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Article type: Research Article
Authors: Yang, Yeling; *
Affiliations: Zhejiang Yuexiu University, School of Art, Shaoxing, Zhejiang, China
Correspondence: [*] Corresponding author. Yeling Yang, Zhejiang Yuexiu University, School of Art, Shaoxing 312000, Zhejiang, China. E-mail: [email protected].
Abstract: Vocal music training for college students impacts the social and emotional aspects of better learning. This impact must be classified progressively to improve the social and musical connectivity coinciding with real-time emotions. Therefore, an intermittent analysis of music learning is required for augmenting socio-emotional changes to the learning method. This article introduces Impact-centric Learning Analysis (ILA) using the Fuzzy Control Algorithm (FCA) for the purpose above. The control algorithm operates in two linear stages: in the first stage, the socio-emotional impact of the learning on the students is analyzed, pursued by the learning changes in the second stage. This first stage inputs student activity scores based on real-time implications. The lowest scores are classified independently in the second stage, and learning changes are carried out. The learning change is targeted to meet the maximum (optimal) impact score from the first stage using fuzzy differentiations based on training sessions and student performance. Therefore, the proposed algorithm generates an optimal impact for the considered features (socio-emotional), preventing trivial vocal music sessions.
Keywords: Fuzzy control, impact optimization, socio-emotional learning, vocal music
DOI: 10.3233/JIFS-233922
Journal: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2024
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