The construction of a localized teaching model of the Orff music teaching method based on big data analysis

Abstract

In the era of the big information wave and rapid development of economic globalization, the traditional music teaching mode in China has failed to completely develop the times. Here focuses on constructing a localized teaching mode of the Orff music teaching method in the case of cloud information analysis, firstly, understanding the definition of cloud information, using the MOOC platform design and offline traditional Orff music teaching method to build the localized teaching mode. The system is designed with SSH structure as the framework and BP-related calculation methods, with basic theory as the key point adopted by related calculation method, implementation process adopted for break-in effect inspiring rules for evaluating the actual use, analyzing the accuracy and stability of the three algorithms through experiments of three cases, and the final from experimental analysis accuracy of BP neural network algorithm is between 77% and 86%, which is higher than the accuracy and stability of the other two algorithms. Furthermore, stability is high, thus building a set of localized and innovative teaching models suitable for Chinese music education, which is conducive to improving students’ aesthetic and artistic level and bringing Chinese music to the world stage.

Keywords

• big data
• mooc platform design
• bp neural network algorithm
• ssh structure
• localized teaching model construction.
• 68t05