Low-Cost EEG Multi-Subject Recording Platform for the Assessment of Students’ Attention and the Estimation of Academic Performance in Secondary School

Abstract

The level of student attention in class greatly affects their academic performance. Teachers typically rely on visual inspection to react to students’ attention in time, but this subjective method leads to inconsistencies across classes. Online education exacerbates the issue as students can turn off cameras and microphones to keep their own privacy. To address this, we present a novel, low-cost EEG-based platform for assessing students’ attention and estimating their academic performance. In a study involving 34 secondary school students (aged 14 to 16), participants watched an academic video and answered evaluation questions while their EEG activity was recorded using a commercial headset. The results demonstrate a significant correlation (0.53, p-value = 0.003) between the power spectral density (PSD) of the EEG beta band (12–30 Hz) and students’ academic performance. Additionally, there was a notable difference in PSD-beta between high and low academic performers. These findings encourage the use of PSD-beta for the immediate and objective assessment of both the student attention and the subsequent academic performance. The platform offers valuable and objective feedback to teachers, enhancing the effectiveness of both face-to-face and online teaching and learning environments.

Automated Monitoring of Human–Computer Interaction for Assessing Teachers’ Digital Competence Based on LMS Data Extraction

“…Different authors support the need to assess the skills that teachers demonstrate when interacting with digital tools. While some authors propose models for assessing teachers during class situations [ 34 , 35 , 36 , 37 , 38 , 39 ], a different set of authors opt to use digital competency assessment frameworks [ 17 , 41 , 42 , 43 , 44 , 45 , 47 ].…”

“…Wang et al [ 36 ] present a similar proposal based on the use of an Extended-Efficient Layer Aggregation Network (E-ELAN) applied in Smart Classroom environments. On the other hand, Fuentes-Martinez et al [ 37 ] propose an alternative solution to using cameras and microphones to record the classroom, by using low-cost EEG platforms. Their objective is to analyze beta bands obtained from EEG to determine a student’s attention level and provide feedback to the teacher.…”

Differences in Electroencephalography Power Levels between Poor and Good Performance in Attentional Tasks

“…Clinically, a randomized controlled trial revealed that a lower frontal α power was significantly associated with a higher incidence of postoperative delirium [ 26 ], which is usually a reversible disturbance in mental status with a degree of inattention [ 27 ]. Another study reported that the results demonstrated a significant correlation between the power spectral density of the EEG β band and students’ academic performance, which relates to their attentional ability [ 28 ].…”