Misrepresentation of health research in exertion games literature

HCI often requires scholars to build upon research from fields outside their expertise, creating the risk that foundational work is misunderstood and misrepresented. The prevailing goal of “exergames” research towards ameliorating obesity appears to be built on just such a misunderstanding of health research. In this paper, we analyse all citations to a single influential study, which has been extensively cited to justify research on exergames. We categorise the 375 citations based on whether they represent the findings of that study accurately or inaccurately. Our findings suggest that 69% of exergames papers citing this study misrepresent the findings, demonstrating a systematic failure of scholarship in exergames research. We argue that exergaming research should cease focusing on games as treatment for obesity, and that HCI publications should demand more critical and scholarly engagement with research from outside HCI

Sensified gaming: design patterns and game design elements for gameful environmental sensing

Participatory Sensing, i.e. collaboratively taking sensor measurements with mobile devices in a Citizen Science fashion, has become increasingly popular. Because such scenarios often require a critical mass of users, applying gamification to different areas in order to increase user engagement has been proposed. However, existing attempts often default to the standard points, badges, and leaderboards and fail to recognize the potential of exploiting game design elements beyond creating user engagement. We propose not to think of Gamified Participatory Sensing when designing such systems, but rather of Sensified Gaming. To this end, this work presents a collection of design patterns and game mechanics that can be used to identify or design suitable games, into which participatory sensing tasks can be embedded. We identified four core tasks from participatory environmental sensing and sensor networks research, reviewed hundreds of design patterns and map each of the 63 selected patterns to the core tasks