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Updated: Dec 19, 2025

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Best practices in eye tracking research.

Benjamin T Carter1, Steven G Luke1

  • 1Brigham Young University, United States of America.

International Journal of Psychophysiology : Official Journal of the International Organization of Psychophysiology
|June 7, 2020
PubMed
Summary
This summary is machine-generated.

This guide details best practices for eye tracking research across disciplines. It covers eye movement basics, research applications, technology, data, and reporting standards for valid studies.

Keywords:
Best practicesEye movementsEye trackingOpen SciencePupillometry

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Area of Science:

  • Behavioral Science
  • Cognitive Science
  • Human-Computer Interaction
  • Neuroscience
  • Psychology

Background:

  • Eye tracking technology offers insights into visual attention and cognitive processes.
  • Understanding eye movements is crucial for various research fields.

Purpose of the Study:

  • To provide a comprehensive guide on best practices for eye tracking research.
  • To outline the fundamental principles, applications, and methodological considerations of eye tracking.

Main Methods:

  • Review of eye tracking technology principles, including eye anatomy and physiology.
  • Explanation of data generation, selection of equipment, and appropriate measures.
  • Discussion of validity challenges and recommendations for robust study design.

Main Results:

  • Eye tracking generates valuable data on visual behavior and cognitive load.
  • Proper selection and use of equipment and measures are key to valid results.
  • Addressing validity challenges enhances the reliability of eye tracking findings.

Conclusions:

  • Adherence to best practices ensures the validity and reliability of eye tracking research.
  • Standardized reporting is essential for the reproducibility and comparability of studies.
  • This guide serves as a resource for researchers across diverse disciplines seeking to utilize eye tracking effectively.