Paratyping: A Contextualized Method of Inquiry for Understanding Perceptions of Mobile and Ubiquitous Computing Technologies

In this article, we describe the origins, use, and efficacy of a contextualized method for evaluating mobile and ubiquitous computing systems. This technique, which we called paratyping, is based on experience prototyping and event-contingent experience sampling and allows researchers to survey people in real-life situations without the need for costly and sometimes untenable deployment evaluations. We used this tool to probe the perceptions of the conversation partners of users of the Personal Audio Loop, a memory aid with the potential for substantial privacy implications. Based on that experience, we refined and adapted the approach to evaluate SenseCam, a wearable, automatic picture-taking device, across multiple geographic locations. We describe the benefits, challenges, and methodological considerations that emerged during our use of the paratyping method across these two studies. We describe how this method blends some of the benefits of survey-based research with more contextualized methods, focusing on trustworthiness of the method in terms of generating scientific knowledge. In particular, this method is a good fit for studying certain classes of mobile and ubiquitous computing applications but can be applied to many types of applications. Notes 1SenseCam has recently been released as a commercial product, known as ViconRevue. However, when this work was conducted, SenseCam was still available only as a research tool, and thus we reference SenseCam and not ViconRevue throughout this work. Acknowledgments. We thank Giovanni Iachello, Molly Stevens, and Gregory Abowd for their help in designing and executing the original paratyping study with the Personal Audio Loop (PAL). We also thank Shwetak Patel for writing the PAL application, Jens Großklags, Elaine Huang, Kris Nagel, Delphine Nain, Jay Summet, and the CHI reviewers for their thoughtful comments on a paper focused on the PAL study. We thank David Nguyen, Gabriela Marcu, James Scott, Marc Langheinrich, and Christof Rudoner for their help in designing and executing the paratyping study with SenseCam. We also thank Paul Dourish, Irina Shklovski, and the members of the STAR Group for their comments on that work. In addition, we thank all study participants for their time and feedback. Support. The paratyping study with the Personal Audio Loop was supported in part by NSF ITR grant 0121661, the NSF GRFP, the MacArthur Foundation, Intel Corporation and Motorola Corporation and was covered under IRB protocol H04153 at the Georgia Institute of Technology. The paratyping study with SenseCam was supported by NSF CAREER Grant 0846063 and support from Microsoft Research and was covered under IRB protocol 2007-6070 at the University of California, Irvine, and 21027 at the University of Toronto. HCI Editorial Record. First manuscript received October 6, 2010. Revision received October 3, 2011. Final manuscript received March 4, 2012. Accepted by Clayton Lewis.— Editor