Introduction: In a cognitive system, human operators work with automation to achieve their goal. However, there are times when the human operator cannot interpret what the automation is doing. This can create dangerous communication gap particularly if the automation provides the wrong advice. This paper proposes the Motivation-Expectation Space (MES) as a representative structure for bridging the gap. Review: The MES has its theoretical foundation from research in Cognitive System Engineering. It represents the goals, means, causes, and effects in an orthogonal structure. These four components were repeatedly observed in research related to decision strategies. The MES was assessed against the information requirements for improving automation trust and dependency and found to suffice in supporting most of the requirements. Contribution: The structured representation of these elements in the MES would likely facilitate the interpretation of the decision strategies, making it easier and faster for the human to understand what the automation is doing. Parallels were also drawn between MES and Situation Awareness to suggest the potential value MES can bring to research in Cognitive System Engineering.
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