This page was originally authored by Hermia Ting (2008). Revised by Rhonda Kalyn (2009)
Complexity theory, also known as Systems Theory, describes life as an environment that is always changing. Variables within a system can change and affect outcomes in unpredictable ways. Change does not follow predictable linear pathways. Instead it branches out in many directions that form complex non-linear pathways. Traditional education is designed for linear pathways with predictable outcomes. Education needs to evolve to adapt to complex non-linear pathways to help learners to adopt to change as it happens. Internet hyperlinking allows readers to branch of into different directions and provides a good example of complexity that is similar to the human thought process.
What is Complexity Theory?
Complexity Theory describes and models complex, non-linear systems, and “develop[s] a unified view of life by integrating life’s biological, cognitive and social dimension” (Capra, 2005, p. 33); that is, understanding the big picture not by looking at the parts, but the interaction between them. A basic premise of Complexity Theory is that non-linear systems are unpredictable, because the interacting agents often acquire collective properties and thus a system becomes greater than the sum of its parts (Phelps, Hase & Ellis, 2005, p. 72).
Complexity in Education
In relation to education, Systems Thinking offers the perspective that learning is based on “non-linearity of thought and on variation as a source and outcome of thinking” (Phelps et al., 2005, p. 73). In the complexivist view then, “learning is occasioned, not caused” (2005, p. 74). Curricula that are pre-defined and pre-structured work against emergence and thus limit learning by laying down tracks for a prescribed route to target knowledge. Thus complexity as a learning theory requires open-ended learning and in doing so provides for universal design for learning—where learning is accessible to all types of learners.
Education needs to evolve to address complexity by helping learners to adapt to constant change. Learners should be instructed on how to apply knowledge to a variety of contexts to help them to acquire the ability to adapt knowledge to changing situations. Education needs to help learners to construct their own learning goals, receive feedback and reflect on their progress. Education should become a continuous process where learners continuously thrive to improve performance and generate new knowledge.
Anderson (2004) compares the Internet’s innate capacity for hyperlinking to the way information is stored “in mental schema and to the subsequent development of mental structures”. In many ways, it is also analogous to the way humans think, in a divergent, non-linear fashion. The opposite would be linear thinking, wherein the individual’s thoughts progress in strict sequential order, just as information is presented in textbooks. Given that human cognition does not function in this sequential way, this is why students ultimately find graphic organizers such as concept maps so useful and are taught early on to reorganize the information they collect from textbooks. Each topic branches off into many other levels of ideas and relationships, and many cross-links exist across the levels between all topics and ideas.
In using the Web and its hyper-linking capabilities, students can form individualized learning paths, a notion that fits well within the Complexivist instructional design framework, one that emphasizes the importance of individual discovery and knowledge construction.
- In Wikis, such as Wikipedia, where multiple links are embedded in each entry. Users can then follow the links to other topics that they want to read about.
- Tagging, as in YouTube and Blogger. Videos and blogs are labeled, or ‘tagged’ under certain keywords, so that when users click on the keywords, related videos and blogs under the same or similar labels come up in the search.
- Online interactive stories (similar to the Choose-Your-Own-Adventure series), such as Gav & Peloso’s Interactive Story and SuperStory. The user gets to choose how the story goes, and when the possibilities have been exhausted, the user can also add their own choices/endings to the story.
Anderson, T. (2004). Chapter 2: Toward a theory of online learning theory and practice of online learning (Anderson, T., & Elloumi, F., Eds.) (33-59). Retrieved November 20, 2007, from http://cde.athabascau.ca/online_book/ch2.html
Bleuel, D., & Peloso, C. (2002, July 11). Gav and Peloso's interactive story. Retrieved February 25, 2008, from http://www.nuc.berkeley.edu/~gav/wayfarence/.
Capra, F. (2005). Complexity and life. Theory, Culture & Society, 22(5), 33-44.
Fraser, S. W., & Greenhalgh, T. (2001). Coping with complexity: Educating for capability. BMJ (Clinical Research Ed.), 323(7316), 799-803
Furnish, T. (2008). Superstory. Retrieved February 28, 2008, from http://www.hungrysoftware.com/#/online/story/.
Phelps, R., Hase, S., & Ellis, A. (2005). Competency, capability, complexity and computers. British Journal of Educational Technology, 36(1), 67-84.
University of Alberta. Complexity and education. Retrieved February 25, 2008, from http://www.complexityandeducation.ualberta.ca/glossary.htm.
Complexity and Education Homepage, has lengthy list of links to other Complexity Theory websites and Complicity: An International Journal of Complexity and Education
Complexity & Artificial Life Research Concept for Self-Organizing Systems, multitude of links to applications of Complexity Theory in a variety of academic fields. Some dead links.
Chaos/Complexity Theory in Second Language Acquisition, paper on the application of Complexity Theory to learning a second language