DebaTable is a technologically enhanced meeting table that mediates discussions and stimulates time-efficient debates. It can be used whereever people come together to discuss ideas and make decisions, such as brainstorms or project meetings.
It works in two different ways: the first is by measuring each participant’s percentage of speaking time within the past few minutes. This percentage is visualised in the middle of the table, with lines pointing to each of the seats. The more you talk, the higher your line will be. Additionally, a slowly expanding circle in the middle of the table shows the discussion time left. The time it takes for this circle to reach its outer limit is based on the average of individual “votes” each participant gives with the discreet sliders located at the edge of the table.
A core principle of DebaTable is its neutrality. The value of the presented data is decided on by the participants themselves. Only they can decide if a high peak in the speech graph is a problem, or just a chairman doing their job. DebaTable only mediates discussion by sparking self-reflection. It does not actively change the discussion in any way: it’s up to the people in the meeting to see the visualisation, reflect on it, and change their own individual discussion style.
Meetings are a core activity of our academic and working lives. DebaTable helps us get better at having them, by letting us better ourselves.
Within this project, I (re-)discovered the value and beauty of physical prototyping and deepened my skills with electronics. Cardboard modeling and paper prototyping made me realise how many new insights “thinking with my hands” could unlock, and it allowed me to verify hunches very quickly. Throughout the project, I used existing products and combinations thereof to create “hacked” low-fi prototypes, which was both really fun and got me to try out experiences fast.
I experimented with different ideation techniques to spur my creativity. Within the first week of my project, I adopted a first-person perspective to experience the problems with meetings myself. I used physical prototyping to try out new ideas quickly and get to new insights.
Throughout the process I had a big focus on (visual) polish, from the working of the visualisation, to the feel of the lacquer finish and the look of the lasercut microphone caps.
At the start of the semester, I mentioned to my coach: “I’m more of a product- than a people person. My designs guidepeople in the right direction subconsciously”.
As usual, I tried to apply my technology- and data-based way of thinking to the social context of meetings, and learned that technology wasn’t the solution to this people-centric problem. After reading a paper on designing ethical values into products, my mind raced to figure out what my stance on the perfect meeting would be.
In the end, people themselves were the solution. By accepting that I couldn’t define a “perfect meeting”, let alone measure and create one, I learned to embrace people’s own interpretations as part of the designed product. I had found a way to incorporate User & Society, but still do it my way.
: Verbeek, P.-P. (2006). Materializing Morality. Science, Technology, & Human Values, 31(3), 361–380. DOI: 10.1177/0162243905285847
The initial value proposition my design made to the end user was that of self-reflection. However, in talks with the squad business coach, it occurred to me that only a small amount of people looking for a meeting room would be convinced of this added value. I decided to couple self-reflection with the promise of meeting efficiency by adding a time-based visualisation.
In order to appeal better to relevant decision makers, I looked into the buying process of the TU/e and learned about the importance of appealing to regulations as well as to the tastes of interior design firms. These directly influenced the envisioned models and table finishes I would be selling.
Both quantitative and qualitative data gathering- and analysis techniques were used throughout this project. One example:
To find out what emotions people experienced, I created four internet-connected sliders, that I would strap to chairs and ask participants to meet on. When the meeting wrapped up, I would quickly download the data, fill it into a pre-prepared Excel sheet, and print out the resulting graph. This required a lot of data systems to work in sync with each other. I then recorded and analysed the qualitative answers given about the quantitative data, and bundled all of this together.
For the visualisation, I employed multiple different techniques to translate microphone- and slider-data into dynamic visualisations: from the noise filtering code and the sliding window that would only “count” the last X minutes, to the various trigonometric functions used to display the dots of the circle and their expansion.
– Cover Photo | by Zeno Kapitein
– Figure 1 | by Zeno Kapitein
– Figure 2 | by Zeno Kapitein
– Figure 3 | by Emma van Dormalen
– Figure 4 | by Roy van de Heuvel
– Figure 5 | by Zeno Kapitein