Research on Evaluation and Confirmation of College Students' Learning Behavior Based on Comprehensive Weighted Fusion Algorithm

In order to solve the problem of the lack of information in the evaluation of university students' learning behavior with single data, a multi-source data fusion evaluation of university students' learning behavior is proposed to explore the application value of data fusion technology in t...

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Bibliographic Details
Published in2021 IEEE 6th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA) pp. 121 - 125
Main Authors Qu, Jinshuai, Liu, Aijiao, Liu, Renfei
Format Conference Proceeding
LanguageEnglish
Published IEEE 24.04.2021
Subjects
behavior evaluation
Big Data
Cloud computing
comprehensive weighting
Conferences
Correlation
data fusion
Data integration
Education
Learning systems
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DOI10.1109/ICCCBDA51879.2021.9442584

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Summary:In order to solve the problem of the lack of information in the evaluation of university students' learning behavior with single data, a multi-source data fusion evaluation of university students' learning behavior is proposed to explore the application value of data fusion technology in teaching. First use Spearman to calculate the correlation between different data sources, calculate the relationship weight and optimization weight of different data sources, and then comprehensively weight for fusion calculation. The fusion calculation of students' comprehensive learning behavior evaluation through comprehensive weighted fusion can not only balance the differences in learning behavior evaluation of students under different teaching methods, but also integrate the advantages and disadvantages of different learning methods. Experiments verify that the comprehensive weighted data fusion algorithm is effective, which can provide help for a more comprehensive analysis of the evaluation of college students' learning behavior and provide a basis for adapting to their own learning.
DOI:10.1109/ICCCBDA51879.2021.9442584