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Volume 24
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10.3390/s24216969
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Article

Application of Electroencephalography Sensors and Artificial Intelligence in Automated Language Teaching

by
Yanlin Chen
,
Wuxiong Wang
,
Shen Yan
,
Yiming Wang
,
Xinran Zheng
and
Chunli Lv
*
China Agricultural University, Beijing 100083, China
*
Author to whom correspondence should be addressed.
Sensors 2024, 24(21), 6969; https://doi.org/10.3390/s24216969
Submission received: 18 August 2024 / Revised: 26 October 2024 / Accepted: 29 October 2024 / Published: 30 October 2024
(This article belongs to the Special Issue Advances of Sensors and Human-Centered Intelligent Systems in Education)
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Abstract

This study developed an automated language learning teaching assessment system based on electroencephalography (EEG) and differential language large models (LLMs), aimed at enhancing language instruction effectiveness by monitoring learners’ cognitive states in real time and personalizing teaching content accordingly. Through detailed experimental design, the paper validated the system’s application in various teaching tasks. The results indicate that the system exhibited high precision, recall, and accuracy in teaching effectiveness tests. Specifically, the method integrating differential LLMs with the EEG fusion module achieved a precision of 0.96, recall of 0.95, accuracy of 0.96, and an F1-score of 0.95, outperforming other automated teaching models. Additionally, ablation experiments further confirmed the critical role of the EEG fusion module in enhancing teaching quality and accuracy, providing valuable data support and theoretical basis for future improvements in teaching methods and system design.
Keywords: EEG sensors in education; real-time cognitive monitoring; sensor-based learning assessment; differential adaptive learning models; deep learning EEG sensors in education; real-time cognitive monitoring; sensor-based learning assessment; differential adaptive learning models; deep learning

Share and Cite

MDPI and ACS Style

Chen, Y.; Wang, W.; Yan, S.; Wang, Y.; Zheng, X.; Lv, C. Application of Electroencephalography Sensors and Artificial Intelligence in Automated Language Teaching. Sensors 2024, 24, 6969. https://doi.org/10.3390/s24216969

AMA Style

Chen Y, Wang W, Yan S, Wang Y, Zheng X, Lv C. Application of Electroencephalography Sensors and Artificial Intelligence in Automated Language Teaching. Sensors. 2024; 24(21):6969. https://doi.org/10.3390/s24216969

Chicago/Turabian Style

Chen, Yanlin, Wuxiong Wang, Shen Yan, Yiming Wang, Xinran Zheng, and Chunli Lv. 2024. "Application of Electroencephalography Sensors and Artificial Intelligence in Automated Language Teaching" Sensors 24, no. 21: 6969. https://doi.org/10.3390/s24216969

APA Style

Chen, Y., Wang, W., Yan, S., Wang, Y., Zheng, X., & Lv, C. (2024). Application of Electroencephalography Sensors and Artificial Intelligence in Automated Language Teaching. Sensors, 24(21), 6969. https://doi.org/10.3390/s24216969

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