Ai-Powered Graphic Design Tools
A Paradigm Shift in Art Curriculum
Bibliographic Data
| ID | 22199209 |
|---|---|
| Authors | Meeta Kharadi (Parul University), Vikas Sagar (Jaypee Institute of Information Technology), Deepak Bhanot (Chitkara University), Soumya Soumya (Presidency University), Smitha K (Noida International University), Smitha K Smitha K, Swati Singh (0000-0001-7420-9438, Noida International University), Vaishali Sunilsingh Bayas (International Institute of Information Technology) |
| Year | 2025 |
| Volume | 6 |
| Issue | 4s |
| Pages | 299-308 |
| Publication date | 2025-12-25 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ShodhKosh: Journal of Visual and Performing Arts (JOURNAL) |
| Journal identifiers | ISSN: 2582-7472 • E-ISSN: 2582-7472 |
| Publisher | Granthaalayah Publications and Printers (PUBLISHER • IN) |
| DOI | 10.29121/shodhkosh.v6.i4s.2025.6855 |
| OpenAlex | W7117424298 |
| Language | EN |
| References cited | 15 |
The large-scale, swift development of AI-based graphic designing systems: generative models, intelligent layout systems, automated typography engines, and multimodal creative assistants has triggered a paradigm shift in the art and design education curricula. These technologies do not only hasten the creative work processes, but they also change the very cognitive, aesthetic and pedagogical principles that design education has been founded on. The paper will discuss the ways in which AI-driven tools can be used to assist ideation, visual problem-solving, adaptive learning, and skill democratization through allowing students to experiment with sophisticated design variants, simulate workflow, and be provided with real-time design feedback. The suggested AI-based algorithm unites a hybrid learning system that includes a generative visual model (GV-Net), attention-focused layout optimizer (AGLO), and an adaptive design feedback recommender (DF-Rec). It is a system that enables the automation in composition generation, color harmony prediction, multimodal creativity improvement as well as individualized learning trajectories through student-performance embeddings. By means of the iterated interaction, learners co-create with AI and enhance fluency, originality and visual coherence. In our analysis, the pedagogical change of using AI-enabled design tools in management schools, design institutes, and interdisciplinary programs can be identified. Quantitative and qualitative assessments have shown that the creativity indices, increased engagement, and better conceptual clarity have been improved compared to the traditional teaching. The paper will be covering the curriculum redesign frameworks, AI-assessment models, the ethical and cultural issues of machine-generated creativity, and the future prospects of hybrid human AI design studios
CLARITY · Creativity · Curriculum · Design education · Environmental graphic design · Generative Design · Generative grammar · Graphic design · Typography · Aesthetic Perception and Analysis · Art, Technology, and Culture · Design Education and Practice
| Highly cited | No |
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