A Case Study of Teaching-Learning Strategies Using Generative Artificial Intelligence in a Problem-Based Learning Program for Fashion Marketing

This study developed and evaluated teaching-learning strategies for fashion marketing education by integrating generative artificial intelligence (AI) within a problem-based learning (PBL) framework. A design-based research approach was used to create a six-week educational program comprising three phases: learning about generative AI, learning from generative AI, and collaborating with generative AI. The program centered on product planning and digital marketing promotion within the 4P marketing mix, utilizing various generative AI tools. Participants included 35 undergraduate students enrolled in a Fashion e-Business course, with 17 completing both the pre- and post-surveys. Data collection used a mixed-methods approach, including quantitative surveys on generative AI literacy, creative problem-solving abilities, and learning satisfaction, as well as qualitative analysis of team project outcomes and instructor observations. Students were divided into nine teams and completed projects involving market analysis, brand development, design creation, and digital marketing campaigns using generative AI tools. Results showed significant improvements in students' generative AI utilization capabilities across both text and image generation. Among the five dimensions of generative AI literacy, creative competency showed the highest growth, followed by communication competency. Students actively utilized generative AI across various domains, with design image generation being the most frequently used application, followed by idea development and text generation. The study presents the first empirical framework for integrating generative AI with PBL in fashion marketing education, demonstrating AI’s potential as a creative partner while preserving the importance of critical thinking.