Abstract for: Assessing understanding and learning about dynamic systems
One of the main goals of system dynamics models is to improve decision making in dynamic systems. This paper addresses the question of how we can measure what people understand about dynamic systems and what benefit people get from exposure to system dynamics models. For this purpose, we use existing literature about assessing understanding and learning in system dynamics to reflect on outstanding research questions in this area. Learning about dynamic systems requires restructuring of existing knowledge into new knowledge as well as re-use of such new knowledge over time and in different contexts. Existing approaches in system dynamics use elements of dynamic systems to represent knowledge. They thus provide a benchmark for expert knowledge and give indications about the gap between novices and experts. However, they do not provide a theory for further investigating how this gap can be closed. In a second part, we therefore analyze the learning sciences literature for elements that can be useful for the development of a theory about the acquisition, retention, and transfer of knowledge about dynamic systems. We describe first elements of such theory and illustrate how they can help in the design and assessment of dynamic decision making interventions.