TY - GEN
T1 - Mobile interaction analysis
T2 - 16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2014
AU - Lettner, Florian
AU - Grossauer, Christian Johannes
AU - Holzmann, Clemens
N1 - Publisher Copyright:
Copyright © 2014 ACM.
PY - 2014/9/23
Y1 - 2014/9/23
N2 - Identifying intentions of users when they launch an application on their smartphone, and understanding which tasks they actually execute, is a key problem in mobile usability analysis. First, knowing which tasks users actually execute is required for calculating common usability metrics such as task efficiency, error rates and effectiveness. Second, understanding how users perform these tasks is important for developers in order to validate designed interaction sequences for tasks (e.g. sequential steps required to successfully perform and complete a task). In this paper, we describe a novel approach for automatically extracting and grouping interaction sequences from users, assigning them to predefined tasks (e.g. writing an email) and visualising them in an intuitive way. Thus, we are able to find out if the designer's intention of how users should perform designed tasks, and how they actually execute them in the field, matches, and where it differs. This allows us to figure out if users find alternate ways of performing certain tasks, which contributes to the application design process. Moreover, if the users' perception of tasks differs from the designer's intention, we lay the foundation for recognising issues users may have while executing them.
AB - Identifying intentions of users when they launch an application on their smartphone, and understanding which tasks they actually execute, is a key problem in mobile usability analysis. First, knowing which tasks users actually execute is required for calculating common usability metrics such as task efficiency, error rates and effectiveness. Second, understanding how users perform these tasks is important for developers in order to validate designed interaction sequences for tasks (e.g. sequential steps required to successfully perform and complete a task). In this paper, we describe a novel approach for automatically extracting and grouping interaction sequences from users, assigning them to predefined tasks (e.g. writing an email) and visualising them in an intuitive way. Thus, we are able to find out if the designer's intention of how users should perform designed tasks, and how they actually execute them in the field, matches, and where it differs. This allows us to figure out if users find alternate ways of performing certain tasks, which contributes to the application design process. Moreover, if the users' perception of tasks differs from the designer's intention, we lay the foundation for recognising issues users may have while executing them.
KW - Navigation sequence visualisation
KW - Pattern matching
KW - Usability task identification
UR - http://www.scopus.com/inward/record.url?scp=84908573619&partnerID=8YFLogxK
U2 - 10.1145/2628363.2628384
DO - 10.1145/2628363.2628384
M3 - Conference contribution
T3 - MobileHCI 2014 - Proceedings of the 16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services
SP - 359
EP - 368
BT - MobileHCI 2014 - Proceedings of the 16th ACM International Conference on Human-Computer Interaction with Mobile Devices and Services
PB - Association for Computing Machinery, Inc
Y2 - 23 September 2014 through 26 September 2014
ER -