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In contemporary society, the rapid advancement of networking technology is instigating profound transformations across various industries. The educational sector, too, is actively exploring the integration of online technologies to revolutionize teaching methodologies and enrich learning outcomes. With the advent of big data and artificial intelligence (AI), novel approaches to augment online vocal music education have emerged (Yousefi Noorale et al., 2020).
Historically, music education predominantly took place through conventional face-to-face interactions. However, this traditional paradigm was constrained by factors such as time, geographical limitations, and resource availability. Nevertheless, with the widespread accessibility of the Internet and technological progress, online education has swiftly risen, offering learners flexible and convenient avenues for learning. Online vocal music education, representing an innovative facet of music instruction, has progressively gained traction among learners (Xu et al., 2019). Nonetheless, online education encounters certain challenges, including the provision of tailored learning support and the enhancement of learner engagement and satisfaction. It is within this context that big data furnishes novel solutions for online vocal music education.
Big data refers to a collection of massive data, including structured data (such as table data in databases) and unstructured data (such as text, images, and audio). These datasets are typically so large that traditional data processing tools struggle to handle them. Big data technology refers to a series of techniques and tools used to collect, store, process, and analyze these massive datasets. It includes, but is not limited to, distributed computing, data mining, machine learning, and AI (Bartlett et al., 2019).
In online learning, big data technology plays a crucial role. First, it helps platforms collect and analyze various data generated by students during the learning process, including learning behaviors, progress, and mastery of knowledge points. Educators can better understand students' learning needs and behavioral patterns by analyzing the data, enabling personalized teaching and guidance. Besides, big data technology assists online learning platforms in optimizing course design and teaching methods. Potential issues or bottlenecks in courses can be identified by analyzing vast amounts of learning data. Moreover, adjustments can be made to course content, teaching methods, and assessment methods, making the courses more tailored to students' needs and learning styles. Additionally, big data technology can support online learning platforms in predictive analytics, such as predicting students' learning outcomes or predicting the risk of student dropout, enabling corresponding measures to improve learning outcomes and retention rates.
Therefore, big data technology is highly relevant to the course design and research of online learning. It helps educators better understand students, optimize teaching, improve learning outcomes, and ultimately advance the development of online education.
AI technology, constituting a vital component of big data, has the capability to emulate human intelligence and behavior, thereby furnishing intelligent learning support for online vocal music education (Wang, 2022). For instance, voice recognition technology can aid learners in rectifying pronunciation errors, while voice evaluation technology can assess their singing proficiency and offer personalized guidance. Moreover, virtual reality and augmented reality technologies can offer learners an immersive music learning experience, heightening their engagement and interest (Shen et al., 2023).