International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 8 Issue 3
May-June 2026
Indexing Partners
Real-Time Cognitive Load-Adaptive Data Visualization Using On-Device Gaze Metrics
| Author(s) | Pinaki Bose |
|---|---|
| Country | United States |
| Abstract | Data visualizations are indispensable tools designed to enhance human cognition and facilitate the interpretation of complex information. They serve as a crucial bridge between raw data and actionable understanding, aiming to simplify intricate datasets for human comprehension. However, the inherent effectiveness of these visualizations is profoundly influenced by individual differences in cognitive abilities, personality traits, and prior experiences. A critical limitation in current personalization efforts for data visualization is their frequent reliance on static user profiles or generalized models, rather than dynamic, real-time assessments of an individual's cognitive state.This deficiency highlights a fundamental need for a more responsive and adaptive approach.The shift from a static, universal design to hyper-personalization in data visualization is not merely an enhancement; it is a fundamental requirement driven by the inherent variability in human cognitive processing and the finite capacity of human working memory. To optimize cognitive resources for effective data interpretation, visualizations must dynamically adjust to the user's immediate mental state, minimizing unproductive mental effort and maximizing genuine understanding and insight generation. |
| Keywords | Cognitive Load, Data Visualization, Gaze Metrics , Real-Time Adaptation, Hyper-Personalization, Eye-Tracking, Machine Learning, Extraneous Cognitive Load (ECL), Human-Computer Interaction (HCI). |
| Field | Engineering |
| Published In | Volume 7, Issue 4, July-August 2025 |
| Published On | 2025-08-15 |
| DOI | https://doi.org/10.36948/ijfmr.2025.v07i04.54996 |
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E-ISSN 2582-2160
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IJFMR DOI prefix is
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