- Interaction Design
- MA
Sigmund Abou Chrouch
- Uncovering biases in design research through Experiential Narratives
- Tutor: Tanel Kärp(MA), Alan Voodla(PhD Candidate)
- This thesis is an attempt to understand and influence how designers address potential biases that emerge when trying to understand users’ tacit knowledge. Tacit knowledge refers to the knowledge that is hard to articulate, but has an important role in driving behaviour. In the research process I narrowed down my focus on one research method - user testing. Throughout my research I gathered some insights into designers’ thinking process and was able to understand the challenges they face in user testing. My research showed that there are a lot of difficult decisions designers have to make to maximise the outcomes of their testing. These challenges and difficult decisions can very well be overwhelming and potentially drive decision-fatigue, which contributes to lower awareness of biases. On the other hand, designer’s often didn’t know enough about biases to meaningfully engage in countering them This pointed towards the conclusion that designers and researchers are not often aware of the potential biases in their testing process and keeping track and addressing them induces extra cognitive load. In order to enhance designers ability to detect and address biases, simplifying this cognitive process emerged as a core principle towards the solution. Throughout the research, I learned the value of relating the biases to the individual’s experience in order to help them learn better. My design proposal is a toolkit that simplifies the learning, identification and awareness of the biases, through the designer’s own experiential narratives. This toolkit has both digital - as a companion plug-in on a collaborative platform, and a physical version as a deck of prompt cards. The toolkit can be used individually or in a collaborative setting. A set of 22 biases are related to prompt questions that encourage users to, to tell their own stories, share them and identify the biases together. This solution aims to create the space and time to explicitly learn, identify and discuss the biases through one’s own past experiences, and link the learning to the design process.
