TINJAUAN LITERATUR TENTANG PEMBELAJARAN SENI MUSIK BERBASIS DEEP LEARNING DALAM MENDUKUNG PEMAHAMAN UNSUR MUSIK (NADA, IRAMA, DAN MELODI) PADA SISWA SEKOLAH DASAR

Authors

  • Hafizatul Reza Nayla Universitas Negeri Padang
  • Dani Anisa Imanda Universitas Negeri Padang
  • Ramanda Febriana Universitas Negeri Padang
  • Azizil Alim Universitas Negeri Padang
  • Desyandri Desyandri Universitas Negeri Padang

DOI:

https://doi.org/10.23969/jp.v11i02.53625

Keywords:

deep learning, music education, elementary school, systematic literature review.

Abstract

Music education in elementary schools continues to face challenges in developing students’ understanding of musical elements, particularly pitch, rhythm, and melody, while deep learning approaches and artificial intelligence (AI)-based technologies offer promising opportunities to improve learning quality, although their implementation in Indonesian primary music education has not yet been systematically reviewed. This study aims to synthesize empirical evidence on the implementation of deep learning-based music education in supporting elementary students’ understanding of musical concepts. A Systematic Literature Review (SLR) was conducted following the PRISMA 2020 guidelines. Literature was collected from Google Scholar, ERIC, Scopus, and Publish or Perish databases covering publications from 1997 to 2026. Of the 100 studies initially identified, 32 articles met the inclusion criteria and were analyzed through thematic synthesis. The findings revealed five major themes: digital technology and multimedia-based learning (31.25%), deep learning and meaningful learning (25.00%), musical elements instruction (18.75%), music education in elementary schools (15.63%), and collaborative learning and student engagement (9.37%). The reviewed studies consistently indicated that deep learning approaches integrated with video-based media, collaborative activities, and AI-supported technologies enhanced students’ understanding of pitch, rhythm, and melody. Learning outcomes showed an average achievement score of 92.5 and a learning mastery rate of 100%. The study concludes that integrating deep learning into music education strengthens students’ mastery of musical concepts while promoting creativity, collaboration, and critical thinking; keywords: deep learning, music education, elementary school, systematic literature review.

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References

Asis, A., & Isogon, E. J. D. (2025). Teachers' pedagogical approaches, content knowledge and practices in teaching music: Bases for the development of instructional material. SSRN. Retrieved from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5395882

Astuti, K. S., Widyastuti, M. G., & Silaen, H. T. (2019). The influence of deep learning model on musicality and character through Dolanan songs. In Advances in Social Science, Education and Humanities Research. https://doi.org/10.1201/9780429024931-11

Bartolome, S. J. (2025). If it's got a melody, it can be sung!: Singing in the life and scholarship of Patricia Shehan Campbell. In Perspectives on music, education, and diversity. Cham, Switzerland: Springer. https://doi.org/10.1007/978-3-031-82737-2_3

Brophy, T. S. (1997). Authentic assessment of vocal pitch accuracy in first through third grade children. Contributions to Music Education, 24, 57–68.

Byrne, R., Murphy, R., Ward, F., & McCabe, U. (2024). Playful music teaching and learning in Irish primary school classrooms. Irish Educational Studies. Advance online publication. https://doi.org/10.1080/03323315.2024.2330886

Chantanasut, T. (2024). Developing and evaluating a rhythm reading practice kit: A study on learning outcomes and music learners satisfaction in music education using quantitative analysis. Journal of Applied Data Sciences.

Costes-Onishi, P., & Kwek, D. (2023). Inquiry-based learning in music: Indicators and relationships between key pedagogical practices and the quality of critical thinking. Research Studies in Music Education. https://doi.org/10.1177/1321103X211057457

Duinker, B. (2023). Rhythmic theory pedagogy, ways of knowing, and experiential learning. Journal of Music Theory Pedagogy, 37.

Guobin, Z., Suttachitt, N., & Charoensloong, T. (2025). Designing innovative online lessons to foster piano playing skills for beginners with no prior experience. Journal of Posthumanism.

Hogenes, M., Van Oers, B., & colleagues. (2016). The effects of music composition as a classroom activity on engagement in music education and academic and music achievement: A quasi-experimental study. International Journal of Music Education, 34(1), 32–48. https://doi.org/10.1177/0255761415584296

Ilari, B. (2020). Longitudinal research on music education and child development: Contributions and challenges. Music & Science, 3, 1–11. https://doi.org/10.1177/2059204320937224

Kemendikdasmen. (2025). Panduan pembelajaran mendalam (deep learning). Jakarta, Indonesia: Kementerian Pendidikan Dasar dan Menengah.

Kalkanoğlu, B. (2025). The effect of using technology in music education and training on academic achievement: A meta-analysis study. Education and Science.

Li, Y. (2022). Study on intelligent online piano teaching system based on deep learning recurrent neural network model. Mobile Information Systems. https://doi.org/10.1155/2022/9469975

Li, Y. (2025). Research on music education simulation based on interactive experience of virtual and reality. Systems and Soft Computing. https://doi.org/10.1016/j.sasc.2025.200232

Li, Y., & Sun, R. (2023). Innovations of music and aesthetic education courses using intelligent technologies. Education and Information Technologies, 28, 8671–8690. https://doi.org/10.1007/s10639-023-11624-9

Mandarić, L. V., & Brajković, E. (2025). AI technologies in music education: Personalized learning for elementary school students. In International Conference on Digital Technologies (pp. 182–194). Cham, Switzerland: Springer. https://doi.org/10.1007/978-3-032-02801-3_12

McGarry, D. (2024). Creating thinking classrooms in music education: Teacher and student perspectives of twenty-first-century instruction (Doctoral dissertation). Liberty University.

Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Systematic Reviews, 10(1), 89. https://doi.org/10.1186/s13643-021-01626-4

Palaigeorgiou, G., & Pouloulis, C. (2018). Orchestrating tangible music interfaces for in-classroom music learning through a fairy tale: The case of ImproviSchool. Education and Information Technologies, 23(2), 709–731. https://doi.org/10.1007/s10639-017-9608-z

Pan, C. (2024). Deep learning perspectives in e-learning: Analyzing music teaching methods within core literacy context. Computer-Aided Design and Applications, 21(S22), 205–218.

Papadogianni, M., Altinsoy, E., & colleagues. (2024). Multimodal exploration in elementary music classroom. Journal on Multimodal User Interfaces. https://doi.org/10.1007/s12193-023-00420-x

Peretti, S., Caruso, F., Pino, M. C., Giancola, M., & colleagues. (2025). The CrazySquare project for music learning in Italian school-age pre-adolescents: Integrating technology into educational practice. Journal of Computers in Education. https://doi.org/10.1007/s40692-024-00320-3

Phanichraksaphong, V., & Tsai, W. H. (2023). Automatic assessment of piano performances using timbre and pitch features. Electronics, 12(8), 1791. https://doi.org/10.3390/electronics12081791

Reinsalu, H., Timoštšuk, I., & Ruokonen, I. (2022). Literature review about the learning engagement in preschool and primary school music education. Problems in Music Pedagogy, 21(2), 35–69.

Ruan, C., & Lin, C. (2023). Research on the construction of vocal music teaching mode based on deep learning model. Computer-Aided Design and Applications, 20(S12), 202–215.

Scott, S. (2011). Contemplating a constructivist stance for active learning within music education. Arts Education Policy Review, 112(4), 191–198. https://doi.org/10.1080/10632913.2011.592469

Stark, T. (2024). Deeper listening: Aural learning as a tool for large instrumental ensemble rehearsals (Master's thesis).

Wang, H. (2021). An empirical study on the development of music cognition by different teaching methods based on parameter equation. Dynamic Systems and Applications, 30(4), 1321–1334.

Wang, T., & Yu, X. (2024). Practical analysis of multi-modal teaching behavior in elementary school music singing game teaching. Arts Educa.

Wang, Y., Tan, W. H., Ye, Q., & Gu, T. (2026). Effects of game-based learning on piano music knowledge among elementary school pupils: Pretest-posttest quasi-experimental study. JMIR Serious Games, 14, e80766.

Webster, P. R. (2011). Construction of music learning. In R. Colwell & P. Webster (Eds.), MENC handbook of research on music learning (pp. 35–83). New York, NY: Oxford University Press.

Wei, Q. (2025). Research on the design and practice of primary school music large-unit teaching under the guidance of core competencies. Journal of Sociology and Education.

Yihan, L., Cuong, T. V., Oo, T. Z., & colleagues. (2025). Content adaptation, validation, and user experience of the Music Island app for Chinese elementary music education. Educational Process: International Journal.

Yuanbo, Z., & Kim, H. (2025). Innovative pathways for practical music teaching: An integrated perspective of grounded theory and analytic hierarchy process. Asia-Pacific Journal of Convergent Research Interchange.

Yusoff, S. M., Marzaini, A. F. M., Hassan, M. H., & colleagues. (2023). Investigating the roles of pedagogical content knowledge in music education: A systematic literature review. Malaysian Journal of Music.

Zhang, Y., & Liu, C. (2025). Melody prediction of vocal performance using LSTM and attention mechanism and its application in folk music innovation. Journal of Computational Methods in Sciences and Engineering. https://doi.org/10.1177/14727978251324133

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Published

2026-06-30