Assessing Cognitive Load Using EEG and Eye-Tracking in 3-D Learning Environments: A Systematic Review

Publication date

2025-09

Authors

Khan, Rozemun
Vernooij, HansORCID 0000-0002-2646-9216ISNI 0000000419500013
Salvatori, DanielaORCID 0009-0005-3006-8502ISNI 0000000507309585
Hierck, Beerend P.ISNI 0000000391184871

Editors

Advisors

Supervisors

Document Type

Article
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License

cc_by

Abstract

The increasing use of immersive 3-D technologies in education raises critical questions about their cognitive impact on learners. This systematic review evaluates how electroencephalography (EEG) and eye-tracking have been used to objectively measure cognitive load in 3-D learning environments. We conducted a comprehensive literature search (2009–2025) across PubMed, Scopus, Web of Science, PsycInfo, and ERIC, identifying 51 studies that used EEG or eye-tracking in experimental contexts involving stereoscopic or head-mounted 3-D technologies. Our findings suggest that 3-D environments may enhance learning and engagement, particularly in spatial tasks, while affecting cognitive load in complex, task-dependent ways. Studies reported mixed patterns across psychophysiological measures, including spectral features (e.g., frontal theta, parietal alpha), workload indices (e.g., theta/alpha ratio), and gaze-based metrics (e.g., fixation duration, pupil dilation): some studies observed increased load, while others reported reductions or no difference. These discrepancies reflect methodological heterogeneity and underscore the value of time-sensitive assessments. While a moderate cognitive load supports learning, an excessive load may impair performance, and overload thresholds can vary across individuals. EEG and eye-tracking offer scalable methods for monitoring cognitive effort dynamically. Overall, 3-D and XR technologies hold promise but must be aligned with task demands and learner profiles and guided by real-time indicators of cognitive load in immersive environments.

Keywords

3-D learning environments, cognitive load, EEG, eye-tracking, immersive technologies, multimodal measurement, psychophysiology, spatial learning, XR in education, Neuroscience (miscellaneous), Human-Computer Interaction, Computer Science Applications, Computer Networks and Communications

Citation

Khan, R, Vernooij, J, Salvatori, D & Hierck, B P 2025, 'Assessing Cognitive Load Using EEG and Eye-Tracking in 3-D Learning Environments : A Systematic Review', Multimodal Technologies and Interaction, vol. 9, no. 9, 99. https://doi.org/10.3390/mti9090099