Characteristics Analysis of Engineering and Design Ideation through Language Information Processing

Abstract

In recent years, STEAM education, which adds "A" (Art) to STEM (Science, Technology, Engineering, Mathematics), has been gaining attention to foster creative talents. Furthermore, students from art disciplines are attracting interest as individuals who can contribute to solving societal issues. It is believed that they are valued for their ability to recognize unnoticed values and issues, and their power to shape or solve them. In this research, we compare students from engineering and design disciplines with generative AI as the subjects and obtain written descriptions of ideas generated in response to the given tasks. Through language information processing analysis, we aim to examine the similarities and differences in the content of design ideation among each group. By clarifying these aspects, we can explore methods to support everyone in generating ideas like those of exceptional creativity.