Use of the motivation-expectation space to communicate strategies in a joint cognitive system
Li, Angela Sin Tan
Date of Issue2011
School of Mechanical and Aerospace Engineering
When humans and automation work together, the human typically takes a supervisory role and rely on the automation to complete certain tasks. However, there are times when the human supervisor cannot understand what the automation is doing. This is complicated by the fact that automation can sometimes fail, which makes the actions of the automation difficult to comprehend. This thesis presents information for calibrating operator's trust and dependence on automation for improving decision performance. The Motivation-Expectation Space (MES) representation is proposed as a tool to aid the monitoring of automation. The literature review suggested that the four components in the MES (goals, means, causes, and effects) are fundamental in how people naturally strategize decisions. The review also revealed that the MES can support most of the information requirements needed for bridging automation trust and dependence. A case study was performed to demonstrate how data obtained through a cognitive task analysis (CTA) could be translated to the MES representation. This was previously demonstrated in a petrochemical context where work constraints are limited primarily to the laws of physics (e.g. temperature). In this thesis, the translation was repeated for an in-car navigation task to gain insights in the MES application for a context with intentional constraints. The case study concluded with (1) a specific definition for each relation depicted in the MES, and (2) the design of the MES representation for an in-car navigation aid. A three group between-subject experiment was conducted to test the effectiveness of the information and orthogonal structure in the MES. The information in the MES was presented in either the orthogonal MES format or textual formats.