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This study examines the integration of user experience (UX) principles into user interface (UI) design education through a Problem-Based Learning (PBL) approach augmented by generative artificial intelligence (AI) technologies. The PBL framework emphasizes addressing real-world challenges, fostering self-directed learning and collaboration among interdisciplinary student teams. Generative AI tools were employed to enhance creativity, streamline design processes, and provide immediate feedback, thereby reducing development time and facilitating iterative problem-solving. The curriculum incorporated UX design theories, UI design practices, and user testing methodologies, with input from industry professionals to bridge the gap between theoretical knowledge and practical application. Data were collected using a 32-item questionnaire evaluating five dimensions: PBL, UX design, UI design, user testing, and generative AI-supported design. Analysis revealed no significant differences between design and technology students in the PBL and user testing dimensions, indicating consistent learning outcomes. However, design students demonstrated significantly higher engagement in UX, UI, and AI-supported design tasks, attributed to the curriculum’s alignment with their academic background. The study underscores the dual role of generative AI as both a creative enabler and a scaffolding tool for interdisciplinary learning. Future research should explore strategies for integrating generative AI in diverse educational contexts and enhancing engagement among technology students in design-focused courses.

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Integrating User Experience in User Interface Design Education: A Problem-Based Learning Approach Enhanced by Generative AI-Supported Design

  • 会议论文

  • 发表日期：

    2025年

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  • Chieh-Ju Huang

摘要

This study examines the integration of user experience (UX) principles into user interface (UI) design education through a Problem-Based Learning (PBL) approach augmented by generative artificial intelligence (AI) technologies. The PBL framework emphasizes addressing real-world challenges, fostering self-directed learning and collaboration among interdisciplinary student teams. Generative AI tools were employed to enhance creativity, streamline design processes, and provide immediate feedback, thereby reducing development time and facilitating iterative problem-solving. The curriculum incorporated UX design theories, UI design practices, and user testing methodologies, with input from industry professionals to bridge the gap between theoretical knowledge and practical application. Data were collected using a 32-item questionnaire evaluating five dimensions: PBL, UX design, UI design, user testing, and generative AI-supported design. Analysis revealed no significant differences between design and technology students in the PBL and user testing dimensions, indicating consistent learning outcomes. However, design students demonstrated significantly higher engagement in UX, UI, and AI-supported design tasks, attributed to the curriculum’s alignment with their academic background. The study underscores the dual role of generative AI as both a creative enabler and a scaffolding tool for interdisciplinary learning. Future research should explore strategies for integrating generative AI in diverse educational contexts and enhancing engagement among technology students in design-focused courses.