Summary
Authors argue that making sense of a complex system requires that a person constructs a network of concepts and principles about some domain that represents key (often dynamic) phenomena and their interrelationships. Invisible, dynamic phenomena pose considerable barriers to understanding. They mention three reasons for this: (a) processing all the simultaneous events and interactions pose a substantial load on working memory because of the mental simulation process and rule-based inferences needed to construct a complete mental model; (b) making connections among different levels of a complex system places added demands on working memory because many systems are characterized by complex causality (namely there may be many intermediate steps that intervene between cause and effect, which may not be linear); (c) complex systems may also have emergent properties that may not be fully predictable from the behavior of individual components. Authors mentioned studies which found that (a) students tend towards very simple causal explanations of complex phenomena; (b) when students reasoned about effects, they missed the connectedness within the system and the complex causal relationships because learners tended to focus on the structure of systems rather than on the underlying function.
Authors describe a way of making sense of complex systems, the Structure–Behavior–Function (SBF) theoretical framework. SBF accounts for a complex system’s multiple interrelated levels, and its dynamic nature. This framework has been used for explaining and justifying design of physical devices such as electrical circuits and heat exchangers. The SBF framework allows effective reasoning about the functional and causal roles played by structural elements in a system by describing a system’s subcomponents, their purpose in the system, and the mechanisms that enable their functions. More specifically, structures refer to elements of a system (e.g., fish, plants, and a filter are some of the elements that comprise an aquarium). Behaviors refer to how the structures of a system achieve their purpose. These are the interactions or mechanisms that yield a product, reaction, or outcome (e.g., filters remove waste by trapping large particles, absorbing chemicals, and converting ammonia into harmless chemicals). Finally, functions refer to why an element exists within a given system, that is, the purpose of an element in a system (e.g., the filter removes byproducts from the aquarium). We define function contextually. The distinction between behavior and function can be confusing because of contextual issues. For example, from the perspective of an aquarium system, fish respiration is a behavior that releases waste products. If we were analyzing the fish as a system, we might consider respiration as a function and gas exchange and various cellular reactions as behaviors.
In this paper, authors extend their previous work to an aquarium ecosystem as they examine how well the SBF framework serves as an epistemic form that captures the differences between expert and novice understanding.
The presented study examines individuals’ representations of an aquatic system from the perspective of structural (elements of a system), behavioral (mechanisms), and functional aspects of a system with an experts-novice design. This design is based on the hypothesis that an expert understanding of complex systems differs from a novice understanding. The study included participants from middle school children to pre-service teachers to aquarium experts. Individual interviews were conducted to elicit participants’ mental models of aquaria. Their verbal responses and pictorial representations were analyzed using the Structure–Behavior–Function (SBF) theory as a framework for coding scheme. The results indicated that representations ranged from focusing on structures with minimal understanding of behaviors and functions to representations that included behaviors and functions. Novices’ representations focused on perceptually available, static components of the system, whereas experts integrated structural, functional, and behavioral elements.
The results of this study clearly indicate that “structures” is the most cognitively available level of a complex system for novices. Those structures that are most perceptually salient are best represented. For the experts, the behavioral and functional levels serve as the deep principles that organize their knowledge of the system. Understanding the behaviors and functions of a system indicate a more elaborate network of concepts and principles representing key phenomena and their interrelationships. The qualitative analysis demonstrated the fine differences in the mental representations of different sorts of experts. Biologists think in global ecosystem terms whereas hobbyists think in more local terms of what it takes to maintain healthy fish and their understanding is more situated in concrete aspects of the aquarium.
Relevance for Complex Systems Knowledge
The paper deals with complex systems. Complex systems are considered as phenomena with both a dynamic nature and a multiple level of organization. Making sense of a complex system is portrayed as a difficult task because it requires a person to think abstractly and often challenges current beliefs regarding phenomena. The characteristics of complex systems make them particularly difficult to understand. They are comprised of multiple levels of organization that often depend on local interactions. The relationships across these levels are not intuitively obvious. For example, in learning about ecological systems, one needs to envision how genes, individuals, populations, and species interrelate. An ecosystem can be viewed from the level of the individual organism to the level of the environment as a whole. A disturbance at one level or component of the system can easily affect others.
