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Application of intelligent multi-sensor technology in higher education teaching system

Yanbin Liu

Yanbin Liu

Ruzhou Vocational and Technical CollegePingdingshan, China
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Liu, Yanbin
, 
Peina Liang

Peina Liang

Henan Quality PolytechnicPingdingshan, China
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Liang, Peina
 and 
Jingjie Ma

Jingjie Ma

Henan Quality PolytechnicPingdingshan, China
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Ma, Jingjie
  
Mar 17, 2025
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Published Online: Mar 17, 2025
Received: Nov 15, 2024
Accepted: Feb 15, 2025
DOI: https://doi.org/10.2478/amns-2025-0207
Keywords
© 2025 Yanbin Liu et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1.

Fusion algorithm structure diagram
Fusion algorithm structure diagram

Figure 2.

Education and teaching system based on multi-sensor technology
Education and teaching system based on multi-sensor technology

Figure 3.

Test results for class 1 and class 2
Test results for class 1 and class 2

Figure 4.

Comparisons of the class 1 and class 2
Comparisons of the class 1 and class 2

Figure 5.

The final exam score report of the class 1 and class 2
The final exam score report of the class 1 and class 2

Figure 6.

Comparisons of final exam results between the class 1 and class 2
Comparisons of final exam results between the class 1 and class 2

Figure 7.

Views on educational teaching system
Views on educational teaching system

Figure 8.

Teaching resources
Teaching resources

Figure 9.

Interactive situation
Interactive situation

Figure 10.

Personalized teaching system experience
Personalized teaching system experience

T-test for the results of the thorough examination

class Class 1 Class 2
N 50 50
mean value 91.16 88.92
standard deviation 19.485 19.176
standard deviation of the mean 2.784 2.712
F 0.143
P 0.706
Sig. 0.565

T test for final exam results

class Class 1 Class 2
N 50 50
mean value 101.26 96.26
standard deviation 9.516 14.851
standard deviation of the mean 1.346 2.1
F 7.046
P 0.009
Sig. 0.048
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