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https://doi.org/10.2139/ssrn.6...
Article . 2026 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2025
License: CC BY
Data sources: Datacite
DBLP
Preprint . 2025
Data sources: DBLP
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Eye-Tracking and Biometric Feedback in UX Research: Measuring User Engagement and Cognitive Load

Authors: Aaditya Shankar Majumder;

Eye-Tracking and Biometric Feedback in UX Research: Measuring User Engagement and Cognitive Load

Abstract

User experience (UX) research has traditionally relied on subjective methods like surveys and interviews, yet these often fail to capture the subconscious dimensions of user interaction. This study explores integrating eye-tracking and biometric feedback-physiological tools that measure gaze behaviour and bodily responses-as robust methods for assessing user engagement and cognitive load in digital interfaces. Drawing on empirical evidence, practical applications, and recent advancements from 2023-2025, we argue that these technologies provide a granular, objective lens into user behaviour, complementing qualitative insights. We present new experimental data, detail our methodology, and situate our work within both foundational and contemporary literature. Challenges such as data interpretation, ethical considerations, and technological integration are addressed, positioning these tools as pivotal for advancing UX design in an increasingly complex digital landscape.

Keywords

FOS: Computer and information sciences, Computer Science - Human-Computer Interaction, Human-Computer Interaction (cs.HC)

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Top 10%
Average
Average
Green