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Ai-Enhanced Visual Editing Tools for Art Schools

Bibliographic Data

ID22198600
AuthorsGuadalupe Lucero Sánchez (0009-0004-4419-1803, Sathyabama Institute of Science and Technology), Godwin Premi M S, Jagmeet Sohal (Chitkara University), Sandhya L Sandhya L, L Sandhya (Presidency University), Rashmi Manhas (Noida International University), Chaitrali Chaudhari (Lokmanya Tilak Municipal General Hospital and Lokmanya Tilak Municipal Medical College), Ravi Kumar (0000-0001-5928-6339, Chitkara University)
Year2025
Volume6
Issue2s
Publication date2025-12-16
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.i2s.2025.6730
OpenAlexW4417500628
LanguageEN
References cited13

Current visual editing tools are changing the way art is taught through the incorporation of generative, analytical, and assistive computational analysis into studio practice through the use of AI. The paper discusses the effect of the diffusion networks, style-transfer systems, semantic segmentation engines, and restorative AI workflows on the learning of art, the development of skills, visual analysis, and exploration of concepts in art schools. The study proves the utilization of AI tools in quick ideation, better color and composition analysis, more available to learners with physical and cognitive disabilities, and more intensive interaction with stylistic experimentation. Simultaneously, the study also reveals such ethical, cultural, and legal issues as dataset transparency, authorship, cultural appropriation, and algorithmic bias. Four-layer integration framework is suggested to be used to be responsible in its adoption, including creative empowerment, skill deepening, ethical literacy, and institutional policy. The results highlight that AI must not be used as a replacement to the learning and practicing of basic artistic abilities but rather as a co-creative collaborator, capable of enhancing the ability to reflect and experiment as well as inclusive and critically informed visual education

Cognition · Creativity · Segmentation · Studio · Workflow · Aesthetic Perception and Analysis · Art Education and Development · Digital Media and Visual Art

  • Does an emotional connection to art really require a human artist? Emotion and intentionality responses to AI- versus human-created art and impact on aesthetic experience

    Open Access•Theresa Rahel Demmer, Corinna Kühnapfel et al.•Computers in Human Behavior•2023

  • Does human–AI collaboration lead to more creative art? Aesthetic evaluation of human-made and AI-generated haiku poetry

    Open Access•Jimpei Hitsuwari, Yoshiyuki Ueda et al.•Computers in Human Behavior•2023

Citation velocityhistorical
Highly citedNo

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