Assistance design features, e.g. decisional guidance, explanations, decision aids, and recommender systems, support individuals in their decision-making and task execution. Researchers propose to provide assistance in an intelligent invocation style. In order to provide the assistance in an intelligent fashion, the assistance system need to identify the individuals’ need for assistance. This Master thesis conducts a laboratory experiment to investigate individuals’ cognitive and affective behavior (e.g. using eye-tracking devices and other neurophysiological measurements) during their task execution and the usage of the provided assistance.
Goal of the thesis
The goal of this Master thesis is to design and, potentially conduct a laboratory experiment to identify individuals’ cognitive and affective behavior during task execution. Based on assistance design features literature an experimental prototype shall be developed and the experiment designed. If time is sufficient, the experiment shall also be conducted.
- This thesis is written as part of a cooperation between Dr. Jella Pfeiffer and Dr. Stefan Morana (Information Systems & Service Design)
- Very good time management and organizational skills
- Good development skills (.NET experience and/or Java is beneficial)
- Interest in experiment in information systems research
- English skills
- Ability to review and synthesize literature
- Gregor, S., & Benbasat, I. (1999). Explanations from Intelligent Systems: Theoretical Foundations and Implications for Practice. MIS Quarterly, 23(4), 497–530.
- Hold, P., & Sihn, W. (2016). Towards a model to identify the need and the economic efficiency of digital assistance systems in cyber-physical assembly systems. In 1st International Workshop on Cyber-Physical Production Systems (CPPS).
- Wandke, H. (2005). Assistance in human–machine interaction: A conceptual framework and a proposal for a taxonomy. Theoretical Issues in Ergonomics Science, 6(2), 129–155.
- Haapalainen, E., Kim, S., Forlizzi, J. F., and Dey, A. K. “Psycho-physiological measures for assessing cognitive load,” in the 12th ACM international conference, J. E. Bardram, M. Langheinrich, K. N. Truong and P. Nixon (eds.), Copenhagen, Denmark, p. 301.