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Ferré Grau, Xavier ORCID: https://orcid.org/0000-0003-3474-9784, Villalba Mora, Elena
ORCID: https://orcid.org/0000-0001-6043-6322, Julio, Héctor and Zhu, Hongming
(2017).
Extending mobile app analytics for usability test logging.
In: "16th IFIP TC13 International Conference on Human–Computer Interaction (INTERACT 2017)", 25-29 Sep 2017, Bombay, India. ISBN 978-3-319-67686-9. pp. 114-131.
https://doi.org/10.1007/978-3-319-67687-6_9.
Title: | Extending mobile app analytics for usability test logging |
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Author/s: |
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Item Type: | Presentation at Congress or Conference (Article) |
Event Title: | 16th IFIP TC13 International Conference on Human–Computer Interaction (INTERACT 2017) |
Event Dates: | 25-29 Sep 2017 |
Event Location: | Bombay, India |
Title of Book: | INTERACT 2017: Human-Computer Interaction |
Date: | 2017 |
ISBN: | 978-3-319-67686-9 |
Volume: | 10515 |
Subjects: | |
Freetext Keywords: | Automated usability evaluation; Usability testing; Log file analysis; Usability evaluation of mobile applications |
Faculty: | E.T.S. de Ingenieros Informáticos (UPM) |
Department: | Lenguajes y Sistemas Informáticos e Ingeniería del Software |
Creative Commons Licenses: | Recognition - No derivative works - Non commercial |
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Mobile application development is characterized by reduced development cycles and high time-to-market pressure. Usability evaluation in mobile applications calls for the application of cost-effective methods, specially adapted to such constraints. We propose extending the Google Analytics for Mobile Applications basic service to store specific low-level user actions of interest for usability evaluation purposes. The solution can serve both for lab usability testing, automating quantitative data gathering, and for logging real use after application release. It is based on identification of relevant user tasks and the detailed events worth gathering, instrumentation of specific code for data gathering, and subsequent data extraction for calculating relevant usability-related variables. We validated our application in a real usability test by comparing the automatically gathered data with the information gathered by the human observer. Results shows both measurements are statistically exchangeable, opening promising new ways to perform usability testing cost-effectively and at greater scale.
Item ID: | 51085 |
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DC Identifier: | https://oa.upm.es/51085/ |
OAI Identifier: | oai:oa.upm.es:51085 |
DOI: | 10.1007/978-3-319-67687-6_9 |
Official URL: | https://link.springer.com/chapter/10.1007/978-3-31... |
Deposited by: | Memoria Investigacion |
Deposited on: | 25 Mar 2019 12:29 |
Last Modified: | 25 Mar 2019 12:29 |