Pembelajaran Deep Learning Berbasis Android di Sanggar Tari Tari Army Dance Production Surabaya
DOI:
https://doi.org/10.54259/diajar.v5i2.7444Keywords:
Dance Learning, Deep Learning, Android, Army Dance ProductionAbstract
This study examines the implementation of Android-based deep learning in dance education at Army Dance Production (ADP) Studio in Surabaya, Indonesia, and investigates the extent to which this technological approach can enhance the quality of learning and student engagement. The primary focus lies in leveraging Android devices as tools for recording, documenting, and replaying dance movements, thereby serving as a medium for evaluation and self-directed reflection among dancers. Through systematic visual documentation, trainees are able to observe movement deficiencies, refine techniques, and improve both expression and ensemble cohesion, either independently or under instructor guidance. This study employs a descriptive qualitative research design. Data were collected through structured observation, in-depth interviews, and documentation involving the studio owner, instructors, and visual records of the learning process. Findings reveal that the integration of Android devices as a documentation medium yields a significantly positive impact on practice quality and student engagement. Students, including those with special needs, demonstrated accelerated movement memorization and improved technique correction through video-based self-evaluation. Furthermore, the systematic uploading of practice sessions to social media platforms such as YouTube, TikTok, and Instagram proved effective as both a documentation archive and a motivational tool. In conclusion, technology-supported dance learning can serve as a foundational step toward broader digital integration in the performing arts, offering a scalable, accessible, and pedagogically sound model for nonformal arts education institutions.
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