Best Practice for Experimental Methods in Architecture: A Concise Guide from A/B Testing to Virtual Reality
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This book provides a comprehensive guide to designing and conducting survey experiments in architecture, focusing on the intersection of research methodology and human interaction with the built environment. It covers a wide range of essential experimental techniques tailored to the architectural field, starting with foundational concepts like A/B testing and factorial design. It further provides clear, step-by-step strategies for implementing experimental designs, empowering architects, designers, and researchers to make data-driven decisions that enhance the spaces we live and work in. The chapters on within-subjects and between-subjects designs provide a deeper dive into how to measure responses to various environmental factors, such as lighting, room layout, and acoustics. Another key focus of the book is the use of emerging technologies like virtual reality (VR) in experimental design. With VR becoming an increasingly important tool in architectural testing, the book explores how virtual environments can be used to simulate real-world conditions, creating highly controlled experiments that can provide rich, actionable insights. The use of pilot testing is also emphasized to ensure that experiments are designed effectively before large-scale implementation. Ethics and Institutional Review Board (IRB) considerations are thoroughly discussed, ensuring that readers understand the importance of safeguarding participants' rights and privacy in any experimental study. The book doesn’t stop at the methodology; it gives practical advice on how to report results, interpret data, and address challenges like external validity, providing readers with a robust framework for translating experimental findings into actionable insights for architectural practice, ensuring that research contributes meaningfully to the design process and the improvement of built environments.
Chandler Zolan is a PhD Student in Architecture at Texas A&M University, whose background is in criminal justice, national securtiy and mass infrastructure design. His research interests are primarily in designing tacit security measures for pro-social infrastructure and architecture, and the primary method of this work is experimentation. Specifically, survey experiments with VR integration, red-teaming exercises and machine learning systems. His MSc Thesis examined the optimization problem between security and comfort in airport and stadium design, and integrated a VR experiment into a representative sample of Americans to assess how to design safe, comfortable spaces. His PhD dissertation expands this for a full examination of airport designs, the integration of red teaming experimentation and the design of a machine learning program to assess blueprints and identify security risks prior to construction in airports.
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