![]() Essentially, this circular figure within the model illustrates how each individual university in the Australian Higher education sector interacts and operates within its environment. The circle on the left hand side of the figure represents the larger social ecosystem of WIL in HRM degrees with an individual uni- versity located in its centre. Figure 1 below, the model of the study, provides a diagrammatic depiction of the study of WIL in HRM within the nine uni- versities whom participated in this study. Each individual university exists within an environment of other Australian universities with both similar and different characteristics. This means that there are several open systems interacting with each other, all having a degree of influence over the development of WIL in HRM degrees in Australian universities. study viewed WIL in undergraduate HRM as embedded within the complex evolv- ing system (CES) of a university which is in turn part of a larger ecosystem. For example, "one individual agent may be a member of a team, and be influenced by patterns outside of the team inside the organization, by the patterns in his or her own family and community, even by political forces on a national or global level" 4:17. Also, systems are not limited to members within the system as members of other systems may be shared and out of view. According to Eoyang and Holladay 4, because relationships between agents are in constant flux, "a stable, permanent reality is impossible uncertainty becomes the rule" 4:16. After this pattern appears, it then feeds back into the individual agents encouraging those agents to adopt the pattern in future cycles. The arrow at the right shows how, over time, the interaction of the indi- vidual parts creates a coherent pattern. In Figure 1, the agents (people, groups, or ideas) are the circles at the bottom that interact with each other. The model is designed to capture, in both theory and practice, "the dynamics of human systems at all scales in ways that inform decision- making and action taking in complex and uncertain environments" 3:636. The Pattern Logic model also incorpo- rates foundational philosophies of perception and knowledge that are particular to the workings of human systems. Those patterns then influence later interactions of the agents" 4:15-16. In Eoyang and Hol- laday's work, a complex adaptive system "is a cluster of individual parts that interact with each other, and over time system-wide patterns appear. ![]() This provided the conceptual model for complex adaptive systems used in my research, and the Conditions for Self-organizing Systems model (described below) was used during data analysis as a retrospective analysis tool as a way to see and set conditions for patterns (see Figure 1). lthough there are many definitions and representations of complex adaptive systems 33,34 the Eoyang Pattern Logic model is represented as a process with a pattern-forming cycle 4. As the system reaches the edge of chaos point it needs to move through the funnel to the right hand side of figure 1 and explore the space of possibilities and view the environment as being full of. A supportive and positive culture between academics must be fostered so that uncertainty and change is embraced and a positive language space is cultured. ![]() As the university reaches a far-from-equilibrium point, it should be encouraged to explore the space of possibilities and adjacent possible, so as to enable the university to break through its traditional way of doing things. ![]() If connectivity and self-organiza- tion were to be encouraged throughout universities, it would assure that emergent properties and patterns would increase, and in turn, the university would co-evolve. Connectivity between stakeholders needs to improve so that the system can learn to co-evolve with its en- vironment rather than adapting to its environment. ![]() suggests that for universities to move to the edge of chaos where full po- tential can be realized, many conditions need to be fostered. ![]()
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