Application of Big Data Technology in College Music Education

Introduction

In the 21st century, human society has officially entered the information age. New internet technologies are continually emerging, followed by a massive amount of data. We need to collect and analyze these data, gain valuable information, and apply it to our daily lives and work (Zhang and Wan, 2020).

China attaches great importance to the development of big-data technology (Yu and Ding, 2020). In recent years, with the rapid development of internet technology, emerging technologies such as big data, artificial intelligence (AI), augmented reality (AR) have gradually matured to the point that they can be found in all walks of life, providing a strong boost to China's informatization and effectively improving residents' working and living standards (Green, 2006). Big-data technology is an important foundation for other scientific developments, and the emergence of big data marks the arrival of a profound revolution in the information age, that is, the “third wave” of information development, which has brought earth-shaking changes to national economic development and to people's productivity and lives (Gao, 2020).

Compared with research on big-data mining in the United States since September 11, 2001, China's research started late, but it is developing rapidly (Cui, 2020). In recent years, projects such as smart cities, digital villages, and intelligent transportation are constantly emerging, which shows that the state attaches great importance to the development of big data and indicates that big data has become the trend of the times (Yuan, 2020).

Figure 1.

The impact of big data on other industries

Research on emerging internet technologies in colleges and universities is at the forefront of the times. Big-data technology is the basis of knowledge in key research fields such as AI and AR, so the importance attached by colleges and universities is natural. Universities use big-data technology to collect student data, analyze and process it, and improve the efficiency of school management. Collecting students' family information, reward and punishment records, achievements in various subjects, and other data can help colleges analyze and understand students' living habits, study status, and other specific situations and formulate better teaching-management systems.

As one of the important components of higher education, music education in colleges and universities involves a large amount of data. It is particularly important to analyze and process these data and use this information as the theoretical basis for adjusting teaching methods. For example, the school's music course offerings are adjusted according to the proportion of students who have chosen the courses in the past. People who are interested in a particular subject account for a relatively large proportion, so there are more courses the following semester.

Big-data technology is, of course, conducive to teaching students in accordance with their aptitude, but when collecting and analyzing students' data, we must protect their privacy. Some data should be accessed only by specific people, and there are certain errors in massive data that need to be identified with discretion. Special attention should be paid to data protection to avoid data leakage.

Based on the rapid development of the big-data era, this article studies the application of big-data technology specifically to university music education. The research aims to help college students cultivate independent thinking and improve their ability to learn music independently through online teaching platforms and to help colleges develop different teaching plans based on students' music learning data.

Big-Data Technology

Big data is the collection of massive amounts of information from various users. The role of big-data technology is not just to collect information blindly, but to analyze and process these data to uncover valuable information (Li, 2021a). At the beginning, big data was used only in the IT research field, but now it has been used everywhere for decades. Nowadays, whether it is in regard to a wide variety of product recommendations, college course offerings, or facial recognition for online payments, massive data information is required (Kang, 2016).