Cognitive load reduction through the use of building blocks in the design of decision support systems

Processes and tasks in organizations become increasingly complex and dynamic. This requires managers of expert teams to quickly gain knowledge and insight outside their prime area of expertise. In these situations analysis tools and decision support tools are required. Often, such tools are used by experts to compose models that managers can use to gain specific insight in complex tasks and decisions. An observed paradox in this process is that once the first model is made, the insight into the system reveals the "real problem" and thus several iterations of the analysis, design and modeling are required to create a model that provides the required support. A proposed solution to increase the efficiency of re-designing is the use of patterns, also named building blocks. This allows the expert to re-use components to accommodate new requirements. However, the advantage of building blocks goes beyond re-use, design efficiency and flexibility. This paper argues that in addition to the benefits described above, there is a specific added value for the use of building blocks by novices to acquire analysis, modeling and design skills. We propose that building blocks decrease the cognitive load of both the design task and the effort of acquiring these skills. We use cognitive load theory from educational psychology to theoretically underpin this proposition. Empirical evidence is presented through two exploratory experiments.