Trends in Informatization of Electronic Music Composition Data in the Context of Distance Education

Xiaopeng Liu

doi:10.4108/eetsis.3826

Authors

Xiaopeng Liu School of Music, Shandong University of Arts, Jinan 250014, Shandong, China

DOI:

https://doi.org/10.4108/eetsis.3826

Keywords:

SPOC distance education, electronic music, data informatics, music education

Abstract

INTRODUCTION: With the development of information technology in education, many educational institutions and companies have flocked to the emerging online education market. MOOC is a new method of e-learning that has changed the world and significantly impacted the educational community.

OBJECTIVES: This paper aims to present typical features for developing an online music education platform using MOOC music, AI-based music learning software, and interactive real-time music learning.

METHODS: This paper discusses different models of music teaching methods and pedagogy and summarizes the advantages and disadvantages of such models.

RESULTS: Online music education is an internet technology that fully uses the Internet right to organize good music education.

CONCLUSION: Based on the characteristics and content of music education, this paper presents possible suggestions for the sustainable and healthy development of new data and information models for music education on the Internet in the future.

References

Rebelo Miguel,Serrano João,DuarteMendes Pedro,Monteiro Diogo,Paulo Rui,Marinho Daniel Almeida. Evaluation of the Psychometric Properties of the Portuguese Peabody Developmental Motor Scales-2 Edition: A Study with Children Aged 12 to 48 Months. Children,2021,8(11).

Kudinova V.A., Karpov V.Y., Boldov A.S., Marinina N.N. Motor skills training model to improve school physical education service quality. Teoriya i Praktika Fizicheskoy Kultury,2021,2021(7).

Adam, T. B., & Metljak, M. (2022). Experiences in distance education and practical use of ICT during the COVID-19 epidemic of Slovenian primary school music teachers with different professional experiences. Social Sciences & Humanities Open, 5(1), 100246.

Anand, R., Sabeenian, R. S., Gurang, D., Kirthika, R., & Rubeena, S. (2021). AI-based Music Recommendation System using Deep Learning Algorithms. IOP Conference Series Earth and Environmental Science, 785(1), 012013. https://doi.org/10.1088/1755-1315/785/1/012013

Asif, S., & Mckechanie, A. (2021). A new service model in East Lothian community learning disability team: Evaluation of service with and without a specialist positive behavior support team. BJPsych Open, 7(1), S309–S309. https://doi.org/10.1192/bjo.2021.817

Bourgeois-Bougrine, S., Bonnardel, N., Thornhill-Miller, B., Pahlavan, F., Buisine, S., Guegan, J., Pichot, N., Lubart, T., & Burkhardt, J. M. (2022). Immersive Virtual Environments’ Impact on Individual and Collective Creativity. European Psychologist, 27(3), 237–253. https://doi.org/10.1027/1016-9040/a000481

Bynoth, R. (2021). A Mother Educating her Daughter Remotely through Familial Correspondence: The Letter as a Form of Female Distance Education in the Eighteenth Century. History, 106(373), 727–750. https://doi.org/10.1111/1468-229X.13237

Cramer, E. M., Jenkins, B. M., & Sang, Y. (2023). What is behind that screenshot? Digital windows and capturing data on screen: Convergence: The International Journal of Research into New Media Technologies, 29(2), 467–480. https://doi.org/10.1177/13548565221089211

Economics, G. comSchool of, & Management, C., Beijing University of Technology, Beijing100124. (2021). Feature and Tendency of Technology Transfer in Z-Park Patent Cooperation Network: From the Perspective of Global Optimal Path. Journal of Data and Information Science, 6(4), 111–138. https://doi.org/10.2478/jdis-2021-0034

Gan, I., & Sun, R. (2022). Digital Barriers and Individual Coping Behaviors in Distance Education During COVID-19. International Journal of Knowledge Management, 18(1), 1–15. https://doi.org/10.4018/IJKM.290023

Hong, Y. S., Han, C. P., & Cho, S. S. (2021). Level-Based Learning Algorithm Based on the Difficulty Level of the Test Problem. Applied Sciences, 11(10), 4380. https://doi.org/10.3390/app11104380

Karkina, S. V., Valeeva, R. A., & Stari, A. I. (2021). Improving Professional Skills of Music Teachers Through the Use of Distance Learning. Journal of Information Technology Research, 14(2), 187–199. https://doi.org/10.4018/JITR.2021040110

Leahy, K. S., & Smith, T. D. (2021). The self-directed learning of adult music students: A comparison of teacher approaches and student needs: International Journal of Music Education, 39(3), 289–300. https://doi.org/10.1177/0255761421991596

Lerch, A., & Knees, P. (2021). Machine Learning Applied to Music/Audio Signal Processing. Electronics, 10(24), 3077-. https://doi.org/10.3390/electronics10243077

Müller, M., Mcfee, B., & Kinnaird, K. M. (2021). Interactive Learning of Signal Processing Through Music. IEEE Signal Processing Magazine, 38(3), 73–84. https://doi.org/10.1109/MSP.2021.3052181

Sha, W., Li, Y., Tang, S., Tian, J., Zhao, Y., Guo, Y., Zhang, W., Zhang, X., Lu, S., & Cao, Y. C. (2021). Machine learning in polymer informatics. 信息材料(英文), 3(4), 9.

Song, R. (2021). Research on the Application of Computer Multimedia Music Systems in College Music Teaching. Journal of Physics Conference Series, 1744(3), 032214. https://doi.org/10.1088/1742-6596/1744/3/032214

Tan, J., Xia, D., Dong, S., Zhu, H., & Xu, B. (2021). Research On Pre-Training Method and Generalization Ability of Big Data Recognition Model of the Internet of Things. ACM Transactions on Asian and Low-Resource Language Information Processing, 20(5), 1–15.

Tuncer, H., & Karata, T. Z. (2022). Recommendations of ELT Students for Four Language Skills Development: A Study on Emergency Distance Education During the COVID-19 Pandemic: SAGE Open, 12(1), 49–76. https://doi.org/10.1177/21582440221079888

Xing, J. (2021). Research on the Application of Preschool Music Education in Colleges and Universities Based on Network Information Technology. Journal of Physics: Conference Series, 1992(2), 022019 (5pp). https://doi.org/10.1088/1742-6596/1992/2/022019

Yao, M., Wang, Y., Li, X., Sheng, Y., Huo, H., Xi, L., Yang, J., & Zhang, W. (2021). Materials informatics platform with three-dimensional structures, workflow and thermoelectric applications. Scientific Data, 8(1), 236-. https://doi.org/10.1038/s41597-021-01022-6

Zhao, Q., & Li, Z. (2021). Application of Computer Vision Media Simulation Technology in Distance Education of New Generation Labor Productivity. Journal of Physics Conference Series, 1992(4), 042044. https://doi.org/10.1088/1742-6596/1992/4/042044

Xiao, Y., He, Y., Gao, X., Lu, L., & Yu, X. (2021). Career Exploration and College Students’ Career Adaptability: The Mediating Role of Future Work Self-Salience and Moderating Role of Perceived Teacher Support. Discrete Dynamics in Nature and Society, 2021(2), 1–10.