Emergence in a complex adaptive system (Holladay, 2005). This figure illustrates the self-organizing process or emergence in a complex adaptive system. 

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... mechanical and reductionist phenomena. From this perspective, we view the components or agents in a system transacting and transforming so that the whole becomes different from the sum of the parts. This position assumes that discrete variables within a complex system cannot be isolated nor controlled because all variables are interdependent and will be somehow changed in ongoing transactions. Emergent, system-wide patterns have the potential to influence or constrain the subsequent dispositions, discourse, and work of individuals and groups within that system. Researchers point to ant colonies, beehives, flocks of birds, and ecosystems as examples of such systems. In the human world, we can point to myriad groups that fit this definition: stakeholder networks; stock traders, gangs, church congregations, and families. In schools, we can point to school boards, grade level teams, and classroom communities. Emergent patterns in these systems are not always democratic or supportive of student achievement. Leaders within complex adaptive systems can attempt to set conditions that influence these patterns, but they cannot claim to control system components or agents over the long term. A number of features of complex adaptive systems can help us think about classrooms and campuses as complex adaptive ecologies. Individual actors and groups are massively entangled and interdependent. This includes interdependence across one scale (or level) of the system as well as interdependence across multiple scales. We can think of this as connections among the parts, the whole, and the greater whole. This can explain why one unhappy student can influence the attitudes of a whole class; it can also explain why high stakes testing can influence instruction, even in content areas that are not tested. Complexity scientists may call this phenomenon “co-evolution” (e.g., Byrne, 1998; Demers, 2007). In complex systems, although system-wide patterns or trends may be anticipated, the behaviors or dispositions of individuals at a particular moment cannot be predicted. For example, we see the butterfly effect--the phenomenon in which small changes at the beginning of a process may be amplified across the system and result in unpredicted and dramatic or significant effects. Conversely, large changes in a system may ultimately result in negligible long-term effects over time (Olson & Eoyang, 2000; Eoyang, 2000). We can think of coherence as “meaning” emerging from the recurring patterns across a complex system or ecology. These patterns begin to “make sense” as they give meaning to otherwise random behaviors or features of a system. In human systems, coherence is sometimes seen or heard as a shared mission or goal or identity; as a pattern among beliefs, structures, functions, roles, and responsibilities; or as familiar discourse patterns. For example, teachers tend to affirm particular student comments and behaviors that are consistent with course objectives or classroom expectations. In a kindergarten class, the teacher may continually communicate through words and actions, "It is OK to make a mistake when you are learning." This encouragement of risk-taking can contribute to the coherence of classroom events that might otherwise seem random. Individuals within a teaching/learning ecology cannot be considered in isolation any more than an individual plant or animal can be productively studied in isolation from its ecological system. Surrounding social and cultural group dynamics and histories make significant contributions to emerging patterns in the system. Although teachers and researchers can focus on particular individuals and groups for a time, the most useful information comes from "zooming in" and "zooming out"--gathering information about individuals and their various contexts. Most complex systems, including those emerging on campuses and in classrooms, involve multiple, overlapping feedback loops. Eoyang explains, "Feedback describes the tendency of a system to use its own output to make adjustments in its inputs and/or processes. Positive feedback amplifies the system outputs, and negative feedback opposes them" (1996). She points to a thermostat as a classical example of a negative feedback system. We see both positive and negative feedback loops in classroom and campus ecologies or systems. For example, a teacher's compliment on a student's performance might encourage similar performance in the future. Teasing from peers for the same performance, however, would probably serve as negative feedback. With deliberate use of questions, comments, and consequences, teachers can use feedback loops to influence students' performance--although we should always remember that particular students may respond in unpredictable ways to what we assume to be a clear message. Feedback is the complex system's primary mechanism for control and for learning so attention to feedback loops between and among all participants and parts of the system is critical if a leader intends to enhance sustainability. In response to internal and external changes, complex adaptive systems transform or self- organize in ways that increasingly fit the changing environment; in other words, when a healthy system responds to changes inside and outside itself, new patterns develop that are more sustainable (Hodgson, 2000). This self-organization is sometimes called emergence. Emergence refers to how “successive symbolic interactions among autonomous individuals result in collective phenomena” (Sawyer, 2005, p. 22). Healthy systems are somehow able to make small, minute-by-minute adjustments (via feedback loops), as well as being able to transform in larger ways when necessary. Those systems have structures and processes in place that allow feedback/information to flow to the participants who need it and allow individuals and groups to make necessary changes in response to that new information. Emergence refers to the “whole” that is different from the sum of its parts (See Figure 1). Teachers sometimes comment that a class of students has "taken on a life of its own"--which is another way of saying that these students, or "semi-autonomous agents," are transacting with one another and generating system- wide patterns. In other words, they are self-organizing, and collective patterns are emerging. In a sustainable system, emerging patterns and relationships move the system both toward internal coherence and toward fit with the environment. These patterns constrain the system to maximize sustainability over time, through whatever changes may arise. As people participate in the system, they tend to follow the strong patterns already in motion. As patterns are repeated, strengthened, and amplified, the patterns tend to constrain subsequent actions and discourse, exerting even stronger influence on the system. Some researchers call these strong patterns “simple rules” that emerge from the system and subsequently influence it (Holladay, 2005). People in the system may experience these rules as norms, customs, cultural practices, or ideologies. These rules may be either explicit or unwritten. When the system is appropriately constrained, simple rules will emerge that move the system toward fitness and coherence and, therefore, toward sustainability. Individual participants--teachers and students--certainly have agency; an individual may not follow these emergent rules, and if enough follow alternative patterns to change the patterns, the dynamics across the whole system may shift so that the existing system is no longer sustainable. In that case, a new or different system may emerge. In complex human systems, we acknowledge that individuals have agency and, therefore, can take action either in concert with systemic patterns or in resistance to those patterns. When people pay attention to feedback, survey relevant options, test hypotheses, and integrate new concepts or principles into their existing knowledge, educators call it "learning." When they act on what they have learned, Eoyang and colleagues call it "adaptive action." Eoyang (2010) asserts that adaptive action--taking immediate action based on feedback, gathering relevant data about consequences, and then considering subsequent action--provides flexibility and adaptability not present in more traditional strategic planning schemes. Holladay & Quade (2010) argue that individuals who understand system dynamics can consider relevant information and take deliberate action as an agent within the system, sometimes in resistance to dominant patterns or rules. These actions can help reshape those system-wide patterns to better achieve particular goals and, potentially, to enhance the adaptability and sustainability of the system. Senge and colleagues (1994; 1999), Dixon (1999), and Dixon and Ross (1999) have called this "organizational learning." Educational researchers call it "critical action ...