Ergonomics in Design: The Quarterly of Human Factors Applications

Human factors/ergonomics (HF/E) can play a role in improving equal opportunity in U.S. voting through the redesign of inefficient voting processes that lead to low voter turnout. This article, which derives from the authors’ winning entry in the HFES 2014 “Voting Systems of Tomorrow” competition, outlines HF/E-driven recommendations for improving the American voting process. These recommendations include a “one-stop shop” for all voting-related information, personalized voter accounts, appointment systems, and several ballot design suggestions. Implementation of these recommendations, on any level, has the potential to improve the proficiency of polling places, lower all-too-common lengthy wait times, and ensure that ballots are accessible to all voters.

In this article, we examine two novel issues in user requirements analysis for a feedback system on household energy consumption: (a) microgeneration and (b) the “Must, Should, Could, Won’t have” (MoSCoW) method. We report on a qualitative user requirements analysis using the MoSCoW method for the prioritization of user requirements. Fifteen interviews resulted in three user groups that were abstracted into personas with different user requirements. Finally, we show that changes in cutoff values resulted in MoSCoW prioritization changes for a maximum of only 5.9%. These are promising results for the robustness of the MoSCoW method.

Although robots are becoming widely known as aids to human success, they are likewise gaining reputations as tools of death. This begs the question of whether robots can be morally programmed. We address this question through discussion of various conceptualizations of robots in society. Using case studies, we highlight the irony of robots functioning both as heroic and hazardous agents. We conclude by assessing whether morality can be designed in robots and present guidelines for designers to attempt such a feat.

The pilot control stations of some unmanned aircraft systems (UASs) have been plagued by poor human–machine interfaces. Human factors guidelines focused on the unique challenges of unmanned aviation will be essential if UASs are to gain unrestricted access to civil airspace. We present a systematic approach that can assist in the development and organization of human factors guidelines for UAS pilot control stations and other human–machine interfaces.

The need for human-centered design in the mining industry to help develop safe and fit-for-purpose equipment is first described. A tool that was specifically developed for mobile mining equipment by the authors and colleagues is introduced; it combines the application of participatory ergonomics, qualitative risk management, and safe design. A case study using this tool for mobile mining equipment access and egress is then presented. The case study shows that focusing on end users and their tasks by means of a structured, human-centered process can help to produce safer redesigns of mining equipment.

Margulieux, L. E., Chen, D.-W., McDonald, J. D., Bujak, K. R., Gable, T. M., Darling, C. M., Schaeffer, L. M., & Barg-Walkow, L. H. (2016). Online collaboration applications evaluated based on ease of use. Ergonomics in Design: The Quarterly of Human Factors Applications, 24(2), 21-30. (Original DOI: 10.1177/1064804615611273)

In the above article, two of the author photos were switched. The correct photos and biographies are given below.

Laura M. Schaeffer is a doctoral student in the engineering psychology program at the Georgia Institute of Technology. She received her master of science degree in engineering psychology from Georgia Tech. Her research interests include instructional design, the role of technology in education, and aiding students during problem solving.

Laura H. Barg-Walkow is a doctoral student in the engineering psychology program at the Georgia Institute of Technology. She received her master of science degree in engineering psychology from Georgia Tech. Her research interests include medical human factors, interruptions, errors, and training, particularly in the domain of health care.