Rhizomatic learning - its a no brainer

I have just finished watching a video by Dave Cormier on Rhizomatic Learning which I have put in below for reference.

In the video Dave describes what is meant by rhizomatic learning, which builds on the rhizome idea of connections growing in all directions being only constrained by their local surroundings. There was something that instantly appealed to me about this because it reminded me dendrites. Dendrites are the small protrusions that normally extend from the cell body of neurons. They are said to form branch like structures such as that the term given to them collectively is a dendritic tree. Here is what one looks like (taken in around 1901):

But the comparison does not end there - dendrites (and the rest of the cell) are constrained only by the careful balance of chemicals in their surroundings and they are dynamic - connections can be strengthened and weakened or formed and lost altogether over time.  When I consider learning to reflect the very process that our brains appear to use to learn (dendritic changes are known to be critical in learning), the idea has a certain beauty to it.  Just to reflect a little more on this and see how far I can stretch the brain analogy, let's think about how dendrites do against the principle's laid out:
1. The best teaching prepares people for dealing with uncertainty - the brain loves uncertainty and change. We have clearly evolved to detect change an many ways. This is most clearly illustrated with our sensory systems which adapt to constant stimuli but respond vigorous to changing stimuli. We have found evidence in the brain of calculations involving weightings for bottom-up and top-down information where we cannot be certain.
2. The community can be the curriculum, learning where there is no answer - ok so at brain level we can probably have a debate about what the community would constitute but to me the logical community would be the 86 million neurons and the even larger number of glial cells. And again, of course, most learning takes place when there is no clear answer - as a infant we engage in a number of actions and yet do not necessarily comprehend them - connections in brain develop at a huge rate, only later to be pruned back to what we really need.
3. The rhizome is a a model for learning for uncertainty - dendrites can respond to uncertainty in the most remarkable ways - they are dynamic and responsive.  Indeed as infants, when the most connections between dendrites and neighbouring neurons are formed, everything we encounter is filled with uncertainty.
4. Rhizomatic learning works for the complex domain so this is a situation where there is uncertainty and there is a need to experiment and see what happens. As explained above dendrites can form connections of different strengths - these can be up or down regulated or removed altogether - they work well for modelling complex domains.
5. We need to make students responsible for their own learning - ok so this is perhaps where my analogy falls down a little but given the we know teaching about the the plasticity of the brain (the ability to shape and re-shape connections) increases effort beliefs, maybe it does not fall down that much.

Neuroscience analogies aside though, I find this approach quite convincing as an educator in theory but I would find it most unnerving as a student and hard to apply in practice as an educator.

With my educator hat on:

• I spend literally hours developing and revising learning outcomes, if I do not know the exact outcome of learning , this would all change.
• I would have to relinquish control of the curriculum and that scares me but I think it would also scare the accreditation organisation for our programme.
• I think students are increasingly taking a consumer approach to their learning (I do not agree with this) and they almost look for content to look for value for money. A rhizomatic approach could screw up our satisfaction metrics, and whilst on the note of metrics, if we stop measuring learning can we also stop using pointless proxy measures to measure teaching.
• I would worry that the lack of curriculum would create more work in the end - there is a better the devil you know sense here.
• If the community create the curriculum, I would need to be quite certain of a suitably diverse community of learners and in the context of my formal teaching that is not really the case.

With my student hat on:

• I like flexible approaches to learning now but as an undergrad or even during my MSc I definitely did not like them. I want to know exactly what I am aiming for and what I need to do to achieve this.
• I also think that inexperienced or nervous learners would not be confident enough to contribute and those lacking skills around communication (digital or otherwise) could also be marginalised.

Based on these first thoughts and concerns, I cannot imagine implementing this on a standard programme for undergraduates but I can imagine the approach working for professional development where learners may be spread out, with different experiences and that the learning will flow from those individuals networked together. I could also imagine it working on optional courses designed to support more skills based learning. At the moment I am playing around with ideas on teaching digital citizenship across the university to obtain a formal qualification, assessed by portfolio where students would work together. One of the ideas I was playing with today was looking at the topic of online security and seeing how that could take a variety of different approaches depending on the students involved in the discussions.

So in summary, the idea of rhizomatic learning has a certain natural beauty to it and it definitely appeals to the neuroscientist in mean but I would be reluctant to introduce it to learners at the start of their HEI journey, instead seeing this as something extra-curricular or more suited to vocational/professional development contexts.