Optimization Path of Art Teaching Methods in Colleges Based on Multiuniverse Algorithm and IOT

Abstract

The optimization path of art teaching methods in universities cannot balance the contradiction and conflict between cost and benefit, which affects the educational efficiency. This paper proposes an optimization path method for art teaching methods in universities based on a multiuniverse algorithm. According to the relationship between teachers, students, and teaching materials, build an efficient art teaching knowledge dissemination model, extract the characteristics of art teaching innovation path, and make decisions on costs and benefits. Establish the art teaching path selection model based on the multiuniverse algorithm, give full play to the leading role of the university organization system through path design, and meet the personalized teaching and learning needs of teachers and students by designing the cost and cost objective function under the optimal benefit of art teaching. Using dance as an example, the art teaching path optimization approach based on a multiuniverse algorithm has an education efficiency of 1.476, which is 0.593 and 0.607 greater than the methods based on association rule and clustering algorithms. As a result, this strategy can improve the quality of art instruction while also facilitating reform and innovation in the classroom.