One cannot take the rhizome as metaphor too literally, then. For instance, some have complained that rhizomes are a multiplication of the same plant over and over, and they find little appeal in this kind of mindless repetition, especially when applied to learning. These people are taking the metaphor too literally. The rhizome of Deleuze and Guattari is not a homogeneous botanical system; rather, heterogeneity is one of the six characteristics of their rhizome. As they say, "Any point of a rhizome can be connected to anything other, and must be" (7). Homogeneity, then, is not one of the points at which Deleuze and Guattari's compare rhizomes to reality. A metaphor invites one to explore all connections between the two things compared, but not all connections will prove useful or enlightening. Love is a rose, but not in all aspects.
If I understand the rhizome correctly, then, it is a metaphor of reality similar to the Enlightenment metaphor of the clock. Just as Galileo, Newton, and Descartes gave us the image of a clock to help us envision how the way too big Universe works, Deleuze and Guattari give us the image of a rhizome to help us make the shift from a mechanistic universe to an organic universe and to the math, science, and technology that make sense of that much expanded, different universe. Both the clock and the rhizome, then, are conceptual metaphors or frames, as Lakoff calls them, that describe reality in terms of either a piece of machinery or a plant; however, reality is neither a clock nor a rhizome. Still, I want to say that Deleuze and Guattari's marvelously twisted rhizomatic prose is about as close as one can get to the quantum, relativistic universe without way more math than I have. The rhizome is a wonderful metaphor in almost natural language for the complex systems that physics has almost completely accepted but still largely describes in mathematical terms—terms that I don't understand.
This may be one of the most important contributions that the rhizome of Deleuze and Guattari makes to connectivism: it emphasizes the shift from a mechanistic, reductionist reality to an organic, relativistic, quantum reality and it captures in natural language something like this new reality. In his definitions of connectivism, George Siemens talks about complexity and chaos theories, but his language does not capture complexity and chaos the way Deleuze and Guattari do. Of course, Siemens has a different audience and different objectives than did Deleuze and Guattari. Still, there are things you can come to understand only by jumping in over your head, and as Mark Twain wisely observed, "If you a hold a cat by the tail you learn things that you cannot learn any other way." Reading Deleuze and Guattari is like holding two cats by the tail. Most people are willing to forgo that joy, but I have found it an endless source of enlightenment.
My friend Dave Cormier makes a most important contribution here by connecting rhizomatic thinking to Dave Snowden's Cynefin framework, which posits five contexts for thinking and decision making, particularly in organizations: simple, complicated, complex, chaotic, and disorder. In his post Seeing rhizomatic learning and MOOCs through the lens of the Cynefin framework, Cormier says that both MOOCs and rhizomatic thinking and teaching match best with the complex domain. As Cormier says:
That description of how to act in a MOOC sounds just about right as a description of rhizomatic learning. The knowledge lives in the community, you engage with it by probing into the community, sensing the response and then adjust. Just like the rhizome. It is a learning approach that is full of uncertainty… not least for the educator. But its one that allows for the development of the literacies that will allow us to sharpen our ability to participate in complex decision making. Dealing with the uncertainty is what the learning is all about.This, then, is a second important contribution of rhizomatic learning to connectivism: a focus on complexity. Rhizomatic thinking enriches the connectivist conversation, and it has allowed me to say things that I could not say otherwise. Deleuze and Guattari have given me language to speak of complexity.
The rhizome also helps me understand why I share Cormier's discomfort with learning in the simple domain. Cormier says:
I think most of what i criticize or, at least, what concerns me about education is the movement between the complicated and simple domains. Our bureaucracies encourage simple domain learning, things that can be tracked and analyzed. Research goals seem to attempt to take things from complicated domains and shove them down into the simple one. Our world is increasingly one where complex decisions need to be made… and thats the kind of education i’m interested in being involved in.Most of education seems calculated to force all knowledge into the simple domain, with one source for truth and one answer on the test. Sophisticated instructors and some graduate programs allow for the complicated domain where "the relationship between cause and effect requires analysis or some other form of investigation and/or the application of expert knowledge" (Wikipedia). Traditional education, by and large, eschews the complex domain, where "the relationship between cause and effect can only be perceived in retrospect, but not in advance." Our traditional testing regimes demand clear answers and outcomes, and complexity refuses to play that game. Thus, our curricula try to make reality as simple as possible throughout most of K-16 education, only grudgingly admitting the complicated and almost totally denying the complex. The problem here is that most of reality is complex or chaotic. As near as I can tell, the truly simple is extremely rare in Reality and the merely complicated is almost as rare. Everything else is complex and chaotic (about 99.999% by my calculations). If 99% of education is forced into the simple and complicated domains and 99% of life is complex/chaotic, then it appears that we have a mismatch between what we are teaching and what we need to learn. Rhizomatic learning can help address this mismatch.