Date of Award
Fall 2012
Access Type
Thesis - Open Access
Degree Name
Master of Science in Human Factors & Systems
Department
Human Factors and Systems
Committee Chair
Elizabeth Blickensderfer, Ph.D.
First Committee Member
Kelly Neville, Ph.D.
Second Committee Member
John J. Burns, Ph.D.
Abstract
Emerging research in complexity science recognizes traditional techniques for engineering systems do not always work for complex systems. Designing complex systems requires individuals to have knowledge of engineering as well as human performance. To this end, design efforts rely often on multi-disciplinary teams. While any two members of a design team may view the system design problem in vastly different manners, this study sought to identify a possible systemic effect on approach by the differing education and experience obtained by social practitioners, represented by human factors, and technical practitioners, represented by systems engineers. It further examined the impact of the complexity of the designed system designed on this systemic effect; in this case, two systems associated with unmanned aircraft systems (UAS). This study relied on measurement of individual mental models, using a graphical brainstorming tool to capture functional decompositions, argued as representing the problem domain component of an individual mental model. This study compared individual functional decomposition models against an average model composed from the same educational specialty, and from an average model composed from the opposite educational specialty. Participants developed models for a simple/closed problem and an open/complex problem. The researcher conducted a repeated measures multivariate analysis of variance on the effects of domain, problem type and the interaction between the two, as well as with interactions with educational specialty. The results indicated higher agreement among mental models when individuals were compared to the average model from their same specialty, that more agreement in mental models occurred in relation to the simple/closed problem than in relation to the open/complex problem, and that open/complex problems can exacerbate the level of mental model dis-agreement among team members with different educational backgrounds.
Scholarly Commons Citation
Gordon, Jerry A., "Level of Agreement in the Mental Models of Human Factors Practitioners and Systems Engineers Working in Collaborative Teams" (2012). Doctoral Dissertations and Master's Theses. 74.
https://commons.erau.edu/edt/74
