Improving Users' Mental Models of Intelligent Software Tools

Improving Users' Mental Models of Intelligent Software Tools,10.1109/MIS.2011.32,IEEE Expert / IEEE Intelligent Systems,Shane T. Mueller,Gary Klein

Improving Users' Mental Models of Intelligent Software Tools   (Citations: 1)
BibTex | RIS | RefWorks Download
optimization algorithms have changed how we live. In many cases, users understand the basic mechanics of the intelligent software systems they rely on, but often (and perhaps more often today than in the past) novices have no direct knowledge of their intelligent devices’ algorithms, data requirements, limitations, and representations. Problems can go beyond those caused by a poor user interface design and a user’s ability to understand a tool’s simple components, which could be alleviated with proper instruction. These problems might be fundamentally cognitive and likely stem from people having an inadequate unsuitable mental model of how a tool works. 1 Usability problems can persist even for software designed with human-centered design principles, especially when the software replaces or augments intelligent human capabilities. In these cases, users might have incorrect expectations about what the automated system is doing, and training and guides are necessary to help them understand the software’s workings. Usability problems can often be overcome by trial-and-error experience or when communities pass down information to newer users, but we believe that the genuine cognitive challenges to forming functional and accurate mental models can be formalized, documented, and “trained in.” This article describes the Experiential User Guide (EUG), a concept designed to address these challenges.
Journal: IEEE Expert / IEEE Intelligent Systems - EXPERT , vol. 26, no. 2, pp. 77-83, 2011
Cumulative Annual
View Publication
The following links allow you to view full publications. These links are maintained by other sources not affiliated with Microsoft Academic Search.
Sort by: