Digital media entertainment technology based on artificial intelligence robot in art teaching simulation

IF 2.8 3区计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS Entertainment Computing Pub Date : 2024-06-23 DOI:10.1016/j.entcom.2024.100792

Xiayan Liao, Peng Cao

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Abstract

The combination of digital media entertainment technology and artificial intelligence robots provides new possibilities for art teaching, providing students with a richer and more personalized learning experience. The aim of this study is to explore the application of artificial intelligence based digital media entertainment technology in art teaching simulation. By designing an intelligent digital media system, the interactivity, personalization, and effectiveness of art teaching can be improved. Research the use of digital media interactive technology to create an immersive art learning environment. Applying artificial intelligence recommendation algorithms to recommend personalized art teaching resources to students based on their learning history, interests, and abilities, in order to improve learning efficiency and outcomes. Combining artificial intelligence recommendation algorithms, intelligently recommend suitable art teaching resources for different students’ needs and levels. Through teaching interaction simulation testing, evaluate the interaction effect and user experience of the system in simulated art teaching scenarios, identify and fix potential problems. By utilizing digital media interaction technology and personalized recommendation algorithms, designing an intelligent digital media system can effectively enhance the interactivity, personalization, and effectiveness of art teaching, providing students with a better learning experience.

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基于人工智能机器人的数字媒体娱乐技术在美术模拟教学中的应用

数字媒体娱乐技术与人工智能机器人的结合为美术教学提供了新的可能性，为学生提供了更丰富、更个性化的学习体验。本研究旨在探索基于人工智能的数字媒体娱乐技术在美术模拟教学中的应用。通过设计智能数字媒体系统，提高美术教学的互动性、个性化和有效性。研究利用数字媒体交互技术营造沉浸式美术学习环境。应用人工智能推荐算法，根据学生的学习历史、兴趣和能力，向学生推荐个性化的美术教学资源，以提高学习效率和效果。结合人工智能推荐算法，针对不同学生的需求和水平，智能推荐适合的美术教学资源。通过教学交互模拟测试，评估系统在模拟美术教学场景中的交互效果和用户体验，发现并解决潜在问题。利用数字媒体交互技术和个性化推荐算法，设计智能数字媒体系统，可有效增强美术教学的交互性、个性化和有效性，为学生提供更好的学习体验。

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来源期刊

Entertainment Computing Computer Science-Human-Computer Interaction

CiteScore

5.90

自引率

7.10%

发文量

期刊介绍： Entertainment Computing publishes original, peer-reviewed research articles and serves as a forum for stimulating and disseminating innovative research ideas, emerging technologies, empirical investigations, state-of-the-art methods and tools in all aspects of digital entertainment, new media, entertainment computing, gaming, robotics, toys and applications among researchers, engineers, social scientists, artists and practitioners. Theoretical, technical, empirical, survey articles and case studies are all appropriate to the journal.