It's Spring Physics, baby!
Last week we convened in the hi-tech Sky-Room of our brand new building at 370 Jay Street to give 5-minute (and all-too-rushed) presentations of our Prototyping plans to our advisors and peers. Now we are on spring break and indefinite lockdown in the midst of the COVID19 pandemic. Here's a recap of how my plans for playtesting 3D Systems Modeling as a design research method have unraveled since then.
(Click here to check out my Prezi, which cleverly uses a spring/node inspired animation similar to the animation in the Mess Map I made on the data visualization software, Kumu, embedded below)
Click here to zoom-in (and perhaps attempt to decipher) my Mess Map of a User-Centered Mobility System.
I used Soft Systems Methodology to create a conceptual framework of the system that rooted various stakeholders' time spent in the act of transit, generally categorized into "Optimal Outputs, " such as arriving on time, using time productively, experiencing safety and comfort and "Suboptimal Outputs," such as arriving late, lack of flexibility and agency, and wasted time. This map contains over 160 elements, which I tried to connect and categorize using the color code in the Legend. I found the functionality of "connections" inKumu to be quite limited, since the lines and nodes in the map do not contain relative meaning based off of the lines' size, shape, angle, thickness. The only descriptive elements of the connections were arrowheads and color, which did not intuit any real meaning in the conceptual framework.
I decided to try "Tagging," another way to categorize the elements, based off of the very compelling but extremely complex Systems Viz Visual Vocabulary by Peter Stroyko. This began to help me make sense of the relationships of elements in the system that were most important to determining various outputs, scenarios, and stakeholder personas.
(If you decide to play around with my Interactive Mess Map, I recommend clicking on the purple "Tags" to better visualize the connections within/between these categories)
Although my sorting exercise was not perfect due to the sheer amount of data and definitions to analyze, I felt I had enough of a direction to start making a 3D Model of my Mobility System.
Here's a list of the materials I used:
White styrofoam spheres of five different sizes
Pipe Cleaners of two different colors (there were five colors available but I only used
Sticker/Beads (to loop on the wire/pipe-cleaners. There were many colors available but I only used one color)
Organic Chemistry Modeling Kit
Wooden Dowels and popsicle sticks (not pictured)
Below is a legend that attempts to explain how this Model related to the Mess Map. Warning: the color code very confusing because it's drawing colors used in both the Mess Map (Green Optimal Output, Red Suboptimal Output, Pink Stakeholders) and the Physical Model (green pipecleaners, blue pipe cleaners, and orange sticker beads).
Despite the abstractness of my "rapid prototype," I got a lot of useful feedback (and validation) from the critique. The attempt to translate the interactive web of chaos from Kumu, into a literal physical model was impossible, but perhaps could make sense in a VR model where it can be viewed from various vantage points that highlight the meaning of "distance" between the nodes in the system. While both the digital and physical prototypes represent idea of nodes in a web of springs, they both neglected any clear physics-based or mathematical models that would help define the abstract sculpture.
A few great examples of conceptual models:
Will Wright explains various dimensions of characters' interaction loops in his game "The Sims." The Players mental model develops through "orthogonal creativity" in relationship with the Interaction Layers.
1983 Atari game by Chris Crawford, Gossip,
This cool video about coding Simple Spring Physics.
Contemplating getting this DIY Magnetic Stick & Balls Kit by Hfelau...not sure what size to get though.
Perhaps, the most compelling finding from this experiment is that physical materials and the mathematical/physics-based models that are embedded within game design (and digital interactive time-based media) provide two valuable tools for Systems Thinking.
The first is the possibility of rules and mechanics that can guide emergent human thinking towards a clearer and more nuanced outcomes. The second is a framework that adds dimensionality and relationships across a set of elements within the system.
Katy Gero, Zahra Ashktorab, Casey Dugan, Qian Pan, James Johnson, Werner Geyer, Maria Ruiz, Sarah Miller, David Millen, Murray Campbell, Sadhana Kumaravel, Wei Zhang. Mental Models of AI Agents in a Cooperative Game Setting. Best Paper Award ACM CHI Conference on Human Factors in Computing Systems (https://dl.acm.org/doi/abs/10.1145/3313831.3376590)