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

Decision Making: Traditional Method01:14

Decision Making: Traditional Method

The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
Reason and Intuition01:37

Reason and Intuition

The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the brain can only use...
Decision Making01:20

Decision Making

Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
Decision Making: P-value Method01:09

Decision Making: P-value Method

The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can have a...

You might also read

Related Articles

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

Sort by
Same author

Computational Modeling of the Effects of Sleep Deprivation on the Vigilance Decrement.

Human factors·2019
Same author

Intuitive Cognition and Models of Human-Automation Interaction.

Human factors·2017
Same author

The Hepatocyte Growth Factor/c-Met Antagonist, Divalinal-Angiotensin IV, Blocks the Acquisition of Methamphetamine Dependent Conditioned Place Preference in Rats.

Brain sciences·2014
Same author

The metabolic syndrome and coronary artery disease: a structural equation modeling approach suggestive of a common underlying pathophysiology.

Metabolism: clinical and experimental·2012
Same author

Modeling the simulated real-world optic flow motion aftereffect.

Journal of the Optical Society of America. A, Optics, image science, and vision·2009
Same author

Oculomotor contribution to the change in perceived speed with viewing distance.

Journal of the Optical Society of America. A, Optics, image science, and vision·2008

Related Experiment Video

Updated: May 11, 2026

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
06:28

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Published on: August 26, 2018

Training intuitive decision making in a simulated real-world environment.

Robert Earl Patterson1, Byron J Pierce, Alan S Boydstun

  • 1Air Force Research Laboratory, RHA/711 HPW Wright-Patterson AFB, OH 45433, USA. Robert.Patterson@wpafb.af.mil

Human Factors
|May 23, 2013
PubMed
Summary

Intuitive decision making, defined as pattern recognition, can be developed through implicit statistical learning in simulated environments. This process is engaged by naturalistic scenes and can be trained effectively.

Related Experiment Videos

Last Updated: May 11, 2026

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
06:28

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Published on: August 26, 2018

Area of Science:

  • Cognitive Psychology
  • Neuroscience
  • Human-Computer Interaction

Background:

  • The causal role of implicit learning in developing intuitive decision-making, specifically pattern recognition in real-world or simulated environments, remains underexplored.
  • Existing research lacks definitive studies demonstrating implicit learning's impact on intuitive decision-making processes.

Purpose of the Study:

  • To investigate if implicit statistical learning can develop intuitive decision-making skills within a simulated real-world environment.
  • To determine the efficacy of implicit learning in fostering pattern recognition-based decision-making.

Main Methods:

  • A dynamic simulated environment was used to create a sense of simulated locomotion.
  • Participants passively observed object sequences during training and made intuitive decisions on related/unrelated sequences during testing.
  • Articulatory suppression was employed to assess the impact on working memory and training effectiveness.

Main Results:

  • Implicit learning was shown to effectively train intuitive decision-making capabilities.
  • Working memory, affected by articulatory suppression, significantly inhibited the training of intuitive decision-making.
  • Training in the simulated environment demonstrated full transferability to a flat display, unlike the reverse.

Conclusions:

  • Intuitive decision-making is fundamentally developed through implicit learning processes.
  • The engagement of implicit learning is facilitated by the inherent meaning within naturalistic scenes.
  • Implicit learning offers a viable method for training and enhancing intuitive decision-making skills.