Adoption of AI Music Generator by Early Childhood Educators in Digital Communities: A Netnographic Study of Practices, Perceptions, and Dynamics - Viktor Purhanudin; Tutut Pristiati; Muhammad Fabian Arrizqi; Mohd Rabe Alvi (Research in Education, Technology, and Multiculture, 2026)
The rapid advancement of generative artificial intelligence (AI), particularly in AI music generation platforms, presents new opportunities for early childhood educators to produce varied and contextually relevant musical learning materials. Empirical evidence regarding how early childhood education (PAUD) educators in Indonesia adopt, construct perceptions of, and negotiate AI music generators within digital communities remains limited. This study examined three research questions: what forms of practice PAUD educators demonstrate in utilizing AI music generators; how educators construct perceptions, opportunities, and concerns through digital community interactions; and what patterns of role differentiation characterize community dynamics around AI music generator adoption. A netnographic approach was employed, with data collected from Facebook Groups, TikTok, and YouTube communities of PAUD educators over 12 months. Data sources comprised 286 digital archival interactions, online interviews with ten purposively selected informants, and researcher field notes, analyzed through inductive thematic analysis with inter-rater reliability verification (Cohen's kappa = .81). Three dominant practice patterns were identified: thematic song creation via text-to-music prompting (54.2%), adaptation and reimagination of existing children's songs (23.8%), and active distribution of AI-generated musical content (22.0%). Educators' perceptions were polarized, combining positive constructions of efficiency, accessibility, and pedagogical creativity with concerns about overreliance on technology, Western-centric algorithmic bias, and unresolved copyright status. Community dynamics revealed three organically differentiated roles, namely active creators, adopters, and critical curators, with platform algorithms creating a discursive hierarchy that privileges practical-demonstrative content over reflective-critical engagement. These findings confirm that PAUD educators' digital communities function as horizontal professional learning ecosystems in which the adoption of AI music generators is negotiated through intersecting values of pedagogy, cultural identity, and technological pragmatism. Keywords: AI music generator, early childhood music education, netnography, digital educator community, music stimulation.