Generative AI in UX Education: Assessing Critical Thinking, Problem Solving, and Design Iteration Speed

Abstract

Recent advancement in generative AI have introduced powerful tools like ChatGPT, Figma AI and UX Pilot that are progressively used in User Experience design processes. These tools can easily generate content, suggest design layouts, and offer interactive feedback, potentially minimizing the need for active cognitive functioning. This raises questions about their impact on design education whether its outcomes prove to be favorable or unfavorable. This study aims to explore how AI technologies have influenced the development of essential abilities in UX education, specifically critical thinking, problem-solving, and design iteration speed using mixed method: qualitative and quantitative. Specifically, by conducting controlled experiments on User Interface and User Experience Design students and gathering feedback through surveys, this study assesses how AI tools have impacted the learning process. The experiment is done by equally dividing the students to design a total of three different UX design tasks, first half with the assistance of AI and the other without. The design outputs were evaluated under a scoring system based on UX principles and usability heuristics. The results revealed that AI primarily enhanced the iteration speed and design process but did not necessarily have impact on the usability of the final results or improvement of the students' problem-solving and critical thinking. Hence, while AI remains crucial for efficiency in the UX education, critical thinking and ethical considerations should be taught alongside in order for students still learn to think on their own accord and to avoid relying solely on the generated results.

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