Data-driven reiterations

Data was paramount to the development of our design solution. With an enormous issue like sustainability, it is necessary to take an iterative, pivotable approach to research. Above all, we kept an open mindset throughout our research process in order to challenge and test every facet of our emerging solution, while simultaneously making sure there were no assumptions being had. Armed with the knowledge gathered during our preliminary interviews, we found that research had helped us narrow in on a target audience and problem. We began to consider the problem of awareness of algae biofuel, and attempted to ideate a solution. This solution manifested itself in an open source write up. The goal of the write up was to provide various implementations of an effective, easy to assemble algae bioreactor that could be implemented by anyone using household materials. This bioreactor would produce algae every 10 days, with each algal harvest resulting in a 30% yield of oil that could then be converted to clean burning biodiesel. This biodiesel would power your home through a generator, and provide clean, free energy. The write up would be accessible to anyone through the internet. However, we wanted to make sure we weren’t making any assumptions, and in order to test this, we engaged in pseudo contextual interviews with experts in design and education including Dr. Nan Renner, Michael Allen, and Rose Hendricks of the University of California, San Diego. We presented them with key points and structure of the write up, along with examples of a successful implementation of the proposed bioreactor, and asked them questions about how it served its purpose as a design solution to the problem of awareness. Their feedback was both critical and thorough. Though the science presented in the write up was sound, the write up itself was not actively engaging what is known as a behavioral change, wherein the target audience is actually shifting their behavior as proposed. At its core, it was a fundamentally flawed concept, relying on information to be the primary motivator, rather than focusing on human centered principles. While this was a setback in our process, it opened us to the nature of human centered design, and informed us that we must triangulate and iterate repeatedly, constantly testing every assumption we have. It was a valuable lesson, one we vowed to learn from in the future. Feedback from this round indicated that a new prototype, something along the lines of a kit that could be assembled into the bioreactor system, was necessary to bring about the behavior change we were pursuing. This led us to another round of standard interviews with a sample of 6 new members of our target audience, college students. Again, we were seeking to test our assumptions on our kit prototype, and our line of inquiry was as follows: “If you could buy a premade bioreactor that makes clean energy, would you do so?”, “Would you want a demonstrable sample?”, “How much would you be willing to spend on a kit like this?”. The feedback from this research round was perhaps the most important yet, with both positives and negatives emerging. While all 6 individuals showed interest in the project, 5 claimed they did not understand the prototype at first. Responses like “Why is this beneficial?”, “What does it do for you?”, “So its energy?”, “Can I get it in a small size to test it?” were popular across the group. Once the science was explained clearly, however, the tone and skepticism of the feedback changed considerably. Every member of the sample interviewed indicated that they were certainly interested in what was being shown to them, and that if framed in a learning context, rather than an intimidatingly named product, they would be very interested in the solution. Feedback included “Show us how to make it!" “A workshop is a good idea, I’d go to that, like a workshop for dummies kind of thing.” Again, our research methods had shown us an ideal pivot point. The very audience we were targeting was beginning to resonate with our ideas, and advocating for a solution. So, with overwhelming data indicating that a workshop may be the ideal solution, we decided to iterate again. With user feedback indicating that the workshop should have a broken down, simple methodology and demonstration, we storyboarded and calculated the costs to build the reactor. We also rebuilt the demonstration reactor to use more household objects, like coffee presses and recyclable water bottles. And with that, our newest user centered prototype was born. So, we immediately set out to demonstrate the workshop with more samples of our target audience. We wanted to use different methods this time, because of the nature of the workshop prototype. These methods included natural observation, wherein extensive notes describing the participants’ actions during the workshop were taken, and contextual interviews, where we would demonstrate the workshop to individuals and ask them contextual questions about the experience afterwards. We spearheaded this research round with natural observation, bringing another sample of 6 college students to attend the workshop and assemble their own bioreactor. Our data was incredibly positive. Users were engaged, discussing and analyzing the build process, properly implementing their own bioreactors. Questions about the process were easily addressed, and all was going well until a critical error happened. The demonstration bioreactor was using a Carbon Dioxide pump that had a relatively sensitive valve. When a user went up to release some of the gas into the reactor, he accidently released far too much, nearly destroying the reactor and drenching himself in algal water. This occurrence showed us a grave oversight on our part in maintaining ease of use and accessibility with the reactor, something that was reflected by the user in question several times afterwards. Again, we found ourselves modifying and iterating, constantly trying to converge on the solution that works for the user. Replacing the bioreactor tank with a bike pump not only lowered costs further, but made the system easier to assemble and understand, as well as less volatile. So, with our newly modified reactor and workshop, we again began our most recent research round. Using contextual interviews, we assembled 2 different samples, the first of which had about 8 people, and the second which had 6. We demonstrated the newest iteration of the workshop and met overwhelmingly positive feedback. Questions included: “Was it easy to understand?” “Will you consider attending a workshop like this?” “Would you inform your peers about these workshops?” “What could be improved in this workshop format?” Feedback centered around marketing the workshop to the general public to increase awareness of the sustainability implementation, including clear visuals to supplement the workshop, clear stages of the algae being extracted and processed to form biodiesel, and standardized yield measures.