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- W2020145237 abstract "An intelligent adaptable system, aware of a user’s experienced cognitive load, may help improve performance in complex, time-critical situations by dynamically deploying more appropriate output strategies to reduce cognitive load. However, measuring a user’s cognitive load robustly, in real-time is not a trivial task. Many research studies have attempted to assess users’ cognitive load using different measurements, but these are often unsuitable for deployment in real-life applications due to high intrusiveness. Relatively novel linguistic behavioral features as potential indices of user’s cognitive load is proposed. These features may be collected implicitly and nonintrusively supporting real-time assessment of users’ cognitive load and accordingly allowing adaptive usability evaluation and interaction. Results from a laboratory experiment show significantly different linguistic patterns under different task complexities and cognitive load levels. Implications of the research for adaptive interaction are also discussed, that is, how the cognitive load measurement-based approach could be used for user interface evaluation and interaction design improvement." @default.
- W2020145237 created "2016-06-24" @default.
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- W2020145237 date "2014-04-01" @default.
- W2020145237 modified "2023-09-28" @default.
- W2020145237 title "Measuring Cognitive Load Using Linguistic Features: Implications for Usability Evaluation and Adaptive Interaction Design" @default.
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- W2020145237 doi "https://doi.org/10.1080/10447318.2013.860579" @default.
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