Abstract
There are inherent difficulties in designing an effective Human–Machine Interface (HMI) for a first-of-its-kind system. Many leading cognitive research methods rely upon experts with prior experiences using the system and/or some type of existing mockups or working prototype of the HMI, and neither of these resources are available for such a new system. Further, these methods are time consuming and incompatible with more rapid and iterative systems development models (e.g., Agile/Scrum). To address these challenges, we developed a Wargame-Augmented Knowledge Elicitation (WAKE) method to identify information requirements and underlying assumptions in operator decision making concurrently with operational concepts. The developed WAKE method incorporates naturalistic observations of operator decision making in a wargaming scenario with freeze-probe queries and structured analytic techniques to identify and prioritize information requirements for a novel HMI. An overview of the method, required apparatus, and associated analytical techniques is provided. Outcomes, lessons learned, and topics for future research resulting from two different applications of the WAKE method are also discussed.
Highlights
Developing Human–Machine Interfaces (HMIs) for systems is a “bread and butter” task for human factors engineers, or Human Systems Integration (HSI) practitioners
There is no shortage of research methods to elicit information requirements; they each have their own limitations
Eliciting and understanding operator information requirements for a prototype is uniquely challenging due to the fact that nobody has used the system, and there are no Concepts of Operations (CONOPS) for how the system would be used in a relevant operational environment
Summary
Developing Human–Machine Interfaces (HMIs) for systems is a “bread and butter” task for human factors engineers, or Human Systems Integration (HSI) practitioners. There is no shortage of research methods to elicit information requirements (i.e., what information is needed by end users to make informed and timely decisions); they each have their own limitations. The increasingly prevalent use of agile lifecycles in system development drives the need for new human factors methods to enable HSI practitioners to have inputs into the system development process more rapidly. The HMI design process (including the elicitation of users’ information requirements) is even more difficult when developing a first-of-its kind system. We will explore the different challenges in this problem space and review possible approaches and research goals, before describing one such novel human factors method for capturing information requirements for HMI development
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