<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>To improve the animation design ability of animation aesthetics students and the teaching ability of teachers, this paper constructs an evaluation system of animation aesthetics education based on Internet+. Firstly, the feasibility of Internet+ education is analyzed, and the Kohonen grid is introduced to fuzzy classify the images and get the corresponding affiliation vector. Then the mean value method is used to fuse the two-dimensional images, and the evaluation index of animation aesthetics education is derived according to the gray value. Secondly, considering the limited capacity of the animation aesthetics education evaluation system, the principal component analysis method is used to calculate the feature values, weight percentages, etc., to filter out the range of index values and construct the evaluation system according to the main indexes. Finally, according to the scores of students’ animation works and teachers’ satisfaction before and after the platform was implemented, it was confirmed that the built platform could optimize the teaching effect. The results showed that after the teachers adjusted their teaching according to the evaluation system, the students’ work scored 90 and above, and the student’s satisfaction with the teachers increased from the highest 6.5 to 9.8, which optimized the teaching effect.</p>
</abstract>

To improve the animation design ability of animation aesthetics students and the teaching ability of teachers, this paper constructs an evaluation system of animation aesthetics education based on Internet+. Firstly, the feasibility of Internet+ education is analyzed, and the Kohonen grid is introduced to fuzzy classify the images and get the corresponding affiliation vector. Then the mean value method is used to fuse the two-dimensional images, and the evaluation index of animation aesthetics education is derived according to the gray value. Secondly, considering the limited capacity of the animation aesthetics education evaluation system, the principal component analysis method is used to calculate the feature values, weight percentages, etc., to filter out the range of index values and construct the evaluation system according to the main indexes. Finally, according to the scores of students’ animation works and teachers’ satisfaction before and after the platform was implemented, it was confirmed that the built platform could optimize the teaching effect. The results showed that after the teachers adjusted their teaching according to the evaluation system, the students’ work scored 90 and above, and the student’s satisfaction with the teachers increased from the highest 6.5 to 9.8, which optimized the teaching effect.

Research on the evaluation system and teaching optimization effect of animation aesthetics education based on principal component analysis method

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

To improve the animation design ability of animation aesthetics students and the teaching ability of teachers, this paper constructs an evaluation system of...

Research on the evaluation system and teaching optimization effect of animation aesthetics education based on principal component analysis method

Published Online: Oct 07, 2023

Page range: -

Received: Oct 22, 2022

Accepted: Apr 17, 2023

DOI: https://doi.org/10.2478/amns.2023.2.00509

Keywords
Educational evaluation system, Kohonen grid, Principal component analysis method, Fuzzy classification, Mean value method

© 2023 Zhiqiang Liu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on the evaluation system and teaching optimization effect of animation aesthetics education based on principal component analysis method

Published Online: Oct 07, 2023

Page range: -

Received: Oct 22, 2022

Accepted: Apr 17, 2023

DOI: https://doi.org/10.2478/amns.2023.2.00509

KeywordsEducational evaluation system, Kohonen grid, Principal component analysis method, Fuzzy classification, Mean value method

© 2023 Zhiqiang Liu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
Educational evaluation system, Kohonen grid, Principal component analysis method, Fuzzy classification, Mean value method