Different Educational Interventions on Individual Cognition of Garbage Classification Based on EEG Monitoring

Rui Zhao, Xinyun Ren, Yan Liu, Yujun Li and Ruyin Long
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Rui Zhao: Faculty of Geoscience and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
Xinyun Ren: Faculty of Geoscience and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
Yan Liu: Faculty of Geoscience and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
Yujun Li: Department of Foreign Language and Culture, North Sichuan Medical College, Nanchong 637000, China
Ruyin Long: School of Business, Jiangnan University, Wuxi 214122, China

IJERPH, 2022, vol. 19, issue 14, 1-17

Abstract: Improvement in an individuals’ cognition is the key to promote garbage classification. This study takes university students as the research subjects, through three educational interventions, including the self-learning, heuristic learning, and interactive learning ways, to seek the most effective intervention based upon event-related potentials (ERPs) that is beneficial to enhance cognition of garbage classification. The results show that the experimental subjects induced P300 and LPP components, representing attentional changes and cognitive conflicts in classification judgments. There are differences in the amplitudes and peak latency of the two components corresponding to different interventions, indicating that the three educational interventions are able to improve the individual’s cognition level of garbage classification within a certain period of time. The interactive-learning intervention triggers the largest amplitudes of P300 and LPP, as well as the smallest peak latency, indicating its effect is the best. Such results provide insight into the design for an appropriate strategy in garbage classification education. The study also shows that an EEG signal can be used as the endogenous neural indicator to measure the performance of garbage classification under different educational interventions.

Keywords: cognition; garbage classification; educational intervention; ERP; P300; LPP (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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