COMPOSTUDIO Model: An Interactive Method for Immersive Project-Based Learning Experience in the Built Environment Studios (Video)

• Main Authors: Nizarudin, Norhanis Diyana, Zakariya, Khalilah
• Format: Copyright
• Language: English; English
• Published: 2021
• Subjects: N81 Study and teaching. Research; Architectural components
• Online Access: http://irep.iium.edu.my/88442/1/COMPOSTUDIO%20Model%20an%20interactive%20method%20for%20immersive%20project-based%20learning%20experience%20in%20the%20built%20environment%20studios%20%28video%29.pdf; http://irep.iium.edu.my/88442/6/FM2021W00999_Compostudio%20model%20an%20interative%20method%20for%20immersive%20project-based%20learning%20experience%20in%20the%20built%20environment%20studios%20%28video%29.pdf; http://irep.iium.edu.my/88442/

The COMPOSTUDIO Model is formulated to improve the effectiveness of hybrid teaching and learning experience for built environment educators and students such as in landscape architecture, architecture, urban planning, and others. To make studios more adaptive in the age of disruption and to rise above the pandemic. COMPOSTUDIO consists of four key components, composite digital and non-digital methods, and composed of a comprehensive process from framing the project until delivering the solutions. By integrating project-based learning, the objectives of COMPOSTUDIO are, (i) to incorporate critical thinking throughout the studio process. (ii) to encourage creativity in problem-solving through composite methods of teaching and learning. (iii) to promote collaboration through immersive physical and virtual experiences, and (iv) to advance 21st-century communication skills among educators and students. The COMPOSTUDIO Model adds value to the existing studio approach by combining interactive and immersive offline and online methods that are practical, easy to use, cost-efficient, and tech-savvy. Using readily available technology, this robust model can be applied and replicated by other built environment studios to produce more engaging studio learning.