Extending mobile app analytics for usability test logging

Ferré Grau, Xavier and Villalba Mora, Elena and 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.

Description

Title: Extending mobile app analytics for usability test logging
Author/s:
  • Ferré Grau, Xavier
  • Villalba Mora, Elena
  • Julio, Héctor
  • Zhu, Hongming
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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Abstract

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.

More information

Item ID: 51085
DC Identifier: http://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/10.1007/978-3-319-67687-6_9
Deposited by: Memoria Investigacion
Deposited on: 25 Mar 2019 12:29
Last Modified: 25 Mar 2019 12:29
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