生成性的校园设计方法
The on-campus learning and living environment is constantly evolving to improve the higher education experience for students. Design strategies are used to encourage learning, increase student retention and graduation rates, and ensure the quality of learning experiences. 横跨AG平台 学习+实践, 我们利用数据驱动设计, a highly collaborative process that generates successful outcomes and useful insights on the innovative possibilities of technology-enhanced campus design.
The most valuable aspect of data-driven design is the unlimited number of experimental designs that are made possible through customizable algorithms and generative modelling. This is valuable because the algorithms can consider several inputs within a given model to accommodate a project’s specifications, and the algorithms and inputs work together to find multiple configurations within the design process. 更多的使用, the technology can become smarter and more efficient, expanding the amount of research and complexity of the inputs that the model can process at one time.
This innovation does not come without its limitations. Human sentiment is still necessary in the design process because data-driven design cannot yet compute at a level that satisfies human opinion and subjectivity. This limitation can also be considered a strength, as the design process is in在这里ntly collaborative and multivalent. 数据驱动的设计, 加上深思熟虑的人类洞察力, 因此提高了设计过程, 把它带到新的高度.
A version of this insight appeared on page 56 of the 高等教育PPP报告2021. It expands on how IBI Group is employing data-driven design principles to deliver sustainable, future-forward campuses across North America.
点击 在这里 to view a recording of the Data-Driven Decision Making in the Design Process panel at the P3 Bulletin Higher Education Hub.
