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Insight Through Dialogue: A Practical Exploration of AIGC in Cross-cultural Design Research

  • Xiaoxuan Zhao,
  • Yue Qiu

摘要

This study systematically reviews the objectives, methodologies, and challenges involved in cross-cultural design research, analyzing the benefits of employing Artificial Intelligence-Generated Content (AIGC) for such studies. It introduces a novel tool that applies AIGC to cross-cultural design research, developed through the use of a fine-tuned ChatGPT-4 model. By creating a specific dataset for the research topic and applying transfer learning techniques, this tool evolves into a chatbot capable of delivering personalized response strategies to users from diverse cultural backgrounds. It leverages natural language interfaces and real-time image generation to meet user needs, conducting research tasks autonomously. Experimental results demonstrate that, compared with conventional cross-cultural research methods such as questionnaires and manual interviews, the chatbot significantly enhances the efficiency of design research and users’ cross-cultural interaction experience, while obtaining more realistic and objective feedback. This study not only underscores the potential application of AIGC in cross-cultural design research but also provides substantial theoretical support and practical guidance for future research in cross-cultural contexts.