Pupillometric and blink measures of diverse task loads

Implications for working memory models

Bibliographic Data

ID5264263
AuthorsSiyuan Chen (0000-0002-3118-5963, University of New South Wales Sydney New South Wales Australia, corresponding author), Julien Epps (0000-0001-6624-5551, University of New South Wales Sydney New South Wales Australia), Fred Paas (0000-0002-1647-5305, Erasmus University Rotterdam Rotterdam The Netherlands)
Year2023
Volume93
IssueS2
Pages318-338
Publication date2023-08-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueBritish Journal of Educational Psychology (JOURNAL)
Journal identifiersISSN: 0007-0998 • E-ISSN: 2044-8279
PublisherWiley (PUBLISHER • GB)
DOI10.1111/bjep.12577
PMID36572995
OpenAlexW4312210690
LanguageEN
Citations received4
References cited46

BackgroundInconsistent observations of pupillary response and blink change in response to different specific tasks raise questions regarding the relationship between eye measures, task types and working memory (WM) models. On the one hand, studies have provided mixed evidence from eye measures about tasks: pupil size has mostly been reported to increase with increasing task demand while this expected change was not observed in some studies, and blink rate has exhibited different trends in different tasks. On the other hand, a WM model has been developed to integrate a component to reconcile recent findings that the human motor system plays an important role in cognition and learning. However, how different tasks correlate with WM components has not been experimentally examined using eye activity measurements.AimsThe current study uses a four-dimensional task load framework to bridge eye measures, task types and WM models.SampleTwenty participants (10 males, 10 females; Age: M = 25.8, SD = 7.17) above 18 years old volunteered. All participants had normal or corrected to normal vision with contact lenses and had no eye diseases causing obvious excessive blinking.MethodsWe examined the ability of pupil size and blink rate to index low and high levels of cognitive, perceptual, physical and communicative task load. A network of the four load types and WM components was built and analysed to verify the necessity of integrating a physical task-related component into the WM model.ResultsResults demonstrate that pupil size can index cognitive load and communicative load but not perceptual or physical load. Blink rate can index the level of cognitive load but is best at discriminating perceptual tasks from other types of tasks. Furthermore, pupil size measurement of the four task types was explained better during structural and factor analysis by a WM model that integrates a movement-related component.ConclusionsThis research provides new insights into the relationship between eye measures, task type and WM models and provides a comprehensive understanding from which to predict pupil size and blink behaviours in more complex and practical tasks

Cognitive psychology · Task (project management) · Engineering · Gaze Tracking and Assistive Technology · Mind wandering and attention · Ocular Surface and Contact Lens · Psychology

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