Statistical Analysis of Eye Movement Data for Beginners

Data processing and (statistical) data analysis are important tasks in empirical research. However, they present a particular hurdle for beginners. For one, they require knowledge of statistical methods, their prerequisites, or use cases; For another, one needs either programming skills or some software system to carry out the analyses efficiently. Empirical eye tracking research poses a further hurdle; Data from an eye tracker is processed more elaborately and usually merged with data from other sources (e.g., questionnaires). In this article, we take a closer look at the possibilities that prospective eye tracking researchers have on their way from data collection to publication-ready analysis. We show that there is currently no software system that allows valid statistical analyses of eye tracking data to be performed without prior knowledge – which means that prospective eye tracking researchers need to learn or be taught the basics before performing actual analyses. As a solution, we present a novel tool: eyenalyzer. It guides through the analysis process – even without prior knowledge and therefore suitable for beginners. In the article, after highlighting the need for the tool, we discuss its development, give a glimpse at the user interface, and point out contribution and future work.

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Publication Details

Published
2024-08-26
DOI
https://doi.org/10.1145/3670653.3670678
Citations
2
Primary Topic
Gaze Tracking and Assistive Technology
Type
article
Field-Weighted Citation Impact
0.74
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article

Statistical Analysis of Eye Movement Data for Beginners

Lisa Grabinger, Jürgen Horst Mottok
2 citations
Gaze Tracking and Assistive Technology
0.74
article

Statistical Analysis of Eye Movement Data for Beginners

Lisa Grabinger, Jürgen Horst Mottok
article en
2 citations

Abstract

Data processing and (statistical) data analysis are important tasks in empirical research. However, they present a particular hurdle for beginners. For one, they require knowledge of statistical methods, their prerequisites, or use cases; For another, one needs either programming skills or some software system to carry out the analyses efficiently. Empirical eye tracking research poses a further hurdle; Data from an eye tracker is processed more elaborately and usually merged with data from other sources (e.g., questionnaires). In this article, we take a closer look at the possibilities that prospective eye tracking researchers have on their way from data collection to publication-ready analysis. We show that there is currently no software system that allows valid statistical analyses of eye tracking data to be performed without prior knowledge – which means that prospective eye tracking researchers need to learn or be taught the basics before performing actual analyses. As a solution, we present a novel tool: eyenalyzer. It guides through the analysis process – even without prior knowledge and therefore suitable for beginners. In the article, after highlighting the need for the tool, we discuss its development, give a glimpse at the user interface, and point out contribution and future work.

OTH Regensburg (DE)
Openalex Percentile: Top 29%
Gaze Tracking and Assistive Technology
0.74
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