Enhancement Strategies for Classroom Teaching Effect of Professional Art Education

Li, Nan

doi:10.3991/ijet.v16i06.21091

Cited by 5 publications

(5 citation statements)

References 13 publications

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“…For instance, Song & Lim (2022) [29] investigated how two teachers utilized teaching methods and technology and how their students responded to their instructional efforts. Li (2021) [30], from both teacher and student perspectives, conducted a multidimensional analysis to identify factors influencing the effectiveness of classroom teaching in professional art education. West & Bautista (2021) [31] applied a systematic concept to the professional development of music and art teachers, viewing policy as a systemic issue to address longstanding accessibility and scalability problems.…”

Section: Literature Reviewmentioning

confidence: 99%

The Analysis of Artificial Intelligence Digital Technology in Art Education Under the Internet of Things

Fang,

Jiang

2024

IEEE Access

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This study aims to explore the integration of Internet of Things (IoT) technology and artificial intelligence (AI) in art education, assessing its impact on learners' experiences and learning outcomes. The study first proposes a digital teaching system that enables the IoT and Generative Adversarial Networks (GANs) to play a role in art education by monitoring students' creative state in real-time, providing immediate feedback, and facilitating the generation of creative works. The system framework includes sensor nodes, an IoT platform, a GAN model, and a user interface to build a real-time interactive environment. Sensor nodes constantly collect physiological, movement, and environmental data from students, and the GAN model receives student data from the IoT platform, combining creative input from students to generate artwork in real-time. The generated works are transmitted to the discriminator through the IoT platform, which evaluates their quality and provides real-time feedback. Students interact with the system through the user interface, observe the generated artwork, adjust generator parameters, and propose new ideas. These interactions influence further artistic creation. The WikiArt public art creation dataset is selected to establish the experimental foundation, and the experimental evaluation focuses on image generation quality, system performance, and student learning outcomes. It is compared with Deep Convolutional Generative Adversarial Network (DCGAN) and Variational Autoencoder (VAE) models. The research results indicate that the designed IoT and GANs integrated system remarkably outperforms DCGAN and VAE in image generation quality, with an Inception Score of 4.5, which is more diverse and recognizable than other models. Regarding system performance, the IoT and GANs integrated system is significantly ahead in image generation speed and user interaction, with a transmission speed of up to 200 Mbps. Regarding student learning outcomes, the system performs excellently in emotional feedback, learning outcomes, and creative work quality, achieving 80% satisfaction and 90% positive feedback. Overall, the research conclusion clearly points out that the integration of IoT and GANs has a significant and comprehensive effect on improving the quality of art education. This study expands the field of art education by integrating IoT and GANs, enhancing students' creative experiences, and providing innovative methods for art teaching in the digital age.

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Section: Literature Reviewmentioning

confidence: 99%

The Analysis of Artificial Intelligence Digital Technology in Art Education Under the Internet of Things

Fang,

Jiang

2024

IEEE Access

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“…Focus on visual tension, impact, and individualization to ensure that students are able to participate actively and demonstrate unique creativity [5][6]. Emphasis is placed on the development of students' subjective activities in creative thinking so that aesthetic expression fully reflects creative thinking and rich and diverse forms of artistic expression are developed [7][8].…”

Section: Introductionmentioning

confidence: 99%

“…Feifei Duan. Applied Mathematics and Nonlinear Sciences, 9(1) (2024)[1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17] …”

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confidence: 99%

Analysis of Outstanding Problems and Countermeasures in the Reform of Fine Arts Teaching in China’s Colleges and Universities Based on the VAR Model

Duan

2024

Applied Mathematics and Nonlinear Sciences

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With the development of society, the artistic cultivation requirements for talents are increasing. This paper discusses in depth the main problems in the current reform of art teaching and puts forward targeted solution strategies, aiming to improve the overall quality of art teaching. In the study, the key factors affecting the quality of art teaching in colleges and universities were analyzed using the VAR model, and a multimodal art education knowledge map was constructed using the Viterbi method. Through the ALKPT knowledge tracking model, this paper assessed and scored students’ mastery of art knowledge and incorporated the results into the art classroom quality evaluation module. Based on the scoring data, the art classroom quality features were standardized, and the comprehensive evaluation results were derived through feature fusion dynamic weight assignment. Impulse response analysis showed that the number of returnees who studied abroad to learn about art positively impacted art teaching. The empirical results showed that after the reform of art teaching, the students’ art theory scores increased by 5 points on average, the scores were distributed between 10 and 20 points, and the achievement gap between students was reduced. This study provides a robust strategy and evaluation tool for optimizing art teaching, improving teaching quality and promoting students’ artistic literacy.

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“…The multi-perspective measurement index system and multi-factor decision-making were combined to create a corresponding measurement model for this purpose. According to the results, the effect can effectively enhance the classroom teaching effect of professional art education [20]. This paper integrates computer hardware and software resources, establishes a real-time 3D virtual environment, applies virtual reality technology to art drawing teaching, and explores the application effect of art drawing virtual teaching.…”

Section: Introductionmentioning

confidence: 99%

Research on the application of virtual reality technology in the teaching of art sketching

Tan

2024

Applied Mathematics and Nonlinear Sciences

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In this paper, we use Bayesian model to calculate color probability, train Bayesian classifier using a skin color training set of different gestures, and realize full skin color foreground object segmentation. The rendering of depth texture is established throughout to realize the unified scene rendering of art sketching teaching space and combined with a deep convolutional neural network to realize the interactive operation of virtual reality sketching teaching. Sampled students of T1 and T2 groups of art majors in Q College were analyzed for the acceptance of the virtual teaching scene of art sketching and explored the usability of virtual teaching of art sketching. Analyze and test the application effect of virtual teaching of art sketching from the two aspects of student’s learning motivation and the results of sketching work innovation assessment. The virtual simulation course of art sketching is designed to meet demand innovation by combining the total score of SUS and the application results. Based on the total SUS score of 62.325 for virtual teaching of art sketching, we added expert scoring data in the course design and obtained the difference between student scoring and expert scoring in terms of ease of operation, R42, and smoothness of operation and interaction, R23, which are only 0.01 and 0.06 respectively, which indicates that the virtual simulation course of art sketching should pay more attention to ease of operation and smoothness of operation. It shows that the virtual simulation course for art sketching should pay more attention to the ease of teaching and smoothness of operation and interaction.

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Enhancement Strategies for Classroom Teaching Effect of Professional Art Education

Cited by 5 publications

References 13 publications

The Analysis of Artificial Intelligence Digital Technology in Art Education Under the Internet of Things

The Analysis of Artificial Intelligence Digital Technology in Art Education Under the Internet of Things

Analysis of Outstanding Problems and Countermeasures in the Reform of Fine Arts Teaching in China’s Colleges and Universities Based on the VAR Model

Research on the application of virtual reality technology in the teaching of art sketching

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