Quality and Usability

Automatic Usability Engineering Methods

Optimized usability engineering of interactive services by usability prediction

Motivation & Project Description

  • State-of-the-art usability measurement methods still involve subjective tests with human participants, which come late in the service development cycle and at a high expense.
  • The aim of this project is to provide usability estimations for multimodal interactive services on the basis of algorithmic models, including
    • Models of human behavior during the interaction
    • Models for predicting usability problems (e.g. ISO 9241)
    • Models for predicting user judgments and hedonistic quality aspects
  • This way services can be developed much quicker and cheaper.


  • Patent for SpeechEval system (user simulation and judgment prediction)
  • Project funding from DFG (revised re-submission): Modellierung von Benutzerverhalten auf techniksoziologischer Basis - Eine neuartige Methodik der Usability-Evaluierung” (with Prof. Rammert)
  • Application for 2nd funding phase of the aforementioned UserModel project started
  • Project application DFG: COGNITIVE (prediction of user affect for sytem adaptivity and evaluation) submitted
  • Project application DFG: Multimodal SpeechEval
  • EU-project proposal: Extra-Ling: Development and testing of adaptive systems
  • New input modalities (3D Gesture recognition and iPhone GUI) for the INSPIRE Smart-Home System
    • DA Florian Greb, Februar 2009
    • DA Tilo Westermann, Januar 2010
  • Models for describing user behavior in response to the service
    • Parameters for quantifying user/system behavior in multimodal interaction (input parameters to models)
    • Models of user interaction behavior for GUIs and VUIs
    • Identification of relevant quality aspects and their interrelationship
    • Models for predicting usability aspects and user judgments on the basis of interaction parameters

Time Frame: 01/2009 - 12/2010

T-labs Team Members: K.-P. Engelbrecht, C. Kühnel, S. Möller, B. Weiss

Students: M. Siebke, R. Tönges

Funding by: Deutsche Telekom Laboratories