Research on the training strategy of college students' design thinking and innovation ability based on multimodal large model
Year: 2025
Type: article
Abstract: The development of Multimodal Large Language Model (MLLMs) offers new technological support for cultivating design thinking and innovation capability in medical education. However, the current training of medical professionals remains predominantly centered on knowledge memorization and one-way didactic instruction. The systematic integration of artificial intelligence and innovation methodologies is still insufficient, while challenges such as limited interdisciplinary integration and inefficient teaching iteration have constrained the cultivation of innovative literacy. To address these challenges, this study constructs the “MLLM+EDIPT” integration framework, which deeply couples the design thinking model from Stanford University's D.school with MLLM technology. It systematically elucidates the cognitive support mechanisms of MLLM across the stages of empathy, definition, ideation, prototyping, and testing. Targeting diverse stakeholders, including hospitals, universities, educators, and students, this study proposes a phased cultivation strategy and competency framework based on school-clinician collaboration. This framework emphasizes the full integration of the “human-centered” philosophy, leveraging AI to enhance situational awareness, feedback timeliness, and methodological rigor, thereby driving the transformation of teaching models from experience-driven to intelligent collaboration. Ultimately, this research aims to provide a theoretically grounded and practically viable pathway reference for the cultivation of top-tier innovative medical talents in the AI era.
Source: Frontiers in Education
Institutions: Sheng Jing Hospital, China Medical University
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,353
Funder: China Medical University
OpenAlex ID: W4415418906