TY - JOUR
T1 - Cognitive and affective brain-computer interfaces for improving learning strategies and enhancing student capabilities
T2 - A systematic literature review
AU - Jamil, Nuraini
AU - Belkacem, Abdelkader Nasreddine
AU - Ouhbi, Sofia
AU - Guger, Christoph
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2021
Y1 - 2021
N2 - Brain-computer interface (BCI) technology has the potential to positively contribute to the educational learning environment, which faces many challenges and shortcomings. Cognitive and affective BCIs can offer a deep understanding of brain mechanisms, which may improve learning strategies and increase brain-based skills. They can offer a better empirical foundation for teaching-learning methodologies, including adjusting learning content based on brain workload, measuring student interest of a topic, or even helping students focus on specific tasks. The latest findings from emerging BCI technology, neuroscience, cognitive sciences, and psychology could be used in learning and teaching strategies to improve student abilities in education. This study investigates and analyzes the research on BCI patterns and its implementation for enhancing cognitive capabilities of students. The results showed that there is insufficient literature on BCI that addresses students with disabilities in the learning process. Further, our analysis revealed a bias toward the significance of cognitive process factors compared with other influential factors, such as the learning environment and emotions that influence learning. Finally, we concluded that BCI technology could improve students' learning and cognitive skills - when consistently associated with the different pedagogical teaching-learning strategies - for better academic achievement.
AB - Brain-computer interface (BCI) technology has the potential to positively contribute to the educational learning environment, which faces many challenges and shortcomings. Cognitive and affective BCIs can offer a deep understanding of brain mechanisms, which may improve learning strategies and increase brain-based skills. They can offer a better empirical foundation for teaching-learning methodologies, including adjusting learning content based on brain workload, measuring student interest of a topic, or even helping students focus on specific tasks. The latest findings from emerging BCI technology, neuroscience, cognitive sciences, and psychology could be used in learning and teaching strategies to improve student abilities in education. This study investigates and analyzes the research on BCI patterns and its implementation for enhancing cognitive capabilities of students. The results showed that there is insufficient literature on BCI that addresses students with disabilities in the learning process. Further, our analysis revealed a bias toward the significance of cognitive process factors compared with other influential factors, such as the learning environment and emotions that influence learning. Finally, we concluded that BCI technology could improve students' learning and cognitive skills - when consistently associated with the different pedagogical teaching-learning strategies - for better academic achievement.
KW - 21st century abilities
KW - Applications in subject areas
KW - Brain computer interface
KW - Improving classroom teaching
KW - Neurofeedback
KW - Teaching/learning strategies
UR - http://www.scopus.com/inward/record.url?scp=85115746108&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85115746108&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2021.3115263
DO - 10.1109/ACCESS.2021.3115263
M3 - Review article
AN - SCOPUS:85115746108
SN - 2169-3536
VL - 9
SP - 134122
EP - 134147
JO - IEEE Access
JF - IEEE Access
ER -