Investigating EEG-based neurofeedback for cognitive enhancement in remote learning - Nuraini Jamil; Abdelkader Nasreddine Belkacem (IEEE, 2025)
This research examines the effectiveness of neurofeedback in improving attention in remote learning environments using the passive brain computer interface (BCI). Participants had three EEG-based neurofeedback training sessions, receiving immediate feedback on their cognitive states to improve attention and diminish inattentiveness by self-regulating brain activity. The results indicated substantial enhancements in attention during the sessions, as shown by elevated beta and gamma activity, which are essential for attention regulation and cognitive processing. Power spectral density (PSD) measurement demonstrated sustained increased brainwave power over time, corroborating individuals’ capacity to modify brain activity successfully. An analysis of variance (ANOVA) with a single factor revealed a significant increase in attention levels throughout sessions (F (2„ 27) = 95.06, p < 0.0001), with post-hoc Tukey’s tests demonstrating considerable improvements between Sessions 1 and 3 (mean difference = 5.261, p = 0.001). The beta and gamma activity study corroborated the participants’ cognitive engagement enhancement, evidenced by less inattentiveness and improved higher-order processing. The negligible latency in processing real-time feedback guaranteed that the feedback stayed pertinent to the task. This study underscores the efficacy of neurofeedback as a valuable instrument for improving attention and cognitive engagement in online learning settings. Future studies should investigate long-term impacts, individualized feedback systems, and the incorporation of additional cognitive training methodologies to optimize the advantages of neurofeedback in educational settings