Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

High-Level and Low-Level Awareness

High-Level and Low-Level Awareness

Controlled processes in human consciousness represent high-alert mental states where individuals deliberately focus their attention on achieving specific goals. Controlled processes can be seen in situations like mastering new technology, where a person might become so absorbed that they ignore surrounding distractions. Such processes involve selective attention, requiring one to concentrate on particular elements of experience while disregarding others. These are governed by executive...

You might also read

Related Articles

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

Sort by

Same author

Loss of ZmDMP increases phosphatidic acid production and disrupts lipid homeostasis in maize sperm cells.

Plant physiology·2026

Same author

Quantitative Assessment of Third Molar Extraction Difficulty and Nerve Injury Risk Using Artificial Intelligence and Image Processing.

Annals of biomedical engineering·2026

Same author

Ginger extract and selenium supplementation: A promising approach to improve diabetic retinopathy.

Molecular vision·2026

Same author

Theoretical perspective on synthetic man-made life: Learning from the origin of life.

Quantitative biology (Beijing, China)·2026

Same author

The effect of exercise intervention on prosocial behavior in junior high school students: the chain mediation effect of empathy and interpersonal relationships.

Frontiers in psychology·2026

Same author

The Effects of Physical Exercise on Adolescents' School Adjustment and Path Analysis-Evidence from the China Education Panel Survey.

Behavioral sciences (Basel, Switzerland)·2025

Search research articles

Related Experiment Video

Updated: Jun 29, 2025

Combining Behavior and EEG to Study the Effects of Mindfulness Meditation on Episodic Memory

Combining Behavior and EEG to Study the Effects of Mindfulness Meditation on Episodic Memory

Published on: May 11, 2020

EEG complexity measures for detecting mind wandering during video-based learning.

Shaohua Tang^1,2,3, Zheng Li⁴

¹School of Systems Science, Beijing Normal University, Beijing, China.

Scientific Reports

|April 8, 2024

Summary

This summary is machine-generated.

This study shows that EEG complexity measures, like multiscale permutation entropy (MPE), can detect mind wandering during learning. These methods offer practical insights for educational technology and brain-computer interfaces.

More Related Videos

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control

Published on: July 5, 2015

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography

Published on: June 15, 2018

Related Experiment Videos

Last Updated: Jun 29, 2025

Combining Behavior and EEG to Study the Effects of Mindfulness Meditation on Episodic Memory

Combining Behavior and EEG to Study the Effects of Mindfulness Meditation on Episodic Memory

Published on: May 11, 2020

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control

Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control

Published on: July 5, 2015

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography

Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography

Published on: June 15, 2018

Area of Science:

Neuroscience
Cognitive Science
Educational Technology

Background:

Mind wandering (MW) during learning reduces educational outcomes.
Detecting MW using electroencephalography (EEG) is crucial for adaptive learning systems.
Traditional EEG features may not fully capture the neural dynamics of MW.

Purpose of the Study:

To evaluate the efficacy of EEG complexity measures for detecting mind wandering.
To compare complexity metrics with traditional band power features.
To explore the practical application of MW detection in video-based learning.

Main Methods:

Utilized a modified probe-caught method to record EEG data during video learning.
Investigated EEG complexity metrics such as multiscale permutation entropy (MPE) and detrended fluctuation analysis (DFA).
Compared complexity metrics against traditional band power (BP) features, employing data augmentation and feature selection.

Main Results:

Band power (BP) features achieved a mean AUC of 0.646 without eye-movement artifacts.
Multiscale permutation entropy (MPE) showed comparable performance (mean AUC 0.639) without artifact removal.
Combining all features improved detection accuracy to a mean AUC of 0.66.

Conclusions:

EEG complexity measures show promise for detecting mind wandering.
MPE offers a viable alternative to BP features, especially when artifact removal is challenging.
These findings have significant implications for developing intelligent tutoring systems and enhancing educational engagement.