Smart Learning Institute

On March 30th, the training session for the Higher Education Track of the 8th Global Competition on Design for Future Education was successfully held. The session featured distinguished academic and industry mentors from Beijing Normal University, Beijing University of Chemical Technology, Communication University of China, and Trimble Inc. It aims to help participants with precise topic selection and improve the quality of submissions. The mentors provided an in-depth analysis of the competition evaluation criteria. They offered professional training on design thinking and the application of AIGC tools, sharing practical resources to comprehensively assist participants in enhancing the innovation and design level of their projects. 

How to Accurately Understand the Competition Evaluation Criteria?

MA Dongming, a teacher of the Department of Product Design at Beijing University of Chemical Technology, and ZHANG Ran, Technical Director of AECO APAC Region at Trimble lnc., provided detailed professional guidance on the five evaluation criteria: problem awareness, innovation spirit, science and education integration, application prospect, and presentation and expression. They encouraged participants to adhere to the seeking truth and being pragmatic principle, to approach specific problems, avoid homogenous topics, and to integrate personal experiences and unique features to create projects with innovative value. They emphasized that the projects should closely align with societal needs and educational development trends, avoiding mere technical stacking.

How to Use Design Thinking to Improve Project Quality?

Vice President of the Competition Steering Committee and Director of the Design and Learning Lab at the Smart Learning Institute of Beijing Normal University, KUAI Hongyan, presented on Project Design Based on Design Thinking. She shared the core concepts and methodologies of design thinking, stressing that design thinking is an innovative method accessible to everyone. Using the EDIPT design thinking model and NetDragon's Design Methodology as examples, she analyzed the design process and application scenarios of different models, encouraging participants to select appropriate design thinking models for project innovation based on real-world scenarios and user needs.

BAI Yuening, a Ph.D. from the Communication University of China, elaborated on design research and divergent thinking methodologies. She pointed out that design research could be approached from multiple perspectives, including cultural, practical, and political aspects, combining both primary and secondary research methods for in-depth analysis. She suggested using mind maps to organize research information, centering on core concepts, branching out related ideas, and applying divergent methods like functional and structural analysis, as well as techniques such as 5W+H and reverse thinking, to break through conventional thinking patterns and stimulate innovative ideas.

How Can AIGC Empower Education Project Design?

DA Ting, a postdoctoral fellow at the Department of Education, Beijing Normal University, and WANG Huanhuan, Assistant Researcher at Beijing Normal University and Focal Contact of UNESCO Chair on Al in Education, explored the value of AIGC in education project design. They highlighted that AI excels in areas such as data processing speed and multidisciplinary information integration, while humans possess irreplaceable capabilities in empathy, creativity, and self-awareness. AIGC can assist in topic selection, creative ideation, prototype design, and visual presentation, while also reminding participants to maintain critical thinking, assess AI-generated content responsibly, and avoid over-reliance, achieving true human-machine collaborative innovation.

What Practical Tools and Resources Are Available?

CHEN Hongyu, Senior Education Researcher at the Smart Learning Institute of Beijing Normal University, and ZHANG Yifan, postdoctoral fellow at Beijing Normal University, introduced a range of practical AIGC tools and techniques. These tools covered low-fidelity prototyping (websites, apps, 3D models), solution visualization, design report drafting and evaluation, as well as image and audio/video material generation. They encouraged participants not to be constrained by AI, but to fully unleash their creativity and effectively use tools to enhance the innovation and uniqueness of their projects.