Abstract
The use of EEG to enhance learning experience in learning environments can contribute to furthering symbiotic relationship between the user and the system. This study examines whether it is possible to predict successful memorization of previously-learned words in a language learning context from brain activity alone. Participants are tasked with learning German-Korean word association pairs, and their retention performance is tested on the day of and the after learning. We perform statistical analysis as well as single-trial classification to investigate whether brain activity as recorded via multi-channel EEG is able to predict whether a word is remembered or not. Our preliminary results confirm above-chance prediction of successful word learning.
Original language | English |
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Title of host publication | Symbiotic Interaction - 6th International Workshop, Symbiotic 2017, Revised Selected Papers |
Editors | Benjamin Blankertz, Anna Spagnolli, Luciano Gamberini, Giulio Jacucci, Jaap Ham |
Publisher | Springer Verlag |
Pages | 63-73 |
Number of pages | 11 |
ISBN (Print) | 9783319915920 |
DOIs | |
Publication status | Published - Jan 1 2018 |
Externally published | Yes |
Event | 6th International Workshop on Symbiotic Interaction, SYMBIOTIC 2017 - Eindhoven, Netherlands Duration: Dec 18 2017 → Dec 19 2017 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 10727 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 6th International Workshop on Symbiotic Interaction, SYMBIOTIC 2017 |
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Country/Territory | Netherlands |
City | Eindhoven |
Period | 12/18/17 → 12/19/17 |
Funding
Acknowledgment. This work was supported by Institute for Information & Communications Technology Promotion (IITP) grant funded by the Korea government (No. 2017-0-00451). This publication only reflects the authors views.
Keywords
- BCI
- Education
- EEG
- Language learning
- Memory
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science