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Designing and evaluating mobile self-reporting techniques: crowdsourcing for citizen science

Younis, Eman M. G.; Kanjo, Eiman; Chamberlain, Alan


Eman M. G. Younis

Eiman Kanjo


In recent years, mobile phone technology has taken tremendous leaps and bounds to enable all types of sensing applications and interaction methods, including mobile journaling and self-reporting to add metadata and to label sensor data streams. Mobile self-report techniques are used to record user ratings of their experiences during structured studies, instead of traditional paper-based surveys. These techniques can be timely and convenient when data are collected ``in the wild''. This paper proposes three new viable methods for mobile self-reporting projects and in real-life settings such as recording weather information or urban noise mapping. These techniques are Volume Buttons control, NFC-on-Body, and NFC-on-Wall. This work also provides an experimental and comparative analysis of various self-report techniques regarding user preferences and submission rates based on a series of user experiments. The statistical analysis of our data showed that pressing screen buttons and screen touch allowed for higher labelling rates, while Volume Buttons proved to be more valuable when users engaged in other activities, e.g. while walking. Similarly, based on participants' preferences, we found that NFC labelling was also an easy and intuitive technique when used in the context of self-reporting and place-tagging. Our hope is that by reviewing current self-reporting interfaces and user requirements, we will be able to enable new forms of self-reporting technologies that were not possible before.


Younis, E. M. G., Kanjo, E., & Chamberlain, A. (2019). Designing and evaluating mobile self-reporting techniques: crowdsourcing for citizen science. Personal and Ubiquitous Computing, 23(2), 329-338.

Journal Article Type Article
Acceptance Date Mar 18, 2019
Online Publication Date Mar 29, 2019
Publication Date 2019-04
Deposit Date Jul 23, 2019
Publicly Available Date Jul 24, 2019
Journal Personal and Ubiquitous Computing
Print ISSN 1617-4909
Electronic ISSN 1617-4917
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 23
Issue 2
Pages 329-338
Keywords Mobile sensing; Mobile self-report; Pervasive computing; Citizen science; User interfaces
Public URL
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