Exploring the Structural Logic and Learning Path of Prompt Language in AI-Assisted Interaction Design

With the rapid development of generative artificial intelligence (AI), prompt language has emerged as a crucial interface for human–AI collaboration, reshaping interaction design processes and the practice of design thinking. This study situates itself within an interaction design course, integrating the five-stage model of design thinking (empathize, define, ideate, prototype, test) with project-based learning to systematically explore the structural characteristics and cognitive pathways of prompt language. By analyzing 362 prompts created by 64 students, the study identifies five types of prompt structures—directive, descriptive, narrative, comparative, and hybrid—and reveals their significant impact on the accuracy, stylistic consistency, and creativity of the AI-generated content. Furthermore, the study proposes a “Prompt Interaction Design Model,” highlighting that prompt language in AI-assisted design functions not only as a task-oriented tool but also as a medium for expressing design thinking and as a vehicle for learning and reflection. This model provides a practical and operable language training framework for design education, enabling students to develop skills in prompt crafting, critical thinking, and creative experimentation. Ultimately, this research contributes to the pedagogical integration of AI tools in design education, offering insights for educators aiming to enhance AI literacy and foster innovative design practices among students.