Self-regulated learning (SRL) is when learners manage their cognition, metacognition, and behaviors to control their learning. This occurs cyclically over three phases: forethought (planning/motivation for learning), performance (learning), and self-reflection (post-learning). Additionally, many believe SRL to be inextricably linked to motivation (Zimmerman, 2008).SRL is considered context-specific instead of a permanent trait. In other words, SRL changes based on situation (McPherson & Zimmerman, 2011). Though short-term SRL is relatively consistent (Weinert, 2023), semiregular collection of SRL over longer times indicates shifts, often within ranges unique to each learner (Osborne et al., 2021). However, since learners develop their ability to self-regulate over time (McPherson & Zimmerman, 2011), it is unclear if shifts indicate relatively permanent changes (e.g., learning to self-regulate) or short-term fluctuations based on context. It is possible that certain factors, such as an upcoming performance, might motivate short-term changes in SRL during an individual practice session.Therefore, the purpose of this study was to investigate the consistency of SRL over 12 weeks. Additionally, the impact of upcoming significant events on SRL was explored. SRL was measured using the Self-Regulation in Music Questionnaire (SRMQ), a forced-choice questionnaire that examines contextual and holistic SRL and has high internal reliability (α=.906; Weinert, 2023). SRL was assessed weekly over a 12-week period, a frequency thought to be sufficient for longer timeframes (Weinert, 2023). Participants (N=30) were students in a university’s orchestra and wind symphony and included a mix of music majors and non-music majors. Participants completed the SRMQ during their normal practice sessions and identified upcoming significant events in the next week.Data analysis is ongoing. Data are being analyzed using a Bayesian multilevel model, which is appropriate for medium sample sizes with varying numbers of repeated observations. Level 2 corresponds to participants and level 1 consists of their repeated observations. Hamiltonian Monte Carlo will be used to explore distributions of the model parameters and assess the impact of time and significant events on SRL.Data analysis is currently underway, however, results are expected to provide information regarding the permanency of SRL—are changes relatively permanent or simply temporary shifts, such as anticipation of an upcoming performance? Evidence of the effect of significant events on both SRL and motivation in individual practice will have implications both for researchers exploring SRL and music educators working with students to optimize their individual practice.