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Mental Model Updating

The research cluster "Mental Model Updating" is concerned with the modeling of memory-based recall and learning processes. The goal is both to explore the basics of these processes as well as their application in the context of the evaluation of cognitive ergonomics. In particular our insights into learning and memory processes can be applied to the explanation and prediction of the effects of users' cognitive limitations and idiosyncrasies on usability evaluations. The research cluster comprises the following topics:


Working Memory Updating

The update of those representations that available for immediate cognitive processing is a process that plays a vital part in a large number of everyday tasks and activities. Among other questions, we are interested in how those processes affect time perception and workload. Another research question concerns itself with the role of activation and inhibition in the repeated manipulation of working memory content.


Learning and Relearning

We are interested in the study of learning mechanisms from many different angles. In the applied domain we are especially interested in learning processes in the context of interaction with mobile communication devices (smart phones, tablets). Another topic is the study of dynamic tasks that demand continuously changing knowledge representations, i.e. mental models. We are especially interested in what facilitates and inhibits mental model change and whether and under which conditions overlearning, i.e. the excessive adaptation to certain temporal situational attributes within a task, can play a role.



Team Learning and Memory

Nele Rußwinkel [1]

Sabine Prezenski [2]

Oliver Klaproth [3]


Finished Theses

  • Dr.-Ing. Marc Halbrügge: Predicting User Performance and Errors on the Basis of the Computational Introspection of Model-Based User Interfaces [4] (2017)
  • Dr. rer. nat. Philippe Büttner: Causal Reasoning in Complex Systems [5] (06.06.2014)



Project-related Publications

Prezenski, S. (2017). Implementing Mental Model Updating in ACT-R [6]. In M. van Vugt, A. Banks & W. Kennedy (Eds.), Proceedings of the 15th International Conference on Cognitive Modeling, p. 121-127. Link to publication [7] Link to original publication [8]

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