Using eye gaze data & visual activities to infer human cognitive styles: Method & feasibility studies
| Autor: | Raptis, George E., Katsini, Christina P., Avouris, Nikolaos M., Belk, Marios, Fidas, Christos A., Samaras, George S. |
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| Přispěvatelé: | Belk, Marios [0000-0001-6200-0178] |
| Rok vydání: | 2017 |
| Předmět: |
Need for cognition
User study Computer science 05 social sciences 02 engineering and technology Visual search tasks Rendering (computer graphics) Visual behavior InformationSystems_MODELSANDPRINCIPLES Visual decision-making tasks Human cognitive styles 020204 information systems 0202 electrical engineering electronic engineering information engineering Eye tracking Systems design 0501 psychology and cognitive sciences 050107 human factors Eye-Tracking Cognitive psychology Cognitive style |
| Zdroj: | UMAP 2017-Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization 25th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2017 UMAP |
| Popis: | Recent research provides evidence that individual differences in human cognitive styles affect user performance and experience in diverse application domains. However, state-of-The-Art elicitation methods of cognitive styles require researchers to apply explicit, in-lab, and time-consuming "paper-And-pencil" techniques, rendering real-Time integration of cognitive styles' elicitation impractical in interactive system design. Aiming to elaborate an implicit elicitation method of cognitive styles, this paper reports two feasibility studies based on an eye-Tracking multifactorial model. In both studies, participants performed visual activities of varying characteristics, and the eye-Tracking analysis revealed quantitative differences on visual behavior among individuals with different cognitive styles. Based on these differences, a series of classification experiments were conducted, and the results revealed that gaze-based implicit elicitation of cognitive styles in real-Time is feasible, which could be used by interactive systems to adapt to the users' cognitive needs and preferences, to better assist them, and improve their performance and experience. ©2017 ACM. 164 173 Sponsors: ACM SIGCHI ACM SIGWEB Conference code: 128764 Cited By :2 |
| Databáze: | OpenAIRE |
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