An Enhanced Mental Model Elicitation Technique to Improve Mental Model Accuracy

Publisher:
Springer
Publication Type:
Journal Article
Citation:
Lecture Notes in Computer Science, 2013, ICONIP, 8226 pp. 82 - 89
Issue Date:
2013-01
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The causal mental model representation has been used extensively in decision support. Due to limited information requirements of this representation, that is concepts and relationships, the users are required to articulate only the mental models, without invoking the corresponding experiential knowledge stored in associative memory. The elicitation of mental models without being endorsed by experiential knowledge may lead to inaccurate, invalidated or biased mental models, and espoused theories, being stored for decision making. We introduce SDA articulation/ elicitation cycle, which invokes a users associative memory during the articulation/elicitation process to validate mental models. It is argued in this paper that by engaging associative memory during the mental model articulation/elicitation process, the accuracy and validity of mental models can be improved, the biases can be reduced, and the theories-in-use can be elicited rather than the espoused theories. A case study is presented to demonstrate the working and contributions of the SDA articulation/elicitation cycle.
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