Optimizing AI-Powered Music Creation Social Media to Amplify Learning Content

Abstract

This research aims to describe the orienting, implementing, and assessing aspects constructed by music teachers in optimizing AI-powered music creation social media to amplify learning content. This research used a qualitative approach with a descriptive method. Data were collected through focus group discussions (FGDs) and documentation studies. The data analysis technique used the Miles and Huberman model with the stages, 1) data collection, 2) data reduction, 3) data presentation, 4) conclusion drawing/verification. Data validity used triangulation techniques, including source and technical triangulation. The results show that, orientatively, the experience of interacting with technological advances and social dynamics has shaped the respondents' knowledge and understanding, not only on various types and functions, but also in determining the strengths, weaknesses, opportunities, and threats of the platform. Implementatively, in line with the values of music education, the integration of a platform that amplifies content into learning is used to engage students' creative dimensions where cognitive, affective, and psychomotor are bound to the ethical principles of AI use and aesthetic criteria of music. By assessment, the involvement of peer teachers and students provided an important drive in establishing effectiveness, impact, and support from stakeholders. This study recommends that the development of AI used in creation is a new challenge for music teachers in strengthening the integrity of their professionalism. The utilization of these tools and resources makes it easier for them to be creative in clarifying and emphasizing the elements of musical sound to build effective and valuable learning.