Design Process and Issues

Jin, Meneely, and Park studied responses to virtual reality and “real life” experiences.  They determined “how participant perceptions of a single interior environment varied among a real-world space (R) and two surrogate VR spaces (one made with 360° spherical photography and one made with 360° spherical digital rendering). . . . Each participant completed a visual acuity task and evaluated perceived brightness, glare, and spaciousness within the real-world space and one of the two surrogate VR environments.

Researchers at MIT’s Senseable City Lab are revolutionizing mapmaking to better understand city life.  The investigators report that “Often using mobile sensors or cellphone data, Senseable City’s mapping style — emerging from peer-reviewed research — broadens cartography in multiple ways: Data-driven maps, whether displayed in video form or as still images, expand the array of things that can be charted; show changes over time; and put new information in the hands of policymakers, residents, and others who want to govern communities well. . . .

In an open access article, Liedgren, Desmet, and Gaggiolo lay out the case for considering higher levels in Maslow’s system when developing design options.  They “argue that the sublime is struggling to find room in product design primarily aimed at commercial and transactional goals such as speed and efficiency. We suggest a new category of products to promote deeper and more meaningful experiences, specifically those offering liminality, transcendence, and personal transformation. . .

Rizzo and team’s work confirms how much language used influences conclusions drawn.  They determined that “sensory language (e.g., words like “crumble” and “juicy” that engage the senses) shapes consumer responses to influencer-sponsored content. A multimethod investigation . . . demonstrates that sensory language increases engagement and willingness to buy the sponsored product. . . . these effects are driven by perceived authenticity.

Researchers have learned that artificial intelligence can effectively design cars.  A recent press release from MIT shares that “machine learning models can not only predict the appeal of new aesthetic designs but also generate designs that are aesthetically pleasing or aesthetically innovative. (And, once trained, the models can run on a standard corporate laptop.)”

Research by Paes and colleagues sheds additional light on the most effective VR based studies.  The investigators report that “Identifying and characterizing the factors that affect presence in virtual environments has been acknowledged as a critical step to improving Virtual Reality (VR) applications in the built environment domain. In the search to identify those factors, the research objective was to test whether three-dimensional perception affects presence in virtual environments. . . .