Journal of Dynamic Decision Making


The Journal of Dynamic Decision Making (JDDM) offers a peer-reviewed interdisciplinary open-access publication outlet for research on cognitive and behavioral processes involved in dynamic decision making. It is free of charge for both authors and readers. Contributions are expected primarily from the field of psychology but also from other disciplines like economics, philosophy, cognitive science, or system dynamics. Please refer to our Focus and Scope as well as our Author Guidelines, if you are interested in making a contribution to JDDM. For further information you may also refer to our Editorial Statement.

 

Recent Articles

 
Barbara Frank, Annette Kluge
To handle complex technical operations, operators acquire skills in vocational training. Most of these skills are not used immediately but at some point later; this is called temporal transfer. Our previous research showed that cognitive abilities such as general mental ability (GMA) and memory are good predictors of temporal transfer. In addition to temporal transfer, operators also have to solve non-routine and abnormal upcoming problems using their skill set; this type of transfer is called adaptive transfer. ... (more)
JDDM doi: 10.11588/jddm.2017.1.40004
Neha Sharma, Varun Dutt
One of the paradigms in judgment and decision making (called “sampling paradigm”) involves decision-makers sample information before making a final consequential choice. In the sampling paradigm, certain computational models have been proposed where a set of model parameters are calibrated to the choice proportions of a group of participants (aggregate models). Also, there exist computational models where a set of model parameters are calibrated to each participant’s choice (individual models). However, currently less is known on how aggregate models account for choices made by individual participants in the sampling paradigm. ... (more)
JDDM doi: 10.11588/jddm.2017.1.37687
Michael Engelhart, Joachim Funke, Sebastian Sager
The question “How can humans learn efficiently to make decisions in a complex, dynamic, and uncertain environment” is still a very open question. We investigate what effects arise when feedback is given in a computer-simulated microworld that is controlled by participants. This has a direct impact on training simulators that are already in standard use in many professions, e.g., for flight simulators for pilots, and a potential impact on a better understanding of human decision making in general. ... (more)
JDDM doi: 10.11588/jddm.2017.1.34608
Alexander Nicolai Wendt
Empirical methods of self-description, think aloud protocols and introspection have been extensively criticized or neglected in behaviorist and cognitivist psychology. Their methodological value has been fundamentally questioned since there apparently is no suficient proof for their validity. However, the major arguments against self-description can be critically reviewed by theoretical psychology. This way, these methods’ empirical value can be redeemed. Furthermore, self-descriptive methods can be updated by the use of contemporary media technology. In order to support the promising perspectives for future empirical research ... (more)
JDDM doi: 10.11588/jddm.2017.1.33724
Natassia Goode, Jens F Beckmann
Many situations require people to acquire knowledge about, and learn how to control, complex dynamic systems of inter-connected variables. Numerous studies have found that most problem solvers are unable to acquire complete knowledge of the underlying structure of a system through an unguided exploration of the system variables; additional instruction or guidance is required. This paper examines whether providing structural information following an unguided exploration also improves control performance, and the extent to which any improvements are moderated by problem solvers’ fluid intelligence. ... (more)
JDDM doi: 10.11588/jddm.2016.1.33346

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