Seeing the woods for the trees: the problem of information inefficiency and information overload on operator performance

Dadashi, Nastaran; Golightly, David; Sharples, Sarah

Abstract

One of the recurring questions in designing dynamic control environments is whether providing more information leads to better operational decisions. The idea of having every piece of information is increasingly tempting (and in safety critical domains often mandatory) but has become a potential obstacle for designers and operators. The present research study examined this challenge of appropriate information design and usability within a railway control setting. A laboratory study was conducted to investigate the presentation of different levels of information (taken from data processing framework, Dadashi et al., 2014) and the association with, and potential prediction of, the performance of a human operator when completing a cognitively demanding problem solving scenario within railways. Results indicated that presenting users only with information corresponding to their cognitive task, and in the absence of other, non task-relevant information, improves the performance of their problem solving/alarm handling. Knowing the key features of interest to various agents (machine or human) and using the data processing framework to guide the optimal level of information required by each of these agents could potentially lead to safer and more usable designs.

Citation

Dadashi, N., Golightly, D., & Sharples, S. (in press). Seeing the woods for the trees: the problem of information inefficiency and information overload on operator performance. Cognition, Technology and Work, 19(4), 561–570. https://doi.org/10.1007/s10111-017-0451-1

• Journal Article Type: Article
• Acceptance Date: Nov 16, 2017
• Online Publication Date: Nov 23, 2017
• Deposit Date: Nov 21, 2017
• Publicly Available Date: Nov 23, 2017
• Journal: Cognition, Technology and Work
• Print ISSN: 1435-5558
• Electronic ISSN: 1435-5566
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 19
• Issue: 4
• Pages: 561–570
• DOI: https://doi.org/10.1007/s10111-017-0451-1
• Keywords: Human computer interaction; Decision support system; Usability engineering
• Public URL: https://nottingham-repository.worktribe.com/output/896607
• Publisher URL: https://link.springer.com/article/10.1007%2Fs10111-017-0451-1
• Contract Date: Nov 21, 2017