Formation of Musical Identity During Vocal Training Based on Machine Intelligence Tools

Bibliographic Data

ID19490226
AuthorsLiubov Kaniuka (Singer (United States)), Tamara Koval (Academy of Municipal Management), Olha Vasylenko (0000-0003-4431-8515, Kyiv Institute of Music. R. Glier), Svitlana Borovyk (Academy of Municipal Management), Volodymyr Humeniuk (0009-0001-5617-9156, Kyiv Institute of Music. R. Glier)
Year2026
Volume7
Issue1
Pages187-207
Publication date2026-03-25
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueShodhKosh: Journal of Visual and Performing Arts (JOURNAL)
Journal identifiersISSN: 2582-7472 • E-ISSN: 2582-7472
PublisherGranthaalayah Publications and Printers (PUBLISHER • IN)
DOI10.29121/shodhkosh.v7.i1.2026.7031
OpenAlexW7140296169
LanguageEN
References cited53

Modern technologies contribute to the gradual development of vocal skills, which affects the rethinking of traditional learning. Digital algorithms are aimed at obtaining individual musical experience, which affects the formation of musical identity. The purpose of the research is to determine the advantages of artificial intelligence for the development of musical identity, which is associated with taking into account the challenges and prospects for vocal and theoretical schools. The research strategy involved the use of systems analysis methods, observation, the R. Likert scale, ANOVA analysis of variance, and the method of analysis of hierarchies. In the course of the research, it was found that the formation of musical identity using digital instruments is associated with a change in the structure of the educational process, assessment methods and planning of the educational approach, the development of vocal technique, planning of song performance methods and repertoire development. The analysis showed that digital instruments influence the formation of musical identity skills, which are related to creativity and aesthetics of performance, cognitive-analytical and performance capabilities. Adaptation of VocalPitchMonitor, SpectraLayers AI, and AI Artistic Evaluation into the educational process allowed for developing the technique, expressiveness of singing, and focus on creating musical improvisations. Based on the students’ results, it was found that the formed level of musical identity was significantly higher after training (4.9 and 4.8 points) than before the start of the study (3.0 and 2.7 points). Observations showed that the prospects of machine intelligence in education are associated with an individual approach to learning (0.36) and receiving systematic feedback (0.33). Among the challenges of such training were the formation of a unified sound (0.28) and the development of technocratization of education (0.26). The practical direction of the research is associated with the selection of effective tools for the formation of musical identity in the process of vocal training of second-year students

Creativity · Likert scale · Musical · Repertoire · Diverse Music Education Insights · Education, Psychology, and Complexity Research · Educational Methods and Outcomes

Tools

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