Detecting usability problems in mobile applications on the basis of dissimilarity in user behavior. Issue 139 (July 2020)

• Record Type: Journal Article
• Authors: Jeong, JongWook; Kim, NeungHoe; In, Hoh Peter
• Is Part Of: International journal of human-computer studies. Issue 139(2020)
• Publication Date: 2020-07
• Subjects: Usability -- Usability testing -- Behavior modeling; Human-machine systems -- Periodicals; Systems engineering -- Periodicals; Human engineering -- Periodicals; Human engineering; Human-machine systems; Systems engineering; Periodicals; Electronic journals; 004.019
• DOI: 10.1016/j.ijhcs.2019.10.001
• Languages: English
• ISSNs: 1071-5819

Abstract

Highlights: This paper presents a technique for detect usability problems effectively via usability testing in mobile application. Users interact with mobile applications in dissimilar ways when encountering usability problems. Dissimilarities of user behaviors helps find usability problems. The methods for tracing, modeling and comparing user behaviors is proposed to measure the similarity of user behaviors. Abstract: Usability is one of the critical success factors for mobile applications. However, usability is not easy to improve. Many usability testing studies have been conducted to detect usability problems easily, however they usually carry a substantial cost and require specific expertise. In this paper, we present methods and tools to detect usability problems effectively via usability testing in mobile application. We expect users to interact with mobile applications in dissimilar ways when encountering usability problems. Based on this approach, we propose tracing, modeling and comparing methods for measuring the similarity of user behaviors. We evaluate the similarity of user behavior and use it in detecting problems. In addition, we developed tools for our methods to run in automatic way to save usability testing costs. An experiment was conducted using two mobile applications to confirm that our proposed method is useful. We tested eight tasks and found lower similarity when users encountered a usability problem. The experimental results show that our methods and tools can help find usability problems in mobile applications.