Design Creative Experiential-Based AI-IoT Courses to Enhance Creative Problem-Solving Skills of Non-STEM Vocational Students

To address the gap in AI education for non-STEM vocational students in Taiwan, this study applies the Universal Design for Learning Guidelines (UDLGs) to develop an AI course based on the Creative Experiential-Based Learning (CEBL) approach. By integrating the Reverse Design Process (RDP) with Ameba82 Mini AI-IoT tools, the instructional design offers a dynamic and creative learning experience that empowers students to develop their creative problem-solving (CPS) skills through real-world applications of AI. The curriculum consists of eight lessons organized around three thematic topics: Smart Home Monitoring System, Garbage Classification Education Tool, and Voice-Controlled Home System. The course culminates in a final project where students refine and apply AI-IoT solutions to realworld problems. By incorporating practical, industry-relevant examples and intuitive, no-code tools, the course makes AI concepts more accessible to non-STEM students, enhancing both engagement and comprehension. Assessment strategies are designed to evaluate both the learning process and the final product, enabling students to demonstrate their CPS development throughout the course. This study contributes a structured approach to AI-IoT course design for non-STEM learners and lays the groundwork for future empirical research on its effectiveness.