Open AccessThe Application of Artificial Intelligence Technology in the Quality Evaluation of Dance Multimedia Teaching in Higher Vocational Colleges
Author(s) -
Yuanhang Jiao
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1533/3/032059
Subject(s) - dance , vocational education , quality (philosophy) , class (philosophy) , computer science , teaching method , multimedia , mathematics education , teaching and learning center , cognition , psychology , artificial intelligence , pedagogy , art , philosophy , epistemology , neuroscience , literature
Through scientific and effective evaluation of dance classroom teaching quality, teachers can objectively and accurately evaluate teaching methods, attitudes and effects, and lay a cognitive foundation for the improvement of dance teaching quality. The purpose of this article is to evaluate the teaching quality of dance multimedia in vocational colleges based on artificial intelligence technology. The application of BP neural network in teaching evaluation and the algorithm of BP neural network teaching quality evaluation model are studied, and the construction of dance classroom teaching quality evaluation system is discussed. First, the same teacher uses the same teaching materials and uses different teaching methods to teach the students in the two classes respectively, and secondly, an interest survey on dance classes. The experimental results show that multimedia teaching has brought great convenience to teachers in preparing lessons and improved their professional level. In addition, the use of courseware to demonstrate actions in teaching avoids the negative impact on student presentations due to differences in teacher age, technology, and personal understanding. Compared with the control class, the experimental class increased the density of free practice by 10.93%, and the heart rate increased by 8 times / min.