlov, John B. Watson, and B.F. Skinner fundamentally shifted the focus of psychology to the observable and controllable aspects of human and animal behavior. This shift marked a critical evolution in the discipline, emphasizing scientific rigor and experimental methodology.
The core premise of behaviorism is its focus on observable behavior rather than internal thoughts or feelings. This approach argues that true scientific...
4.0K
Behavioral Genetics and Its Designs01:23

Behavioral Genetics and Its Designs

777
Behavior genetics explores how genetic inheritance influences human behavior. It focuses on how genes, passed from parents to offspring, contribute to the development of behavioral traits and tendencies. This branch of genetics seeks to understand the complex interplay between inherited genetic factors and environmental influences in shaping our behaviors.
The primary methodologies used in behavior genetics include family studies, twin studies, and adoption studies, each providing unique...
777
Law of Effect01:06

Law of Effect

2.0K
B.F. Skinner, a prominent figure in behavioral psychology, introduced operant conditioning by emphasizing the role of consequences in shaping behavior. This theory builds upon the law of effect proposed by Edward Thorndike, which posits that behaviors followed by satisfying outcomes are likely to be repeated. In contrast, those followed by unsatisfying outcomes are less likely to recur.
Edward Thorndike's foundational work involved studying learning in animals, particularly using puzzle...
2.0K
Introduction to Learning01:18

Introduction to Learning

706
Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
706
Real-World Application of Classical Conditioning01:15

Real-World Application of Classical Conditioning

987
Classical conditioning not only includes the initial pairing of stimuli but also extends to more complex forms, such as higher-order conditioning. Higher-order conditioning involves creating associations beyond the primary conditioned stimulus, resulting in a chain of conditioned responses.
Higher-order, or second-order, conditioning occurs when a neutral stimulus becomes associated with an already established conditioned stimulus through repeated pairings. For instance, if a dog has been...
987

You might also read

Related Articles

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

Sort by
Same author

A pilot study of the <i>Watch Me Walk</i> program to increase the level of physical activity of older adults with intellectual disabilities.

Journal of intellectual disabilities : JOID·2026
Same author

Exploring Physical Activity Engagement and Related Variables During Pregnancy and Postpartum and the Best Practices for Self-Report Physical Activity Postpartum.

International journal of environmental research and public health·2025
Same author

Machine Learning to Detect Vocal Stereotypy: Improving Duration-Based Measures.

Behavior modification·2025
Same author

Natural Setting Interventions to Increase Physical Activity Level in Older Adults With Intellectual Disabilities: A Systematic Review.

Journal of applied research in intellectual disabilities : JARID·2025
Same author

Machine learning to detect schedules using spatiotemporal data of behavior: A proof of concept.

Journal of the experimental analysis of behavior·2025
Same author

Making physical activity fun and accessible to adults with intellectual disabilities: A pilot study of a gamification intervention.

Journal of applied research in intellectual disabilities : JARID·2024
Same journal

A Mediational Theory of Verbal Relations.

Perspectives on behavior science·2026
Same journal

It is Time to Retire "Noncontingent Reinforcement".

Perspectives on behavior science·2026
Same journal

Using Wearable Technology to Predict the Occurrence of Severe Behavior Problems among Neurodiverse Individuals: A Systematic Review.

Perspectives on behavior science·2026
Same journal

Toward a Modern View of Pavlovian Conditioning in Applied Behavior Analysis.

Perspectives on behavior science·2026
Same journal

Behavior, Process, and Evolution in the Multiscale Molar Paradigm.

Perspectives on behavior science·2026
Same journal

Citing the Literature.

Perspectives on behavior science·2026
See all related articles

Related Experiment Video

Updated: Nov 23, 2025

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.7K

Tutorial: Applying Machine Learning in Behavioral Research.

Stéphanie Turgeon1, Marc J Lanovaz1,2

  • 1École de psychoéducation, Université de Montréal, C.P. 6128, succursale Centre-Ville, Montreal, QC H3C 3J7 Canada.

Perspectives on Behavior Science
|December 31, 2020
PubMed
Summary
This summary is machine-generated.

This tutorial introduces machine learning (ML) algorithms for behavior analysis researchers. It demonstrates applying ML methods to identify parents of children with autism who need behavior analytic web training.

Keywords:
Artificial intelligenceBehavior analysisMachine learningTutorial

More Related Videos

Decoding Natural Behavior from Neuroethological Embedding
08:00

Decoding Natural Behavior from Neuroethological Embedding

Published on: October 3, 2025

311
Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
10:43

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

Published on: June 10, 2021

5.6K

Related Experiment Videos

Last Updated: Nov 23, 2025

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis
05:41

A Step-by-Step Implementation of DeepBehavior, Deep Learning Toolbox for Automated Behavior Analysis

Published on: February 6, 2020

9.7K
Decoding Natural Behavior from Neuroethological Embedding
08:00

Decoding Natural Behavior from Neuroethological Embedding

Published on: October 3, 2025

311
Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
10:43

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

Published on: June 10, 2021

5.6K

Area of Science:

  • Behavior analysis
  • Machine learning
  • Applied behavior analysis

Background:

  • Machine-learning (ML) algorithms can enhance decision-making in education and clinical practice.
  • Behavior analysis researchers have been slow to adopt ML methodologies.
  • Lack of ML training in behavior analysis programs may explain this gap.

Purpose of the Study:

  • To promote increased research using ML in behavior analysis.
  • To provide a tutorial on applying ML algorithms for behavior analysis researchers.
  • To address the barrier of ML not being a standard part of behavior analysis training.

Main Methods:

  • Demonstration of applying four ML algorithms: random forest, support vector machine, stochastic gradient descent, and k-nearest neighbors.
  • Application of algorithms on a small dataset.
  • Step-by-step guidance for implementation.

Main Results:

  • The tutorial successfully demonstrates the application of ML algorithms.
  • The methods presented can identify parents of children with autism who would benefit from behavior analytic web training.
  • The step-by-step approach facilitates the implementation of ML for novel research.

Conclusions:

  • This tutorial aims to increase the adoption of ML in behavior analysis research.
  • Researchers can use these methods to apply ML to new research questions and datasets.
  • Facilitating ML implementation can advance the understanding and application of behavior analysis.