Pedagogical Transformation in Audiovisual-Based Vocal Learning: Evidence from a Pre-Experimental Triangulation Study
DOI:
https://doi.org/10.24114/grenek.v15i1.73625Keywords:
Vocal Learning, Audiovisual Media, Digital Pedagogy, Self-Regulated Learning, Vocal CompetenceAbstract
This study examined pedagogical transformation in audiovisual-based vocal learning within digital music education, focusing on reflection, self-directed learning, learning interaction, student engagement, and vocal competence. A pre-experimental one-group pretest-posttest design with a concurrent triangulation approach was used. Thirty-two fifth-semester students completed a 12-week intervention involving vocal technique videos, self-directed practice through performance recordings, video-based reflection, and synchronous and asynchronous feedback. Data were collected using a pedagogical transformation instrument and objective vocal competence assessments by two independent evaluators. Analysis applied paired-samples t-tests, Cohen’s d, and Pearson correlation. Results showed significant improvements in all pedagogical indicators and vocal competence dimensions (p < .001). Reflection showed the largest gain (d = 2.13), followed by self-directed learning (d = 1.87). Changes in pedagogical indicators correlated strongly with vocal competence development (r = .74, p < .001). The findings highlight reflection, self-directed learning, and engagement as key dimensions in digital vocal learning.
References
Archibald, M. M. (2015). Investigator Triangulation. Journal of Mixed Methods Research, 10(3), 228–250. https://doi.org/10.1177/1558689815570092
Barclift, K., & MacLeod, R. B. (2023). Exploring Preservice Music Teachers’ Self-Reflections: A Comparison of Immediate and Video Reflections. Journal of Music Teacher Education, 33(3), 29–43. https://doi.org/10.1177/10570837231208224
Biasutti, M., Philippe, R. A., & Schiavio, A. (2021). Assessing teachers’ perspectives on giving music lessons remotely during the COVID-19 lockdown period. IRIS, 26(3), 585–603. https://doi.org/10.1177/1029864921996033
Boelens, R., Wever, B. D., & Voet, M. (2017). Four key challenges to the design of blended learning: A systematic literature review. Ghent University Academic Bibliography (Ghent University), 22, 1–18. https://doi.org/10.1016/j.edurev.2017.06.001
Bond, M., Bedenlier, S., Marín, V. I., & Händel, M. (2021). Emergency remote teaching in higher education: mapping the first global online semester. International Journal of Educational Technology in Higher Education, 18(1), 50–50. https://doi.org/10.1186/s41239-021-00282-x
Broadbent, J., & Fuller‐Tyszkiewicz, M. (2018). Profiles in self-regulated learning and their correlates for online and blended learning students. Educational Technology Research and Development, 66(6), 1435–1455. https://doi.org/10.1007/s11423-018-9595-9
Cohen, J. (2013). Statistical Power Analysis for the Behavioral Sciences. https://doi.org/10.4324/9780203771587
Creswell, J. W., & Creswell, J. D. (2023). Research Design Qualitative, Quantitative, and Mixed Methods Approaches (6th ed.). SAGE.
Elmabaredy, A., & Gençel, N. (2024). Exploring the integration of self-regulated learning into digital platforms to improve students’ achievement and performance. Discover Education, 3(1). https://doi.org/10.1007/s44217-024-00233-4
Field, A. P. (2017). Discovering Statistics Using Ibm Spss Statistics. https://bvbr.bib-bvb.de:443/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029907115&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
Graham, C. R. (2018). Current Research in Blended Learning (pp. 173–188). https://doi.org/10.4324/9781315296135-15
Jansen, R. S., Leeuwen, A. van, Janssen, J., Jak, S., & Kester, L. (2019). Self-regulated learning partially mediates the effect of self-regulated learning interventions on achievement in higher education: A meta-analysis. Educational Research Review, 28, 100292–100292. https://doi.org/10.1016/j.edurev.2019.100292
Lakens, D. (2013). Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Frontiers in Psychology, 4, 863–863. https://doi.org/10.3389/fpsyg.2013.00863
Laucirica, A., Reizábal, A. L. de, Merzero, A., & Martín, J. A. O. (2021). Evaluación psicoacústica y profesional sobre la interpretación vocal en estudiantes de canto. Revista Electrónica Complutense de Investigación en Educación Musical - RECIEM, 18, 73–81. https://doi.org/10.5209/reciem.69012
Liljequist, D., Elfving, B., & Roaldsen, K. S. (2019). Intraclass correlation – A discussion and demonstration of basic features. PLoS ONE, 14(7). https://doi.org/10.1371/journal.pone.0219854
Martin, F., Sun, T., & Westine, C. D. (2020). A systematic review of research on online teaching and learning from 2009 to 2018. Computers & Education, 159, 104009–104009. https://doi.org/10.1016/j.compedu.2020.104009
McPherson, G. E., Blackwell, J., & Hattie, J. (2022). Feedback in Music Performance Teaching. Frontiers in Psychology, 13, 891025–891025. https://doi.org/10.3389/fpsyg.2022.891025
Moura, N., Dias, P., Veríssimo, L., Oliveira‐Silva, P., & Serra, S. (2024). Solo music performance assessment criteria: a systematic review. Frontiers in Psychology, 15, 1467434–1467434. https://doi.org/10.3389/fpsyg.2024.1467434
Nugroho, T. S. A., & Kusumaningrum, M. R. M. (2021). Strategi Pembelajaran Daring Praktik Vokal di Prodi Musik Fakultas Seni Pertunjukan ISI Yogyakarta. Tamumatra Jurnal Seni Pertunjukan, 4(1). https://doi.org/10.29408/tmmt.v4i1.4018
Osborne, M. S., McPherson, G. E., Miksza, P., & Evans, P. (2020). Using a microanalysis intervention to examine shifts in musicians’ self-regulated learning. Minerva Access (University of Melbourne), 49(4), 972–988. https://doi.org/10.1177/0305735620915265
Otčenášek, J., Frič, M., Dvořáková, E., Otčenášek, Z., & Ubik, S. (2022). The subjective relevance of perceived sound aspects in remote singing education. The Journal of the Acoustical Society of America, 151(1), 428–433. https://doi.org/10.1121/10.0009143
Panadero, E. (2022). A review of self-regulated learning: Six models and four directions for research. Frontiers in Psychology, 13, 861482. https://doi.org/10.3389/fpsyg.2022.861482
Panadero, E., Fraile, J., Pinedo, L., Rodríguez-Hernández, C. F., Eizmendi, E. B., & Díez, F. (2022). Teachers’ Well-Being, Emotions, and Motivation During Emergency Remote Teaching Due to COVID-19. Frontiers in Psychology, 13, 826828–826828. https://doi.org/10.3389/fpsyg.2022.826828
Rapanta, C., Botturi, L., Goodyear, P., Ortiz, L. G., & Koole, M. (2020). Online University Teaching During and After the Covid-19 Crisis: Refocusing Teacher Presence and Learning Activity. Postdigital Science and Education, 2(3), 923–945. https://doi.org/10.1007/s42438-020-00155-y
Redmond, P., Heffernan, A., Abawi, L., Brown, A., & Henderson, R. (2018). An Online Engagement Framework for Higher Education. Online Learning, 22(1). https://doi.org/10.24059/olj.v22i1.1175
Reeve, J., & Shin, S. H. (2019). How teachers can support students’ agentic engagement. Theory Into Practice, 59(2), 150–161. https://doi.org/10.1080/00405841.2019.1702451
Sandberg-Jurström, R., & Lindgren, M. (2022). Mapping the applicants’ learnability: a discourse analysis of assessors’ talk of admission tests for Swedish specialist music teacher education. Music Education Research, 24(5), 599–610. https://doi.org/10.1080/14613808.2022.2098263
Santoveña-Casal, S., & López, S. R. (2023). Mapping of digital pedagogies in higher education. Education and Information Technologies, 29(2), 2437–2458. https://doi.org/10.1007/s10639-023-11888-1
Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009884217&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
Siddiq, F., Røkenes, F. M., Lund, A., & Scherer, R. (2023). New kid on the block? a conceptual systematic review of digital agency. Education and Information Technologies, 29(5), 5721–5752. https://doi.org/10.1007/s10639-023-12038-3
Wan, L., Crawford, R., & Jenkins, L. (2022). 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
Wong, J., Khalil, M., Baars, M., Koning, B. B. de, & Paas, F. (2019). Exploring sequences of learner activities in relation to self-regulated learning in a massive open online course. Computers & Education, 140, 103595–103595. https://doi.org/10.1016/j.compedu.2019.103595
Zimmerman, B. J. (2002). Becoming a Self-Regulated Learner: An Overview. Theory Into Practice, 41(2), 64–70. https://doi.org/10.1207/s15430421tip4102_2
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Delvia Mona, Yensharti, Mia Fahmiati

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors published with the Grenek: Jurnal Seni Musik agree to the following terms:
- Authors retain copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work. (See The Effect of Open Access)





