Author(s)

Yue Zhu ¹

Affiliation(s)

¹ Xi'an Shiyou University, Xi'an, Shaanxi, 710065, China

Corresponding Author

Yue Zhu

ABSTRACT

Vocal music teaching in colleges and universities is an emotional art course. In the process of vocal music teaching and training, teachers not only teach vocal music skills, but also train students' singing practice. This paper aims to study the teaching and training mode of vocal music in colleges and universities under the data fusion technology. This paper proposes a neural network algorithm, and takes students majoring in vocal music in college A as the experimental object. It was learned that there were 1,500 questionnaires in the experiment, and 499 valid questionnaires from University A. 187 people chose this major because of their personal interests. This part accounted for about 37.47%, and 207 people chose this major because of family reasons, accounting for about 41.48%. It shows that the students of school A choose to study vocal music mainly because of family factors and personal hobbies. The experimental results show the effectiveness of data fusion technology in the research of vocal music teaching and training mode in colleges and universities.

KEYWORDS

College Vocal Music Teaching, Data Fusion Technology, Training Mode, Information Processing Technology

CITE THIS PAPER

Yue Zhu, Construction on Vocal Music Teaching and Training Mode in Colleges and Universities Based on Data Fusion Technology. Advances in Educational Technology and Psychology (2024) Vol. 8: 117-125. DOI: http://dx.doi.org/10.23977/aetp.2024.080317.

REFERENCES

[1] M. Baughman. "Reservice teachers' experiences as first-time voice instructors." National Journal of Music Education, 40(2):301-312, 2022.
[2] L, Fu. "Discussion on the differences between theory and practice in vocal music teaching." Region - Educational Research and Reviews, 3(1):6-9. 2021.
[3] H, Fahey. "Stylistic pluralism and the experiences of classically trained teachers of singing in the Republic of Ireland." International Journal of Music Education, 39(3):301-312. 2021.
[4] J. Tomlinson. "Music therapist collaboration with teaching assistants for facilitating verbal and vocal development in young children with special needs: A mixed methods study." British Journal of Music Therapy, 34(2):95-107, 2020.
[5] A. Stoi and N. Jankovi. "Integrating music and language contents and skills in the academic course English language for children through songs and movement." Inovacije U Nastavi, 33(4):61-78, 2020.
[6] A. Ludwig Simone. "Performance analysis of data fusion methods applied to epileptic seizure recognition." Journal of Artificial Intelligence and Soft Computing Research, 12(1):5-17, 2022. 
[7] W. Gao, P. R. Miles, R. C. Smith and W. S. Oates. "The maximum entropy method for data fusion and uncertainty quantification in multifunctional materials and structures." Journal of Intelligent Material Systems and Structures, 33(9):1182-1197, 2022.
[8] Y. L. Hu, D. X. Qin and S. Y. Zhang. "Smart transportation travel model based on multiple data sources fusion for defense systems." Soft Computing, 26(7):3247-3259, 2022.

Sponsors, Associates, and Links

---

• Curriculum and Teaching Methodology
  
  
• Transactions on Comparative Education
  
  
• Applied & Educational Psychology
  
  
• Advances in Vocational and Technical Education
  
  
• Adult and Higher Education