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Award ID contains: 1711425

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  1. ; ; ; (, NeuroIS Retreat)
    Accepted Manuscript Full Text Available
  2. ; ; ; ; (, Proceedings NeuroIS Retreat 2019)
    Cognitive load has received increased focus as an area that can be more richly explored using neuroIS tools. This research study presents the application of electroencephalography and eye tracking technologies to examine cognitive load of student learners in biochemistry. In addition to leveraging the Pope Engagement Index and eye tracking analysis techniques, we seek better understanding of the relationship that various individual characteristics have with the level of cognitive load experienced. While this study focuses on a particular STEM student population as they manipulate various learning models, it has implications for further studies in human-computer interaction and other learning environments. 
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    Accepted Manuscript Full Text Available