Abstract
Landscape design plays an important role in community building, residential buildings, and urban planning. Landscape design education requires multidisciplinary teaching of construction, management, ecology, and environmental protection as it requires the understanding of planting design, green energy, water resources, culture, and history. Therefore, it is necessary to establish an appropriate curriculum to educate students to be landscape designers. To find which courses are appropriate for such a curriculum, we defined the important teaching courses in landscape design education by integrating the results of the Delphi, analytical hierarchy process (AHP), and fuzzy logic theory (FLT) model as a DA fuzzy model, which provided a multi-attribute decision-making model. The DA Fuzzy model evaluates individual courses and selects the best plan with multiple courses. Three factors were defined to be important for landscape design education: professional skills, professional practice, and interdisciplinary collaboration. Each factor has three subfactors: hand-drawing ability, 3D drawing ability, and eco-friendly design (professional skills); project simulation, project practice, and humanistic value and responsibility (professional practice); interdisciplinary communication, Internet interdisciplinary course, and collaborative design (interdisciplinary collaboration). The highest relative weight was found for professional skills, followed by professional practice and interdisciplinary collaboration. Ecofriendly design, project practice, collaborative design, simulation project, and 3D drawing ability were found important as subfactors. The result indicates that project practice and collaborative design illustrate the importance of multidisciplinary knowledge and collaboration with various industries along with the consideration of the environment.
Author supplied keywords
Cite
CITATION STYLE
Hsueh, S. L., Sun, Y., Gao, M., Hu, X., & Meen, T. H. (2022). Delphi and Analytical Hierarchy Process Fuzzy Model for Auxiliary Decision-making for Cross-field Learning in Landscape Design. Sensors and Materials, 34(5), 1707–1719. https://doi.org/10.18494/SAM3817
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.