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Educational Value of Ai-Powered Folk Art Repositories

Bibliographic Data

ID22195041
AuthorsKumod Kumar Gupta (0000-0003-4682-1720), Bharat Bhushan (0000-0001-7161-6601, Chitkara University), Pooja Goel (0000-0001-7635-5842, Noida International University), Jyoti Saini (0009-0009-3987-856X, University of Mumbai), Aniket Prakashrao (Yashwantrao Chavan Maharashtra Open University), Amit Kumar (0000-0003-4000-1780, Chitkara University)
Year2025
Volume6
Issue1s
Publication date2025-12-10
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueShodhKosh: Journal of Visual and Performing Arts (JOURNAL)
Journal identifiersISSN: 2582-7472 • E-ISSN: 2582-7472
PublisherGranthaalayah Publications and Printers (PUBLISHER • IN)
DOI10.29121/shodhkosh.v6.i1s.2025.6640
OpenAlexW4417295186
LanguageEN
References cited14

The application of artificial intelligence (AI) to a psychological collection of folk art is one of the revolutionary methods for studying, preserving, and teaching cultural history in the digital era. AI empowered folk art repositories employ the latest technologies such as computer vision, machine learning, and natural language processing to collect, categorize, tag, and recommend various types of folk art. Not only are these sites used to safeguard endangered art forms, they also provide constantly changing accessible learning environments. AI systems can identify style trends, regional influences and elements of themes in vast collections of folk art by curating them intelligently. Through this, students can experience personalised and interactive learning experiences. This essay explores the pedagogical potential of these sorts of collections examining basic concept, development and application in the classroom. A focus is given to how AI tools are used to assist students and teachers to learn about other cultures, develop creative thinking and become more culturally literate. In addition, the study discusses how mentally and emotionally enriching it can be to engage in communication with digitally produced content that is culturally rich in its content and style. Case analysis of existing AI-based art education tools is conducted in order to provide a view of how they function and how results are realized in real-world experience. But the study also discusses important issues, including the reliability of the data, how it can be ethically represented, the limitations of technology, and how computational bias can result in culture homogenization

Cultural diversity · Digital content · Folk culture · Traditional knowledge · Visual arts education · Aesthetic Perception and Analysis · Art Education and Development · Digital Media and Visual Art

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