Comparing expert and novice understanding of a complex system from the perspective of structures, behaviors, and functions

Abstract

Complex systems are pervasive in the world around us. Making sense of a complex system should require that a person construct a network of concepts and principles about some domain that represents key (often dynamic) phenomena and their interrelationships. This raises the question of how expert understanding of complex systems differs from novice understanding. In this study we examined individuals' representations of an aquatic system from the perspective of structural (elements of a system), behavioral (mechanisms), and functional aspects of a system. Structure–Behavior–Function (SBF) theory was used as a framework for analysis. The study included participants from middle school children to preservice teachers to aquarium experts. Individual interviews were conducted to elicit participants' mental models of aquaria. Their verbal responses and pictorial representations were analyzed using an SBF‐based 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. This study suggests that the SBF framework can be one useful formalism for understanding complex systems.

A Global Perspective of the Variables Associated with Acceptance of Evolution

“…When an individual becomes more science literate, he/she is more likely to comprehend how the process of change takes place and how outcomes of change over time are manifested in living organisms. One who is scientifically literate is also better equipped to understand emergent and complex systems that are inherent to scientific theories such as evolution (Hmelo-Silver and Pfeffer 2004). Exposure to and grappling with systems thinking and evolutionary processes such as natural selection increase science literacy.…”

Educating the Developing Mind: Towards an Overarching Paradigm

“…For example, representing (1) the structure (e.g., what does it consists of, such as the wings of birds or airplanes); (2) the function (what is it for, such as for motion); and (3) the process (how does it operate, such as the flying movements of the birds or propulsion by the spinning of propellers or air emission of jet engines) of the phenomenon of interest enables students to grasp the relations both within and across concepts and disciplines and, when working on a problem, plan actions accordingly. Interestingly, several scholars proposed variants of these schemes as a means for guiding learning and problem solving in fields as different as engineering (Kalyuga et al 2010) and biology (Hmelo-Silver and Pfeffer 2004). Kalyuga and Hanham (2011) have recently shown that a hierarchical exposition of how systems operate is more effective in producing learning and transfer.…”

Instruction in Computer Modeling Can Support Broad Application of Complex Systems Knowledge

“…Alternatively, learners may employ "mid-level constructions, " whereby small groups are treated as homogeneous entities or a small number of individuals are described as interacting within small groups, rather than complex patterns emerging from interactions across all of the individual agents (Levy and Wilensky, 2008). Learners, therefore, often make incorrect inter-level causal explanations (or confuse how levels are causally related) because ascribing aggregate-level patterns to agent-level interactions is complex, multiple levels may compete for limited attention, and considering multiple levels simultaneously may require a larger working memory than most learners have (Hmelo-Silver and Pfeffer, 2004;Chi, 2005).…”

“…Breaking down complex systems into structural, behavioral, and functional components may make the implicit functions and behaviors of a system explicit and may instantiate a schema that can be used to understand a variety of complex systems (Hmelo-Silver and Pfeffer, 2004). In fact, experts are much better at breaking apart complex systems into the structures, behaviors, and functions of the interacting individual agents than are novices (Hmelo-Silver et al, 2007).…”