TY - GEN
T1 - Brain-Computer Interface Approach for improving the Pedagogical Practices for Virtual Learning
T2 - 2022 IEEE Learning with MOOCS, LWMOOCS 2022
AU - Jamil, Nuraini
AU - Belkacem, Abdelkader Nasreddine
AU - Benkhelifa, Elhadj
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The coronavirus epidemic (COVID19) has com-pelled the global halting of various services, including educational service, resulting in a massive crisis-response movement of education institutions to online learning platforms. Therefore, teachers had to shift from the traditional face-to-face modality and quickly adapt to virtual learning to continue their education. This conceptual paper discusses a theoretical framework for mon-itoring and improving the level of interaction between students and teachers during virtual learning environments. Through this interaction, teachers can gather some essential cognitive learning behaviors of their students by collecting some biomedical signals. In this conceptual framework, we propose a theoretical end-to-end approach to support teachers in understanding the cognitive learning behaviors of their students during online learning and where face-to-face contact is not possible. This shall be enabled by monitoring the brain patterns of students during their learning, using Brain-computer interface techniques to enhance their cognitive skills and maximize their learning. This approach is also expected to underpin new pedagogical methodologies to support remote learning.
AB - The coronavirus epidemic (COVID19) has com-pelled the global halting of various services, including educational service, resulting in a massive crisis-response movement of education institutions to online learning platforms. Therefore, teachers had to shift from the traditional face-to-face modality and quickly adapt to virtual learning to continue their education. This conceptual paper discusses a theoretical framework for mon-itoring and improving the level of interaction between students and teachers during virtual learning environments. Through this interaction, teachers can gather some essential cognitive learning behaviors of their students by collecting some biomedical signals. In this conceptual framework, we propose a theoretical end-to-end approach to support teachers in understanding the cognitive learning behaviors of their students during online learning and where face-to-face contact is not possible. This shall be enabled by monitoring the brain patterns of students during their learning, using Brain-computer interface techniques to enhance their cognitive skills and maximize their learning. This approach is also expected to underpin new pedagogical methodologies to support remote learning.
KW - Brain-Computer Interface (BCI)
KW - Cognitive Science
KW - Pandemic
KW - Virtual learning
KW - pedagogy
UR - http://www.scopus.com/inward/record.url?scp=85142653282&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85142653282&partnerID=8YFLogxK
U2 - 10.1109/LWMOOCS53067.2022.9927791
DO - 10.1109/LWMOOCS53067.2022.9927791
M3 - Conference contribution
AN - SCOPUS:85142653282
T3 - Proceedings of 2022 IEEE Learning with MOOCS, LWMOOCS 2022
SP - 72
EP - 77
BT - Proceedings of 2022 IEEE Learning with MOOCS, LWMOOCS 2022
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 29 September 2022 through 30 September 2022
ER -