Abstract

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.

Details

Title
Designing and evaluating mobile self-reporting techniques: crowdsourcing for citizen science
Author
Younis, Eman M G 1 ; Kanjo, Eiman 2 ; Chamberlain, Alan 3 

 Information Systems Department, Faculty of Computers and Information, Minia University, Minia, Egypt 
 Computing and Technology, Nottingham Trent University, Nottingham, UK 
 School of Computer Science, University of Nottingham, Nottingham, UK 
Pages
329-338
Publication year
2019
Publication date
Apr 2019
Publisher
Springer Nature B.V.
ISSN
16174909
e-ISSN
16174917
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2199610763
Copyright
Personal and Ubiquitous Computing is a copyright of Springer, (2019). All Rights Reserved., © 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.