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The Effect of Electroencephalogram Feedback in Virtual Reality Interactive System on Creativity Performance, Attention Value, and Cognitive Load.

Authors :
Wu, Ling
Chau, Kien Tsong
Wan Yahaya, Wan Ahmad Jaafar
Wang, Shuxin
Wu, Xin
Source :
International Journal of Human-Computer Interaction. Jul2024, p1-18. 18p. 5 Illustrations.
Publication Year :
2024

Abstract

AbstractThis study aimed to systematically investigate the impacts of virtual reality (VR) technology integrated with electroencephalogram (EEG) vibrotactile feedback on undergraduate students’ creativity performance, attention value, and cognitive load. 4P’s creativity model was adopted as the macro strategy, with cognitive load theory and constructivist theory serving as a micro strategy. A 2 × 2 quasi-experimental factor design was utilized. A total of 149 undergraduate students with varying spatial abilities were randomly assigned to an experimental group (using a VR interactive system with EEG vibrotactile feedback) and a control group (without feedback). Covariance analysis (ANCOVA) and analysis of variance (ANOVA) were employed to identify significant differences among the systems and examine interaction effects among variables. The quantitative results provided empirical evidence that the experimental group exhibited significantly higher levels of creativity performance and attention value than the control group. Furthermore, undergraduate students with higher spatial ability demonstrated lower cognitive load, superior creativity performance, and attention value compared to those with lower spatial ability. The study also revealed that the system positively impacts learning in university creativity education and holds promising potential for improving traditional VR interactive training systems. These findings contribute valuable insights for future research on the application of VR interaction technology and EEG technology in cognitive training for creativity. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10447318
Database :
Academic Search Index
Journal :
International Journal of Human-Computer Interaction
Publication Type :
Academic Journal
Accession number :
178311130
Full Text :
https://doi.org/10.1080/10447318.2024.2371692