Abstract
Current learning technologies have no direct way to assess students' mental effort: are they in deep thought, struggling to overcome an impasse, or are they zoned out? To address this challenge, we propose the use of EEG-based cognitive load detectors during learning. Despite its potential, EEG has not yet been utilized as a way to optimize instructional strategies. We take an initial step towards this goal by assessing how experimentally manipulated (easy and difficult) sections of an intelligent tutoring system (ITS) influenced EEG-based estimates of students' cognitive load. We found a main effect of task difficulty on EEG-based cognitive load estimates, which were also correlated with learning performance. Our results show that EEG can be a viable source of data to model learners' mental states across a 90-minute session.
Original language | English (US) |
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Title of host publication | LAK 2017 Conference Proceedings - 7th International Learning Analytics and Knowledge Conference |
Subtitle of host publication | Understanding, Informing and Improving Learning with Data |
Publisher | Association for Computing Machinery |
Pages | 80-89 |
Number of pages | 10 |
ISBN (Electronic) | 9781450348706 |
DOIs | |
State | Published - Mar 13 2017 |
Externally published | Yes |
Event | 7th International Conference on Learning Analytics and Knowledge, LAK 2017 - Vancouver, Canada Duration: Mar 13 2017 → Mar 17 2017 |
Publication series
Name | ACM International Conference Proceeding Series |
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Other
Other | 7th International Conference on Learning Analytics and Knowledge, LAK 2017 |
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Country/Territory | Canada |
City | Vancouver |
Period | 3/13/17 → 3/17/17 |
Bibliographical note
Funding Information:This research was supported by the National Science Foundation (NSF) (IIP 1416595; DRL 1108845; IIS 1523091). Any opinions, findings and conclusions, or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the NSF.
Publisher Copyright:
© 2017 ACM.
Keywords
- Cognitive load
- EEG
- Engagement
- Intelligent tutoring systems