Search Results

Now showing 1 - 1 of 1
  • Article
    An Investigation Into The AI-Assisted Visualization Of Children’s Songs: The Case Of Ali Baba’s Farm
    (Nilgun SAZAK, 2025) Südor, S.; İpekçiler, B.
    This study aims to visualize children’s songs, which are part of primary-level music education, using AI-supported tools. The objectives of the Ministry of National Education’s music course curriculum were examined, and both the themes to be emphasized in song selection and the pedagogical functions of children’s songs were analyzed. In the literature review, the Web of Science and Google Scholar databases were used. The obtained source data were analyzed with the VOSviewer software to generate conceptual maps, through which thematic trends in the field were identified. In the practical part of the study, the children’s song “Old MacDonald’s Farm” was visualized in detail using two different AI-supported tools: RunwayML and WZRD.ai. In RunwayML, prompt-based scenes were generated using the “text-to-video” feature, and visuals compatible with the lyrics of the song were created. On the WZRD.ai platform, visuals were automatically generated in response to sound waves, and the limitations of the platform were examined. Based on the findings, it was concluded that RunwayML offers more effective results for pedagogical content production, while WZRD. ai, despite its technical capabilities, falls short in delivering child-appropriate visual stimuli. The study also provides a theoretical foundation on synesthesia and discusses how AI tools can be integrated into music education in early childhood and primary school levels. The findings indicate that AI-supported visualization tools have the potential to provide engaging and flexible educational materials that support learning at the primary school level. It is recommended that teacher training programs develop hands-on modules for these tools, and that future research focus on how these technologies can be adapted to various songs, age groups, and learning domains. © © 2025 The Author(s). This is an open access article distributed under the Creative Commons Attribution License (CC BY), which permits unrestricted use, distribution, and reproduction in any medium or format, provided the original work is properly cited.