Südor, Serdar

Profile URL
https://hdl.handle.net/20.500.14411/6708
Name Variants
Südor, Serdar S.,Südor Sudor,Serdar S., Südor S., Serdar Serdar Südor S.,Sudor Serdar, Südor Sudor, Serdar Südor,S. Sudor,S. S.,Serdar S., Sudor Serdar, Sudor
Job Title
Doçent Doktor
Email Address
serdar.sudor@atilim.edu.tr
Main Affiliation
Graphic Design
Status
Website
ORCID ID
0000-0001-9769-1300
Scopus Author ID
60278113800
Turkish CoHE Profile ID
6C180C75420ED96D
Google Scholar ID
WoS Researcher ID

Research Topics

Domains
Physical SciencesSocial Sciences
Fields
Computer ScienceSocial Sciences
Subfields
Computer Science ApplicationsComputer Vision and Pattern RecognitionHuman-Computer InteractionArtificial IntelligenceEducation
Specific Research Areas
Teaching and Learning Programming
Augmented Reality Applications
Hand Gesture Recognition Systems
Artificial Intelligence in Games
Child Development and Digital Technology

Sustainable Development Goals

SDG data is not available
Documents

1

Citations

0

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Publication Collaboration

Affiliation Name Count
Mimar Sinan Güzel Sanatlar Üniversitesi 1
Gazi Hastanesi 1
Atilim University 1
1 / 1
Data obtained from OpenAlex
Scholarly Output

1

Articles

1

Views / Downloads

1/0

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

0

Scopus Citation Count

0

Patents

0

Projects

0

WoS Citations per Publication

0.00

Scopus Citations per Publication

0.00

Open Access Source

0

Supervised Theses

0

JournalCount
Online Journal of Music Sciences1
Current Page: 1 / 1

Scopus Quartile Distribution

Quartile distribution chart data is not available

Competency Cloud

GCRIS Competency Cloud
Author of Publication: search.filters.isAuthorOfPublication.8cac614e-6ebd-4341-844d-3026e29d23bc

Scholarly Output 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, 2025-07-28) 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.