Predicting Properties of Cognitive Pupillometry in Human–Computer Interaction: A Preliminary Investigation

Pierre-Majorique Léger (), Patrick Charland (), Sylvain Sénécal () and Stéphane Cyr ()
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Pierre-Majorique Léger: HEC Montréal
Patrick Charland: Université du Québec à Montréal
Sylvain Sénécal: HEC Montréal
Stéphane Cyr: Université du Québec à Montréal

A chapter in Information Systems and Neuroscience, 2018, pp 121-127 from Springer

Abstract: Abstract This paper aims to investigate the predictive property of pupil dilation in an IT-related task. Previous work in the field of cognitive pupillometry has established that pupil size is associated with cognitive load. We conducted a within-subject experiment with 22 children aged between 7 and 9. For the hard questions, visit duration, pupil size and its quadratic effect were significant predictors. We discuss the potential of using this unobtrusive approach for neuro-adaptive and auto-adaptive applications.

Keywords: Eye-tracking; Pupillometry; Cognitive load; HCI—learning (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-319-67431-5_14

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DOI: 10.1007/978-3-319-67431-5_14

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