Digital Feedback and Self-Regulated Learning in Professional Art Education: A Structured Integrative Review and the M-SRL Framework
DOI:
https://doi.org/10.34142/27091805.2026.7.02.05Keywords:
professional art education; self-regulated learning; digital feedback; piano pedagogy; music technology; evidence frameworkAbstract
Object. This structured integrative review examines how digitally captured information becomes feedback in piano and adjacent music practice, and how that feedback relates to self-regulated learning (SRL) — with particular attention to a distinction that is easy to blur: observable practice traces are not the same thing as stronger claims about learning.
Methods & methodology. Four OpenAlex searches through 15 August 2026 yielded 327 records and 322 unique records. All unique records received title-and-abstract screening; 33 direct-scope metadata candidates were identified, and nine reconciled evidence units met a five-condition claim-level gate covering publication identity, population and task, intervention or exposure, outcomes, and limitations stated with maximum defensible wording. The synthesis was qualitative, because designs, measures, exposures, and outcome families were too heterogeneous for a defensible pooled estimate.
Scientific novelty. M-SRL is proposed as an unvalidated seven-dimension, music-specific evidence-reporting framework. It does not claim first-in-field status for technology-supported SRL or digital feedback; its search-bounded contribution is narrower — to align capture, inference, output, timing, agency, outcome, and artistic-pedagogical authority in one reporting vocabulary.
Results. Evidence was heterogeneous. Favourable findings for self-evaluation, metacognition, motivation, usability, or immediate performance coexisted with null findings, small samples, bundled interventions, short exposures, and divergent measures. No general superiority of visual, auditory, haptic, immersive, or AI-mediated feedback could be established from the reconciled evidence. Digital traces increase observability; they do not, by themselves, establish pedagogical effectiveness.
Conclusions. M-SRL separates observable traces from stronger pedagogical and artistic claims and offers a testable reporting vocabulary for future digital music-practice research, while preserving the role of teacher, learner, and artistic judgement.
Downloads
References
Amm, V., Chandran, K., Engeln, L., & McGinity, M. (2024). Mixed reality strategies for piano education. Frontiers in Virtual Reality, 5, 1397154. https://doi.org/10.3389/frvir.2024.1397154 [in English]
Behzadaval, B., Serra Marin, L., & Nijs, L. (2026). Application of visual information in music education digital technologies: A scoping review. Education Sciences, 16(2), 309. https://doi.org/10.3390/educsci16020309 [in English]
Boucher, M., Creech, A., & Dubé, F. (2021). Video feedback and the self-evaluation of college-level guitarists during individual practice. Psychology of Music, 49(2), 159–176. https://doi.org/10.1177/0305735619842374 [in English]
Butler, D. L., & Winne, P. H. (1995). Feedback and self-regulated learning: A theoretical synthesis. Review of Educational Research, 65(3), 245–281. https://doi.org/10.3102/00346543065003245 [in English]
dos Santos Silva, C., Araújo, M. V., & Marinho, H. (2024). Attitudes in music practice: A survey exploring the self-regulated learning processes of advanced Brazilian and Portuguese musicians. Frontiers in Psychology, 15, 1324100. https://doi.org/10.3389/fpsyg.2024.1324100 [in English]
Fujimoto, M. (2026). Interpretive autonomy predicts self-regulated learning behaviors in lessons, practice, and performance among classical musicians. Frontiers in Psychology, 17, 1859878. https://doi.org/10.3389/fpsyg.2026.1859878 [in English]
Hamond, L., Himonides, E., & Welch, G. (2020). The nature of feedback in higher education studio-based piano learning and teaching with the use of digital technology. Journal of Music, Technology & Education, 13, 33–56. https://doi.org/10.1386/jmte_00015_1 [in English]
Hamond, L. F., Welch, G., & Himonides, E. (2019). The pedagogical use of visual feedback for enhancing dynamics in higher education piano learning and performance. OPUS, 25(3), 581–601. https://doi.org/10.20504/opus2019c2526 [in English]
Kaleli, Y. S. (2020). The effect of computer-assisted instruction on piano education: An experimental study with pre-service music teachers. International Journal of Technology in Education and Science, 4(3), 235–246. https://doi.org/10.46328/ijtes.v4i3.115 [in English]
Li, W., Cui, X., Manoharan, P., Dai, L., Liu, K., & Huang, L. (2025). AI-assisted feedback and reflection in vocal music training: Effects on metacognition and singing performance. Frontiers in Psychology, 16, 1598867. https://doi.org/10.3389/fpsyg.2025.1598867 [in English]
López-Calatayud, F., & Tejada, J. (2023). Self-efficacy in instrumental practice with intonation assessment software: A multiple case study with novice violin and viola students. Journal of Music, Technology & Education, 16(1–2), 57–76. https://doi.org/10.1386/jmte_00060_1 [in English]
López-Calatayud, F., & Tejada, J. (2024). Self-regulation strategies and behaviors in the initial learning of the viola and violin with the support of software for real-time instrumental intonation assessment. Research Studies in Music Education, 46(1), 48–65. https://doi.org/10.1177/1321103X221128733 [in English]
López-Íñiguez, G., & McPherson, G. E. (2024). Using a music microanalysis protocol to enhance instrumental practice. Frontiers in Psychology, 15, 1368074. https://doi.org/10.3389/fpsyg.2024.1368074 [in English]
McPherson, G. E., & Zimmerman, B. J. (2011). Self-regulation of musical learning: A social cognitive perspective on developing performance skills. In R. Colwell & P. Webster (Eds.), MENC handbook of research on music learning: Volume 2: Applications (pp. 130–175). Oxford University Press. https://doi.org/10.1093/acprof:osobl/9780199754397.003.0004 [in English]
Nusseck, M., Wild, F., Sischka, C., & Spahn, C. (2025). Effects of audio feedback interventions with the Disklavier on the performance of piano students. Frontiers in Psychology, 16, 1568021. https://doi.org/10.3389/fpsyg.2025.1568021 [in English]
Osaki, I., Fujioka, T., Schumann, E., & Maezawa, A. (2026). Piano practice support system with visual feedback and evaluation protocols for learning experience based on subjective and objective metrics. In Proceedings of the 18th International Conference on Computer Supported Education (CSEDU 2026), Vol. 1, 535–544. https://doi.org/10.5220/0015064300004021 [in English]
Ou, J., Nogueira, J., & Qin, C. (2025). Exploring the impact of AI-assisted practice applications on music learners’ performance, self-efficacy, and self-regulated learning. Frontiers in Psychology, 16, 1675762. https://doi.org/10.3389/fpsyg.2025.1675762 [in English]
Panadero, E. (2017). A review of self-regulated learning: Six models and four directions for research. Frontiers in Psychology, 8, 422. https://doi.org/10.3389/fpsyg.2017.00422 [in English]
Pike, P. D. (2017). Exploring self-regulation through a reflective practicum: A case study of improvement through mindful piano practice. Music Education Research, 19(4), 398–409. https://doi.org/10.1080/14613808.2017.1356813 [in English]
Priem, J., Piwowar, H., & Orr, R. (2022). OpenAlex: A fully-open index of scholarly works, authors, venues, institutions, and concepts. arXiv. https://doi.org/10.48550/arXiv.2205.01833 [in English]
Song, H., Tsiakas, K., Ham, J., Markopoulos, P., & Barakova, E. I. (2024). ‘How would you score yourself?’: The effect of self-assessment strategy through robots on children’s motivation and performance in piano practice. International Journal of Social Robotics, 16, 327–340. https://doi.org/10.1007/s12369-023-01080-3 [in English]
Turan, H. S. (2026). A thematic review of online piano education research (2019–2024). Music Education Research. Advance online publication. https://doi.org/10.1080/14613808.2026.2655762 [in English]
Utermohl de Queiroz, D., Foletto, C., & López-Íñiguez, G. (2025). Pedagogical approaches to promote self-regulation in musical instrument learning: A PRISMA scoping review. Psychology of Music. Advance online publication. https://doi.org/10.1177/03057356251348414 [in English]
Wan, L., Crawford, R., & Jenkins, L. (2022). Facilitating self-regulation of instrumental practice with digital technology: A framework, a synthesis of literature and a call for research. Australian Journal of Music Education, 54(2), 83–98. [in English]
Wan, L., Crawford, R., & Jenkins, L. (2023). Digital listening tools to facilitate children’s self-regulation of instrumental music practice. Journal of Research in Music Education, 71(1), 67–90. https://doi.org/10.1177/00224294221093521 [in English]
Whittemore, R., & Knafl, K. (2005). The integrative review: Updated methodology. Journal of Advanced Nursing, 52(5), 546–553. https://doi.org/10.1111/j.1365-2648.2005.03621.x [in English]
Wilson, K., & Pfeiffer, P. E. (2023). Feedback in augmented and virtual reality piano tutoring systems: A mini review. Frontiers in Virtual Reality, 4, 1207397. https://doi.org/10.3389/frvir.2023.1207397 [in English]
Winne, P. H. (2020). Construct and consequential validity for learning analytics based on trace data. Computers in Human Behavior, 112, 106457. https://doi.org/10.1016/j.chb.2020.106457 [in English]
Published
License
Copyright (c) 2026 Даві де Олівейра Емерік (Автор)
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
