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SpaceMaze: incentivizing correct mobile crowdsourced sensing behaviour with a sensified minigame

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posted on 2020-06-04, 11:54 authored by Matthias Budde, Jan Felix Rohe, Lina Hirschoff, Patrick Schlosser, Michael Beigl, Jussi Holopainen, Andrea Schankin

Modern mobile phones are equipped with many sensors, which can increasingly be used to sense various environmental phenomena. In particular, mobile sensing has enabled crowdsourced data collection at an unprecedented scale. However, as laypersons are involved in this, concerns regarding the data quality arise. This work explores the gamification of smartphone-based measurement processes in practice by embedding a sensing task into a mobile minigame. The underlying idea is – rather than to educate the user on how to correctly perform a measurement task – to opportunistically execute the measurement in the background once the smartphone is in a suitable context. To this end, this paper presents the design and evaluation of SpaceMaze, a smartphone game with the goal of minimising user error by introducing appropriate game mechanics to influence the phone context, using the example of mobile noise level monitoring. A large user study that compares SpaceMaze to two non-gamified apps for noise level monitoring (N = 360 in total) shows that SpaceMaze can successfully reduce user errors when compared to simple non-gamified ambient noise level monitoring applications and that the minigame is generally perceived as being enjoyable. Solutions for remaining problems, such as noise generated by the players, are discussed.

Funding

The authors would like to thank all study participants. This work has been partially funded by the German Federal Ministry of Education and Research (BMBF) as part of project Software Campus [grant number 01IS12051], and the German Federal Ministry of Traffic and Digital Infrastructure (BMVI) as part of project SmartAQnet (Budde et al. 2017b) [grant number 19F2003B]. Parts of the game design and evaluation have been previously published as part of Matthias Budde's doctoral dissertation at Karlsruhe Institute of Technology (KIT) (Budde 2018).

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