Cognitive load and visual attention assessment using physiological eye tracking measures in multimedia learning

Effective multimedia content design can boost performance, capture visual attention, and optimize cognitive load. The current study employs eye-tracking technology to establish metrics to measure cognitive load, analyze visual attention allocation, and evaluate learners' performance in English language learning. The study focuses on creating and comparing two different multimedia presentations. The differentiation between them lies in their adherence to or deviation from Mayer's educational multimedia design principles: coherence, signaling, and spatial contiguity. participants were randomly assigned to two groups. The first group viewed with principles version, while the second group viewed without principles version, during which their eye movement data were collected. Subsequently, both groups participated in a recall test and completed the NASA-TLX questionnaire. The research establishes connections between specific eye-tracking parameters, subjective cognitive load scores, and recall test results through regression models and analyzes fixation distributions. The study also delves into microsaccades rate and changes in pupil size, each analyzed within times of interest. The study's findings indicate that the examined metrics can significantly help distinguish between the two conditions: principles and no principles. These metrics are pertinent for assessing individuals' cognitive load and visual attention and serve as beneficial indicators for gauging the efficacy of the designed multimedia content.

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Publication Details

Journal
PLoS ONE
Published
2025-12-01
DOI
https://doi.org/10.1371/journal.pone.0337195
Primary Topic
Visual and Cognitive Learning Processes
Type
article
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article

Cognitive load and visual attention assessment using physiological eye tracking measures in multimedia learning

Reza Ebrahimpour, Alireza Bosaghzadeh, S. Hamid Amiri, Fatemeh Shahnabati et al.
PLoS ONE
Visual and Cognitive Learning Processes
article

Cognitive load and visual attention assessment using physiological eye tracking measures in multimedia learning

Reza Ebrahimpour, Alireza Bosaghzadeh, S. Hamid Amiri, Fatemeh Shahnabati, Atefeh Sabourifard
article en

Abstract

Effective multimedia content design can boost performance, capture visual attention, and optimize cognitive load. The current study employs eye-tracking technology to establish metrics to measure cognitive load, analyze visual attention allocation, and evaluate learners' performance in English language learning. The study focuses on creating and comparing two different multimedia presentations. The differentiation between them lies in their adherence to or deviation from Mayer's educational multimedia design principles: coherence, signaling, and spatial contiguity. participants were randomly assigned to two groups. The first group viewed with principles version, while the second group viewed without principles version, during which their eye movement data were collected. Subsequently, both groups participated in a recall test and completed the NASA-TLX questionnaire. The research establishes connections between specific eye-tracking parameters, subjective cognitive load scores, and recall test results through regression models and analyzes fixation distributions. The study also delves into microsaccades rate and changes in pupil size, each analyzed within times of interest. The study's findings indicate that the examined metrics can significantly help distinguish between the two conditions: principles and no principles. These metrics are pertinent for assessing individuals' cognitive load and visual attention and serve as beneficial indicators for gauging the efficacy of the designed multimedia content.

PLoS ONEVol. 20(12)
Sharif University of Technology (IR), Institute for Cognitive Science Studies (IR), Institute for Research in Fundamental Sciences (IR), Shahid Rajaee Teacher Training University (IR)
Openalex Percentile: Top 60%
Visual and Cognitive Learning Processes
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