Machine Learning-Based Aesthetic Music Education Informatics Assessment Method

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Abstract

Purpose. An instrumental mechanism for the identification, theoretical substantiation, and introduction of didactic conditions is a dynamic functional-structural model that performs orientation, managerial, formative, and analytical functions in the optimal organization of students' independent educational activity with the use of information and communication technologies. Method. During the research, a comprehensive target program of research and experimental work was developed, which was based on the step-by-step implementation of the didactic model, and its effectiveness was proved. Findings. The integration of traditional and electronic learning technologies within the framework of research and experimental work ensured systematic, planned, optimized organization, and enhanced control and diagnostic procedures of students' autonomous skills due to the requirements of manufacturability, adaptability, and control laid down in the tried-and-tested models of blended learning. Following the completion of the experimental work, quantitative, qualitative, and statistical analyses revealed positive dynamics in the levels of organization of independent educational activity of students of technological and pedagogical specialties with the use of information and communication technologies in motivational, content, operational, and productive criteria in the experimental group. Implications for Research and Practice. According to the results of experimental work in the experimental groups, statistically significant positive dynamics were recorded: 10% more students became with a high level of organization of independent educational activity, 13.3% ones were with a sufficient level, thus a number of students with indicators of critical and insufficient levels decreased on 23.3%.

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APA

Li, Y. (2022). Machine Learning-Based Aesthetic Music Education Informatics Assessment Method. Wireless Communications and Mobile Computing, 2022. https://doi.org/10.1155/2022/4301761

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