In this paper we lay the foundations for studying decision-making in complex dynamic construction management scenarios using situational simulations as experimental testbeds. We draw on research conducted in dynamic decision making, construction data-mining and situational simulations to develop methods to study human decision-making data collected in ICDMA - a situational simulation of a real four story steel frame office building construction project. Specifically, we address challenges in the collection, organization and analysis of human subject data. We define a discipline driving the collection of human decision-making data, establish a semantics to organize the data and a simple mathematical syntax to represent it. We also present an analysis of preliminary experimental work and show that our method can be used to analyze patterns in complex construction decision-making. Finally, we present an agenda of research in construction decision-making using situational simulations that can be conducted using our proposed methods.