Version 1
: Received: 14 May 2024 / Approved: 15 May 2024 / Online: 15 May 2024 (08:24:16 CEST)
How to cite:
Peng, L.; Fang, X.; Guo, L. Investigating the Impact of Music Performance Anxiety (MPA) on Academic Performance in Music Education: A Nonlinear Data Fusion Model Approach. Preprints2024, 2024051014. https://doi.org/10.20944/preprints202405.1014.v1
Peng, L.; Fang, X.; Guo, L. Investigating the Impact of Music Performance Anxiety (MPA) on Academic Performance in Music Education: A Nonlinear Data Fusion Model Approach. Preprints 2024, 2024051014. https://doi.org/10.20944/preprints202405.1014.v1
Peng, L.; Fang, X.; Guo, L. Investigating the Impact of Music Performance Anxiety (MPA) on Academic Performance in Music Education: A Nonlinear Data Fusion Model Approach. Preprints2024, 2024051014. https://doi.org/10.20944/preprints202405.1014.v1
APA Style
Peng, L., Fang, X., & Guo, L. (2024). Investigating the Impact of Music Performance Anxiety (MPA) on Academic Performance in Music Education: A Nonlinear Data Fusion Model Approach. Preprints. https://doi.org/10.20944/preprints202405.1014.v1
Chicago/Turabian Style
Peng, L., Xiangkun Fang and Longchuan Guo. 2024 "Investigating the Impact of Music Performance Anxiety (MPA) on Academic Performance in Music Education: A Nonlinear Data Fusion Model Approach" Preprints. https://doi.org/10.20944/preprints202405.1014.v1
Abstract
This research aims to investigate psychological anxiety factors, particularly Music Performance Anxiety (MPA), that influence the sustainability of music learning systems. This study employs an innovative integration of qualitative and quantitative methodologies, marking the first use of a nonlinear system paired with a comprehensive data framework for analyzing questionnaire responses. This approach allows for a detailed examination of the effects of these factors on academic outcomes. Previous research has primarily focused on the fragmented music learning system from the perspective of teachers' instructional strategies, emphasizing phased teaching methods and learning objectives which focus often neglected a significant subset of music learners. Addressing this oversight, the current study specifically centers on the emotional aspects of anxiety within music learning systems, with a particular emphasis on students, who play a crucial role in music education. This perspective enables a deep exploration of how MPA and other related emotional factors affect music learning systems. A notable innovation of this research is the development of a stochastic nonlinear system designed to model the psychological factors impacting student music learning, complemented by a quantitative model that assesses actual learning outcomes. By analyzing this nonlinear system, the research identifies weight values for various negative emotions, particularly those related to MPA, that significantly influence the music learning process. The integration of MPA and other anxiety related emotional factors with practical learning outcomes provides a comprehensive understanding of their combined impact on the music learning system. These insights are invaluable for educators and policymakers aiming to enhance both the effectiveness and emotional well-being within music education. This comprehensive approach offers a novel perspective in understanding and improving the dynamics of music education through a more empathetic and scientifically grounded lens.
Keywords
music education; Music Performance Anxiety (MPA); nonlinear system; questionnaire investigation; data fusion
Subject
Arts and Humanities, Music
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
