Measuring Change in Mental Models of Complex Dynamic Systems
By J. Doyle, M. Radzicki, W. Trees. 2008
61 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Management Science and Operations Research
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Shane T. Mueller
- Gary Klein
- Robert R. Hoffman
- Niloofar Zarei
- Eric D. Ragan
- Sina Mohseni
- William J. Clancey
- Abigail Emrey
In Management Science and Operations Research
- Gary Klein
- Robert R. Hoffman
- Shane T. Mueller
- Martin F. G. Schaffernicht
- Stefan N. Groesser
- Peter Pirolli
- Daniel M. Russell
- David William Aha
Citations in the corpus
- Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI (2019, background): “…represent and measure or evaluate mental models (Besnard, Greathead and Baxter 2004; Borgman, 1986; deGreef and Neerincx, 1995; Dodge et al., 2018; Doyle, Radzicki, and Trees, 2008; Kim, et al., 2016; Klein and Hoffman, 2008; Muramatsu and Pratt, 2001; Schaffernicht and Groesser, 2011; Tullio et…”
- A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems (2018, background): “taining user trust over time. Time-based measurements, also referred to as dynamic measurements, allows designers to monitor explanation usability and effectiveness in various contexts and situations [50, 185]. For instance, Zhang et al. [222] explore the effect of intelligent system explanations in”
- A comprehensive method for comparing mental models of dynamic systems (2011, methodology): “This is because existing methods for eliciting mental models are not designed to measure them, but to improve them (Doyle et al., 2008).”