MouseView.js: Reliable and valid attention tracking in web-based experiments using a cursor-directed aperture

Alexander L. Anwyl-Irvine*, Thomas Armstrong, Edwin S. Dalmaijer

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

Abstract

Psychological research is increasingly moving online, where web-based studies allow for data collection at scale. Behavioural researchers are well supported by existing tools for participant recruitment, and for building and running experiments with decent timing. However, not all techniques are portable to the Internet: While eye tracking works in tightly controlled lab conditions, webcam-based eye tracking suffers from high attrition and poorer quality due to basic limitations like webcam availability, poor image quality, and reflections on glasses and the cornea. Here we present MouseView.js, an alternative to eye tracking that can be employed in web-based research. Inspired by the visual system, MouseView.js blurs the display to mimic peripheral vision, but allows participants to move a sharp aperture that is roughly the size of the fovea. Like eye gaze, the aperture can be directed to fixate on stimuli of interest. We validated MouseView.js in an online replication (N = 165) of an established free viewing task (N = 83 existing eye-tracking datasets), and in an in-lab direct comparison with eye tracking in the same participants (N = 50). Mouseview.js proved as reliable as gaze, and produced the same pattern of dwell time results. In addition, dwell time differences from MouseView.js and from eye tracking correlated highly, and related to self-report measures in similar ways. The tool is open-source, implemented in JavaScript, and usable as a standalone library, or within Gorilla, jsPsych, and PsychoJS. In sum, MouseView.js is a freely available instrument for attention-tracking that is both reliable and valid, and that can replace eye tracking in certain web-based psychological experiments.
Original languageEnglish
Number of pages25
JournalBehavior Research Methods
Early online date29 Sep 2021
DOIs
Publication statusE-pub ahead of print - 29 Sep 2021

Bibliographical note

Funding Information:
This study was funded by Whitman College's Technology Experimentation Fund. ALAI and ESD are supported by the Templeton World Charity Foundation (grant TWCF0159) and the UK Medical Research Council (grant MC-A0606-5PQ41).

Funding Information:
We are grateful to Dr Becky Gilbert for advice on jsPsych integration, to Dr William Webster for Gorilla integration, and to Dr Thomas Pronk and Dr Rebecca Hirst for PsychoJS integration and documentation. We thank the following students for their help with data collection: Jessica Bowlus, Zoe Brown, Grace Hammerlund, Daniel Leong, Nomonde Nyathi, Sam Patterson, Devi Payne, and Julia Schillings. This study was funded by Whitman College's Technology Experimentation Fund. ALAI and ESD are supported by the Templeton World Charity Foundation (grant TWCF0159) and the UK Medical Research Council (grant MC-A0606-5PQ41).

Publisher Copyright:
© 2021, The Author(s).

Keywords

  • Attention
  • cyberpsychology
  • eye tracking
  • JavaScript
  • online experiments
  • open-source

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