論文アブストラクト： Online experimentation with volunteers could be described as a form of citizen science in which participants take part in behavioral studies without financial compensation. However, while citizen science projects aim to improve scientific understanding, volunteer-based online experiment platforms currently provide minimal possibilities for research involvement and learning. The goal of this paper is to uncover opportunities for expanding participant involvement and learning in the research process. Analyzing comments from 8,288 volunteers who took part in four online experiments on LabintheWild, we identified six themes that reveal needs and opportunities for closer interaction between researchers and participants. Our findings demonstrate opportunities for research involvement, such as engaging participants in refining experiment implementations, and learning opportunities, such as providing participants with possibilities to learn about research aims. We translate these findings into ideas for the design of future volunteer-based online experiment platforms that are more mutually beneficial to citizen scientists and researchers.
論文アブストラクト： Research on the viability of using crowdsourcing for HCI performance experiments has concluded that online results are similar to those achieved in the lab---at least for desktop interactions. However, mobile devices, the most popular form of online access today, may be more problematic due to variability in the user's posture and in movement of the device. To assess this possibility, we conducted two experiments with 30 lab-based and 303 crowdsourced participants using basic mouse and touchscreen tasks. Our findings show that: (1) separately analyzing the crowd and lab data yields different study conclusions-touchscreen input was significantly less error prone than mouse input in the lab but more error prone online; (2) age-matched crowdsourced participants were significantly faster and less accurate than their lab-based counterparts, contrasting past work; (3) variability in mobile device movement and orientation increased as experimenter control decreased--a potential factor affecting the touchscreen error differences. This study cautions against assuming that crowdsourced data for performance experiments will directly reflect lab-based data, particularly for mobile devices.
論文アブストラクト： Learners worldwide collectively spend millions of hours per week testing their skills on assignments with known answers. Might some of this time fruitfully be spent posing and exploring novel questions? This paper investigates an approach for learners to contribute scientific ideas. The Gut Instinct system embodies this approach, hosting online learning materials and invites learners to collaboratively brainstorm potential influences on people's microbiome. A between-subjects experiment compared the performance of participants who engaged in just learning, just contributing, or a combination. Participants in the learning condition scored highest on a summative test. Participants in both the contribution and combined conditions generated novel, useful questions; there was not a significant difference between the two. Though participants in the combined condition both learned and contributed, this setting did not exhibit an additive benefit, such as better learning in the combined condition. These results highlight the promise and difficulty of double-bottom-line learning experiences.
論文アブストラクト： Desirable outcomes such as health are tightly linked to behaviors, thus inspiring research on technologies that support people in changing those behaviors. Many behavior-change technologies are designed by HCI experts but this approach can make it difficult to personalize support to each user's unique goals and needs. This paper reports on the iterative design of two complementary support strategies for helping users create their own personalized behavior-change plans via self-experimentation: One emphasized the use of interactive instructional materials, and the other additionally introduced context-aware computing to enable user creation of "just in time" home-based interventions. In a formative trial with 27 users, we compared these two approaches to an unstructured sleep education control. Results suggest great promise in both strategies and provide insights on how to develop personalized behavior-change technologies.