Evaluation of Potential Correlation of Piano Teaching Using Edge-Enabled Data and Machine Learning

Abstract

Data science has expanded at an exponential growth with the advancement of big data technology. The data analysis techniques need to delve deeper to find valuable information (Sarac 2017). The notion of edge computing is broadly acknowledged. Edge-enabled solutions provide computing, analysis, storage, and control nearer to the edge of the network, which support the efficient processing and decision-making. Machine learning has also attained significant attention in this context due to its flexibility and its ability to provide a variety of supervised, unsupervised, and semisupervised techniques. This research presents a specific model to evaluate the potential correlation of piano teaching using machine learning. The data analysis is performed at the edges of network for efficient results (Tan et al. 2017). The association rule mining technique of machine learning is utilized with the integration of improved T-test method. The improved T-test is performed for the measurement of association rules and proposed a new measure and influence degree of association rules. It is evident from the results that the use of the degree of influence as a measure of association rules to find the potential relevance of multimedia-assistant piano teaching evaluation data is extremely feasible. It overcomes shortcomings of existing measurement standards and reduces the generation of redundant rules. The existing literature highlights the concepts of evaluation of potential correlation and evaluates the advantages. However, there is a lack of an effective strategy for piano teaching. The proposed model performs efficient calculation and storage. The feasibility and effectiveness of the proposed framework are verified using the analysis of the actual dataset. The verification results show that it is feasible and valuable to find the potential relevance of multimedia-assisted piano teaching evaluation.

[Retracted] Practice and Reflection on Piano Teaching Reform of Music Major in Colleges and Universities under Diversified Environment

“…Research on the teaching content and teaching purpose of piano: Some scholars take Yanbian University and some professional art colleges and normal universities in China as the research center to study the piano teaching content of these schools, and make a comparative study with the method of comparison; Efremova N. did systematic research and analysis from three aspects: the teaching purpose, teaching content, and teaching method of piano course for normal university [ 4 ]. Sun summarized his music experience in six contemporary music fields: piano art, comparative music, ethnomusicology, music education, music philosophy, and music aesthetics [ 5 ]; Wa studies the talent training mode from the perspective of higher music education, systematically combs and analyzes the history of the emergence and development of music education at home and abroad, provides examples and ideas for the creation of higher music education training mode, and puts forward the strategy of constructing the talent training mode of higher art education conducive to people's comprehensive development and social progress through the analysis of typical cases of music education at home and abroad [ 6 ].…”

Design of Piano Intelligent Teaching System Based on Neural Network Algorithm

“…Its appearance has changed the traditional information-based education mode and provided a modern education mode for students [11]. Also, it has evolved from a static piano-assisted teaching method to a new system of educational theory with dynamic piano curriculum strategies [12].…”

Application of Multimedia Technology in Online Piano Teaching

“…is online teaching method proposes new challenges for both teacher teaching and student learning [13].…”