USING TEXT-TO-IMAGE GENERATOR FOR INDUSTRIAL DESIGN IDEATION: A CASE STUDY IN LIGHTING-INSPIRED DESIGN

Idea generation is a critical component of industrial design education, serving as the foundation for creativity and innovation in the field. Equipping students with effective idea generation skills is essential for producing outstanding designs. However, the translation of conceptual ideas into impactful visual representations remains a challenge. Conventional methods, relying solely on visual sketch descriptions, often constrain the creative process and limit design possibilities, risking the compromise of originality through overreliance on established trends. In this context, the emergence of generative Artificial Intelligence (AI), particularly text-to-image technology, presents a transformative solution. This paper delves into the potential of leveraging text-to-image generation in industrial design education, specifically focusing on lighting-inspired design. The objectives of this study encompass exploring the method's potential in the early stages of idea generation, providing practical recommendations for educators and students, and analyzing associated challenges. This study conducted with 23 Bachelor of Industrial Design students in College of Creative Arts, UiTM Kedah, who been given task to developed a concept for lighting-inspired design using these popular text-to-image generators: recraft.ai, stablecog.com, and ideogram.ai. The study employs two stages of idea generation, which are, Stage 1 involves inputting text prompt to generate an image while Stage 2 employs Text-Guided Image-to-Image using image provided in stage 1. Through carefully crafted prompts, this methodology encourages users to explore diverse design alternatives while maintaining alignment with specific objectives. As an educational tool, it facilitates a deeper understanding of design principles, aesthetics, and visual composition. The key lies in using design-related terminology in well-structured prompts to ensure relevant results. It is crucial to acknowledge that, although this technology enhances design aesthetics, consideration for technical viability and functional aspects remains imperative. By addressing potential challenges and limitations, educators and students can maximize the tool's potential to expedite idea generation, stimulate creativity, and ultimately foster innovation.

Authors

Publication Details

Journal
International Journal of Modern Education
Published
2024-09-30
DOI
https://doi.org/10.35631/ijmoe.622021
Primary Topic
Design Education and Practice
Type
article
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article

USING TEXT-TO-IMAGE GENERATOR FOR INDUSTRIAL DESIGN IDEATION: A CASE STUDY IN LIGHTING-INSPIRED DESIGN

Mohammed A. Amin
International Journal of Modern Education
Design Education and Practice
article

USING TEXT-TO-IMAGE GENERATOR FOR INDUSTRIAL DESIGN IDEATION: A CASE STUDY IN LIGHTING-INSPIRED DESIGN

Mohammed A. Amin
article en

Abstract

Idea generation is a critical component of industrial design education, serving as the foundation for creativity and innovation in the field. Equipping students with effective idea generation skills is essential for producing outstanding designs. However, the translation of conceptual ideas into impactful visual representations remains a challenge. Conventional methods, relying solely on visual sketch descriptions, often constrain the creative process and limit design possibilities, risking the compromise of originality through overreliance on established trends. In this context, the emergence of generative Artificial Intelligence (AI), particularly text-to-image technology, presents a transformative solution. This paper delves into the potential of leveraging text-to-image generation in industrial design education, specifically focusing on lighting-inspired design. The objectives of this study encompass exploring the method's potential in the early stages of idea generation, providing practical recommendations for educators and students, and analyzing associated challenges. This study conducted with 23 Bachelor of Industrial Design students in College of Creative Arts, UiTM Kedah, who been given task to developed a concept for lighting-inspired design using these popular text-to-image generators: recraft.ai, stablecog.com, and ideogram.ai. The study employs two stages of idea generation, which are, Stage 1 involves inputting text prompt to generate an image while Stage 2 employs Text-Guided Image-to-Image using image provided in stage 1. Through carefully crafted prompts, this methodology encourages users to explore diverse design alternatives while maintaining alignment with specific objectives. As an educational tool, it facilitates a deeper understanding of design principles, aesthetics, and visual composition. The key lies in using design-related terminology in well-structured prompts to ensure relevant results. It is crucial to acknowledge that, although this technology enhances design aesthetics, consideration for technical viability and functional aspects remains imperative. By addressing potential challenges and limitations, educators and students can maximize the tool's potential to expedite idea generation, stimulate creativity, and ultimately foster innovation.

International Journal of Modern EducationVol. 6(22)
Openalex Percentile: Top 74%
Design Education and Practice
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USING TEXT-TO-IMAGE GENERATOR FOR INDUSTRIAL DESIGN IDEATION: A CASE STUDY IN LIGHTING-INSPIRED DESIGN — Mohammed A. Amin · International Journal of Modern Education (2024) | TGRS Research Map | TGRS