Some of the key characteristics underlying the notion of knowledge ecology may be deduced from the characteristics of (a) knowledge and (b) ecology. Although there is no common definition of the term knowledge, there is a wide agreement that knowledge is social, personal, flexible, dynamic, decentralized, ubiquitous, networked, and complex in nature (Chatti et al., 2007). An ecology is an open, complex adaptive system comprising elements that are dynamic and interdependent (Brown, 1999). Key characteristics of knowledge ecology include: complexity, adaptation, emergence, self-organization, openness, and decentralization.
Complexity and adaptation: Knowledge ecology is a good example of a complex adaptive system (Holland, 1995). In a complex adaptive system, the behavior of the whole is much more complex than the behavior of the parts. Knowledge ecology is complex in that it is diverse and made up of multiple interconnected elements and adaptive in that it has the capacity to change and learn from experience (Holland, 1995; Holland, 1998). Knowledge ecology is also a complex system comprising many interacting identities in which cause and effect relationships cannot be distinguished (Snowden, 2002). Knowledge ecology thus has a non-deterministic character; it can evolve in ways that we may not expect or predict.
Emergence and self-organization: Emergence is central to the theory of complex adaptive systems (Holland, 1998). Goldstein (1999) defines emergence as "the arising of novel and coherent structures, patterns and properties during the process of self- organization in complex systems". Emergent properties are irreducible. As Lewes (1875) puts it: "The emergent is unlike its components in so far as these are incommensurable, and it cannot be reduced to their sum or their difference". Holland (1998) argues that emergence must be the product of self-organization, not centralized control (cited in Ryan, 2007). Thus, as an example of a complex adaptive system, knowledge ecology holds emergent properties and includes self- organized entities. Knowledge ecology is co-constructed and maintained by individuals. It emerges naturally and is derived from the bottom-up networking of multiple personal knowledge networks. Knowledge ecology houses the learning that occurs in a bottom-up and emergent manner, rather than learning that functions within top-down and hierarchical structures under the control mechanisms of outside forces.
Openness and decentralization: As with complex systems, ecologies are open and their boundaries are difficult to be determined. And, knowledge is decentralized and ubiquitous in nature. Thus, openness and decentralization are central attributes in knowledge ecologies.
Source:
Chatti, M. A., Jarke, M. & Quix, C. (submitted). Connectivism: The Network Metaphor of Learning.
References:
Brown, J. S. (1999). Learning, Working & Playing in the Digital Age. AAHE Conference on Higher Education, Washington, D.C.
Chatti, M. A., Jarke, M. & Frosch-Wilke, D. (2007). The future of e-learning: a shift to knowledge networking and social software. International Journal of Knowledge and Learning, 3(4/5), 404-420.
Goldstein, J. (1999). Emergence as a Construct: History and Issues. Emergence: Complexity and Organization, 1(1), 49-72.
Holland, J. H. (1995). Hidden Order: How Adaptation Builds Complexity. MA: Addison-Wesley.
Holland, J. H. (1998). Emergence: From Chaos to Order. MA: Addison-Wesley.
Lewes, G. H. (1875). Problems of Life and Mind. Vol. 2. London: Kegan Paul, Trench, Turbner, & Co.
Ryan, A. J. (2007). Emergence is coupled to scope, not level: Research Articles. Complexity, 13(2), 67-77.
Snowden, D. J. (2002). Complex Acts of Knowing: Paradox and Descriptive Self-Awareness. European Conference on Knowledge Management, Dublin, Ireland.
