Improving the Efficiency of College Art Teaching Based on Neural Networks

Improving the Efficiency of College Art Teaching Based on Neural Networks

Xi Jin
DOI: 10.4018/IJWLTT.336546
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Abstract

How to develop a teaching management system to improve the teaching efficiency of art courses has become an important challenge at present. This article takes university art teaching courses as the research object, uses dynamic L-M algorithm to optimize a large number of parameters, proposes an improved neural networks evaluation model, comprehensively analyzes the main influencing factors of art course teaching effectiveness, and establishes a teaching efficiency index evaluation system. The research results indicate that equating the number of hidden layer nodes to the number of samples can improve the performance of neural networks. The improved L-M algorithm was used to train the neural networks, and the maximum error of all test samples was only 0.04, verifying the feasibility and rationality of the improved neural networks model for evaluating course teaching effectiveness. The research results provide theoretical data support for neural networks to improve the efficiency of university art education.
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Introduction

As China enters a new stage of economic development, the quality of higher education has become a new challenge that affects the country's economic and social development (Gang & Weishang, 2021). In the context of comprehensive implementation of teaching reform, the teaching focuses on quality education. It is necessary to continuously promote the reform and innovation of quality education and improve the comprehensive literacy of college students (Xing et al., 2021). Although the art teaching system in universities is undergoing tremendous changes, teachers do not attach enough importance to art courses, and it is not easy to truly integrate them into the concept of quality education (Rivas et al., 2021). Art education can improve students' observation, imagination, and creativity, and the evaluation of art teaching level has great theoretical value and practical significance for art classroom education (Xu & Xia, 2022).

Some research results have been achieved in improving the quality of university teaching. Some researchers have explored the core competencies, teaching systems, and methods of university education in different disciplines by analyzing the core concepts of quality education (Liu, 2022). It is concluded that art education can strengthen students' visual literacy and enhance their other qualities. By focusing on the main manifestations of art literacy and combining individual differences and characteristics, the overall effectiveness of art education can be effectively improved. In the context of national first-class curriculum construction, some researchers focus on a scientific curriculum quality evaluation system and conduct in-depth analysis of the standards for first-class curriculum construction by analyzing the problems in existing evaluation systems (Alemdar et al., 2017). Some researchers have studied and developed methods for evaluating the quality of university teaching.

Some researchers have studied the impact of intelligent teaching apps on university course teaching, and analyzed the impact of university teaching quality through satisfaction evaluation. Based on the current situation of using intelligent teaching apps in ordinary universities in Shanxi, 780 satisfaction survey questionnaires on using apps were collected. A regression model for teaching quality evaluation was established using factor analysis, and the factors that affect the satisfaction of teachers and students with using apps were identified, including subjective attitude, learning effectiveness, course design, and communication interaction. Therefore, corresponding measures to improve the quality of school teaching were proposed. Some researchers have proposed innovative teaching methods in art classroom teaching activities by analyzing core literacy concepts. By deeply integrating the curriculum’s core competencies and designing the optimal teaching context, teachers can optimize and improve the core competencies, summarize the shortcomings of situational teaching methods, and propose targeted optimization and improvement measures. Some researchers believe that reforming university teaching methods has helped improve teaching quality and efficiency (Bhatkalkar et al., 2020). Some researchers have focused on art teaching and proposed the concept of cultivating core competencies. It is believed that the integration of core competencies in the teaching process of fine arts in China should be based on the cultivation of aesthetic literacy so that students can genuinely acquire the ability to perceive, evaluate, and create beauty. Taking art graduate teaching courses as the research object, this paper analyzes the problems in art graduate education and establishes an art teaching quality evaluation system from four dimensions: final testing, achievement evaluation, work evaluation, and intermediary evaluation. By analyzing the laws of the self-construction of the art discipline, we continuously optimize the teaching quality evaluation system to improve the teaching quality of art graduate students.

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