What if? Could it be that…? It is impossible, but still: why not try to…? These have been some of my starting questions throughout the exploratory processes of this series concerned with what a pedagogy of abundance might look like. While suggesting that rhizomatic learning could be such a pedagogy of abundance, I have taken on the challenge put forward by Martin Weller in his article “A pedagogy of abundance” (2011):
The issue for educators is twofold I would suggest: firstly how can they best take advantage of abundance in their own teaching practice, and secondly how do they best equip learners to make use of it? It is the second challenge that is perhaps the most significant. Exploring pedagogies of abundance will be essential for educators to meet the challenge and equip their learners with the skills they need in an age of digital abundance. (Weller 2011:232-233)
My exploration has intendedly been processes of experimentation and of developing knowledge about rhizomatic learning as a pedagogy, whereas I have not been that interested in discussing the way Dave Cormier has adopted, adapted and rewritten the theories of Deleuze and Guattari in his vision of rhizomatic learning. Others have done that. But the exploratory processes and the ongoing questioning also mean that I have been presenting views, assumptions and perspectives on rhizomatic learning as a pedagogy of abundance – views, assumptions and perspectives that are up for evaluation throughout this series.
It might be provoking that my voice hasn’t been a firm, authoritative academic voice, present at once, when it comes to rhizomatic learning in this series. That is what we are used to, and maybe implicitly expect in blogposts, too, even though the blog as genre is a genre that foregrounds processuality and ongoing reflection – a space of construction, experimentation and improvement. But I have rephrased views earlier on in this series, I have tried out how far similarities between networked learning and rhizomatic learning might vouch for rhizomatic learning being a variation of networked learning, and I have focused on communities of practice, serendipity and bricolage as important aspects of ‘community’ and ‘networking’ in rhizomatic learning. I’m going to evaluate and rephrase these aspects that I have attributed to rhizomatic learning once more, while stating that rhizomatic learning is not a version of networked learning.
Exploration is exploring an area over time for new possibilities, experimenting while building up a knowledge base, and sometimes acquiring new knowledge through serendipity or through searching for interesting problems, (Darsø 2001:76). My exploratory approach in this series has been about asking curious questions, trying out hypotheses and making mistakes, then starting out somewhere else and eventually having to reconsider my previous analysis and viewpoints and assumptions once again. Much along the same line that Michelle Knobel and Judy Kalman point out teachers need to go:
Creativity and change require an ability to brave the unknown and a willingness to try, rethink and redo…While it is widely recognized that failure is an integral part of learning, it is often not welcome or ignored in professional development context or classrooms. Teachers have to be at ease with mistakes and taking risks when trying to learn something new; they’re also well served by appreciating what making mistakes and trying to correct them means for their students. Placing teachers in the learners’ seat is as much a part of their professional development as is theorizing education, critiquing policy, or analyzing practices. (Knobel and Kalman 2016:15)
Knobel and Kalman write about teachers’ professional development but to me this is also very much becoming the practical precondition for taking on Weller’s claim and exploring pedagogies of abundance. And when it comes to discussing pedagogies and necessary skills in an era of knowledge abundance, this is also what the researchers introduced in this series all recommend: rethink, reexamine, reimagine, recast, evaluate, update, redo the existing pedagogies and our models of learning and teaching to suit a world of knowledge abundance embracing digital media and new social and cultural practices.
Two pedagogies dealing with community, networks, complexity
The pedagogies and learning theories that are up for consideration as pedagogies and learning approaches of abundance all focus on collaborative, networked and distributed learning, and as social and situated pedagogies and learning theories they foster and build on self-directed learning and participatory culture. That counts for rhizomatic learning and networked learning, too. So there are a great many similarities between rhizomatic learning and networked learning, and in this series I wanted to challenge my understanding of what rhizomatic learning is as a pedagogy by comparing it to networked learning, taking off from a broader conception of open networked learning as it is presented by Kop, Fournier and Mak (2011)(see Part 1 of this series).
This broader and descriptive conception unfolds a perspective that includes connectivism as networked learning and shows an understanding of networked learning that is not compatible with the dominating understanding of networked learning as a theory, pedagogy and practices according to Ryberg, Buus and Georgsen who distinguish between connectivism and networked learning (Ryberg, Buus and Georgsen 2012:44-45). I introduced this dominating understanding of networked learning in Part 4 of this series, and it places rhizomatic learning – where each learner brings his/her context and has his/her own needs as a starting point – as a parallel to connectivism as a pedagogy and approach to learning that is not included in networked learning, and so rhizomatic learning is not a variation of (open) networked learning, although I claimed that in Part 1 and Part 4 of this series.
Despite the fact that rhizomatic learning and networked learning are having keywords, concepts and educational values in common, they are not the same and must be seen as two distinct theories with pedagogies and practices that in many ways respond similarly to societal developments and changes in education, teaching and learning. In his video “Embracing Uncertainty – Rhizomatic Learning” (2012) Dave Cormier in fact comments on many people’s assumptions that rhizomatic learning is networked learning and agrees to some degree that they look the same, but he also maintains that they are not. And I agree with him, but my comparison with networked learning – starting with my asking “What if?”, “Could it be that…?” – has made visible where some of the challenges might occur when choosing rhizomatic learning as a pedagogy of abundance in a campus-based course integrating online-learning. The theory, pedagogy and practice of rhizomatic learning certainly resisted being forced into the pedagogical framework of networked learning. This calls for a few precisions, definitions and comments in order to see rhizomatic learning and networked learning as two distinct theories, pedagogies and practices that in each their way are responding to an emerging new model of education (see Part 1 of this series) and a shift to an era of knowledge abundance.
Networks and community are equally important to rhizomatic learning and networked learning, and in my presentation of Dave Cormier’s campus-based course integrating online-learning drawing on his e-book “Making the community the curriculum” (2016) in Part 2, I saw a community of practice as the framework that can give direction to the learning processes initiated by the rhizome as a metaphor for the learning process. I listened to Dave Cormier presenting his idea of the rhizome, and in the embedded video “A talk on Rhizomatic Learning for ETMOOC” (2013) I heard him point to a community of practice as the kind of community he works with. I listened many times and I quoted what I heard. But I must have been wrong. Frances Bell and Jenny Mackness have kindly told me that Dave Cormier is not promoting a community of practice in his theory or pedagogy but just a community, and it is true that Cormier usually doesn’t define what he means by community in his writings or in his talks on video (Bell, Mackness & Funes 2016). So I have to admit that most places where I have written ‘communities of practice’ in relation to rhizomatic learning in this series it should have said ‘community’ in order to be true to Cormier’s way of conceiving rhizomatic learning. Nevertheless, the descriptions of the campus-based course integrating online-learning and the way the community is integrated into the learning processes introduced in the e-book still look very much like the practices of a community of practice to me.
A statement that definitely differentiates rhizomatic learning from networked learning is the comment I quoted in Part 2 of this series: “First rule of community learning is to give up control…” (A talk on Rhizomatic Learning for ETMOOC (2013) – embedded in Making the community the curriculum (2016)). It is a comment that in many ways is provokingly in opposition to the pedagogical values of networked learning as they are introduced in Part 4 of this series. The resistance to conformity that is inherent in rhizomatic learning as a learning approach became visible when I tried to fit the four cornerstones of rhizomatic learning into the design and processuality of a facilitated learning process much more consistent with networked learning (see Part 2 of this series). When dealing with education the rhizomatic way, students have to develop an understanding of the learning process they are going through while they are going through it, Dave Cormier says:
- Students have to understand what they are looking for when joining the course.
- Students have to take it upon themselves to engage and to continue to grow.
- Students have to choose and to make a syllabus for themselves through connecting, responding and collaborating.
- Students have to understand what it is to learn and what it is to know in a subject matter or a discipline and to be able to make decisions about how to create their own learning within that process.
So when I asked for a learning process that is facilitating, modelling and scaffolding students to get to know and understand what it is to learn, what it is to know and negotiate meaning, and what counts as knowledge in a discipline or a subject matter, I was in accordance with networked learning, whereas Dave Cormier clearly promotes self-directed learning right from the beginning of the learning process.
Networks play an equally important part of the understanding of learning in rhizomatic learning and networked learning, but as social and distributed theories they differ in their understanding of what a network is. The rhizome is a special kind of network that is non-linear, multi-perspective, heterogeneous and growing in any direction. But in part 1 I already added two concepts, serendipity and bricolage, to my description of the rhizome, knowing that none of them are part of Deleuze and Guattari’s writing. I did it to emphasize the chances of discovering new people, unknown resources, innovating ideas and knowledge through networking and thus describe the rhizome as a network that spreads via experimentation in a context, as Dave Cormier has put it in his talk “Embracing Uncertainty – Rhizomatic learning” (2012). This way the rhizome as a network combines the processes of networking with connecting knowledge in ever changing constellations, in assemblages with no entry point and no exit point. This exploratory aspect of networking is crucial to understanding the rhizome as the motor in rhizomatic learning when it comes to creating new, accurate and up-to-date knowledge. Apparently it is a self-perpetuating process once it has started but a process that may at the same time underexpose and overexpose the node in the processes of connecting ideas, people, resources and knowledge. It might almost seem more important to connect than what and who you connect with or where, when, how and why you connect.
When I called for a kind of balance between networks and community in Part 4 of this series, it turned out to be one of the aspects where rhizomatic learning resists my comparison with networked learning:
“But there needs to be some kind of balance to see rhizomatic learning as a variation of networked learning: a balance between the messy and sometime chaotic self-directed learning processes where individuals form and determine their own routes and learning through connecting to people and resources, and the open and mutual engagement in a learning community based on participatory culture and knowledge construction.“
After all, the balance between networks and community I advocate here is more a balance of networked learning – assuming that the community is existing prior to the learning process – than that of rhizomatic learning, as rhizomatic learning leaves room for smaller groups or individuals to break away. The community is not necessarily a stable group but an emergent grouping formed on the basis of interest and a result of ongoing networking in rhizomatic learning.
Networked learning makes room for several types of network theories within the framework of the theory, but social network analysis (SNA) might be at the centre as with Maarten de Laat when he defines “learning as a social network relationship” in Part 4 of this series (De Laat 2012:27; Haythornthwaite & De Laat 2010). With its focus on strong and weak ties social network analysis is integrated in De Laat’s definition of networked learning as a perspective: “…that aims to understand social learning processes by asking how people develop and maintain a ‘web’ of social relations used for learning and development…” (De Laat 2012:26). In Part 4 I also focused on personal learning networks as a road to collaboration and participation in networked learning, but I think it is important to add the distinctions Haythornthwaite and De Laat make when individual’s personal learning networks are integrated in a learning network as it is intended seen from a networked learning perspective. They add the two social network terms ‘ego-centric networks’ and ‘whole networks’. The ego-centric network is a personal network seen from the individual’s point of view and has the learner at the centre of the network as presented in part 4, and the term was also used by Rajagopal, Brinke, Van Bruggen and Sloep as a synonym for the personal learning network in their article presented in Part 4:
Considering the network from the learner’s perspective provides a view of who they learn from (beyond peers), but also where conflicts in understanding may come from (e.g., unvetted online resources). It also reveals the conflicting – or complementary – demands on individuals… (Haythornthwaite and De Laat 2010:189)
On the other hand, the whole network view opens up to insights into how information and learning is occurring across a set of people, and this view is what we usually associate with social network analysis (SNA):
A whole network perspective provides a view of the entire structure, and thus of the ‘character’ of the network to which an individual belongs. Is the network collaborative: e.g., do most or all people freely share information, engage in discussion, or help search for information? Is the network divided into cliques, and if so on what basis (information hoarding? different interests? separate tasks?). Perhaps the most important contribution to SNA is this whole network view that takes the results of pair-wise connections to describe what holds the network together. As we begin to use SNA to examine and reveal learning networks, we are just at the beginning of understanding how and what makes for the kind of network outcomes we desire. (Haythornthwaite & De Laat 2010:189)
Social network analysis is not only a matter for educators but also for students to become aware of, and so both the skills, the competencies and the understanding of how to build and maintain ego-centric networks (personal learning networks) and how to use the social network analysis perspective must be part of what students know about networks and networking seen from a networked learning perspective. So here networked learning is much more specific than rhizomatic learning about what networks, networking literacies and learning literacies are and what must be integrated in a pedagogy of abundance. The way networks are applied in practice in rhizomatic learning and networked learning differ due to the differences in the conception of networks in the two learning theories. And still, I would like serendipity, bricolage and a bit of messiness to become part of social networking in networked learning in order to accentuate the necessity for diversity, inquiry and exploration if learning is going to happen and new knowledge to evolve.
I have tried to keep my own exploration open and running for as long as possible. My comparison between rhizomatic learning and networked learning has tended to join the two learning theories and pedagogies together to an extend that has more or less merged the two into one and the same in Part 4 of this series, until my exploration collapsed. It happened when I made the impossible attempt to merge in the design principles of rhizomatic learning with the principles and goals of networked learning. It is a paragraph of absurd prose.
And although I’m now ripping the bonds apart, there is yet another keyword that rhizomatic learning and networked learning have in common: complexity. Dealing with change, uncertainty and complexity are equally concerns and backdrops for the two learning theories. In this post-modern or late modern context complexity can be seen as a trend in education that is closely connected to seeing fluidity, contingency and emergence as characteristics of the post-modern or late modern which also changes the understanding of what counts as knowledge: knowledge is dynamic, continuously changing and emergent. This understanding of knowledge is based on complexity theory that stresses non-linearity, unpredictability and disorder as normal conditions, and as a consequence knowledge can be characterized as 1) indeterminate, 2) emergent and self-organizing, 3) both-and, 4) dominated by uncertainty, 5) emphasizing potentiality, and 6) working in a participatory universe (Darsø 2001:91).
I presented Maarten de Laat’s call for ‘New learning’ in Part 4:
and in her talk “New Metaphors for Networked Learning” (2016) Caroline Haythornthwaite also advocates for opening up to complexity at many levels of education, stating that “Structure giving way to complexity”. She sees complexity as one of a number of trends that are at work simultaneously and have effects on learning, information dissemination and knowledge production (Haythormthwaite 2015:294).
Both De Laat and Haythornthwaithe respond to the challenges in Martin Weller’s educational model of abundance from a networked learning perspective and embrace change and complexity in both learning and education to meet these challenges. In many ways Caroline Haythornthwaite is complementary to Martin Weller’s model when she puts forward her view on the impact of social and technical changes on emergent models of knowledge and practice:
The dynamic and emergent nature of our media and learning spaces reformulates questions away from what is the best structure, system, or set of facts to address a problem to how to plan for complexity, be prepared for emergent factors, and continue to evolve and use a knowledge base. This changes the orientation from: closed systems and communities to open systems and crowds; information retrieval to contribution; individual – to – social learning; individual – to – community knowledge-building (Scardamalia and Bereiter, 2006); authority-defined knowledge and practice – to – peer knowledge and practice; following a class syllabus and being in a class to defining the content of the class and what it means to be in a class (Paulin & Haythornthwaite, in press)./This is not a call for a clean sweep of past questions and practices. These have worked well for many years and continue to be important ways of learning and knowledge building. But, like the complexity brought about by the interplay of contemporary new media trends, learning practices also have become more complex. (Haythornthwaite 2015:302)
Likewise Dave Cormier has sharpened his perspective on complexity in his recent talk “The rhizomatic lense – seeing learning from the perspective of abundance” (2015). When discussing how and why rhizomatic learning is supporting complexity in a world of abundance Cormier positions rhizomatic learning as an ‘answer’ to my inquiry about what a pedagogy of abundance might look like:
And still, despite the resemblances and the parallels in keywords, concepts and educational values, the question of what counts as knowledge is exactly where it becomes evident to me, that rhizomatic learning is not a variation of networked learning. So it is time to break off the experiment of comparison and introduce a change of perspective in my exploration while asking: how is rhizomatic learning working on reinstalling the complex domain in disciplines and subject matters and how is complexity linked to the aim of being a pedagogy that promotes and fosters new, accurate and up-to-date knowledge and innovation in a world of abundance. This is also a matter of what counts as knowledge in rhizomatic learning.
Knowledge and knowledge management in an era of knowledge abundance
In an era of knowledge abundance and knowledge being connected through digital media, knowledge management becomes an important aspect of learning and education. How to find, handle, interpret, validate, negotiate, create, improve, apply and share information and knowledge through connecting , communication and collaboration with online resources, experts, peers, networks, communities and communities of practice is essential in the processes of knowledge creation, I wrote in Part 1 of this series. And in his e-book “Teaching in a Digital Age” (2015) Tony Bates adds that knowledge management is perhaps the most overarching skill needed in the 21st century, as “Knowledge is not only rapidly changing with new research, new developments, and rapid dissemination of ideas and practices over the Internet, but the sources of information are increasing, with a great deal of variability in the reliability or validity of information.” (Bates 2015:19). And this is a double challenge to any pedagogy of abundance, I would say. But there are different views of what constitutes knowledge, how knowledge is acquired, and how knowledge is validated depending on the domain, the discipline or the subject matter in question. So Bates agrees with the view on knowledge as dynamic, expanding and constantly changing which has been introduced by Maarten De Laat, Caroline Haythornthwaite and Dave Cormier. But Bates resists the idea advocated by among others Dave Cormier that the nature of knowledge has undergone radical changes (Bates 2015:62).
As a backdrop for understanding what constitutes knowledge, how knowledge is acquired, and how knowledge is validated in rhizomatic learning, I’ll dwell on Tony Bates’ arguments about knowledge and academic knowledge in a digital age. While discussing academic versus applied knowledge in his book, Bates comments: “The difficulty I have with the broad generalisations about the changing nature of knowledge is that there have always been different kinds of knowledge…Thus while beliefs about what constitutes ‘important’ knowledge may be changing, this does not mean that the nature of academic knowledge is changing.” (Bates 2015:62). And Bates develops his arguments:
I agree that academic knowledge is different from everyday knowledge, but I challenge the view that academic knowledge is ‘pure’, not applied. It is too narrow a definition, because it thus excludes all the professional schools and disciplines, such as engineering, medicine, law, business, education that ‘apply’ academic knowledge. These are just as accepted and ‘valued’ parts of universities and colleges as the ‘pure’ disciplines of humanities and science…(Bates 2015:62-63)
These arguments are also met within the views on new production of knowledge by Gibbons, Limoges, Nowotny et al as they promote two modes of knowledge production: Mode 1 and Mode 2. Mode 1 is focused within a particular discipline, produces knowledge in the absence of interested parties (autonomy), is an individual matter with criteria of one particular discipline (peer reviewed publications, peers and experts as gatekeepers in relation to relevant problems, ideas and research techniques in the discipline, making quality and control two sides of the same coin while establishing an understanding of what good or ‘correct’ research is inside that particular discipline). Mode 1 is associated with ‘traditional’ research in universities and higher education, but it is also an ideal of knowledge production that is already taught in K-12 schools.
Mode 2 is focused on application in practice. Mode 2 knowledge production is set in a web of co-producers coming from different disciplines, domains and contexts, and Mode 2 is centered on the usefulness for the involved parties and for the society in general, so heterogenous groups of professionals, practitioners and experts collaborate on problems defined in a specific but complex context of application and people. This makes Mode 2 a collective phenomenon with a wider set of criteria that is not grounded in a normative understanding of what good or ‘correct’ research is, but has to be evaluated from several parameters of quality due to the heterogenous group of people involved and their different norms of quality. So Mode 2 is transdisciplinary and heterogenous. Mode 2 knowledge production is taking place not only at universities and colleges but also in contexts like professions, businesses, research centres, libraries, museums, trades and ministries (Darsø 2001:126-127; Hobel, Nielsen, Thomsen and Zeuner 2015:14-16).
As in Tony Bates’ discussion of academic versus applied knowledge, Mode 1 and Mode 2 are to be seen as modes of knowledge production supplementing each other. Mode 1 has not become obsolete, and it is still needed and has its role to play in knowledge production in an era of knowledge abundance. Mode 2 knowledge is to be considered just as valid as Mode 1 knowledge. And the two of them are interdependent on many occasions. The production of Mode 1 knowledge is obviously associated with academic knowledge which is a specific kind of knowledge according to Tony Bates:
“In summary, academic knowledge is a second order form of knowledge that seeks abstractions and generalization based on reasoning and evidence.
Fundamental components of academic knowledge are:
- reproduction, and
Transparency means that the source can be traced and verified. Codification means that the knowledge can be consistently represented in some form (words, symbols, videos) that enables interpretation by someone other than the originator. Knowledge can be reproduced or have multiple copies. Lastly knowledge must be in a form such that it can be communicated and challenged by others.” (Bates 2015:61)
When it comes to academic knowledge, Bates argues that although some aspects of knowledge do change in a digital age where knowledge is dynamic, expanding and ever changing as quoted earlier, academic knowledge does not and should not change a lot with regards to its values and goals. But Bates has his eyes on the necessity for the students of today to learn not only content but also how it can be applied and used and to develop the skills that are needed to go on learning (Bates 2015:61). Knowledge involves, Bates says, “…two strongly inter-linked but different components: content and skills. Content includes facts, ideas, principles, evidence and descriptions of processes and procedures.” (Bates 2015:18), while skills are consisting of the skills that are required in a knowledge-based society – also known as 21st century skills and presented in the model of 21st century learning in Part 3 of this series. To Bates the point is that the development of skills should be given the same attention as content acquisition so that learners have both the knowledge and the skills to handle and succeed in an era of knowledge abundance (Bates 2015:19). And as mentioned earlier: knowledge management is the most important skill of them all.
So Bates wants to develop the conception of academic knowledge, but he doesn’t see it as redundant or as a kind of knowledge that can be replaced by self-directed learning and networking (Bates 2015:66). Here Bates’ view almost echoes the view on past and emergent models of knowledge and practice presented by Caroline Haythornthwaithe earlier. Mode 1 knowledge has to go hand in hand with Mode 2 knowledge, and likewise learning has to be a combination of content, skills and competencies, and attitudes. At least this is how I read Tony Bates, and that is the reason why “…it is not sufficient just to teach academic content (applied or not). It is equally important also to enable students to develop the ability to know how to find, analyse, organise and apply information/content within their professional and personal activities, to take responsibility for their own learning, and to be flexible and adaptable in developing new knowledge and skills. All this is needed because of the explosion in the quantity of knowledge in any professional field that makes it impossible to memorise or even be aware of all the developments that are happening in the field, and the need to keep up-to-date within the field after graduating.” (Bates 2015:63).
What counts as knowledge in rhizomatic learning?
What counts as knowledge in rhizomatic learning? How is rhizomatic learning working on reinstalling the complex domain in disciplines and subject matters, and does it make innovation happen? Looking at rhizomatic learning as a model for knowledge production suited for an era of ever changing knowledge, knowledge management becomes a core theme closely connected to the question of how we know what we know. And while Tony Bates equally emphasizes Mode 1 and Mode 2 knowledge as important forms of knowledge in an era of knowledge abundance, supplementing each other, Dave Cormier focuses on Mode 2 knowledge and knowledge production as a collective phenomenon while he is in alignment with the view of knowledge introduced in Martin Weller’s educational model of abundance (see Part 1 of this series):
- A change to a more participatory, socially constructed view of knowledge is needed to suit a demand-pull model of education.
- New technologies are the basis in realizing this new conception of knowledge as networked and socially constructed. (Weller 2011:228)
In his much cited article “Rhizomatic Education: Community as Curriculum” (2008) Dave Cormier supports this view due to its promotion of new technology, web 2.0 and participatory culture:
The existing educational model with its expert-centered pedagogical planning and publishing cycle is too static and prescribed to accommodate the kind of fluid, transitory conception of knowledge that is necessary to understand the simplest of Web-based concepts. The ephemeral nature of the Web and the rate at which cutting-edge knowledge about it and on it becomes obsolete disrupts the painstaking process by which knowledge has traditionally been codified. Traditional curricular domains are based on long accepted knowledge, and the “experts” in those domains are easily identified by comparing their assertions with the canon of accepted thought (Banks 1993);…In less-traditional curricular domains then, knowledge creators are not accurately epitomized as traditional, formal, verified experts; rather, knowledge in these areas is created by a broad collection of knowers sharing in the construction and ongoing evolution of a given field. Knowledge becomes a negotiation (Farrell 2001). (Cormier 2008)
Tony Bates discussion of academic knowledge, Mode 1 and Mode 2 knowledge echoes in Cormier’s writing, and while supporting Weller’s claim for a changing view on knowledge, Cormier especially opposes the rules of transparency, codification and communicability as aspects of reliability and validity of information and knowledge in traditional academic knowledge management:
New communication technologies and the speeds at which they allow the dissemination of information and the conversion of information to knowledge have forced us to reexamine what constitutes knowledge; moreover, it has encouraged us to take a critical look at where it can be found and how it can be validated. The explosion of freely available sources of information has helped drive rapid expansion in the accessibility of the canon and in the range of knowledge available to learners. (Cormier 2008)
Thus the foundations upon which we are working are changing as well as the speed at which new information must be integrated into those foundations. The traditional method of expert translation of information to knowledge requires time: time for expertise to be brought to bear on new information, time for peer review and validation. In the current climate, however, the delay could make the knowledge itself outdated by the time it is verified (Evans and Hayes 2005; Meile 2005)…Information is coming too fast for our traditional methods of expert verification to adapt. (Cormier 2008)
In favour of Mode 2 knowledge production Dave Cormier also goes along with a change to a more participatory and socially constructed view of knowledge: “In particular, social learning practices are allowing for a more discursive rhizomatic approach to knowledge discovery. Social learning is the practice of working in groups, not only to explore an established canon but also to negotiate what qualifies as knowledge.” (Cormier 2008). Here Cormier proposes his view of knowledge: knowledge is dynamic, emergent and ever changing – a view that is grounded in the rhizome as a more flexible conception of knowledge for the digital age. So in the theoretical arguments framing rhizomatic learning as a pedagogy of abundance, the rhizome is both 1) a conception of knowledge (what knowledge is), 2) a specific kind of network (what it means to know), and 3) a metaphor for learning in a specific context (what it means to learn). And so, as a multi-perspective metaphor, the rhizome cristallizes as a metaphor for “coping with the loss of a canon against which to compare, judge, and value knowledge.” (Cormier 2008). Cormiers answer to this condition of uncertainty is to focus on complex problems and collaborative problem-solving that match the complexity and uncertainty of rapidly changing knowledge and the abundance of ideas, resources, people and practices online.
Through the solving of complex problems that call for networking and collaborative interaction while experimenting, developing and co-creating new, accurate and up-to-date knowledge, Cormier challenges authoritarian and hierarchical ways of thinking and claims to replace the canon and the curriculum of a discipline or subject matter with interpretations, negotiations, peer-defined knowledge and practice, and with diverse and changing perspectives on complex problems set in a complex situation and context. The idea of the tree as knowledge is substituted for the idea of weed as knowledge as Cormier expresses it in his talk “The rhizomatic lense – seeing learning from the perspective of abundance” (2015). Stressing the processuality of rhizomatic learning this way, Cormier emphasizes that knowledge is not a thing but a result of negotiation and a way of knowing. And so Dave Cormier tries to save knowing from becoming a fixed canon of ‘pure’ content. It is this dichotomy between ‘pure’ and applied knowledge Tony Bates offers resistance to in “Teaching in a Digital Age” (2015), and in a sense Cormier tries to overcome the dichotomy when he adopts Dave Snowden’s The Cynefin Framework as the complexity model he connects to and combines with his own conception of knowledge in order to establish a vision of learning: rhizomatic learning works in the complex domain of The Cynefin Framework.
As a complexity model The Cynefin Framework presents four “domains of knowledge all of which have validity within different contexts” (Snowden 2002:11), and in an early article Snowden announces that “It is about creating focused dynamic interactions between traditional and unexpected sources of knowledge to enable the emergence of new meaning and insight.” (Snowden 2002:3). Knowledge is not just to be considered a thing but also to be managed as flow, “…as an ephemeral, active process of relating.” (Snowden 2002:5-6). So as a complexity model The Cynefin Framework works with both-and, with paradox:
Philosophers have long seen paradox as a means of creating new knowledge and understanding. Physicists breaking out of the Newtonian era have had to accept that electrons are paradoxically both waves and particles – if you look for waves, you see waves, if you look for particles, you see particles. Properly understood knowledge is paradoxically both a thing and a flow…we look for both in different ways and embrace the consequent paradox. (Snowden 2002:7)
This sounds familiar to me, there is alignment with the ideas of rhizomatic learning, and in fact there is also a paradox entangled in the rhizomatic learning process: students following their own paths like rhizomes while getting accustomed to lines of flight and flow. As I wrote in Part 3 of this series an important aspect of rhizomatic learning as a pedagogy is that in many ways it turns the ‘end goals’ of a traditional learning process into its starting point: as a student you need to know what you have come in to learn when you enter the rhizomatic learning process, but to know what you have come in to learn implies critical thinking, reflection and independence, and that is paradoxically also what and why you have come in to learn. By introducing non-linearity in the form of the rhizome as a metaphor for learning in an experimenting, multi-nodal, multi-directional, multi-perspective and participatory way, learning itself becomes a complex system that is a network of many interdependent parts which interact according to the context.
A parallel can be found in Dave Snowden’s article where he describes the processes of the complex domain this way:
By increasing information flow, variety and connective-ness either singly or in combination, we can break down existing patterns and create the conditions under which new patterns will emerge, although the nature of emergence is not predictable. (Snowden 2002:16).
It is these processes of grasping relationships and recognizing changes in culture, Dave Cormier tries to initiate by describing the phases of the students’ self-directed learning processes as 1) orient, 2) declare, 3) network, 4) cluster, and 5) focus (Cormier 2015). The unpredictability of the non-linear dynamic exploration and connection of knowledge, people, resources and ideas is kept in a kind of balance by a sense of insight and temporary order through working in informal communities (cluster) and focusing on the complex problems and challenges chosen in order to co-create new, accurate and up-to-date knowledge. But there are also traces of the domain of chaos in rhizomatic learning as a pedagogy: it is the uncharted domain focusing on new and innovative knowledge and working through temporary communities (Snowden 2002:10-13).
The complex domain is a domain of informal learning according to Snowden: “…we create ecologies in which the informal communities of the complex domain can self-organise and self-manage their knowledge to transfer to the formal, knowable [complicated] domain on a just in time basis.” (Snowden 2002:19). And ‘just in time’ requires openness to networks. But when Snowden in his article insists on keeping a connection between complex and complicated, informal and formal, and between learning and teaching when it comes to an educational context, Cormier focuses wholeheartedly on the complex domain and students following their own pathways in his introductions to rhizomatic learning in the video talks embedded in this series.
That is, Dave Snowden is intensely concerned about the exchange and flow of knowledge between the four domains in his complexity model, while – although he recognizes the dialogue between the complex and the complicated domains – Dave Cormier seems to see the complex domain as an alternative to the ‘traditional’ knowledge production in the complicated domain as he writes in his article:
If a given bit of information is recognized as useful to the community or proves itself able to do something, it can be counted as knowledge. The community, then, has the power to create knowledge within a given context and leave that knowledge as a new node connected to the rest of the network. (Cormier 2008)
Informal learning is connected to the complex domain in Dave Snowden’s complexity model, and his vision of the community is associated with clustering – communities being based on mutual interest – and with swarming like in swarming bees as an alternative that “is used where no naturally occurring cluster can be found, either to create a cluster or to make one visible.” (Snowden 2002:21). Snowden’s conceptualizations match Cormier’s emphasis on initiating informal learning through introduction to an existing professional community where students can participate, and the processes of clustering and swarming, forming temporary communities, look very similar to the learning approach of rhizomatic learning that the student has to adapt and perform in order to learn what he/she has come in to learn: 1) orient, 2) declare, 3) network, 4) cluster, and 5) focus. I think the answer to why community is not to be understood as a community of practice in rhizomatic learning can be found here: the metaphor of swarming, the idea of clustering and the heterogeneity and temporary existence of them both goes against the idea of what a community of practice is in The Cynefyn Framework: a community based on known membership and known objectives and belonging to the complicated domain, not the complex. So social learning has a special meaning in rhizomatic learning as it connects students following their own pathways into clusters for a while where the processes of knowledge production and negotiation of meaning causes learning based on a social constructivist view of learning.
Aiming at bringing the knowledge flow of complexity at work in a pedagogical and educational context, rhizomatic learning has an affinity with Dave Snowden’s thinking – and not with networked learning – as it becomes very visible with Snowden’s characterization of The Cynefin Framework:
…an idealised model of knowledge flow involving three key boundary transitions – the disruption of entrained thinking, the creation and stimulation of informal communities and the just in time transfer of knowledge from informal to formal.(Snowden 2002:18)
But in his visions for learning Dave Cormier at the same time sketches what he sees as a key issue for a pedagogy and a practice that incapsulates the conditions of complexity in a digital age: “…a weird historical process has happened: as we have got more abundant access to knowledge, we have reduced the complexity of the teaching.” (Cormier 2015). In Cormier’s world abundance is synonymous with fact checking and how to-videos online, with foundational knowledge and surveys a few clicks away, as he presents it in his talk “The rhizomatic lense –seeing learning from the perspective of abundance” (2015). Abundance understood as the explosion in the quantity of knowledge – stressing heterogeneity and a diversity of knowledge, ideas, resources and people being available – is what is associated with complexity in Cormier’s world, and that is what qualifies rhizomatic learning to be seen as a pedagogy of abundance according to Martin Weller’s educational model of education (see Part 1).
This focus on knowledge production, on the other hand, calls for a pedagogical attention to teaching students how to be sure they enter and stay in the complex domain, and this has all to do with acquiring skills, competencies and meta knowledge about knowledge management, I think. In the complex domain both problems and solutions are ambiguous, so you’ll have to ask not just good questions but complex questions that deal with relevant and critical just in time problems, and there are no correct answers but possibilities coming from connecting knowledge, people, ideas and resources while crossing the borders of disciplines, subject matters and institutions. Complex problem-solving is about asking new and open questions, about recycling and combining the information and knowledge already available while coping with paradoxes, about finding new methods, and about trying to rethink and reimagine preconditions, understandings, norms and values. This is where networking and interdisciplinarity play a crucial role along with negotiating meaning, where the possibilities of networks and serendipity are tried out, and problem-solving and heterogeneity meet and stimulate each other. Understanding dynamic processes and complex contexts are the hearth of the matter here. As Mode 2 knowledge production, knowledge production in rhizomatic learning is focused on application in practice of actual, relevant problem-solving and set in a web of co-producers coming from different disciplines, domains and contexts as described earlier. But introducing students to a full description of what, how, why, where and when to do to enter and stay in the complex domain is not a part of Dave Cormier’s pedagogical considerations.
Innovation is an asset of the pedagogy of rhizomatic learning and implicitly connected to the practice of rhizomatic learning where the processes of qualifying new knowledge might produce innovation (Darsø 2001:29) – and when comparing with Cormier’s thinking about what counts as knowledge, it seems that it is rather radical innovation than incremental innovation that is the purpose. Innovation is about producing something new, that has to be useful and have value and it has to be usable and applicable in practice. And value has to be understood in the broadest possible sense, not just in the economical sense. The new – whether it is knowledge, procedures, methods, programming or artefacts – is not an innovation until it has been proven usable and valuable in practice and accepted by its users. And this is exactly what the complex domain – and especially the domain of chaos – is about in Dave Snowden’s thinking: an emergent practice focused on producing the new, the different, the unique (Snowden 2010). So students will have to master not only entering and staying in the complex domain but also to try to work actively with producing innovative knowledge in order to accomplish the rhizomatic quest, but I don’t think they will get there by navigating the complexity only.
Students will need to know how to work with the uncharted and with ‘unknowledge’, that is asking questions about the knowledge you don’t know you don’t know, and asking questions about areas you didn’t know existed, by asking “What if?”, “Could it be that…?, “It is impossible, but still: why not try to…?”. That would also be a start working deliberately, creatively, critically and reflective not only with uncertainty and complexity, understanding dynamic processes and changing perspectives, but also with producing new knowledge and innovation. As it is, there is no guarantee that rhizomatic learning as a pedagogy and a practice produces anything but knowledge that is new to the students but well known to the experts, the discipline, the subject matter or the social practice. Students still need to learn and be taught how to. But by saying that, I have left the informal space of rhizomatic learning.
A conclusion and almost the end of my exploration
The question of what counts as knowledge is what distinguishes rhizomatic learning from networked learning. Rhizomatic learning is concerned with producing innovative Mode 2 knowledge and based on a social constructivist view on learning, as far as I can see, as the starting point of the rhizomatic learning process is the individual learner or student. Networked learning, on the other hand, is engaged in working with foundational knowledge and Mode 1 knowledge as well as Mode 2 knowledge production, as I see it. Networked learning strives to keep a connection between teaching and learning, formal and informal education, and deals with both the simple, the complicated and the complex domains in Dave Snowden’s complexity model, so to say, whereas rhizomatic learning has its specific focus on self-directed learning and preferably in informal spaces in the complex domain. Networked learning is based on a socio-cultural perspective on learning and teaching (Hodgson, McConnell and Dirckinck-Holmfeld 2012:292-293; Ryberg, Buus and Georgsen 2012:51). This is the reason why networked learning values more strongly tied groups and communities of practice/learning/inquiry/knowledge – contrary to rhizomatic learning – while building on collaborative interdependences between learners and on relational dialogue, critical reflexivity and shared experiences during the learning processes:
“Rather, learning and knowledge construction is located in the connections and interactions between learners, teacher and resources, and seen as emerging from critical dialogues and enquiries. As such, networked learning theory seems to encompass an understanding of learning as a social, relational phenomenon, and a view of knowledge and identity as constructed through interaction and dialogue.” (Ryberg, Buus and Georgsen 2012:45)
“…there is a shift from seeing knowledge as an object to seeing knowing and indeed learning as a situated activity and something people “do” together, collectively and socially.” (Hodgson, De Laat, McConnell and Ryberg 2014:22)
I won’t blame you, if you still find it hard to see and understand the differences and distinctions between rhizomatic learning and networked learning. It can still be difficult to grasp that the definition of networked learning, quoted at the beginning of Part 4 in this series, doesn’t cover rhizomatic learning, too. You need to dig deep down into these two pedagogies to find out that they are not the same. And it shows that it might not be that easy to take on Martin Weller’s challenge and start exploring and experimenting with possible pedagogies of abundance. But it is also necessary to remember that these two pedagogies and practices of abundance might not be fully developed, described, conceptualized or theorized, even though networked learning has a quite long history by now. They might still be considered pedagogies in the making, so to speak.
I have come to an end with my exploration and I will conclude firstly that rhizomatic learning is a pedagogy of abundance not only in Dave Cormier’s view but also in the sense of Martin Weller. There is agreement between Weller’s educational model of abundance and the principal lines in Cormier’s thinking. Secondly I’ll repeat that rhizomatic learning is not a version of (open) networked learning as this blogpost hopefully has proved. And thirdly it is equally important to stress that networked learning is not a generic term for several pedagogies of abundance but a specific pedagogy with a range of specific practices and a possible pedagogical choise for an era of knowledge abundance side by side with among others problem based learning, communities of practice, connectivism, rhizomatic learning and connected learning.
Is there anything left to say then? Well, after all I think there is still a little summing up to be done on pedagogies of abundance in general. It is not quite the end yet.
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