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

You might also read

Related Articles

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

Sort by
Same author

Investigation of an Optimal Material Addition Rate for Energy Consumption and Dimensional Accuracy in Fused Filament Fabrication of CFR-PEEK.

Polymers·2024
Same author

Automated and Continuous Fatigue Monitoring in Construction Workers Using Forearm EMG and IMU Wearable Sensors and Recurrent Neural Network.

Sensors (Basel, Switzerland)·2022
Same author

The Double-Edged Sword of Safety Training for Safety Behavior: The Critical Role of Psychological Factors during COVID-19.

International journal of environmental research and public health·2022
Same author

Simulating energy consumption based on material addition rates for material extrusion of CFR-PEEK: a trade-off between energy costs and cycle time.

The International journal, advanced manufacturing technology·2022
Same author

Data Quality and Reliability Assessment of Wearable EMG and IMU Sensor for Construction Activity Recognition.

Sensors (Basel, Switzerland)·2020

Related Experiment Video

Updated: Nov 15, 2025

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

Industrial Energy Assessment Training Effectiveness Evaluation: An Eye-Tracking Study.

Laleh Ghanbari1,2, Chao Wang1,2, Hyun Woo Jeon2,3

  • 1Bert S. Turner Department of Construction Management, Louisiana State University, 3319 Patrick F. Taylor Hall, Baton Rouge, LA 70803, USA.

Sensors (Basel, Switzerland)
|March 6, 2021
PubMed
Summary

Eye-tracking technology quantitatively evaluated industrial energy assessment training effectiveness. Trainees showed improved performance in production, recycling, and waste management, reaching expert knowledge levels in identifying energy-saving opportunities.

Keywords:
energy efficiencyeye-trackingindustrial energy assessmenttraining effectivenessvisual attention behavior

More Related Videos

Eye Tracking During A Complex Aviation Task For Insights Into Information Processing
07:48

Eye Tracking During A Complex Aviation Task For Insights Into Information Processing

Published on: April 4, 2025

881
Loneliness Assuaged: Eye-Tracking an Audience Watching Barrage Videos
06:45

Loneliness Assuaged: Eye-Tracking an Audience Watching Barrage Videos

Published on: May 29, 2020

4.4K

Related Experiment Videos

Last Updated: Nov 15, 2025

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
Eye Tracking During A Complex Aviation Task For Insights Into Information Processing
07:48

Eye Tracking During A Complex Aviation Task For Insights Into Information Processing

Published on: April 4, 2025

881
Loneliness Assuaged: Eye-Tracking an Audience Watching Barrage Videos
06:45

Loneliness Assuaged: Eye-Tracking an Audience Watching Barrage Videos

Published on: May 29, 2020

4.4K

Area of Science:

  • Educational Technology
  • Industrial Engineering
  • Human-Computer Interaction

Background:

  • Evaluating training program effectiveness is crucial for improvement.
  • Eye-tracking technology offers a quantitative method to assess visual attention and learning.
  • Limited research exists on applying eye-tracking in industrial energy assessment training.

Purpose of the Study:

  • To quantitatively evaluate the effectiveness of industrial energy assessment training using eye-tracking technology.
  • To identify specific areas within the training that require further focus.
  • To assess the impact of the training on trainees' ability to identify energy-saving opportunities.

Main Methods:

  • Utilized eye-tracking technology to measure attentional allocation of trainees during industrial energy assessment training.
  • Conducted the study in a controlled environment to minimize external distractions.
  • Evaluated subject performance post-training to identify areas needing more attention.

Main Results:

  • Trainees demonstrated significant performance improvements in production and recycling/waste management post-training.
  • The training program successfully enhanced participants' knowledge of energy-saving opportunities.
  • Trainee knowledge levels in identifying energy-saving opportunities reached those of experienced participants.

Conclusions:

  • Eye-tracking is a viable tool for quantitatively assessing the effectiveness of industrial energy assessment training.
  • The developed training program is effective in improving key areas of energy assessment and knowledge acquisition.
  • The study provides a foundation for further research into optimizing industrial energy assessment training using objective measures.