Optimization of Intangible Cultural Heritage Art Education and Inheritance Paths Assisted by Artificial Intelligence

Abstract

Nowadays, digital information technology has made outstanding achievements in the protection of many large-scale tangible heritage, “digital protection of intangible cultural heritage” is gradually known and used by people, and the data has become a new valuable resource. This paper firstly analyzes the influencing factors of the inheritance of intangible cultural heritage art, and obtains the final fitting results of the logistic regression model. It optimizes the curriculum objectives, curriculum content, and teaching methods of art education, and proposes the reform of art education. Taking Shaanxi folk songs as an example, a survey experiment was designed to analyze the respondents' evaluation of Shaanxi folk songs, and most of the respondents believed that the inheritance and development of folk songs needed to be intervened, and the support rate of "inheritor training" was the highest, with an average score of 5.26, followed by "documentary record" and "nationwide promotion", with a score of 5.24. The students were guided to the teaching practice of non-heritage music inheritance, and their artistic performance and cognition were analyzed through the control test. The mean values of artistic performance and cognitive assessment of the students in the experimental class are 7.984 points and 8.208 points respectively, which are better than those of the control group, indicating that the teaching practice of the experimental class is more efficient and the non-heritage culture can be better inherited and educated.