Monthly Archives: April 2014

Coda: Rickert’s Wonderful World of Oz Meets Pocahontas

First, an aside: I couldn’t stop myself from thinking of this scene from The Wizard of Oz in an entirely new way. While it’s clearly made with the human worldview of home in mind, I began to think of the technology of the sepia tone, the production tools, the stage scenaries and props, a plot filled with concepts of place in terms of time and dreams, the natural (i.e., the tornado). Thanks a lot, Rickert.

I get it. There’s a pattern here; I think I finally see it. When I started reading Rickert’s Ambient Rhetoric, I thought this was a logical next step to our discussions of ecology, ecosystems, affordances, agency, and ANTS, to bring us full circle to Rhetorical Situation where we began. I had no problems buying into Rickert’s premise that the subject-object binary and rhizomatic network pathways so common to discussions of Internet network theories might need some additional theorizing to be really useful. After all, that’s what FrankenTheory building is all about, right? Taking the theories of others and repurposing them or resisting them to fit an application or case study we see as worthy of analysis?

Cave paintings

Cave paintings

So I enjoyed this text and found innumerable ways to connect it to AND frame our semester’s worth of reading. Rickert’s visit to antiquity – from cave paintings to Aristotle to Plato, to (dare I say it?) the 1970s ambient musician Eno and Microsoft Windows’ early operation system music all created a foundational premise for his argument that was quite engaging. I drank in his discussions of complex systems as evolving environments where – like Deleuze’s rhizome metaphor – the human subject is no longer “all that” given the way our networked lives have evolved to become, well, cyborg like. His discussion of the Earthrise image and the rhetorical nature it reveals, the importance of distinguishing between things and objects – it all really makes sense to me. In fact, I found Rickert articulating so well what I’ve envisioned for many years now: humans and our worldviews err in seeing ourselves through the lens of the “I” for it ignores the almost spiritual balance of existence. I’m avoiding using the words “ecosystem” and “ecology” because Rickert problematizes them in significant ways in Chapter 8, but if delivered through the ambient, these terms may be rendered “safe,” revealing (as he argues) ways these concepts and theorizing “place” as ambient “can be transformative … when it affects our mode of being in the world, making our relationship to the earth not that of subject to depicted object but that of mutually sustaining assemblages of humans and nonhumans fitted into an ecologically modulated world” (218).

I thought of the many movies I’ve watched over the last decade or more with an ecofriendly message – Wall-E, Avatar, Fern Gully, and the one that started it all, Pocahontas – and thought how even the rhetorical moves embedded there remained somewhat human-centered. Even when the messages (as Rickert points out) encourage an eco-consciousness, they still localize the human agency as primary, with rhetoric in persuasive mode rather than a transformative ontological relationship (163).

Even though Pocahontas’ “Color of the Wind” comes close to how I started envisioning Rickert’s approach to ambient rhetoric as “one in which boundaries between subject and object, human and nonhuman, and information and matter dissolve” (1), it soon became clear that it missed one of the features of an ambient rhetoric in terms of how “rhetoric’s comportment toward objects in turn shapes rhetoric itself” (204). As Rickert observes, ambient rhetoric:

  • Can’t be separated from “material being,”
  • Emerges from the environment,
  • This emergence and relationship aren’t simply due to human direction, and
  • In “grappling with these entangled, mutually coevolving and transformative interactions among persons, world, and discourses,” we will need “a new appreciation for…their complexity” (163).

In other words, environmental messages miss the mark when it comes to successfully achieving a rhetoric of ambience. I can already see the benefit of this revisioning to comp/rhet, and thought again and again of how this book takes the call to remap the canon of rhetoric made by Prior et al. in a new direction.

Rickert’s journey through Latour, Heidegger, Foucault, and others clearly qualifies as a FrankenTheory, finding and resolving a gap in the scholarship that – by pulling interdisciplinary threads – offers a richer theory. At the heart of this is the object/subject dichotomy and, as he argues, its continued control of our theories and applications of rhetoric. Rickert’s Ambient weaves together theorists of sociology, psychology, classical rhetoric, linguistics, and more as a means of exploring how these often stumble over a continued reliance on this either/or scenario. As the Borg would say, Rickert is taking the “biological and technological distinctiveness” of others’ theories and rhetorical history and adding it to his own to deal with our culture’s (and our field’s) “standard technological quandary where we are either masters of technology or by technology mastered” (204).

His turn to the technological has ramifications for the way MOOCs are currently being theorized as places of learning and places for teaching. His exploration of the image Earthrise as ambient was just the start. His argument that even the network metaphor is insufficient for the task is compelling, pointing out that it still relies heavily on a binary conceptualization of our complex system of inhabiting (122), a flaw he asserts is addressed by his theory of ambience.

Figure 2. Optical array and its variation following the observer position (from J. Gibson, 1979)

Figure 2. Optical array and its variation following the observer position
(from J. Gibson, 1979)

While looking for appropriate images to supplement my post this week, I came back across Maury’s recent post on her 3rd case study, which embedded an image from Gibson’s 1979 work on affordances and the visual similar to that on the left. I found these images to be especially productive in terms of thinking of what Rickert was framing in his book on rhetoric and ambience as the “I” centeredness of rhetoric’s history of discourse and meaning (and the way we often continue to theorize rhetoric and networks in a technological era of MOOCs and communications’ technology). Earlier in the term, I considered Latour’s actants as a way to frame discussions about Composition MOOCs, but Rickert layers in Heidegger seem to carry it a step further: “things make claims on us that help constitute not just the various kinds of knowledge we produce but also our very ways of being in the world” (229). In the case of a MOOC, many scholars (who resist dismissing education MOOC technologies as pedagogically blasphemous) would likely agree with this, and certainly Gibson’s theory of affordances would align neatly here. I can see how conceptualizing the online environment of a MOOC as an ambient place, where learning happens not merely at the direction of the human teacher/student, but also when theorized and discussed in terms of ways the diffusion of knowledge through such a complex system must always already be seen in terms of Foucault’s traces. Indeed, at times I wondered in the marginal comments in my book at whether ambient rhetoric is Foucault’s trace metaphor reborn. What would happen if we discussed learning / teaching / collaboration / writing in a MOOC in terms of “dwelling”? How might that open up the discussion about MOOCs as place and the technology’s impact on design as actant / ambient / attunement? In fact, Rickert’s chapter 7 provided me with a host of new ways to discuss the tensions of the place of MOOCs in education. His exploration of the concept of “dwelling” as an “ecological attunement to the environment” (223) may suggest students and teachers (human actants) are less well served when seen through the “worldview” of a God’s eye perspective and its resulting treatment of objects / subjects and their interpretation (224-25). In fact, Rickert’s theory of ambient rhetoric highlights the cultural lens that may have been at the heart of one of my arguments that a “nostalgic” approach to face-to-face pedagogy is at the core of some of our field’s tensions when it comes to online pedagogy practices.

Really, Rickert’s work brought together for me much of our semester’s trajectory. His theorizing is thick with name dropping, clearly demonstrating how to build a FrankenTheory to fill the gaps made visible by those who have come before. Throughout the work, he builds upon Heidegger’s theories of rhetoric in interesting pathways, reinforcing his view that an ambient rhetoric is preferred over traditional rhetoric in the way it becomes “a responsive way of revealing the world for others” (162). His book brought to mind rhizomes and networks, hardware and ANT. For me, even our final mind map took on new meaning as I read his argument that “the complex cannot be…analyzed through…the component elements but rather enters a new state of order … that transcends the initial state” (100). As we watched our mind maps grow in complexity, we might also say we have been“haunted by increasing points of connection but also by their interactive emergence into new forms” (101). Thus, after reading Rickert, I found myself wondering if being asked to reconceptualize and recreate our semester’s worth of work in Popplet might have been the plan all along.

Coda: it seems only appropriate that I conclude my final reading post with a rerun…

"The A Team": Dr. Romrigo

“The A Team”: Dr. Romrigo

Works Cited

Rickert, Thomas. Ambient Rhetoric: The Attunements of Rhetorical Being. Pittsburgh: University of Pittsburgh Press, 2013.

“Play Ball!” MindMap Reframed

So, I puzzled over how to reconceptualize a mindmap 15 weeks in the making using concepts, rather than components. I reviewed our class syllabus for footholds, pondered my case study foci, watched a little ESPN on a break, checked the Red Sox score, and then (you see this coming, don’t you?)…

Baseball Diamond

Baseball Diamond

It’s beautiful, really — but like the game itself is rough around the edges (just look at the recent ejection of a pitcher for “hiding” pine tar on his neck). But, bear with me, let’s see how this metaphor plays out.

Coming up with the bases for this diamond was fairly simple: Pitcher’s mound = Operationalizing Theory, our course initiator. Whether through blogs or assigned asynchronous activities, it seemed we were all swinging away … at first a fast ball (How it Works, Rhetorical Theory), then a curve ball (Foucault), and even an occasional knuckle ball (Prior, Guattari). Thinking next of First Base = Nodes and Agency. Here is our first task, our first accomplishment, our first move into the field of play. Identifying the lineup, determining who’s on first, what’s on second, and on third? (Abbot & Costello say it best.) Here’s where the analogy gets a little squirrely, however; the deeper we went into the game (some might say into extra innings), the lineup and rotation changes. Suddenly, we’re talking about genre as not just a border but having agency, even distributing knowledge. (It seemed so simple when I started.)

On to Second Base = Connections & Communication. We were often asked in our case studies to address the question “What’s moving in the network? How are nodes situated? Describe the nature and directions of the relationships formed.” Again and again, we reshuffled the roster, trying out new combinations, looking for that “sweet spot” of theory to create a FrankenTheory that captured the complexity of our objects of study (dare I say, a pennant?). One of our final readings this term was concerned with Operating Systems, which — come to think of it — captures agency, nodes, movement, and signals for so many of the theorists and readings we covered. So, take a base.

Third Base = Meaning & Knowledge … nearly home. Our network theories always already involved knowledge. Whether it was in terms of creating or distributing, all of our theorists and practitioners (ourselves included) touched this base. You may notice I repeated a node here — the OS makes another appearance. Those kinship patterns — cultural discourse, ways of knowing, ways of learning — have to be embedded here, as well as back at 2nd base. And, wouldn’t you know it, 1st base as well. That’s the power of an ecological system — there’s material transfer happening all over the place.

At last, Home Plate = Why theory? It’s why we came to the park in the first place. I saw this as both the goal of the course, but a destination too. It’s where I locate myself as a scholar, and a practitioner. And true to any baseball game, it isn’t just the bases that matter. It isn’t even the players. We can’t complete this mindmap without widening the reach of this network to include those fans, the “10th man.” This is where we write our Case Studies, add new theoretical layers, toss out uncooperative ones. This is where we find the ecology of our field, where the game really becomes interesting.

Extra innings? Double header? Maybe next time. Right now, I think it’s time for the 7th inning stretch.



Reading Notes: Althusser and Hall, Tip-Toeing Toward Ambient Rhetoric

Several interesting take-aways from this week’s reading – although I will only focus on a few that really struck me as intriguing points of intersections. Indeed, I really seem to have more questions than connections this time around, and so this post seems quite fragmented. But, here we go….

First: Sir Ken Robinson’s TED talk “Changing Educational Paradigms” immediately came to mind while reading Althusser (and, to a lesser extent, Hall) this week. And so, I’ll begin by sharing this:

It’s fitting, I think, to jump next into Althusser’s input on the State-then-Educational System as ideological conditional “apparatus.” The concept of reproduction is key to both Althusser and Hall (and I suspect Rickert as well), but in slightly different forms – and I think in interesting ways. Althusser is, he asserts, promoting a “theory of ideology,” and advances a number of theses. But it’s where (i.e., which border node) Althusser seems to connect to Hall in terms of behavior and ideology that I found particularly worthy of note.

Production Line: Peeps

Production Line: Peeps

Althusser’s Marxist perspective frames his text in terms of the role of production in “social formation” (1). In order to keep this social formation in place, production plays a pivotal role, but this must be “reproduced” within the population in order to maintain it. To do this, he argues that this society must “reproduce (1) the productive forces, [and] (2) the existing relations of [the dominant mode of] productions.” Further, “what distinguishes the productive forces from the means of production” [emphasis mine] is “the reproduction of labour power.” But it isn’t simple addition to the labor pool; it’s reproduction that is key. And according to this author, reproducing the “infrastructure” or the economic base isn’t enough – the superstructure of state and ideology are what support the entire structure / system.

Interestingly, just when I think this is going to be a political / Marxist critique of ideological systems, Althusser insists that he is making a distinction between the “repressive state apparatuses” or RSA (the government or police forces) and the “ideological state apparatus” or ISA (the church, education, family, and even culture and literature). It is the ISA which is at the center of his theories in this chapter. Interestingly, he distinguishes between the two, in part, by referring to the scale of their function, with the ISA functioning “massively.”

(So I wondered at this point, what would Althusser think of educational MOOCs, which by this publication weren’t even a glint in a programmer’s eye?)

The turn toward the Educational system (supplanting that of the Family-Church influence) struck me as an interesting line of thinking given our graduate-level learning is currently focused on Theories of Networks, and we know that theories cannot be ideology / bias-free. When Althusser comments on what / how students learn (“’rules’ of good behavior” as well as “submission to the rules of the …ruling ideology”), I hear him channeling good old political Marxism, with ruling classes and the working classes at odds, but with class struggles taking place at these ISA sites.

(Would Foucault see these sites as nodes of differance?)

In other words, it isn’t enough to reproduce the working class system; the “relations of exploited to exploiters and exploiters to exploited” must also be reproduced. Thus, the nodes of the network PLUS the network relationships themselves are informed and multiplied.

Althusser’s a bit of a tough go for me at this point, but several of his points seem to provide potential connections into Hall’s article worth highlighting for future comparison to Rickert:

  • An individual’s “ideas are his material actions inserted into material practices governed by material rituals…themselves defined by the material” conditions / apparatus from which those ideas emerged.
  • “individuals are always-already subjects. Hence individuals are ‘abstract’ with respect to the subjects which they always already are.” (This reminded me a bit of the Hall comments about the relationship between individuals and society when it comes to mass communication methods and coding/decoding.)

Hall takes it from here: writing about mass communication studies as overly “linear” and lacking “a structured conception of the different moments as a complex structure of relations” (478), his statement strikes me as a possible push back to Althussers’ superstructure / linear materiality of these important relationships within complex systems involved in a “production process” (Hall 479). While Althusser focuses on ideological (re)production, Hall’s focus is on the systems of mass communication and coding/decoding messages passing through those systems (mainly television). Perhaps we might consider this a layer deeper – at the “genetic” levels” – of these infrastructures.


From blog page: Richard Cassaro, 2011

First, Hall defines codes as “the means by which power and ideology are made to signify in particular discourses” (483). So if Althusser is concerned with ideologies’ reproduction through dominant systems like government-run educational institutions, Hall jumps into the deeper end of this pool on the subject of another object of similar charges – mass media. Rather than Althusser’s theorizing of the ideology itself, Hall’s focus is on the communication process – specifically explaining the four stages of communication: production, circulation, consumption (or use), and reproduction. Interestingly, Hall’s comments bear a similar tone to Althusser’s when he says that messages are imprinted by “institutional power-relations” at each of these four stages, essentially “reproducing a pattern of domination” (477). Each of these moments, he argues, should be seen as “different moments” in a “complex structure of relations” (478). Relations which, at least according to Althusser, are marked by public behaviors commensurate with some form of conditioning – or as Hall would assert, a coding and decoding.

Hall pushes back against theorists who linger too long over the outcome of behavior in this media-ideological brewing pot (480). Instead, he fixes his gaze on the communication Production-to-Reproduction scale and the naturalization of some meanings due to wide distribution. This, he says, has an “ideological effect” of “concealing the practices of coding which are present.”

(Is this, then, what Althusser would see as the process used by the ISA? And what would Foucault say or add to this?)

QR Code

QR Code

These codes become wrapped in Hall’s nuanced meanings of connotation and denotation as they infuse the “structure of discourses in dominance” where meanings can be mapped into hierarchical and “dominant or preferred meanings” (483). This power of relationship ties between coding and decoding bring to mind our early discussions of Hardware Theory, and the compartmentalized nature of that communication system.

(I wonder – how have digital spaces impacted this, especially as Hall asserts that dominance = a “pattern of ‘preferred readings’” that are distributed through these systems of mass communication?)

So Hall’s discussion of coding and decoding and the relationships between those two acts as independent yet co-limiting, creating a system of dependence and even perpetual balance which he calls “a fundamental alignment and reciprocity” (481) is at the root of “class struggle in language” (482), reflections of how ideology affects discourse at the connotative level.

Final note: Hall’s argument is situated in the midst of mass communication systems (like television) being theorized as ideological influences upon public behavior. He insists that it isn’t the behavior we need to study – it’s the system by which messages are coded and decoded in discourse that deserves closer study. Also of interest is his approach to the “subjective capacity” of television’s power to mediate / transfer messages and meaning (485). Althusser states that “actors…and their respective roles, are reflected in the very structure of all ideology,” but does that mean they are no longer individualized in his theorizing? Hall seems to think such individualization vs. subjectivity when it comes to successful decoding has been misrepresented. He argues that miscommunication happens – not because individuals “misinterpret” the messages intended meanings, but because there is a lack of reciprocity between the first and fourth stages of the communication process.

The idea of how knowledge (and ideologies) are transmitted and/or infused into a network or community is one that carries with it all sorts of sharp edges. Educators can either be facilitators of knowledge creation and transfer, or we can be ideological reproductive agents. According to Ken Robinson, our traditional system of education is a mass production line from K-16.

Are MOOCs treated with such critical suspicion in part because their structures violate this system?

And so, the final connection: Hall writes about the influence of the media to shape and transmit the “structure of discourses in dominance” (483). His “definition of a hegemonic viewpoint” as one which “defines within its terms the mental horizon … of possible meanings of a whole sector… of society” (486) seems to serve as the “how” to Althusser’s argument that ISAs (education) create that horizon. Class struggle for both authors begin, then, with communication networks.

Works Cited:

Althusser, Louis. “Ideology and Ideological State Apparatus.” Lenin and Philosophy and Other Essays, Monthly Review Press 1971. Web (

Hall, Stuart. “Encoding, Decoding.” The Cultural Studies Reader, 3rd ed. Simon During, Ed. New York: Routledge, 1993.

Case Study 3.5: Scaffolding Synthesis Project

Subject: Composition MOOCs: Theorizing Pedagogy, Space, and Learning.

The Composition MOOC is one of many different types of course offerings in an emerging trend (some would call it a fad) of online higher education. This is a site of considerable tension in our field of composition studies, perhaps because many scholars see this as a step backward and away from the hard-won push for smaller-sized, learner-centered classrooms for freshman writing courses (FYC). However, there are some scholars who argue that these digital spaces can, with careful attention to the space’s design, exemplify the best-practice models of collaborative learning and scaffolding teaching practices found to be so productive in an f2f FYC course. This final case study is not intended to be an argument for Composition MOOCs; rather, it is my intention to theorize the potentiality of such a space using the following theories.

1.  Which 2-4 theories are you choosing and why?

1st Foucault – As I’ve said all semester long, Foucault is woven into everything we’ve explored this term; so it seems only reasonable to apply his theories of knowledge archaeology to this OoS. Indeed, for this reason Foucault will lay the groundwork of my final Case Study.

  •  “Discontinuities, ruptures, gaps” (169) – I envision applying Foucault’s concepts of gaps, ruptures, and irregularities (“differance”) to several possible areas of theorization / operationalization. First, the apparent tensions within scholars/practitioners within our field over MOOC spaces may allow me to explore (as I did in Case Study 2) what I may call the gaps between two space-dependent pedagogical traditions.
  • What I’ve seen in some of the literature: some compositionists argue that our field must consider a refreshed pedagogy for learning spaces like MOOCs (Debbie Morrison’s “A Tale of Two MOOCs”). The assertion is that the traditional f2f methods and technologies cannot be simply overlaid onto the MOOC space with any hope of success.
  • Discursive Functions, Formations, and Relations – Foucault charges that his theory “reveals relations between discursive formations and non-discursive domains (institutions … and processes)” (162), allowing theorists and practitioners alike to “map…the point at which [these multiple dissensions] are constituted, to define the form they assume, the relations that they have with each other” (155). This part of Foucault’s theory seems to be a productive fit to a complex system composed of both human and technological features, where navigation between humans must take place in spaces mediated through techonologies.

2nd Ecology Theory – The potential for mapping a dynamic and complex “living” network of actors as described by this theory is one of the more productive connections for a MOOC I’ve found thus far. Given the mechanics of the numerous digital platforms and software needed to operate this learning/teaching/collaborative space, it seems a natural tendency to see a MOOC along the lines of Hardware Theory (HT), which may be at the heart of many critical concerns about this trend in education. Therefore, this theory offers several useful threads in contrast to HT.

  • Gipson’s theory of affordances will allow me to discuss the structural elements of MOOC spaces in more agency- and relationship-oriented terms. Some studies on MOOC participant identities seem to suggest that these students are typically older professionals; however, many MOOC critics problematize the connectivity and structure (the “massiveness”) of the space as if the students are the 18-year old freshmen common to a physical, f2f classroom space. Therefore, Gibson’s theory may move the discussion toward the space itself in terms of activity potential.
  • Additionally, Gipson’s critical attention to the observer within the environment speaks to not only the observer/participant MOOC space designer / instructor but also the scholarly critics “reading” this trend. This points to the influence of scholarly traditions of rhetorical and pedagogical value systems informing our concept of the 21st century writing classroom space, a potential secondary network or ecology system impacting the MOOC network, and is well worth examining as part of a case study.
  • Bateson’s concept of boundaries within an ecosystem seem especially promising as a means to discuss boundaries – both as frontiers and as “economies of information” (466-67). Given the many nodes and boundary interfaces of technology-mediated teaching and learning spaces, these concepts appear to be promising methods of discussing the MOOC environment.

3rd Spinuzzi’s Activity Theory and connected activity systems provide a concrete means of application in the potential comparison between Spinuzzi’s designer vs. user and the Composition MOOCs between instructor vs. student participant. Spinuzzi’s use of distributed cognition (Activity Theory) and interconnections also maps onto MOOC spaces in potentially useful ways, particularly when focusing on “interrelated sets of activities” (62) rather than the individual learner — i.e., networks. MOOC classroom models vary widely, earning such monikers as xMOOC and cMOOC, the latter of which has been deemed most effective by several scholars due to its emphasis on coordinated collaborative networking. As Porter observes, we as scholars and compositionists must remain critically aware of the design of the learning / teaching spaces we employ / deploy, and Spinuzzi’s discussion of mediation and mediators

4th The Neurobiology Metaphor – as stipulated in my third case study, the neuronal network mapping metaphor provides interesting ways in which to discuss learning and knowledge transfer within a large, complex network system much like a MOOC classroom space.

2. How are they similar enough that you can justify getting them to work together?

  • Complex systems and affordances of web technology-based classrooms invite these theories to weigh in.
  • Hardware / framework of the technology invites discussions of the activity AND the space, as impacted by the affordances of the technology itself.
  • Mapping the complex systems nodes and networks (ecology, neuro, hardware, AT) PLUS the traces of Foucault all have the potential to align when talking about the learning space of a MOOC and the risks involved.
  • Each of these theoretical tools at some point hinge upon the concept of “relationships,” a concept key to collaborative, workshop-based FYW pedagogy.
  • Each of these theorists provide a means of exploring the types of collaborative activities which an ideal cMOOC might employ to foster distributed cognition.

 3. How do they fill each other’s gaps?

Foucault emphasizes gaps and differences; clearly these theorists provide distinctive focal points for their own work, creating potential for layering.

None of these theorists wrote with MOOCs in mind, yet their attention to varying components of a network may produce a FrankenTheory that covers the key moving parts essential to any discussion of a Composition MOOC.
Foucault calls our attention to those theoretical areas of dissonance that often go unmapped (traces). Spinuzzi and Activity Theory allows the focus to be centered on the concrete nodes of activity with a system, where and how the participants interact (where the learners learn and connect). Ecology looks at the system from a larger scale, allowing me to discuss systems within systems. Neurobiology allows us to look at the potentiality for knowledge transfer in terms of “how” learners learn.

4. How do these theories align with how you position yourself as a scholar?

  • For a Compositionist who mixes in rhetoric with digital media interests, online spaces for teaching are an intriguing area of study. MOOC spaces seem to carry incredible potential for the type of scaffolded learning and teaching practices common to writing centers, theories that have informed my scholarly interests in writing center theory as well as learning theory (such as pedagogy vs. andragogy, a key area of difference that appears to be fruitful ground of inquiry).
  • I am also a pragmatist, looking to ways to operationalize theory in practical classroom application. As an instructor, I am more interested in discovering ways to make every space – online or brick-and-mortar – one in which students are visible and active in their learning.
  • These theories intersect in varying ways with each of these positions.

5. How do these theories align with your own biases and background (the reason you came to this project in the first place)?

  • I must admit, I’ve been suspicious of MOOCs as a productive place for freshman writing instruction since I first learned of them a few years ago. As a proponent of our field’s insistence upon smaller-scaled classrooms following a student-centered workshop / studio activity design, the sheer size and decentered nature of the MOOC seemed destined for trouble. I have taught freshman writing sequences online in the past, and it quickly became clear to me that the nature of the space cannot merely mirror that of the f2f classroom. The MOOC design takes this distinction to entirely new levels of complication.
  • But the very nature of our field demands flexibility and openness to new ground / tools with which to best equip college-level writers for the demands of communication across disciplines as well as across technology-mediated spaces. MOOCs may be in their early stages of a full life in the realm of Composition Studies, or they may be on the road to extinction – a fast-burning flame. Another possibility is that they must simply be reclassified, recognized as a unique learning space for unique student populations. What the scholarly discussions seem to reveal is that we as a field are not yet certain how to deal with MOOCs, all the more reason why such theorizing (even after the fact) can be so productive.
  • My interests are also in the field of rhetoric, and in particular the rhetoric of classroom space. From what I’ve read so far, it seems that much of the criticism leveled at MOOCs within higher education emerges from ideologically-infused rhetorical frameworks. These gaps might be revealed – perhaps even bridged – through such intentional FrankenTheorizing.

Mind Map 20 April: Social Networks & Math

This week’s MindMap: Social Networks.

In anticipation of reconceptualizing my semester’s mindmap work, I opted this week to create a more synthesized set of nodes entitled “Rhizome Kinship Patterns.” I also opted not to connect this set to any others as I want to reposition all of these nodes a bit differently. However, had I drawn links beyond the weekly reading / activity, I would have drawn connections to Guattari (earlier iteration), ecology nodes, as well as the node entitled “operationalizing theory.” The key to this group, it seems, is what Scott calls a bridge between theory and practice” (1) by creating an  system for analyzing and packaging these “rhizome kinship patterns” of data for the purpose of research. The rhizomes proposed by Deleuze and Guattari seem less pragmatic but represent complex systems in a way that I envisioned being linked to Scott‘s analytical system as an offshoot (no intentional reference to rhizomatic vocabulary).

wheelsonbusIn fact, I tried to represent a type of associational pattern with my MindMap juxtaposition of these three (although I am not at all sure I did it justice). In my writing notebook, it actually looked more like I had drawn Scott as the rear wheels of an odd looking bus (Rainie and Wilson’s Operating System), and D&G were the front wheels. Sitting atop it all is the concept of kinship network patterns secured in an oversized luggage rack if you will (in an attempt to suggest that this field of research must be transmitted / moved through theory and theory application). I was trying to visualize here what I thought connected these authors. These three articles seem to be working towards a common purpose: conceptualizing bundles of activity into recognizable forms, useful for analysis and discourse in a quest to discover “what is significant in the situation under investigation” (Scott 54).  Since Scott’s data analysis could be seen as one sort of “driving force” behind the theorizing being done by Rainie, Wilson, Deleuze, and Guattari, I thought this bus could be rear-wheel drive.

Scott, Social Network Analysis, Figure 2.1

Scott, Social Network Analysis, Figure 2.1

Scott‘s matrices appear almost painfully linear in comparison to the more naturalistic rhizomes of D&G, and perhaps the two offer a way to balance this research engine. Scott (as was mentioned during class, and as we experienced in our in-class activity) dealt in the minutiae of counting those intersecting data packets produced by research on Social Networks. That is, until I considered how this could also be about  recognizing patterns erupting into new lines from “the middle” (rhizomes) of a data set. At least, that’s how I felt when trying to wrestle the activity into submission. (I believe I had to tap out to Leslie and Jenny.)

I went back and forth trying to decide how best to position the Rainie and Wellman node as the role mobile communication networks play in creating a realm or axes in which the other theorists might traverse. At first, I thought of making the Rainie/Wellman a sort of “train tracks” but Popplets really didn’t represent that well at all. Therefore, I thought placing it in a “vehicle” mode, being carried by the theorizing and operationalizing done by the other authors, might be suitable. It’s certainly a work in progress, I confess.

Finally, thoughts on my OoS: the concept of rhizomes has crept into my writing time and again this semester, so I was rather looking forward  to discussing the representation in our last class. I must confess, I do wish we could have spent more time on that particular element of our reading assignment, as I would have liked to have heard others’ thoughts on the connections between rhizomes and mobile communication systems. Alas, this week’s Popplet also represents that limited scope.

Works Cited:

Deleuze, Gilles and Felix Guattari. A Thousand Plateaus: Capitalism and Schizophrenia. Minneapolis: Univ. of Minnesota Press, 1987.

Rainie, Lee and Barry Wellman. Networked: The New Social Operating System. Cambridge: MIT Press, 2012.

Scott, John. Social Network Analysis: A Handbook. London: Sage Publications, Ltd., 2000.


Mobile Technology On the Move: Rainie, Scott, and Deleuze

Rhizomes and Social Networks –

This week’s readings bring us around to the rhizome analogy, one which Deleuze and Guattari wax philosophic over (when they apparently are indulging in some pharmaceutical hallucinations, I gather). Their rhizomatic illustrations seem to serve as a useful hinge upon which to balance Scott’s article that narrates the building blogs of an evolving system of theory, and that of Rainie and Wellman’s anecdote-filled discussion of the Third Revolution.

I read Scott first, in preparation for our Tree collaboration, and found it especially helpful in terms of the way it moved the reader relatively smoothly through a narrative of who was building upon whom. Interestingly, his self-proclaimed purpose is to “bridge [the] gap between theory and practice” (1), something many of our “show and tell” build projects seem designed to do as well. (Frankentheorists Anonymous.) His focus is on “social network analysis” (1) for the purpose of “identifying…key concepts” and finding “kinship patterns” (1-2), a useful foundation for the next two readings of this set, as he provides some useful pragmatic elements as balance to Deleuze/Guattari’s more ideological treatise, and as well to inform the analogous turn of Rainie and Wellman. Several key terms of note:

  • Attribute data = “attitudes, opinions, and behaviors” that serve as “characteristics” of individuals and/or groups (2).
  • Variable analysis= a way to measure the “values of particular variables” like “income, occupation, education” (2).
  • Relational data = “the contacts, ties, and connections…which relate one agent to another and [what seems most important] cannot be reduced to the properties of the individual agents” (3). He asserts that this is key to the social sciences in that it highlights the focus upon “the structure  of social action,” not simply the individuals (4).
  • Ideational data = describes the “meanings, motives, definitions and typifications themselves” (3)

He cites three main lines of development of analysis: sociometric & graph theory, dealing with small  groups; cliques or “cohesive sub-groupings” (16); and anthropologists / networks (26).  Interestingly all three claim to build upon the other, but differentiate by shifting the focus of outcomes in varying directions, largely based on the perception of scaling the cause-effect. The graph theory raises the ever-important element of research, and that is the influence of the group upon “individual perceptions” in terms of how social organizations inform the system a the very basic level of the “I” (8-9). Scott points to the usefulness of sociometrics in creating “analytical diagram[s]”  such as what researchers often use to map data: graphs, bar charts, etc. (10). He presents a variety of different diagrams other than basic lines that graph networks of behavior in terms of relationships (13) in structural terms that sound a great deal like the networks we’ve been exploring to date. His nod to interdisciplinarity as a strong influence in determining such representations struck a chord with me, thinking of ways we’ve been drawing upon any number of fields to make connections to English Studies. (I’m often surprised to see how well they fit!)

I appreciated his article’s focus on making analysis accessible, and for his advice on what potholes we need to avoid when theorizing any analysis – like forced applications. That seems to be a risk whenever working with metaphors – there is always something that doesn’t quite fit. Enter: FrankenTheory. Where one analogy fails, we usher in a second (or a third) as a layering system of interpretive tools.  His cautions are clearly well-founded. I especially appreciate his observation in Chapter 3 that one of the risks of “construct[ing] sociograms” is their tendency to obscure the important smaller nodes of connections – masking the trees in the larger scale of the forest (40). I was painfully aware of my wildly out-of-control Mind Map at this point – in anticipation of the need to restructure it by theme. (I wondered if that directed activity is intended as an offshoot of Scott’s observation here!)

Scott brings us back to the notion of boundaries in Chapter 3, observing: “What these  problems point to is the fact that the determination of network boundaries is not simply a matter of identifying the … obvious boundaries of the situation.” That’s because locating or naming said boundaries in research “is the outcome of a theoretically informed decision about what is significant in the situation under investigation” (54).  As Dr. Romberger pointed out recently, our research will inevitably require us to be transparent in recognizing our biases as part of our analysis.

From "How Stuff Works": "How Grass Works"

From “How Stuff Works”: “How Grass Works”

Next in the order of things comes – in my scheme of things, at least – Deleuze and Guattari’s treatise on rhizomes. I find their conceptualization of this physical schema especially useful as an alternative to a more traditional linear mapping of relationships and networks. Their attention to the characteristics of a rhizomatic form (grass-like) vs. an arborescent (tree-like) form became a bit of a mantra when our group was designing our theory lineage line. Especially helpful was their delineation of characteristics, again opening up possibilities for transferring to discussions of our Objects of Studies. The non-genetic nature of rhizomes seems to suggest that thinking of theories evolving out of previous theories overly simplistic, that such hierarchical imagery too often leaves out the multi-directional influences of other networks (cultures, individuals, etc.). This clearly gels with so many of our other theorists (Castells and Latour, most recently) who argue that we must see network influences happening in a multi-directional format – again, thinking back to Dr. Romberger’s asterisk when explaining ANT.

I found their commentary on Eastern vs. Western cultural thinking especially note-worthy, and in particular their suggestion that American cultures manage to blend both in many ways. Perhaps this has more to do with the “age” of a culture than ethnocentricity, with a culture of immigrants – blending a myriad of histories and cultures – creating  a multi-nodal sense of identity.

There is one concept that I must confess I have not quite wrapped my brain around – maps and tracings…that tracings must be put on the map, not the other way around (21). Perhaps, like Winnie the Pooh, I need to go to my Thinking Spot and ponder that for a time.

Meme: Cell Phone Culture and Zombies

Meme: Cell Phone Culture and Zombies

Finally, Rainie and Wellman cap off this trio by placing these ideas of rhizome connections and data collecting in the context of the age of mobile communications networks.  I must confess, thinking of our culture and communities as an OS – not unlike Maverick from Apple or (ugh) Windows 8 – is one I’m not entirely ready to embrace. Clearly, Rainie and Wellman resist the argument that our age of cell phone-networked cultures is creating isolationists. And while they do give a nod toward some of the downsides of the mobile-technology obsessed, I did get the sense that they are firmly in the cheer camp of “more mobile is good for us.” (Would this mean the meme above could be rendered as a Zombie Rhizome?)

Their distinction between networked versus embedded remains a bit fuzzy to me. They seemed to go to great lengths to clarify the notion of individuals networked vs. embedded into groups, pointing out ways in which mobile communication technologies allow for greater, rhizomatic growth beyond a spatially limited contact list. They clearly want us to see this in terms of social groups problem-solving by outreach and information gathering efforts. At the heart of this is what they call “three revolutions”:

  • The social network revolution – extending the social circle beyond proximity and traditional family / village units;
  • The internet revolution – increased communication and knowledge gathering powers; and
  • The mobile revolution – creating “appendages” to our physical bodies for the purpose of making connections unencumbered by time or space (even referring to  Castells’ “space of flows” on page 102).

These three revolutions are mutually influential “in the network operating system” (107), in good and bad ways. I laughed when they pointed to the examples of “present absence” (103) in an image of teenagers sitting in the same room engaging with each other through mobile devices rather than face-to-face interactivity. Or the public space invading private space in the case of cell phone conversations in public – I think we’ve all been a part of that.

Samsung: Social Networks

Samsung: Social Networks

But what makes this a “revolution,” exactly? Is this, in some ways, enthusiastic hyperbole? If we define revolution as “no turning back” change, then yes – the impact of communications technologies on our social interactivity is revolutionary. Is it rhizomatic? Yes, I think so, certainly given the ways in which these authors talk about individuals’ abilities to expand outside of their geographically located spaces and branch out into new networks at will, even jumping past traditional bridges (thinking here of Facebook’s Friend features as a “partial membership in multiple networks” — 12) to move into new realms of connections – the “Connected Me” (19). Such technology also shatters traditional (or else, long standing) boundaries such as work / home, public / private, and aligns with Deleuze and Guattari’s description of the rhizome beginning in the “middle” and not the ends (21), rupturing at “segmentary” points along the line yet still remaining connected (9). Could this be possible with any other technology other than Internet-linked channels?

The principal characteristics outlined on page 21 is quite useful when using a rhizome as analogy – it stands apart in many ways from an ecology, or a neurosystem of the brain. It appeals to the controlled chaos theory mentioned in Castells as well, but seems to offer some troubling qualities (like having neither subject nor object) that may make it unwieldy if combining it with a discussion of rhetorical spatial features (thinking here of the MOOC) – that is, of course, unless I weave in ANT.

In summation, I have to end with a reference to the graphic at the beginning of Chapter 1 in Deleuze/Guattari. My house is full of musicians, so staff paper is familiar to me. And when I first spotted the graphic I was reminded of what my book of blank music staves looked like in the hands of a two-year old with crayons. I did not at first spot the rhizome. In fact, I’m still not sure I do. But if we’re talking about the difficulties in crafting visual representations of data from a highly complex subject that seems perpetually in motion (in terms of theorizing, anyway), then yes. I can see it. Or maybe it’s just the Rorshach representation of our overflowing minds at the end of a very busy semester.

Rorschach Image

Rorschach Image

Works Cited:

Deleuze, Gilles and Felix Guattari. A Thousand Plateaus: Capitalism and Schizophrenia. Trans. Brian Massumi. Minneapolis: Univ of Minnesota Press, 1987. Chapter 1 only

Rainie, Lee and Barry Wellman. Networked: The New Social Operating System. London: MIT Press.

Scott, John. Social Network Analysis: A Handbook 2nd ed. Los Angeles: Sage, 2010. Chs. 1-3.

Case Study 3 — MOOCs and Student Learning: Under the Microscope

The rhetorical nature of classroom spaces has certainly influenced our field’s scholarship when exploring digitally mediated writing classrooms. Terms such as constructed, architecture, location, ecology, environment, and space appear regularly in our field’s discussions of where and how writing takes place in FYC (first-year composition), typically in terms of ways location influences and mediates student identity and pedagogical practices. However, spatiality also provides other useful layers of analysis when exploring the composition classroom and our field’s discourse. Michel Foucault argues that we must explore discourse “through the use of spatial, strategic metaphors” (emphasis mine) if we hope to perceive “the points at which discourses are transformed” (qtd. In Binkley and Smith). While Foucault was concerned with “relations of power,” this Case Study is designed to suggest that our exploration of composition classroom spaces need not be limited to the geometric, architectural renderings of four walls, tables, and chairs, or – for that matter – a computer terminal, a Blackboard platform, and an Internet connection. In the last two case studies, I have examined MOOCs from a structural lens (how it works) as well as a pedagogical lens (how we teach). For this case study, it may be productive to “drill down a level” and use a different architectural metaphor to theorize MOOCs, this time using a lens that foregrounds the learning process (how students learn) itself. Given the subject of MOOCs as a space for learning and sharing knowledge, it seems intuitive to utilize a neuronal network as a fitting and productive metaphor with which to explore this Object of Study (OoS) as not only an environment of constructed connections but as a representation of cognition – how humans learn.

A Brief Literature Review / Overview

Three scholars provide the foundation of this Case Study, all of whom approach the subject of learning and composition studies for somewhat different purposes. However, their points – or nodes – of intersection provide an interesting network of terminology and theory with which to inform my approach to this OoS. Margaret Syverson takes an ecological systems’ approach to the subject of the composition classroom, while Bill Hart-Davidson’s article is more narrowly concerned with MOOCs and learning theory. The final component of this Case Study is one of the early designers of MOOC-based college learning, Stephen Downes, who builds upon George Siemens’ theory of Connectivism (an outgrowth of Vygotsky’s theories of learning and Hutchins’ theory of Distributed Cognition) in his work in MOOC design and deployment.

Syverson begins her book on An Ecology of Composition with the premise that a student’s “process of composing” – i.e., learning – takes place within a dynamic “complex system,” which she theorizes using ecological principles (2-3). Writers interact with and are affected by this environment, as they learn through a variety of (mediated) encounters: instructor-student, student-student, readers-writers, etc. She explains such interactivity is a “network of independent agents – people, atoms, neurons” which “act and interact in parallel with each other, simultaneously reacting to and co-constructing their own environment” (3). Her theory is an interdisciplinary one, borrowing from the fields of biology, ecology, behavioral sciences, and learning theory in order to address what she perceives as gaps in our field’s ability to account for student writer improvement (or lack of same) (2). She argues that our discipline often focuses primarily on the “social; there is little discussion of the material or physical world as a significant component of composing activity” (24).  If we approach this idea of composition as an ecological system, one which narrows the lens to the realm of learning, then a neuronal metaphor may offer new language and frameworks with which to consider the MOOC as a space for composition.

Stephen Downes refers to George Siemens’ definition of connectivism as “the thesis that knowledge is distributed across a network of connections, and therefore that learning consists of the ability to construct and traverse those networks” (Slide 15, Slideshare). Their MOOC, which he describes in a Slideshare presentation from 2009, explores the underlying learning theories informing the structure of the MOOC itself in light of their attention to how students best learn. While his course is not specific to freshman composition content, his theorizing of learning taking place within a network – complete with discussions of how distribution nodes like Moodle (slide 20) Twitter (slide 24) and UStream (slide 25). Each of these components creates the “mechanisms to input, process and distribute content” (slide 27) – the course map — but students themselves “add to the map” (slides 46-56). Both Downes and Siemens’ work on MOOCs provides the “ideal” baseline for my approach to composition MOOCs.

Vygotsky's Zone of Proximal Development, from blog of Johnna Lorenzano 2012

Vygotsky’s Zone of Proximal Development, from blog of Johnna Lorenzano 2012

The key contributor/node of operationalization for this third Case Study is Hart-Davidson’s article recently published in Invasion of the MOOCs: The Promise and Perils of Massive Open Online Courses, which focuses on student learning – specifically learning to write — in digital environments.  He observes that digital technology like MOOCs may promote “peerlearning,” which he asserts is “the way most humans actually learn to write” (212).  His analysis relies heavily upon Lev Vygotsky’s theory of learning, and especially the “zone of proximal development” principle, or ZPD (212-213). Briefly, we might summarize this theory in terms of a composition classroom learning model as “I do – We do – You do”: the instructor provides the learner with a scaffolded structure of activity that is at first mediated through modeling, then co-created or co-supported with student involvement, until finally the student requires no further mediated support and proceeds independently. Hart-Davidson summarizes Vygotsky’s importance to his approach to writing in MOOC classrooms by pointing out that peer learning involves “networks” – each individual bringing to the mix “a rich set of resources” that “boosts the learning potential” (213). The “zone of proximal development” or “ZPD” allows students to perform (i.e., write) and learn “better than one of us alone because we are surrounded by resources – one another – to scaffold our learning” (214). In such a network, “[t]here may be no stable individual ‘experts’ at any given moment, but among the group there exists a collective ability for a successful performance” (214).

Hart-Davidson’s contribution to this next layer of analysis is especially productive here, as he asserts that these peer networks and their resource potential lead to “the possibility of … near-constant connection with a peer network [as]…the best reason to think about digital technology in relation to writing, learning, and teaching” (215). Along these lines, he points out that MOOCs as a “model of learning” are far too often designed as a “learning one-to-many” model, which evidence suggests “work less well than peer learning in the zone of proximal development” (215). Thus, Hart-Davidson’s study of MOOCs as theorized using learning theory provides a sense of the framework in which this Case Study may fit.

Neurobiology as Metaphor: Conceptualizing Learning as a Knowledge Interactivity Network

While it should be acknowledged here that Downes resists the equation of the computer = human mind analogy as a myth, his reasoning behind that resistance offers a useful segue into the use of neuropathways as a more precise and productive metaphor. Downes writes that the equation of the way our brains work – through external stimuli, transfer of information through neurotransmission signals – at first glance may seem akin to the type of “processing” performed by computers, but he rightly argues that communication is much more than a simple transmission to be processed (Connectivism 122-123). Moreover, he points out that the originating metaphor of mind:computer originated prior to the technology itself (123), and as our understanding of the brain physiology has advanced, so too must the metaphor.

Borrowing heavily from the online textbook chapter, “Neurobiology,” as a guide to this metaphor, I would assert that the way students learn to write in any classroom follows the same highly generalized schema of the brain function described as “(1) take in sensory information, (2) process information between neurons, and (3) make outputs” (“Introduction”).  However, such a model is obviously limited, and does not represent the complexity of learning and teaching that happens in composition classrooms – especially those that practice student-centered pedagogy models. Downes refers to the type of community networks typical of effective MOOC designs as “a ‘community of communities’” (Connectivism 120), a description which he illustrates using terminology drawn from the field of neuroscience. Downes’ description of a community-as-network asserts that “nodes are highly connected in clusters” and these clusters are defined “as a set of nodes with multiple mutual connections.” These connections are instrumental in the movement or transmission of a “sessage from one community to the next” (Connectivism 120). What makes Downes’ use of neurophysiology terminology so appropriate to this case study is the way in which he applies it to the MOOC. He clearly points to the less effective organizational schema of a classroom designed to move information unidirectionally in the “school-and-teacher model…which is a hub and spokes model” and favors the alternative “community of practice” mode which “maximizes the voice of each of its members” (121). His description of the theory of connectivism relies on terminology very similar in language and meaning to neurobiology, suggesting a useful correlation to the composition field is already in progress. For example, Cormier writes of “knowledge networks” and Spinuzzi (as well as other Activity Theorists) points to Hutchins’ theory of distributed cognition to illustrate how humans – not just freshman writers – learn most efficiently when in a collective and collaborative network of others.


At this point, it would be useful to create a map of correspondence between key neurobiology terms and analysis of learning in Composition MOOCs. Neurobiology definitions are drawn from Chapter 10 of the online textbook Rediscovering Biology. As terms commonly create the creative connection potential between metaphor and object, these become the means of addressing the key network questions at the heart of the Case Study. The primary terms are defined here; others are defined in the course of addressing key questions of networks in the section that follows.

  • NEURON: a “specialized cell” that “works by changes in its voltage.” It is dependent on, and sensitive to, changes in its environment in terms of ions. The chemical imbalances create movement across the membrane of the cell, leading to exchanges in material or electrical impulses (i.e., information).
  • NETWORK: a vast series of neurons that make up the nervous system and brain.
  • SURFACES or MEMBRANE: critical borders of a cell that facilitate transfers of energy, chemicals, and influence transmission or nerve impulses along “sodium channels.”  Transmission along these channels is only one-way.
  • AXON: the long extension at the opposing end of the neuron that “ends in ‘synaptic terminals’ which send signals to the dendrites of an adjacent neuron.”
  • DENDRITE: small extensions at one end of the neuron designed to “receive information.”
  • VOLTAGEGATED CHANNELS: see neuron and membrane definition.
  • EXOCYTOSIS: process in which neurotransmitters are released.
  • SYNAPSE: the “meeting points” between neurons.

How It Works: Mapping the Terminology to Questions of Application

1.    How does the metaphor define this OoS?

Neurobiology as metaphor provides a useful structure and vocabulary that in many ways parallels the MOOC as a student learning space. This parallelism seems well suited to facilitating an exploration of key concepts of neurobiology as a means of illuminating the connections between MOOC designs. Through this, I am hoping to discover new means through which to analyze how MOOCs may best maximize the benefits of networked learning and knowledge transfer as key features of a technology-mediated writing classroom space. A case study of this length cannot possibly fully develop such a plan, but it may provide the groundwork for a more intensive operationalization at another time. In short, this Cyborg-theory may lead to a fully realized Franken-theory for Composition MOOCs.

The neurological network system of neurons may be visualized as a network within a network, a scalable system w/in a system. While any writing classroom might borrow this metaphor overlay to explain the relationships between participants within the classroom, as well as the relationship between the classroom and the educational institution hosting it, the MOOC classroom model creates additional areas for analysis. While the previous two case studies examined other layering possibilities (the structural lens, followed by the  pedagogical lens), a neurobiology metaphor allows for a more narrow scale of lens, allowing for a closer examination of what is at the heart of the classroom space: how we learn. The neurobiology metaphor provides a way of parsing that process as both a biological as well as a writing theory network of activity. The connection seems obvious, given our field’s emphasis on accommodating multiple learning styles in our lesson designs, as well as a call to be hyper-aware of technology’s mediating power and influence on pedagogy as well as learning, a vigilance called for by Cynthia Selfe in her 1999 book Technology and Literacy in the Twenty-First Century: The Importance of Paying Attention. 

Cynthia Selfe Cover Image

Cynthia Selfe Cover Image

Despite this utility, this metaphor may not be as widely useful in terms of mapping all of the connective potentiality for learning as mediated through a Composition MOOC. What it does provide, however, is a useful redirection, moving the discussion out of the realm of socio-cultural theory and into a more pragmatic realm of asking, “How does this space and technology facilitate learning and transfer for our student writers?” The neuronal pathway activity that corresponds to learning and memory are part of that deeper layer, a layer that serves to reinforce attention to the student perspective.

2.    Nodes & Agency: Relationships Defined & Transformed by Neurobiology (What and/or who is a network node & how are different types of nodes situated?)

An immediate assumption commonly ascribed to node identification within a networked classroom like a MOOC is that the human participants are the nodes. Another possible and logical application is that each mediating digital feature (such as those examples illustrated in Downes and Siemens MOOC) serves as a node, attracting and housing as they do participation, direction, and collaborative action. For example, students working in a Composition MOOC might be asked to participate in a collaborative space such as a Wiki to create a group research writing exploration project, creating a node of activity predetermined by the primary instructor. Such a node would simply be a creation of the instructor in terms of course design, but becomes a co-created space thanks to the ways student participants use it.

In Hart-Davidson’s article, he represents these learning communities through visualizations which, when compared to an image of a neural network, suggests possible overlap potential between the two systems.

Bill Hart-Davidson, "Learning Many-to-Many" (c) Creative Commons License

Bill Hart-Davidson, “Learning Many-to-Many” (c) Creative Commons License

Hart-Davidson reviews “the way learning involves interaction” (215), incorporating graphics which “represent…our thinking about what writing classrooms should look like” and “the kinds of interactions we think best facilitate learning to write” (216). He uses these representations to explore how, in the history of composition studies, we have “decentered” the traditional classroom model in a “disruption of the lecture model in favor of more engaged, peer-learning models in the undergraduate curriculum” (quoting Harris, 216). His “one-to-many” model (the center graphic above) is the lecture model (216), contrasted with the preferred  “studio model” (above left) or the one-to-one system (above right) of “peer groups – few to few” (217). He locates the new MOOC model – see graphic below as a “many-to-many learning infrastructure” that may be the apex of online learning modes, one which he asserts “[m]ost…MOOCS…get wrong” (217).

Bill Hart-Davidson, "Learning Many-to-Many" (c) Creative Commons License

Bill Hart-Davidson, “Learning Many-to-Many” (c) Creative Commons License

Just as a neural node – the neuron – serves as a locus or site of transmissions between neurotransmitters and neuroreceptors, it also serves as a facilitator of that transmission of signals (knowledge or information) via synapses, defined as the “meeting points” between neurons (Chapter 10). The synaptic space separating the two neurons is more than just a gap; these are “functional links between the two neurons” over which “signals are transferred” (Chapter 10). This transfer is facilitated by structural configurations, key to the system’s operation and what we might refer to as “knowledge building.” As mentioned earlier, the discourse of “space” is one that is a common site of tension discussions of pedagogy, access, technology, and digital spaces, and therefore may be reconceptualized using this metaphor.

The students, instructors, and teaching assistants operating in a Composition MOOC (such as the situation described by Halasek et al. in Case Study 2) might be described using these terms, as long as the classroom is designed according to the “Many-to-Many” model explored by Hart-Davidson. Yet an alternative representation may suggest that instead of seeing these nodes / neurons as the active agents in both the productivity as well as design and direction of the learning (via synaptic transmissions), they might be perceived as the larger framework itself, with nodes being located in the transmissions themselves. This alternative, however, is troublesome in terms of metaphoric alignment, and may be better expressed as networks of nodes embedded within networks of nodes – a complex system understood in terms that function equally well along a scale of size. In other words, individual neuronal nodes might be interpreted as sites of collaborative activity set up by the course designers as infrastructural lines of connectivity potential (like Downes’ examples of Twitter, the course Moodle Forums, or UStream). However, the metaphor also allows for a smaller scaled analysis, with each node / neuron representing the human actors in the system, learning through connectivity. This is the feature which aligns best with Syverson’s Ecology of Composition, and – more importantly – Hart-Davidson’s description of learning in a MOOC space.

Image of Neuron. The dendrites are in green; the axon is in blue. Taken from

If we think of the brain as an incredibly complex system, one in which neural pathways are active and creating multiple connections and covering a wide range of spatial locations, it would be difficult to envision a successful MOOC as one in which a “learning one-to-many” model would produce the kind of learning and writing our field has come to accept as optimal. However, this is also one area where the metaphor may falter, as the synaptic transfer occurs in “only one direction” over synaptic space (Chapter 10). As our field actively resists returning to any practice premised upon a one-way power structure (i.e., transmission) between teacher and student as described in Freire’s banking model of education, this unidirectional transfer is troublesome. However, what if we think of this as a communications network, in which communication between speaker / rhetor / writer and listener / audience / peer reader (or instructor) requires that we see this in terms of delivery, not power? In this light, an understanding of presynaptic and postsynaptic neurons create a critical unity, perhaps even in terms of collaborative energy. The presynaptic neuron’s firing transmits information across the axon, a “long extension at one end of the neuron that “ends in ‘synaptic terminals’ which send signals to the dendrites of an adjacent neuron” called the postsynaptic neuron. These neurological elements may be rather easily translated into a discussion of peer-to-peer communications when student writers are framed as co-creaters of the learning taking place – made possible by the type of peer-to-peer activity promoted by Downes, Siemans, Syverson, and others who see the composition classroom as more of an ecology than a top-down delivery system.

This adjacency may be another area where this metaphor falters. The neurological system is predicated on physical proximity – a system of neurons transfer information based on physicality. Can a MOOC space adequately replicate this in a way that is as productive to learning as a face-to-face classroom space provides? This is a key challenge to Composition MOOCs. Proponents of MOOCs like Downes would argue that the digital technologies available to us as teachers allows for a level of interactivity not possible just years ago. Digital tools like Skype, Google Hangout, Group Prezi spaces, and even Facebook create potential for what we might refer to as synaptic plasticity, a feature of the human neural network that promotes change as a way of ensuring viability and learning (Unit 10). Creating new forms of synaptic spaces may be a feature of the more effective MOOC designs. These are interesting tensions that may prove productive to future analyses.

3. Agency and Relationships: Nodes, Neurons, Synapses

The neurobiology text reveals that there is no standardized neuron – they come in varying sizes, all of which must be employed in signal transmission and processing activity for the network to function efficiently. This physiological characteristic of the neural network may become important to discussions of how learning takes place in a MOOC when considering the dependence on a collaborative “many to many” model (Hart-Davidson).  The premise of the composition MOOCs deemed “successful” (although no real assessment studies have been done to substantiate that) is that learning is decentralized; in other words, the massiveness of the MOOC space demands a model of classroom design and learning facilitation that employs peer-to-peer knowledge building. As Hart-Davidson observes, “digital technologies” have the potential “to get us closer to supporting the way most humans actually learn to write” (212). More specifically, he is pointing to “Peerlearning” (212), a term that stems from Vygotsky’s theory that employs “peer scaffolding” (213). In essence, this theory is based on the idea that “we learn most and most effectively from peers rather than adults or other figures” (213). Even though Vygotsky was writing about children, his theory has become an important thread in writing center theory as well as in composition. Further, if we apply the neurobiology metaphor, this becomes increasingly important to discussions of Composition MOOCs.

Neuroscientist Wolfhard Almers (“Expert Interview Transcripts”) indicates that the neuronal system is massive, making it a suitable metaphoric partner to this discussion of learning networks in MOOCs. Moreover, the size and activity of neurons in the brain are not uniform: “On average, [neurons] make about a thousand connections, very roughly. But there are neurons that that send a signal to only one other cell. And there are other neurons that get input from only, you know, maybe ten cells. So it varies quite enormously. There are big neurons and small neurons” (Almers, “Expert Interview Transcripts”). This may suggest that productive activity taking place within the network between cells (what we might call learning as knowledge transfer) isn’t dependent on one node (the teacher or tutor in the one-to-many or one-to-one model described by Hart-Davidson). In Composition theory, this valuation of the individual student contributions and voices is important to a student-centered classroom framework, one which accounts for varied learning styles in classroom design.

A Synapse, Image from Rediscovering Biology, Chapter 10 “Across the Synapse”

The neurotransmitters are the key to connectivity within the network, and specifically between synapses. Neurotransmitters are the key to movement within a neural pathway. A chemically-based reaction to stimuli, these “energy impulses” create a connection between two neurons. The very act of transmission transforms both neurons, opening “channels” and allowing movement through the phenomenon not unlike a differential seeking balance (Chapter 10). This action may be useful to discuss as a metaphor of how the types of peer writing practices employed in a MOOC writing class transmit and encounter text; emphasizing the rhetorical importance of audience by introducing the authority of “reader” may change or alter the writer’s perception of what he or she is doing and can have profound effects on a student’s understanding of the process and the text. (Lisa Ede and Andrea Lunsford wrote about this topic decades ago and more recently in a compilation that explores the current trend in English Studies to better foreground audience in Composition.) The usefulness of this metaphor is wide ranging, as the neurotransmitter’s role as agent or node can be applied to questions of student agency, affordances of the system itself (that is, technology choices made by both the course designers as well as the students to facilitate learning and/or writing).

4.    What is moving within the network?

The neuronal system is akin to a cascade. One neuron does not work in isolation – it is a network of networks, embedded in an ecosystem that makes knowledge acquisition (and memory – which might be described in terms of “transfer potential”) possible. Similarly, in a decentered composition classroom, the importance of collaborative peer networks is key to learning and writing growth. The question has been raised by Syverson, however, is whether or not the way we teach writing promotes the type of long-term learning that is needed to translate into transfer. She suggests that there “is no evidence that students are writing, reading, or thinking better than any time in the past” (2). What, then, is happening – or more to the point, not happening – in the learning space of the composition classroom? This is where the neurobiology metaphor may provide fresh pathways to address this.

The term Long-Term Potentiation (LTP) describes a process crucial to learning and memory formation in which the synaptic communication is modified over time. Postsynaptic neurons’ firing rate “depends on how much stimulation it receives from presynaptic neurons.” But in this process of LTP, the Postsynaptic Neuron keeps firing “at an elevated rate” as it has “become more sensitive…to a given stimulus” (Chapter 10). A feature of LTP that carries over into this analysis of MOOCs and learning is one that highlights the role of networked learning pathways as promoted by Hart-Davidson:

LTP, like learning, is not just dependent on increased stimulation from one particular neuron, but on a repeated stimulus from several sources. It is thought that when a particular stimulus is repeatedly presented, so is a particular circuit of neurons. With repetition, the activation of that circuit results in learning. Recall that the brain is intricately complicated. Rather than a one-to-one line of stimulating neurons, it involves a very complex web of interacting neurons. But it is the molecular changes occurring between these neurons that appear to have global effects.”

Such changes on the “small” scale of an individual brain takes on important nuance when that scale is upsized to “massive” in an online MOOC.

5.    How do networks emerge, grow, and/or dissolve?

If the MOOC platform for learning is designed to create new networks of connection among and between student participants, how does that help us better understand the way the pathways to learning are designed? If we interpret network growth in terms of learning, the neurological metaphor offers interesting possibilities for analyzing this in a Composition MOOC. The activity, growth, and nature of the neural system is characterized in terms of Brain Function:

“Basically, the brain works by communication between neurons. There are trillions of neurons in the human brain, and it’s the communication between these neurons that make us feel, think, be able to sense, to actually have consciousness. And it’s this continuing communication between neurons that’s important for processing information. But also, the synaptic connections between neurons in our brain are changing all the time, and it’s this change, or what we call “synaptic plasticity,” or changes in synaptic connections that underlie things like learning and memory, or any response to our environments, so the information we take in is processed” (Unit 10).

These processes of information transfer ideally lead to some form of cognitive permanence in the form of learning and memory. As Hart-Davidson observes, in terms of writing improvement (a sign of learning), “writing improves most for students that spend time revising” (219). Practice makes perfect, we’ve all heard. In the context of neurological network growth, learning means the creation of new pathways and new neurons. In neurobiology, this is referred to as Neuronal Communication / Memory. Neuroscientists study memory creation as well as brain physiology, and assert that the process of learning involves the creation of new networks between neurons. Learning, in other words, changes the brain and the way the nodes interact with other nodes.

Hart-Davidson refers again to Vygotsky’s theories of learning when he argues that the peer-network nature of writing in digital spaces like properly designed MOOCs (i.e., those that follow the many-to-many model) “provide … the ideal conditions for deliberate practice” as a result of the “connectivity” of such networks. Applying the metaphoric terms associated with neuronal communication and memory, such practice could be interpreted in terms of “enhancing certain connections between certain neurons…[to] sculpt out a pathway, a neuronal pathway through this network of neurons” (Chapter 10).

Beyond the basic neurophysiology of learning, this terminology also avails itself to exploring the nature of the MOOC ecology as both massive and open. The sheer number of students involved in the network creates collaborative potential that may not exists in a twenty-person f2f classroom. The variable of experience brought into the classroom also increases with the “open” nature of a MOOC, unrestricted as it is by limits of college tuition or geographical boundaries. Of course, there are other boundaries, such as technological access and / or equitability; however, if the sites built into the MOOC infrastructure are also open (i.e., free) with a reasonable level of operational skill required, this may become less restrictive if one considers that people who are currently opting to take MOOC courses have thus far been demonstrated to be non-traditional students. 

who takes MOOCs

There is the opposite to growth, of course. How do MOOCs fail, and what does that tell us about learning in MOOCs? There are numerous voices that weigh in on this: attrition rates are reportedly high for MOOCs, and many are designed with a one-to-many approach which has been proven again and again to be counter-productive for a writing course (Hart-Davidson). Of course, there may also be failure at the node level when students do not participate, thereby stunting the benefits of collaborative peer-to-peer interactivity and, in turn, learning. We see this as well in f2f classroom spaces, even without the “massive,” so how are these concerns about network growth or dissolution addressed if we apply neural network metaphor terms?

Networks grow best when student driven, but the instructor can facilitate these network nodes by creating software / program / virtual locations for such growth  (Google Docs, Group Prezis, Discussion Boards, Email). The University of Manitoba’s course “Connectivism and Connective Knowledge,” part of that University’s Certificate in Emerging Technologies for Learning program, is a useful example of a MOOC that utilizes what Hart-Davidson might refer to as the many-to-many approach to learning. New communication nodes that emerge “off the grid” – initiated by students to collaborate (Facebook, email, etc.) – are other ways which a MOOC network may grow and transform in pursuit of learning and connectivity. This might be explored in terms of Neurogenesis, the generation of new neurons. Until recently, neuroscientists believed this process ended by “early childhood,” but recent technological developments have led them to discover that “the brain maintains a reservoir of stem cells that are capable of generating new neurons” (Chapter 10), much like a networked Composition MOOC that encourages “peerlearning” (Hart-Davidson 212).

Networks falter when a MOOC is more xMOOC than cMOOC, a model that relies on the “one-to-many” educational delivery system (video lectures and quizzes and essays) described by Hart-Davidson. Networks may also falter if too little invention authority is granted to students. Some structural integrity (as course design) is needed to prevent a free-for-all and undirected – systems of scaffolding, like neuronal pathways. However, just as neuroscientists have discovered that neuronal networks grow new neuronal pathways as needed in response to new or increased stimuli, the same general metaphor-inspired principle may be applied to explore ways in which MOOCs may facilitate learning. Again, the Manitoba MOOC, and the idea of connectivism as explained here by course co-designer Stephen Downes, may provide a useful example of networked systems of communication and collaboration that illustrate neuronal-like connections designed to foster interactivity and exchange of knowledge to move the learning forward. The premise of an effective many-to-many MOOC course design is to accentuate these individual neural networks and make them part of the learning, not an accessory to it.

Conclusion: MOOCs have been cast by many skeptics (including many composition scholars) as a troubling “break” from traditional models of higher education. However, if seen through the prism of learning models, a Composition MOOC space may instead become one that facilitates creativity and independent thinking by participants who become co-creative powers within a network of learners. The concepts of neurobiology applied as both metaphor and learning theory may facilitate this view.

A limitation of this approach is that the metaphoric image of a neural network isolates the picture into one location. The neural network nodes are a very small part of a much larger system, equated to “a basic cellular mechanism in the brain” (Chapter 10). The dilemma for this application is how this “smallness” can correlate to the “bigness” of a MOOC. Some possibilities have been proposed, but there are other limitations.

What this metaphor does not do – and where an ecology theory might help – is properly explain how this fits into the wider system beyond that of a neural pathway, into the environment that provides the stimuli responsible for neuronal firing and transmission. For a Composition classroom, that might introduce other surfaces beyond the neural pathways and into the realm of stimuli and actions. Syverson asserts that we must see the composition process and students engaged in it as “situated in an ecology, a larger system that includes environmental structures, such as pens, paper, computers, books, telephones, … and other natural and human-constructed features, as well as other complex systems operating at various levels of scale.” Student learning, as Vygotsky might agree, takes place within “a meta-complex system composed of interrelated and interdependent complex systems and their environmental structures and processes” (Syverson 5). The metaphor of neurology does not extend the environment this far.

Finally, comparing the overall efficiency of a neural network to the learning going on in a MOOC reveals several gaps, the most obvious of which are the assumptions we must make in an online space for teaching composition in order to avoid allowing the MOOC to become a glorified test or worksheet bank. Perhaps we need to think about the type of student who might be in a MOOC; why is that student in THAT space? This question as well might be best answered with the additional overlays of such theories as Ecology. In the meantime, however, the neurobiology lens offers interesting ways to connect other scholars and Compositionists in a thoughtful exploration of learning facilitation in networked spaces.

Works Cited:

Binkley, Roberta and Marissa Smith. “Re-Composing Space: Composition’s Rhetorical Geography.” Composition Forum 15 (Spring 2006). Web. 1 Apr. 2014.

Cormier, Dave. “MOOCs as Ecologies – Or – Why I Work On MOOCs.” Dave’s Educational Blog: Education, Post-Structuralism and the Rise of the Machines.” 25 June 2011. Web. 1 Apr. 2014.

Downes, Stephen. Connectivism and Connective Knowledge: Essays on Meaning and Learning Networks. 19 May 2012. Creative Commons. Web. 30 Mar. 2014.

Downes, Stephen. “The Connectivism and Connective Knowledge Course.” Slide Share. 24 Feb. 2009. Web. 30 Mar. 2014. <>

Downes, Stephen and George Siemens. “Connectivism and Connective Knowledge: Getting Started.” MOOC course, University of Manitoba. 2009. Web. 30 Mar. 2014. <>

Hart-Davidson, Bill. “Learning Many-to-Many: The Best Case for Writing in Digital Environments.” Invasion of the MOOCs: The Promise and Perils of Massive Open Online Courses. Eds. Steven D. Krause and Charles Lowe. Anderson, SC: Parlor Press, 2014.

 Syverson, Margaret A. “Introduction.” The Wealth of Reality: An Ecology of Composition. Southern Illinois UP, 1999. 1-27.

Castells: Time and Space Walk Into A Bar…

Star Trek: "City on the Edge of Forever"

Star Trek: “City on the Edge of Forever”

Several times while reading Castells, I thought of science fiction and the philosophical musings about time, space, dimensions, and what not. So imagine my surprise when I read Castell use the phrase, “city on the edge.” His references to time and space as abstractions made the next jump inevitable: one of Star Trek’s most feted episodes, outlined here. For those of you unfamiliar with the series, time isn’t tied to space and permanency at all. Perfect fit for Castells.

The Wall Street Journal, "A Revolution In the Making." (Image by Ryan Etter)

The Wall Street Journal, “A Revolution In the Making.” (Image by Ryan Etter)

Chapters 2 & 3: Castells’ early chapters lay the historical groundwork for these next sections, establishing as he does his argument that we are a part of a global (not planetary) information revolution on or above the same level of significance as the Industrial Revolution. (See this Wall Street Journal article for some interesting connections.)

Instead of the manufacturing industry, however, the new revolution is based on communication technology. His book describes this new network in terms of nodes and links, diffusions and systems – with transformations and innovations occurring where ideas are exchanged, usually at nodes that “interact with economy and society” (62-69). This new economy, however, is not one of power in terms of energy production but “informational” in terms of mass communication and the “new culture” it creates (77, xxx). Interestingly, he argues that the infrastructure itself is not at the heart of this phenomenon – it is the communication itself (xxxvii). This is the economy of chained networks and nodes he describes as being the components of this network society – what seems remarkably like an ecology.

Connections to Ecosystems and Neurobiology: In his early chapters, he outlines key agency nodes that are the basis of this society: information, pervasiveness, networking logic, flexibility, and convergence (69-71). The product of this new economy is not goods and services, however; it is “information” (78). Therefore, could it be he is describing not just an economy of knowledge, but an ecosystem of knowledge with information as its key medium for growth? Thinking back to the neurobiology readings, the chemical-based electrical impulses that constitute information and the neuronal system they travel could be considered a medium. Like Castells’ description of the economic system of his new society, these information corporations form strategic alliances very much like Spinuzzi’s chained activity networks comprised of nodes (each one an alliance). This system evolves and diffuses along what Castells calls a “global web” (122) – growing in ways that sound remarkably like neural pathways, networks within networks (131). I found his description of diffusion rather interesting, extending knowledge from major concentrations of states / businesses typically characterized as dominant economic / power centers (nodes again), but “skewed toward and defined by advanced cultures” (126). His  explanation of this seems to replay a long history of the ways in which economies and their “affordances” favor the strong and the rich — discrimination that is based on value systems, but in this economy, it’s information and communication that are the valued coins of a global system built on local nodes (134). It is the technology itself, Castells asserts, that changes how the market establishes that value (156), citing the growth and confluence of tech-influenced infrastructures composed of financial markets, software companies, companies like Yahoo that facilitate communication, and companies like Amazon that create a new market base of strictly online commerce (148-153).

So, key concepts for Chapter 2 might be summed up in these two quotations:

  • “The new economy brings information technology and the technology of information together in the creation of value out of our belief in the value we create” (160-162).
  • The “[e]ssential component of the new economy: networking. The organizational transformation of the economy, as well as … society … are … a necessary condition for institutional restructuring and technical innovation” (160).

rand_world_1_horizIn Chapter 3, Castells discussed a history of trends in the emergence of this new culture. He goes to great lengths to be sure we as readers understand that by culture, he does not mean “a set of values and beliefs linked to a particular society” (163). Rather, he grounds his definition of the term in the idea of “ideational bases for institutionalized authority relations” or “organizational logics” (164) – a concept that again seems highly similar to our exploration of intersecting ecologies (Guatteri, I believe). In this chapter, he takes us through the evolution of “the large corporation,” moving through Fordism (166) to the new management he calls “Toyotism” (169).  From Taylorism / Fordism to this new era of management and corporate systemization, he points to the evolution of what he calls a “horizontal corporation” (176) that is in essence “an articulated network of multifunctional decision-making centers” (178). Networks like the Cisco Systems are the new archetype that has emerged to replace the former (Fordism) with a “business model of the Internet-based economy…a global networked business model” (180). Like Bateson, Castells notes that the importance of the mind or “mentality” – not the tools or the computer-based infrastructure –is the driving force of this evolution (185). However, Castells also notes that without the computer, none of this would have been possible (185). Yin and yang.

He coins the phrase “spirit of informationalism” as a characteristic of this new networked society and, while rather interesting, it seemed as though it was Castells’ effort to avoid the traditional conceptual frame of the term “culture” in this discussion. He seems to want this term of “culture” to exist in multiple dimensions – which at times makes it a bit confusing, as though he wants it both ways – but settles on a definition of this defining “spirit” as “the culture of ‘creative destruction’ (215). Perhaps this is an inevitable dilemma of any discussion of this sort of networked ecosystem based on knowledge / information / communications – we are exploring a system that employs both the philosophical as well as the physical. Some ephemerality is to be expected, I suppose. (Just so long as we don’t need to follow Bateson’s use of LSD to be fully versed in the proposal.)

Chapters 5-7: With the basic definitional concepts behind him, Castells moves into a discussion of the “culture of virtuality” in Chapter 5, beginning with a brief discussion of language and communities. This chapter reminds me of the Amanda Case TED talk, “We Are All Cyborgs Now” (see video below) in which her explanation of communication technologies (ironically sponsored by Cisco) allowing us to fold space seems to offer an example of Castells’ “space of flows” and “timeless time.” He walks us through the influence of Marshall McLuhan in the 1960s on the “diffusion of television” creating “a new galaxy of communication” (358) and an environment of communication (362). Reviewing the criticisms of television as a communications media, Castells points out that while the system may be one-way, the communication process still allows for “each culture and social group” to form “a specific relationship to the media system, such as might happen if surfing channels is understood as a way the audience “create[s] its own visual mosaic” (370). This chapter explores the formative pressures created by government, business, and social policies / politics have influenced the emergence of communication systems beyond (diffused from) the television set that have contributed to the “notion[s] of mass culture” permeating this discussion (359). He asserts that references to this “mass media” system is actually incorrectly framed as a “form of culture”; it is more accurate to refer to it as a “technological system” instead (364). There was simply SO much packed into this chapter that I find myself forced to gloss over the depths to resort to summarizing it from the shoreline: he begins with culture and language, and he concludes the chapter with the observation that our new systems of communication blur the boundaries between virtuality and reality so much (he refers the the Dan Quayle-Murphy Brown episode as proof) that it creates a “new text of the real and the imaginary” (405). This creates the potential to “embrace and integrate all forms of expression” as well as “radically transform space and time” in its creation of “a new culture” (406). As students of new media, this observation should either excite or frighten us to no end.

Link to my Object of Study: This chapter’s observations led me to wonder whether MOOCs behave similarly to how Castells describes the television interactivity conundrum. I wondered if this isn’t an illusion, however, when proponents of MOOCs assert that the virtual space allows students to be co-creators of their learning and the learning space. But how much co-creation is possible if the spatial design must conform first to the educational system that funds its existence and awards credence by framing it in the system of milestones / assessment practices expected of an institution of higher education? Knowledge diffusion may be less prescribed, but the structural system would still dictate some degree of potential pathway order. In fact, Castells remarks that the “[s]patial inequality in Internet access” cited in many MOOC criticisms “is one of the most striking paradoxes of the Information age, given the supposedly placeless characteristic of the technology” (377). Yet it seems this may be countered by what Castells refers to as the system’s potential for “innovation, flexibility, and decentralization,” which then “translate into new patterns of communications” (385-86).

Chapters 6 and 7 move down a more theoretical, even metaphysical, pathway as he introduces two concepts: the space of flows and timeless time. These two chapters were especially challenging, as I’m clearly all about pragmatic application of theory. (This is where my reference to the Amanda Case TED talk came in handy, as a way to provide a touchstone reference.) The concept of space / flowing reminds me of the neuron pathways and “channels” described in last week’s readings, but it also seems to echo the theories of Activity and even Actor Network, where the movement and agency highlight both the limits and the permeability of boundaries (a form of space). One of the more interesting observations in this chapter was his assertion that “space is the expression of society” (440). It is as if he sees space much like we might see boundaries and pathways – but acknowledging that the “map is not the territory” (Bateson’s reference to Korzybski on page 455). This would seem to substantiate Castells’ comment that “[s]patial forms and processes are formed by the dynamics of the overall social structure.” A bit frightening is his observation that the “background of meaning” informing this space is no longer cultural “experience, history, and specific culture,” but is being replaced instead by “dominant interests” (450). To avoid this, Castells champions the concept of “nude architecture,” or his “space of flows” (450). But how can any type of architecture be totally devoid of influence or neutral? Even the hypothesis itself places a preferred value on this new culture and network system, lauding its benefits while also pointing out its dangers. This is a point in the book where I think the author extends his toe just a bit too far over the line.

In sum, his “space of flows” appears to be – like our neuron studies – a metaphor meant to replace pre-existing models or interpretive lenses with something more nuanced, more suited to the space/non-space that is our concept of the vast web structure of the Internet…a structure that can only be conceptualized if we include the non-forms like space, movement, ideas. And because our concept of space is grounded in not-space (i.e., the nodes of the material world), the same must be true of time. Humans are creatures dependent on the concrete – we tie ourselves to timelines and structures so we have a sense of place and identity. Castells argues that “linear, irreversible, measurable, predictable time is being shattered in the network society” (463), and we therefore need a new form – his “timeless time” – to take its place. He defines these two concepts as linked, and much like Case refers to the “folding of space” through a communication technology, one shapes the other…and in turn both shape / characterize this new “network society” (499).

Castells’ philosophy of society and technology is compelling, yet I wonder if it can really be a replacement or even an evolution if it can only be grounded through negation of existing frameworks of human activity and concrete concepts such as place / space. Thinking back to CHAT and the call to revisit the canons of our culture, I am reminded of Ecclesiastes: “There is nothing new under the sun” (Ecclesiastes 1:9) if one of the primary hubs of new systems remains the human being at the center of it all…the one who has the agency to step back and forth through portals christened “The Guardian of Forever.”

Works Cited:

Bateson, Gregory. Steps to an Ecology of Mind. New Jersey: Jason Aronson Inc., 1987.

Case, Amanda. “We Are All Cyborgs Now.” 11 Jan. 2011.

Castells, Manuel. Rise of the Network Society. 2nd ed. Malden, MA: Wiley-Blackwell, 2010.

“City on the Edge of Forever.” Star Trek. NBC. 6 April 1967. Television.

“Unit 10: Neurobiology.” Rediscovering Biology. Annenberg Foundation. 2013. Web.

Mind Map April 6th: Neurons and Synapses

imdb: "The Frankenstein Theory" movie poster image

imdb: “The Frankenstein Theory” movie poster image

This week’s mind map began with an image choice that was — excuse me — a “no brainer” (you’re welcome, punsters; and I’m sorry, punsters). The image of the neuron — with all its accompanying transmission components — seemed well suited to my attempts to show connections and flows of information through the Popplets. Clearly, I love brain-based metaphors. But I digress…

The connections we discussed in class regarding Ecosystems and Brain Chemistry revealed several assumptions I had been working through that may have falsely equated the two on some levels. Therefore, even though I’ve positioned the two sets of readings close together to signify connections, thanks to comments made by Daniel in our FrankenTheory Activity about nodes and neurons and his comments during class about seeing the biosystem as the core of a larger ecological system, I’m also seeing the “gaps.” Dr. Julia explained such gap perception in terms of distributed cognition allows us to use the neurology material as a metaphor for our networked OoSs, but we must be mindful of the limitations — thus, the need for a FrankenTheory.

So, the links I drew in the Mind Map between Bateson in particular — thinking as I was of his reference to Korzybski that “the map is not the territory” (455) — seemed to fit my emerging understanding of the metaphor’s possibilities and limits. An example of my thinking on this showed up in my notes:

“Also opens up the chance to speak about affordances if we link this to an ecology. Is it the same, though? Can we talk about the neuronal network as an ecosystem? Perhaps not, although pointing to the ecology as a way to extend this metaphor, talk about the connections to other, non-self enclosed networks might be a way around this.”

cyborgbrainOther unexpected connections emerged as I looked over my Popplet’s existing links. For example, the explanation of neurotransmitters reminded me (and Leslie) of the “How It Works” bus processes, and the potential for multiple-directionalized connections and transmissions.

Still another connection with the bio text took me back to Guattari and Bateson on subjectivity, specifically to Guattari’s politicized definition of ecologies in that we must be theorize our own places in this ecosystem as “in the weeds,” not a god’s-eye view. So, out shoots a tendril to Guatteri and to Bateson. From there, I return to Distributed Cognition, which adds a wider, ecosystem-like layer beyond the neurobiology “core” (thanks to Daniel for that term) – and provides a systems framework for it to place the whole shebang into a cultural perspective, opening up a possible “node” of connection with my OoS of composition MOOCs. In fact, for my 3rd Case Study, I feel like I must combine the threads of both neurobiology AND ecosystem theory (especially Bateson) in order to do it justice.

Thus do I come to my wrap-up for this week’s Mind Map choices: the ecosystem / neurobiology connections illustrate how even a metaphor can function as a means to open new ways to discuss something still “new and strange” like a MOOC, hopefully in ways that will allow for the different space of a “classroom” network and all of its potential pathways.





An Ecology of Reading Notes: Castells & Neurobiology, or NeuroEco

I’ll start this week with the readings on neurobiology because of my interests in that field. I’m actually quite fond of making references to mind mapping and neurobiology when looking for metaphors to explain critical thinking or other complex activities (whether for my own use or for my students – pity them). I’m sure this has to do with my life-long interest in the sciences, so it’s only natural I gravitate toward such analogies as black holes, synaptic connections, neural networks, and – of course – the Borg.

The Borg, Star Trek: The Next Generation from Memory

The Borg, Star Trek: The Next Generation
from Memory

While reviewing these materials, I was struck by the overt parallels with our theories covered thus far in terms of networks and network activities: nodes = neurons, boundaries = cell membranes, and neuron-to-neuron transfer = over gaps. So now that it’s clear that both these filters are permanently seated as my reading lenses, these connections – and their links to some of our theorists and our theme – take on a new level of profundity when linking out to ways my classroom pedagogy (and my Object of Study) can be articulated with the help of this week’s readings / concepts.

In sum, this chapter provides an overview of how the brain’s neurons essentially constitute networks within networks, part of the higher brain function – what the textbook refers to as a systems-level operation. These neurons process and transmit electrical impulses and chemical information as part of knowledge generation, transfer, memory, and a host of physiological functions. The description is vividly reminiscent of the chained activity system described by Spinuzzi, except that these neural pathways seem anything BUT “informal linkages” (Spinuzzi “Networks” 74). The textbook section on Neurobiology parallels many of our recent discussions and, of course, Castells’ preliminary chapters outlining a history of knowledge development (a knowledge economy).  Our brains take in information, process that information, and then create some product our “outputs” (“Introduction”).  With advancing technology such as imaging systems, researchers are able to examine knowledge at the molecular level, observing exactly how “neurons talk” by comparing the process to a “24-hour call center” (reminding me of Activity Theory). (This change of perspective remains that of an observer – something our previous week’s discussion pressures thanks to our attention to the Observer vs. Integrated Participant roles we as humans play within an ecosystem.) The specific nodes in this “talking process” that strike me as most compelling and connection-rich are the concepts of “voltage-gated channels” (buses come to mind), “LTP,” and the system of movement / boundaries / and mediators that is the neuron.

A Synapse, Image from Rediscovering Biology, Chapter 10 “Across the Synapse”

I found several of the key vocabulary terms as defined by the glossary important to both this summary and my OoS theory:

  • Neuron = a cell referred to as a type of “battery” which collects and transfers information. Key to communication in cellular activity. In essence, we might see it as an activity node. Two ends, one for reception, one for delivery/transfer. Neurons “make the connections” (Neurobiology video).
  • Dendrite = found on the neuron’s surfaces, akin to a “tree” structure, these receive chemical/electrical messages
  • Axon = found at the opposing end of the neuron, transmits the processed incoming signal to other neurons
  • Membranes = cell barriers, surfaces
  • Synapses = what connects two neurons in order to exchange information
  • Receptors = receiving the molecular information, on a “post-synaptic neuron,” before transferring on the information.
  • Neurotransmitters = molecules that travel “across the synapse and, by binding to the receptor on the postsynaptic neuron,” key to signal transfer
  • Exocytosis = when neurotransmitters are released
  • Vesicles = described like a “soap bubble,” nodes of transmission for the neurotransmitter. The boundaries or membranes essentially carry the information, serving like a moving truck for the information.
  • LTP or Long Term Potentiation =  key to memory. If a neuron is hyper stimulated, say with increased sensory stimuli like neurons become “more sensitive to stimuli.” It has to do with the pre-synaptic and post-synaptic connections. Rather than a synchronous 1:1 pre- post- activity, increased input or stimulation increases the firing duration. This might happen because more neuro-transmitters are released. Or, the receptor is modified somehow (chemically), increasing the action potential.
  • Neurogenesis = a key to adaptation. Apparently the adult brain holds “in reserve” new / potential neurons, contrary to what was previously believed to be limited to early brain development which ceases at a certain maturation stage. New technologies revealed that the brain isn’t as much like a computer – with limited input / data potential – as once believed. Interestingly, this was discovered by looking at the gaps – examining activity that suggested another force was in play (Foucault’s traces).
  • Voltage-gated channels = either open or closed, “membrane potential of the cell,” by chemicals like neurotransmitters. These occur in the cell membrane of the neuron. Essentially, the charged electronic particles (ions) move according to the gradients of the charge (positive moves toward negatively charged areas and vice versa). These channels might be seen as communication avenues, or conditions with a culture that permits (as Castells might argue) potential energies to move information from the local to the global (xxxv) in a “space of flows” (xxxiii).

The dendrites are in green; the axon is in blue. Taken from

The textbook chapter’s focus is on neurobiology, and specifically neuron activity and transfer. The video mentions “molecular to global perspectives,” creating a possible node of connectivity with our ecology readings of past weeks, as well as Castells’ discussion of economics. In fact, there is simply so much here that resonates as a potentially powerful metaphor for our exploration of networks, especially those that involve human agency (a link to ANT certainly). The environment of the ecologies discussed last week seem to parallel in many ways with the process of neurogenesis. Changes in the environment (or ecology) affect the nature of the brain circuitry. Behavior and the brain combine, effects moving in both directions. Behavior regulates the response by the brain to the environment, as well as the reverse. Such “two-way” transmission results in transformation, not unlike the systems described by Castells when he explores ways in which “major social changes” – or our environment – are “characterized by a transformation of space and time in human experience” (xxxi), perhaps what might create what he calls a “space of flows” within a networked society (xxxiii).

Castells' The Rise of the Network Society

Castells’ The Rise of the Network Society

Castells’ primary focus appears to be an explanation of what he calls “a new form of society, the network society” which is a culture “based on multimodal communication” (xvii). Rather than providing us another theory, Castells asserts that this is a “structural analysis” (xix) – much like what we read in the Neurobiology Textbook. What is learned? Certainly a host of new terms, but also a means of examining familiar concepts in new ways…concepts such as knowledge, communication, connections, and structures.

Castells’ preface mentions the idea of “mega nodes” (xxxviii), an interesting concept of concentrated power, nodes that serve as switching points in the global network or system of economies. Castells seems to argue that these mega nodes – usually concentrated intersections located at “points of connection in this global architecture of networks” which “attract wealth, power, culture, innovation, and people” – are places of convergence or intersections that are not only geospatial but economic (xxxviii). The function of these mega nodes remind me of a TED video about “filter bubbles” as these mega nodes act as directional potential for those at the farthest reaches of this system, exerting control much like the LTP of the synaptic connections might function. Castells argues that “our societies are…structured around a bipolar opposition between the net and the self,” creating a “structural schizophrenia between function and meaning” (3). His opening chapter (chapter 1) explores the history of technology in terms of a revolution similar to the industrial revolution – what he calls the “information technical revolution” (29). Essentially, information technology is akin to the new energies of the Industrial Revolution” (30). The “pervasiveness” of information technology is woven into everything and “the mind is a direct productive force” in this system, not simply something that “makes decisions in the ‘system’” (31) The computers then become extensions of the mind, and this is where the neurobiology readings intersect, for the neuroscientists now see the computer analogy for our brain’s functioning no longer sufficient – it’s far more complex. Castells’ early chapters also reveal a complexity to which the neurobiology readings create an interesting parallel – or overlay – in the ways that such systems function. Since Castells pointed out early in his book that he was not trying to create a theory, only a structural analysis…even so, it still feels like a theory, given his references to economic/political powers tracing the creation of nodes and driving innovation into the pattern of the system (Chapter 1) and the existence of a “new culture” (xvii).

In fact, it is this local to global framework which pairs so well with the neurobiology textbook reading, especially since Castells is apparently locating his discussion of economies within communication  — specifically an economy based on information. He points to agency nodes, “material foundations of the network society,” that point back to our readings on ecology, and even as far back to Activity Theory and Actor Network Theory. In many ways, Castells’ early chapters illustrate the foundations of a network system that seems to move much like neurons and neurotransmitters do.

It’s all really heady stuff (no pun intended), and its grounding in information being communicated seems to connect in complex ways with the complex neurobiology model we read this week. It may take me a while to process all of this – but there is so much potential applications to studying MOOCs here, I’ll likely need to sift through it to pick and choose.

In the meantime, all this talk of brains and neurochemistry has led me to one of my favorite movie scenes. Perhaps an appropriate reminder of how we must sometimes tread carefully when working with networks and nodes.