| Literature DB >> 27633232 |
Sébastien Tremblay1, Jean-François Gagnon2, Daniel Lafond2, Helen M Hodgetts3, Maxime Doiron4, Patrick P J M H Jeuniaux4.
Abstract
While simple heuristics can be ecologically rational and effective in naturalistic decision making contexts, complex situations require analytical decision making strategies, hypothesis-testing and learning. Sub-optimal decision strategies - using simplified as opposed to analytic decision rules - have been reported in domains such as healthcare, military operational planning, and government policy making. We investigate the potential of a computational toolkit called "IMAGE" to improve decision-making by developing structural knowledge and increasing understanding of complex situations. IMAGE is tested within the context of a complex military convoy management task through (a) interactive simulations, and (b) visualization and knowledge representation capabilities. We assess the usefulness of two versions of IMAGE (desktop and immersive) compared to a baseline. Results suggest that the prosthesis helped analysts in making better decisions, but failed to increase their structural knowledge about the situation once the cognitive prosthesis is removed.Keywords: Complex decision making; Knowledge representation; Visual analytics
Mesh:
Year: 2016 PMID: 27633232 DOI: 10.1016/j.apergo.2016.07.009
Source DB: PubMed Journal: Appl Ergon ISSN: 0003-6870 Impact factor: 3.661