Innovative Digital Teaching Methods for Children’s Ink Painting Course for Higher Teachers Based on Graphics Algorithms

The article calculates the average image entropy of the image domain, quantitatively analyzes the information has richness asymmetry in the task of digitally generating ink paintings, and constructs an asymmetric cyclic coherent ink painting digital generation model based on graphical algorithms.The model integrates a generative adversarial network, and the generator is centered on the Dense Block and replaces the residual block with a dense block to improve the characterization ability.The position fusion attention network is utilized to capture the main body region of the ink painting and combined with the edge extraction technique to extract the significant main body edges of the image and simulate the salient features of the ink painting strokes.The model is integrated into the teaching of "Children's Ink Painting" course in a high school teacher, and students are instructed to use the algorithm to generate digital ink paintings to further explore the effectiveness of the teaching method.In this paper, the model is iterated for 30 times, and the total objective function converges to the minimum value of 0.85, and the measured values on PSNR, UIQM and UCIQE are improved by 4.44, 0.3 and 0.68 respectively compared with the optimal values of the comparison model, and the model can obtain the highest evaluation score (8) of the generated image at the fastest convergence speed (50 epochs), and the degree of overlap with the real image on the LPIPS distance is higher.After the experiment, the dimensions of digital pedagogical literacy level of the experimental class increased by 3.37 to 7.63 points compared with the control class and showed significant differences.As for the satisfaction of learning experience, students' satisfaction with digital teaching resources is the highest, which is 4.70 points.The experimental results show that the model constructed in this paper has good performance of ink painting image generation and can be used as a digital teaching method for children's ink painting course in high school teachers.

Publication Details

Journal
Journal of Combinatorial Mathematics and Combinatorial Computing
Published
2025-03-30
DOI
https://doi.org/10.61091/jcmcc127a-428
Primary Topic
Digital Media and Visual Art
Type
article
Field-Weighted Citation Impact
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article

Innovative Digital Teaching Methods for Children’s Ink Painting Course for Higher Teachers Based on Graphics Algorithms

Journal of Combinatorial Mathematics and Combinatorial Computing
Digital Media and Visual Art
article

Innovative Digital Teaching Methods for Children’s Ink Painting Course for Higher Teachers Based on Graphics Algorithms

article en

Abstract

The article calculates the average image entropy of the image domain, quantitatively analyzes the information has richness asymmetry in the task of digitally generating ink paintings, and constructs an asymmetric cyclic coherent ink painting digital generation model based on graphical algorithms.The model integrates a generative adversarial network, and the generator is centered on the Dense Block and replaces the residual block with a dense block to improve the characterization ability.The position fusion attention network is utilized to capture the main body region of the ink painting and combined with the edge extraction technique to extract the significant main body edges of the image and simulate the salient features of the ink painting strokes.The model is integrated into the teaching of "Children's Ink Painting" course in a high school teacher, and students are instructed to use the algorithm to generate digital ink paintings to further explore the effectiveness of the teaching method.In this paper, the model is iterated for 30 times, and the total objective function converges to the minimum value of 0.85, and the measured values on PSNR, UIQM and UCIQE are improved by 4.44, 0.3 and 0.68 respectively compared with the optimal values of the comparison model, and the model can obtain the highest evaluation score (8) of the generated image at the fastest convergence speed (50 epochs), and the degree of overlap with the real image on the LPIPS distance is higher.After the experiment, the dimensions of digital pedagogical literacy level of the experimental class increased by 3.37 to 7.63 points compared with the control class and showed significant differences.As for the satisfaction of learning experience, students' satisfaction with digital teaching resources is the highest, which is 4.70 points.The experimental results show that the model constructed in this paper has good performance of ink painting image generation and can be used as a digital teaching method for children's ink painting course in high school teachers.

Journal of Combinatorial Mathematics and Combinatorial ComputingVol. 127a
Quality Education
Openalex Percentile: Top 85%
Digital Media and Visual Art
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