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Erschienen in:
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2021 | OriginalPaper | Buchkapitel

Research on Classroom Attention Analysis Based on Multi-source Data Correlation

verfasst von : Ya-Nan Zhang, Runsha Dong, Yang Wu, Xinzhou Cheng, Chen Cheng, Lexi Xu

Erschienen in: Signal and Information Processing, Networking and Computers

Verlag: Springer Singapore

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Abstract

In view of the problem that it is difficult to supervise and improve the attention level of teenagers in class in education and teaching activities, based on multi-source data correlation, we combine with big data technology to analyze and research the attention level of teenagers in class. This paper analyzes the collected eye characteristics data of students in the classroom and other personalized related data to conduct a correlation analysis. Then, we derive a set of theoretical models to remind students of concentration improvement, as well as intervention of teachers’ teaching activities. Finally, the proposed theoretical model can improve the teaching quality ultimately.

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Vorheriges Kapitel The Analysis of Dual-Polarized Antenna in Polarized Wireless Channels
Nächstes Kapitel Supervised Machine Learning in 5G NSA Networks for Coverage and Performance Analysis
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Metadaten
Titel
Research on Classroom Attention Analysis Based on Multi-source Data Correlation
verfasst von
Ya-Nan Zhang
Runsha Dong
Yang Wu
Xinzhou Cheng
Chen Cheng
Lexi Xu
Copyright-Jahr
2021
Verlag
Springer Singapore
Buch
Signal and Information Processing, Networking and Computers

Print ISBN: 978-981-334-101-2

Electronic ISBN: 978-981-334-102-9

Copyright-Jahr: 2021

DOI
https://doi.org/10.1007/978-981-33-4102-9_108

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