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.
|Original language||English (US)|
|Title of host publication||Information Systems and Neuroscience - NeuroIS Retreat 2019|
|Editors||Fred D. Davis, René Riedl, René Riedl, Jan vom Brocke, Pierre-Majorique Léger, Adriane Randolph, Thomas Fischer|
|Number of pages||5|
|State||Published - 2020|
|Event||International Conference on Information Systems and Neuroscience, NeuroIS Retreat 2019 - Vienna, Austria|
Duration: Jun 4 2019 → Jun 6 2019
|Name||Lecture Notes in Information Systems and Organisation|
|Conference||International Conference on Information Systems and Neuroscience, NeuroIS Retreat 2019|
|Period||6/4/19 → 6/6/19|
Bibliographical noteFunding Information:
This work was funded by the National Science Foundation under Grant Num-
This work was funded by the National Science Foundation under Grant Number 1711425.
© Springer Nature Switzerland AG 2020.
- Cognitive load
- Eye tracking
- Individual characteristics
- Student learners