Salient complex systems ideas

A system is complex when the elements or parts that make up the system are interconnected and communicate in multiple, nonlinear ways (Mitchell, 2009; Yoon, 2011). The patterns of interactions form a collective network of relationships that exhibit emergent properties that are not observable at subsystem levels (Penner, 2000; Resnick, 1994; Yoon, 2008). When perturbations occur, the network self-organizes, often in

21 unpredictable ways, and new properties can emerge without a centralized or intended design (Bar-Yam, 1997; Jacobson, 2001; Jacobson et al., 2011). To have an understanding of complex systems, one needs to look at the ways the system and its components interact with one another and with the environment, respond to perturbations, and self-organize by studying the dynamic processes through which they evolve over time (Goh, Yoon et al., 2011; Jacobson et al., 2011; Yoon, 2011).

Pavard and Dugdale (2000) summarize four sets of ideas or properties that appear to be generally applicable to a variety of complex systems. Their framework is adapted as an organizing map to illustrate some salient complexity ideas inherent in several scientific domains. It is appropriate at this point to recognize that there are no “tidy descriptions and unambiguous definitions” of complex systems (Davis & Sumara, 2006, p. ix). Many researchers in their attempts to come up with a list of characteristics, processes, or ontologies depicting complex systems caution the problematic nature of this task (Garnsey & McGlade, 2006; Jacobson et al., 2011). Nonetheless, by drawing upon seminal literature of early complex systems researchers (e.g., Bak, 1999; Capra, 1996; Kauffman, 1995; Prigogine & Stenger, 1984) and recent reviews of the topic (e.g., Davis & Sumara, 2006; Lesh, 2006; Mitchell, 2009), the non-exhaustive framework attempts to embrace the diversity in this field.

2.3.1.1 Non-determinism and nonlinearity

Complex systems are non-deterministic, that is, it is difficult to anticipate precisely the properties of such systems even if the behaviors of their components are known (Prigogine & Stenger, 1984; Lewin, 1999). This difficulty stems from the fact that

22 the components affecting the system operate through complex feedback and causal mechanisms. These mechanisms interconnect the components in multiple nonlinear ways, which in turn make prediction of cause-and-effect(s) difficult (Garnsey & McGlade, 2006; Kauffman, 1995). For example, the plants, animals, and other abiotic elements that make up an ecosystem are so intricately connected to one other that it is complicated to predict how an ecosystem will respond after a perturbation such as an extinction of a certain insect species due to the use of a pesticide (Bar-Yam, 1997).

2.3.1.2 Open and dynamic nature

Complex systems are open and dynamic in nature (Kauffman, 1993; 1995). Being open or ambiguously bounded, complex systems allow the inflow and outflow of information, matter and energy through the boundaries of the systems (Davis & Sumara, 2006). Researchers argue that it is this permeability facilitating the continuous exchange of materials with the environment that enables these systems to be dynamic (Bar-Yam, 1997; Gell-Mann, 1995). The term ‘dynamic’ means that there is no apparent beginning, middle and end to the processes underlying the complex systems (Jacobson, 2001). Understanding this open and dynamic nature of complex systems is often problematic as it requires one to perceive a system beyond its natural spatial and temporal boundaries to include the surrounding environment and an extended timescale (Booth-Sweeney & Sterman, 2006; Mitchell, 2009). For instance, to fully comprehend the processes driving the earth’s water system, one has to consider the continual process of the Sun’s input, heat loss to space, and conversion to energy in living organisms over a long period of time (Ben-Zvi Assaraf & Orion, 2005).

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2.3.1.3 Emergence and self-organization

Scientists have shown that each component in complex systems acts in accordance to a set of behavioral and interactional rules, and that it is the collective enactment of these rules that self-organizes into emergent characteristics at the system level (Corning, 2002; Sawyer, 2005). Emergence refers to the phenomenon where the complex entity manifests properties that exceed the summed traits and capacities of individual components (Davis & Sumara, 2006). In other words, the patterns that occur at the system level ‘emerge’ from the simpler interactions among the components (Capra, 1996; Lesh, 2006). Closely related is the idea of self-organization, which refers to the spontaneity of this emergence (Bak, 1999). Self-organization is in opposition to the notion of organization by deliberate design, which is most people’s intuitive understanding about systemic patterns (Bar-Yam, 1997; Kauffman, 1995). Take for instance the behaviors of slime mold cells. Scientists believe that the process where individual mold cells come together to form an aggregate structure in the absence of food and disperse again when there is abundant food, is the emergent, self-organizing result of simple chemical interactions among the cells in response to the environment. That is, the aggregation-dispersal phenomenon is not the result of a deliberate behavior encoded within each cell, as it has been widely believed (Resnick, 1994).

2.3.1.4 Decentralization

Decentralization is the idea that the specific characteristics and order of a complex system cannot be precisely localized to one component or a part of the system (Davis & Sumara, 2006; Kelso, 1995), and these systemic characteristics and order can be

24 attributed to the interrelationships or multiple connections that exist among the components (Bar-Yam, 1997). The idea of decentralization is somewhat related those of emergence and self-organization, except that the former focuses on the collective influence of the components over a system, while emergence and self-organization refer to the outcomes of the influence. For instance, the seemingly organized way birds fly in a formation is found to be the result of localized interactions at the individual level, and not of a centralized control, say the leader bird at the head of the flock (Resnick, 1994). However, the order that these natural complex systems display is often intuitively interpreted to be only possible through centralized control imposed from within or outside the system (Chi, 2005; Jacobson, 2001).

These ideas describing the nature of complex systems have been synthesized from writings of complexity in multiple scientific domains. By proxy of their commonalities, it is likely that they are among the most salient to be understood in the field (Waldrop, 1992). Seen in this light, teachers’ understanding of this field can be delineated into their knowledge and conceptual beliefs of these four complex systems ideas – nonlinearity and non-determinism; open and dynamic nature; emergence and self-organization; and decentralization. These ideas have proven to be counter-intuitive or even in conflict with commonly held beliefs, posing challenges in understanding and teaching for both teachers and students alike (Casti, 1994; Chi, 2005; Jacobson, 2001). What are these challenges? The next section discusses them.

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