The rapid development of wearable bio-sensing techniques has made it possible to continuously record neurophysiological signals in naturalistic scenarios such as the classroom. The present study aims to explore the neurophysiological correlates of middle-school students' academic performance. The electrodermal signals (EDAs) and heart rates (HRs) were collected via wristband from 100 Grade seven students during their daily Chinese and math classes for 10 days in 2 weeks. Significant correlations were found between the academic performance as reflected by the students' final exam scores and the EDA responses. Further regression analyses revealed significant prediction of the academic performance mainly by the transient EDA responses (R ² = 0.083, p < 0.05, with Chinese classes only; R ² = 0.030, p < 0.05, with both Chinese and math classes included). By combining the self-report data about session-based general statuses and the neurophysiological data, the explained powers of the regression models were further improved (R ² = 0.095, p < 0.05, with Chinese classes only; R ² = 0.057, p < 0.05, with both Chinese and math classes included), and the neurophysiological data were shown to have independent contributions to the regression models. In addition, the regression models became non-significant by exchanging the academic performances of the Chinese and math classes as the dependent variables, suggesting at least partly distinct neurophysiological responses for the two types of classes. Our findings provide evidences supporting the feasibility of predicting educational outputs by wearable neurophysiological recordings.

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