Analysis of Piano Teaching in Colleges and Universities from Perspective of Big Data

Abstract

The two characteristics of big data technology are excellent data perception ability and strong data processing ability. At the same time, it also has innovative technologies for distributing, storing, parsing, capturing, and processing data with different structures. Big data technology can be used as a means of college teaching mode analysis. From this point of view, it is necessary to study piano teaching in colleges and universities with the technology. Corresponding to the problems of low data results and accuracy in the traditional algorithm of piano teaching in colleges and universities, we propose an analysis and evaluation model of piano teaching in universities based on big data. The big data analysis of the constraint parameters of the piano teaching mode in universities is promoted, too, and the quantitative recursive analysis of piano teaching in universities is carried out. Finally, the model is optimized, and the simulation test is carried out with MATLAB. The average evaluation accuracy of this method reaches 95.99%, and the average utilization rate reaches 94.12%. Compared with the conventional two methods, this method is better than the other two methods, which shows that the big data method is better applied to the evaluation of piano teaching mode in universities.