Implementation of a Technology-Based Deep Learning Model in Music Theory Instruction: A Classroom Action Research Study at SMA Negeri 45 Jakarta

Abstract

Music theory instruction at the senior high school level is frequently delivered through conventional, memorization-based methods, which tend to limit engagement and motivation among today's digital-native students. This study aims to describe teachers' strategies in implementing a Deep Learning Model grounded in three principles — Mindful, Meaningful, and Joyful — and to analyze its impact on students' music theory learning outcomes with the support of the MUSSICA web-based learning platform. The study employed the Kemmis and McTaggart Classroom Action Research (CAR) model, conducted across two cycles involving 41 students of class XI-E at SMA Negeri 45 Jakarta. Data were collected through participatory observation, semi-structured interviews, Google Form-based achievement tests, and a Deep Learning reflection instrument, then analyzed qualitatively using the Miles and Huberman model of data reduction, display, and conclusion drawing. The results show that the mean learning outcome score increased from 63.02 on the Cycle I Post-Test to 82.34 on the Cycle II Post-Test, with the classical mastery percentage rising from 41.5% to 85.4%, surpassing the predetermined success indicator of 80%. The Deep Learning reflection instrument yielded a mean score of 61.8 out of 75 (high category), with the Joyful dimension scoring highest. This study affirms the relevance of the Deep Learning Model as a pedagogical instrument within Indonesia's Kurikulum Berdampak and offers a practical implementation model for technology-based music education in secondary schools.