Human Centered Computing

Collecting usage data for designing adaptive interfaces

Betreuer: Prof. Dr. Claudia Müller-Birn
Fach: Data/Community Analytics
Abschluss: Bachelor Thesis

Inhalt

One approach to learning how users apply a software is to analyze their behavior. A better understanding of user’s behavior can help to improve usability and the quality of interaction. Three types of data can be collected to build suitable user models: user data, usage data, and environmental data. Particularly in the web domain, the analysis of usage data is widely adopted by employing tools such as Google Analytics and Piwik. Such tools provide information on click streams or navigation paths. The problem with these tools is that they provide off-the-shelf metrics often too generic to help answering specific usability questions. The goal of this thesis is to design, develop and test a software component that helps to measure user behavior in a web application. Instead of using the collected data for usability analysis, the data should be provided to third parties that can use the provided data for adapting their services accordingly.

References

  • Kerry Rodden, Hilary Hutchinson, and Xin Fu. 2010. Measuring the user experience on a large scale: user-centered metrics for web applications. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '10). ACM, New York, NY, USA, 2395-2398. 
  • Gerhard Fischer. 2001. User Modeling in Human–Computer Interaction. User Modeling and User-Adapted Interaction 11, 1-2 (March 2001), 65-86