Exploring the integration of generative design in STEM classrooms: student perceptions and learning experiences

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Authors: Juan Zheng, Shiyi Liu, Shan Li, Charles Xie
Cited by: 0
References: 40

Abstract

While K-12 schools are increasingly adopting Artificial Intelligence (AI)-powered learning environments to provide dynamic support and enhance student engagement, the integration of advanced AI applications in specific domains remains uneven. Generative design, an innovative approach in design and engineering that leverages AI and computational power to explore and generate multiple design solutions, has gained traction in the engineering design field. However, integrating generative design into the teaching and learning of engineering design remains a relatively unexplored area. This study introduces an instructional model guiding the integration of generative design into students’ engineering design processes. We validated this model through an AI-powered engineering design curriculum, which involved a total of 109 students from two suburban high schools in the Midwestern United States. Results revealed significant increases in students’ perceived engineering design knowledge, actual engineering design knowledge, and confidence in iterative design. Additionally, students acknowledged the benefits of generative design following their engagement with the curriculum. Nonetheless, concerns emerged regarding the ease of use and students’ comfort levels in utilizing generative design. This study presents implications for STEM research and practice, particularly regarding integrating generative design into K-12 classroom settings for engineering design processes. Furthermore, it offers insights for researchers aiming to optimize AI-powered learning environments.

Fields of Study & Subjects

Design Education and Practice Artificial Intelligence in Education Engineering Education and Pedagogy

Publication details

Journal / source
International Journal of Technology and Design Education
Volume
36
Issue
4
Pages
1535–1552
Publication date
13 March 2026
Language
EN