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Front Psychol. 2018 May 23;9:803. doi: 10.3389/fpsyg.2018.00803. eCollection 2018.

An Examination of Recording Accuracy and Precision From Eye Tracking Data From Toddlerhood to Adulthood.

Frontiers in psychology

Kirsten A Dalrymple, Marie D Manner, Katherine A Harmelink, Elayne P Teska, Jed T Elison

Affiliations

  1. Institute of Child Development, College of Education and Human Development, University of Minnesota, Minneapolis, MN, United States.
  2. Department of Computer Science & Engineering, College of Science & Engineering, University of Minnesota, Minneapolis, MN, United States.
  3. Department of School Counseling, School of Education, North Dakota State University, Fargo, ND, United States.
  4. Department of Comparative Human Development, University of Chicago, Chicago, IL, United States.
  5. Department of Pediatrics, University of Minnesota Medical School, University of Minnesota, Minneapolis, MN, United States.

PMID: 29875727 PMCID: PMC5974590 DOI: 10.3389/fpsyg.2018.00803

Abstract

The quantitative assessment of eye tracking data quality is critical for ensuring accuracy and precision of gaze position measurements. However, researchers often report the eye tracker's optimal manufacturer's specifications rather than empirical data about the accuracy and precision of the eye tracking data being presented. Indeed, a recent report indicates that less than half of eye tracking researchers surveyed take the eye tracker's accuracy into account when determining areas of interest for analysis, an oversight that could impact the validity of reported results and conclusions. Accordingly, we designed a calibration verification protocol to augment independent quality assessment of eye tracking data and examined whether accuracy and precision varied between three age groups of participants. We also examined the degree to which our externally quantified quality assurance metrics aligned with those reported by the manufacturer. We collected data in standard laboratory conditions to demonstrate our method, to illustrate how data quality can vary with participant age, and to give a simple example of the degree to which data quality can differ from manufacturer reported values. In the sample data we collected, accuracy for adults was within the range advertised by the manufacturer, but for school-aged children, accuracy and precision measures were outside this range. Data from toddlers were less accurate and less precise than data from adults. Based on an

Keywords: calibration; development; eye tracking; methods; quality assessment; toddlers

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