Towards an index of opportunity: understanding changes in mental workload during task execution
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Using a low-cost electroencephalograph for task classification in HCI research
UIST '06 Proceedings of the 19th annual ACM symposium on User interface software and technology
Building Dependable EEG Classifiers for the Real World --- It's Not Just about the Hardware
FAC '09 Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009
The relationship between scan path direction and cognitive processing
Proceedings of the Third C* Conference on Computer Science and Software Engineering
Modeling mental workload using EEG features for intelligent systems
UMAP'11 Proceedings of the 19th international conference on User modeling, adaption, and personalization
Mental workload, engagement and emotions: an exploratory study for intelligent tutoring systems
ITS'12 Proceedings of the 11th international conference on Intelligent Tutoring Systems
Recognizing Student Emotions using Brainwaves and Mouse Behavior Data
International Journal of Distance Education Technologies
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We have begun to model changes in electroencephalography (EEG)-derived measures of cognitive workload, engagement and distraction as individuals developed and refined their problem solving skills in science. For the same problem solving scenario(s) there were significant differences in the levels and dynamics of these three metrics. As expected, workload increased when students were presented with problem sets of greater difficulty. Less expected, however, was the finding that as skills increased, the levels of workload did not decrease accordingly. When these indices were measured across the navigation, decision, and display events within the simulations significant differences in workload and engagement were often observed. Similarly, event-related differences in these categories across a series of the tasks were also often observed, but were highly variable across individuals.