Tag Archives: neurobiology

The OoS Matrix: FrankenTheorizing Composition MOOCs

What Is A MOOC?

What Is A MOOC?

Composition MOOCs: Theorizing Pedagogy, Space, and Learning.

Why Here? Why Now? As argued in earlier case studies, 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. Some of the most common concerns expressed by scholars and practitioners in our field about MOOCs are as follows:

  1. They will “devalue the current education system” (Friend).
  2. They will “disrupt” the same (Friend).
  3. MOOCs are a “lightning rod for virtually all that thrills and ails contemporary higher education” (Mitrano).
  4. They are simply another step in the commodification of higher education (Barlow).
  5. By that same token, “college leaders” see MOOCs as the competition, as MOOCs are – by nature – “open” and free of charge (“”What You Need to Know About MOOCs”).
  6. They are anonymous and diffused, thus threatening the teacher/student relationship.
  7. They foster or are founded on wrong-headed teaching practices.
  8. They threaten the role of and need for teachers.
  9. They turn teachers into mere “content developers” (Gardner).
Cover of Sullivan & Tinberg text, What is College-Level Writing?

Cover of Sullivan & Tinberg text, What is College-Level Writing?

Yet, there are other scholars in our field who argue that these digital spaces can, with careful attention to the space’s design, exemplify best-practice models of collaborative learning and scaffolded teaching practices found to be so productive in a face-to-face (f2f) first-year composition (FYC) course (Decker, Cormier, Downes, Hart-Davidson, Bourelle et al.). Some have even gone so far as to argue that many of the criticisms err by conflating MOOC classroom pedagogy design with higher education operations in general (Cormier, Gardner). This discussion reflects our field’s cautious approach to MOOCs in the spirit of Cynthia Selfe’s counsel on “the importance of paying attention” when it comes to 21st century technology literacies. As well, the debate itself seems to emerge from a common paradigm: the place-anchored classroom, one that often limits the “node-load” of a network to a basic binary structure of teacher-learner. However, as this semester’s case studies have demonstrated, a Composition MOOC encompasses a much broader scale of elements: it is a networked space filled with nodes and agencies that emerge from not only the basic system of learning (teacher to student), but ecologies of other systems as well (institutional, assessment, collaborative relations between students independent of teacher directives, software, texts, etc.). As such, when current theories of networks are applied to MOOCs, they are often done so as if all MOOC classroom designs are the same. As Decker points out, this is most certainly not the case (4). Indeed, some Compositionists argue that our field should consider a refreshed pedagogy for learning spaces like MOOCs (Debbie Morrison’s “A Tale of Two MOOCs”). The assertion is that traditional f2f methods and technologies cannot be simply overlaid onto such a complex system / space with any hope of success.

Be that as it may, this final case study is not intended to be an argument for or against Composition MOOCs. Rather, using key threads gleaned from the theories of Spinuzzi, Foucault, Bateson’s and Gibson’s ecologies, and Neurobiology, it is my intention to theorize the potentiality of such space by highlighting key areas of tension in the current debate.


Foucault, Archaeology of Knowledge cover

Foucault, Archaeology of Knowledge cover

Thread 1: Foucault’s attention to “unities of discourse” provides an open door through which to begin mapping an amalgamation of theory, and serves as the premise by which this theory will address the question of “why this / why now?” Put another way, Foucault’s concepts of gaps, hierarchies, systems, and traces are the elemental glue that holds this FrankenTheory partnership together, calling our attention to those theoretical areas of dissonance that often go unmapped (traces). Foucault’s rejection of a linear, universalist lens by which to explore networks of knowledge pushes at what often appears to be a primacy of Composition Pedagogy Theory (situated in an f2f paradigm) in many of the aforementioned tensions when it comes to MOOCs and English Studies. In essence, his theory establishes a primer for this FrankenTheory, as he defers to a concept of a web — of influences and events (a network) — as a more “realistic” way to see and explore knowledge and knowing (3). Indeed, he asserts that we must see knowledge in terms of a complex system through a lens defined by terms he uses to explain statements as nodes. He proposes a more productive network is not a stable system, but one of complexity and discontinuities which have the power to transform current theoretical frameworks (5). Foucault allows that his “notion of discontinuity… is both an instrument and an object of research” (9), and for this reason becomes what amounts to a genomic element to this attempt to create new theory for examining both the Composition MOOC and theories currently infusing the discourse.

http://www.learner.org/courses/biology/textbook/neuro/neuro_6.html

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

Thread 2: The field of Neurobiology contributes to this discussion in several important ways. First, as a metaphor, it frames the concepts of knowledge and learning in productive ways that can be extended into discussions of ecologies and complex activity systems, as well as the nature of discourse in technologically mediated / created spaces. The neuronal network mapping metaphor provides interesting ways with which to discuss learning and knowledge transfer within a networked system much like a classroom space. It also provides our field with a concrete look into the physiological network that is at the very heart of any learning space: the brain. Learning theories grounded in behavioral / psychology theories are all rooted in this central processing unit; considering the biomechanical processes situates the conversation in a way that moves the more theoretical and ontological discussions back into the realm of “how and where” of learning. Neurobiology, then, allows us to look at the potentiality for knowledge transfer in terms of “how” learners learn. However, the biomechanical will only move the discussion so far; the messiness of a “massive” system composed of many students from varying backgrounds, differently motivated, in many places, and mediated by diverse technologies may push a neurobiology-based metaphor beyond its limits. Alone, it is limited. Combined with these other threads of theory and operationalization, it becomes an important conceptual layer for discussions of the “how.”

Spinuzzi: Traffic Systems (image from NobleEd.com)

Spinuzzi: Traffic Systems (image from NobleEd.com)

Thread 3: Spinuzzi’s Activity Theory contributes in two important ways: (1) distinctive terminology that begins to move our focus from the biomechanical to the relational and (2) as a pragmatic illustration of complex systems operationalized. His work with Actor-Network Theory and Activity Theory illustrates the power of Foucault’s gaps and disruptions when seeking common borders at which this conversation can turn. For example, Spinuzzi points to the gaps of “designer vs. user,” which in turn can productively correlate to a Composition MOOC’s gap / borders between instructor vs. student participant. Further, Spinuzzi’s use of distributed cognition (Activity Theory) and interconnections maps onto MOOC spaces in potentially useful ways, particularly when focusing on “interrelated sets of activities” (such as those described in Downes’ description of a connectivist course) rather than the individual learner, or networked minds vs. an individual mind (62). 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 (Downes, Cormier). As scholars and compositionists, we must remain critically aware of the design of the learning / teaching spaces we employ / deploy, and Spinuzzi’s discussion of mediation and mediators provides a means with which to explore these. Spinuzzi’s Activity Theory allows our focus to center on concrete nodes of activity within a system: where and how the participants interact (where the learners learn and connect).

School of Natural Resources & Environment, UF

School of Natural Resources & Environment, UF

Thread 4: Ecology Theory deals exclusively with complex systems, not classroom spaces. However, the potential for mapping a dynamic and complex “living” network of actors, boundaries, and affordances as described by Bateson and Gibson is one of the more productive connections for MOOC discussions.Given the mechanics of the numerous digital platforms and software needed to operationalize a learning/teaching classroom space, it is not surprising to see so many critiques of MOOCs more in line with Hardware Theory, focusing on the mediating structures, than Learning Theory. Bateson and Gibson provide a counterweight to such limitations by attending to the power of boundaries to serve as both frontiers as well as informational economies (Bateson 467). Ecology Theory can thus extend our focus upon a classroom system to a larger scale, allowing me to discuss systems within systems. As proof of this usefulness, Margaret Syverson takes an ecological systems’ approach to the subject of the Composition classroom on the premise that a student’s “process of composing” – i.e., learning – takes place within a dynamic “complex system” based squarely upon ecological principles (Syverson 2-3).

Shaffer MOOC crib sheet

Shaffer MOOC crib sheet

The networked nature of complex systems and the affordances of web technology-based classrooms create a discursive space where each of these theories find play. Building upon Foucault’s concept of traces and gaps, each of these threads serves as both lens and map for examining the nodes and networks that comprise MOOC learning spaces, as well as highlighting the misfits or gaps. Further, each of these theoretical lenses at some point hinges upon the concept of “relationships,” a key component for distributed cognition as well as collaborative, workshop-based FYC theories of pedagogy. Finally, each of these theories provide the means by which to explore collaborative learning as both node and activity, a step which may contribute to the design of future cMOOCs and shape the nature of English Studies.

In sum, exploring this Object of Study using such a FrankenTheory may allow our field to address not only those concerns listed above but others like them, utilizing a network theory that may offer an appropriately complex lens to account for and grapple with the complexity of emerging digital learning, teaching, and theorizing spaces. The design of this synthesis falls into three broad sections, each based on significant questions that seem to lie at the heart of our field’s treatment of MOOCs: (1) knowledge and learning (or, “what does it mean to know?”), (2) the locus or framework of learning (or “how does location shape learning?”), and (3) agency (“who has it and why does that impact the discourse?”).


Baseline Concept: Knowledge and Learning

The concepts of knowledge and learning are key to this attempt to create a viable synthesis using these four theories, becoming an effective organizing principle with which to explore how these theorists give shape or problematize integration into a new theory of networks. Of particular worth is how these theories align and diverge in terms of the theorists’ framing of the terms and how, once synthesized, they become a useful tool with which to describe Composition MOOCs.

Stephen Downes: Connectivism

Stephen Downes: Connectivism

First, spaces in which knowledge is acquired and disseminated are shaped by premises that undergird what we mean when we consider the term knowledge as a thing to be constructed and transferred. David Cormier asserts that in traditional models of online courses that base their knowledge delivery system on a one-to-many model, it is the institution or the instructor who possess the knowledge desired by the students. In their original design, MOOCs constitute “an ecosystem from which knowledge can emerge” as a result of “negotiation”… a nod toward their roots in Vygotsky and the “social nature of learning” (Downes “Connective Knowledge”). From this perspective, it is not enough to use the term “knowledge” as a Composition classroom’s outcomes. Rather, the term “connective knowledge” emerges, pointing to a “gap” in Composition discourse where a network-based FrankentTheory might prove useful.

The field of neurobiology describes the function of the human brain as a communications network that first “takes in sensory information” via neurons, then “process[es] that information between neurons” as thinking, with the end result or response described in terms of neuronal “outputs” (“Neurobiology”). In other words, knowledge, as treated by neurobiology, is to some degree a byproduct of neurotransmitter activity transferring electrical and chemical impulses that create memories (in essence, knowing a thing). However, the network system – and in particular relationships within that system — in which such processes take place are just as important to how we understand knowledge creation, or learning. Synaptic connections operate on a cause-effect basis, transmitting data in one direction over a gap between neuronal structures. It is important to note that these “synapses are not merely gaps but … functional links between the two neurons” (“Neurobiology”). Foucault might say that these synaptic gaps – like black holes – are significant areas of scrutiny because of their functional nature. The entire “communication infrastructure” in which these neurons exist, however, are not the origin of the process.” Rather, the process that occurs within this series of embedded networks (synaptic systems) “develops because there is something to communicate.” In sum, knowledge is both product and initiator of this sequence of events that result in what neurobiology calls learning. When used as a lens with which to examine 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 (from Learning Platforms like Blackboard to blog spaces for assigned student writing to student-created back channels in Facebook for student-directed discussions) but as a representation of cognitive transfer – how humans learn. In neurobiology terms, knowledge is both a material to be transferred between neurons but also an initiator that signals neuronal development, altering existing circuits and driving the creation of new neurons to make new connections (“Neurobiology”).

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. Each component creates the “mechanisms to input, process and distribute content” (slide 27) – the course map or neuronal network — but students themselves “add to the map” (slides 46-56). The growth of this system — what student writers add and how they add it — might be discussed in terms of our neurobiology metaphor if we align Downes’ “mechanisms” with neurobiology’s initiating force of knowledge to be transmitted, addressing the questions, “how do we know?” and “what is knowledge?” Downes’ use of neurophysiology terminology illuminates a potential connection (what Foucault might say is a case of “minding the gap”) 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” which are instrumental in the movement or transmission of a “message from one community to the next” (Connectivism 120).

The parallelism to neurobiology is clear here: nodes, transmission, clusters, etc. However, for English Studies and Composition Studies in particular, while such a cellular-based network may ground this physiological process as a scientific set of facts, it does not address the broader question of how this translates to behaviors situated in dispersed cultural and social network systems. This is where Spinuzzi may fill the gap. For example, when Cormier writes of “knowledge networks,” it creates a point of intersection with Spinuzzi ‘s Activity Theory. Spinuzzi employs 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.

Spinuzzi’s effort to correlate Activity Theory with Actor Network Theory provides a view of knowledge and learning from the perspective of activities performed in order to acquire or transmit knowledge. Spinuzzi distinguishes two competing discourse communities and their approaches to knowledge: designers and users, each creating very different hierarchies and relations to the other nodes within the network. His concept of centripetal and centrifugal “impulses” (20) creates a fascinating analogy with which to consider the discourse practices of these two communities and how that creates a perspective of knowledge or learning that could be useful within this FrankenTheory. His suggestion that the centripetal nature of a designer describes a discourse community that gravitates toward “formalization, normalization, regularity, convention, stability, and stasis” (20) may help us characterize a sort of knowledge creation privileging to which Foucault points in his work. The centrifugal nature of the user, on the other hand, represents “resistance…, innovation, — and chaos” (20), features that may also contribute to discussions of agency. This passage alone opens numerous connection nodes of analysis regarding the ways we envision networks functioning or moving knowledge. Spinuzzi’s identification of competing concepts of creation and operationalization of knowledge thus provides a useful tether to which the other theories may connect when examining this Object of Study.

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). Not only are these points of transformation of a practical matter in the case of MOOCs (e.g., making choices between online platforms and applications to locate collaborative writing), they become the very “gaps” or “traces” (7) so key to Foucault’s theory of knowledge, revealing as they do points of contention and discontinuity where additional theorizing might take the discourse in new directions.

Foucault’s Archaeology of Knowledge offers this work a theoretical foundation with which to explore several key terms: knowledge and knowing (writing and learning), networks, disruptions of unities, différence and traces (169). With regard to knowledge in particular, Foucault argues that the reason some maintain that “the history of thought could remain the locus of uninterrupted continuities” creates a shelter “[f]or the sovereignty of consciousness” (12). Further, he argues that we must “question those ready-made syntheses” that inform current theories of the individual and society. For this FrankenTheorizing of MOOCs, this concept may provide a way to highlight the presence of a “status quo” element to current critical frameworks of knowledge and/or learning that are applied to scholarly treatment of MOOCs in Composition. Gardner and Cormier both point to ways the original MOOC design was more true to composition theory pedagogies of collaborative, decentered learning spaces. However, when MOOC spaces were corporatized through “Coursera, edX, and Udacity,” classes offered through MOOCs became prone to the “sage-on-stage teaching models” against which our field of composition has come to resist (Gardner). The “status quo” of decentering classrooms, however, always already exists within the larger “status quo” of an educational system that relies on assessment to measure what it deems “academic knowledge.” Within that system, MOOC designs are often perceived as “payload delivery systems,” making the online instructor complicit in this framing of teaching as a “content delivery expert” (Gardner).

black hole

From “Nature Communications” website: Black Holes

Foucault calls us to pay attention – much like Cynthia Selfe does – to ways in which points of disruption or tension in this discussion may actually define what we see. Foucault’s description on page 29 of how looking at absences or gaps (disruptions and displacements, the difference) actually helps define what we see makes its way into this FrankenTheory much the way black holes reveal the unseen by observing the actions of other bodies within its sphere of influence. Foucault writes, “in analyzing discourses themselves,” we should look for “the emergence of a group of rules proper to discursive practice” in order to see them as “practices that systematically form the objects of which they speak” (49). Foucault’s interest here is in the “discursive formation,” and I would argue at its core is the concept of knowledge and knowledge networks. With regard to previous comments on “delivery systems” and knowledge, this “disruptive” or transformative power of a MOOC creates a troubling gap in terms of how knowledge is conceptualized as content to be delivered, shared, and transferred within most academic communities. As a result, 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.

Finally, theories of Ecology as advanced by Bateson and Gibson deal with knowledge in terms of more philosophical ideas rather than concrete transfers of material knowledge made within and between ecosystems. Bateson concerns himself with affordances and perspective within what he refers to as an ecology of the mind. Using a blind man and stick analogy to explore the “mental system” that is involved with knowledge and learning, “the stick” or the non-human node within the system that is considered an affordance serves as “a pathway along which transforms [or the effects] of difference are being transmitted” (465). For Bateson, then, the focal point of any discussion is not the “what” but the “how.” Gibson also focuses on the role of affordances – the environment – but in terms of knowledge, there is a considerable degree of unawareness that takes place between actor and activity. Perception is key. The human-centeredness may seem to situate the power of knowledge squarely in “the eye of the beholder,” but Gibson’s explanation of the role of other players in the environment (water, soil, animals) also suggests that the privileging of humans in the knowledge network may be tenuous.

Perhaps the most relevant “gap” in the discussion of MOOCs where Gibson’s theory may be helpful is his exploration of objects versus affordances. Gibson asserts that in an ecology network, objects should not be defined by their “qualities,” but by their “affordances” (134). He is careful to make the importance of this distinction clear when he observes that “to perceive an affordance is not [the same as] to classify an object” (134). He explains that such a distinction “rescues us from the philosophical muddle of assuming fixed classes of objects, each defined by its common features and then given a name” (134). In the case of a Composition MOOC, this distinction becomes especially relevant when our inquiry turns to the nature of distributed activities and network nodes in terms of student identity within the MOOC. By simply employing classifications such as instructor or student, too often these terms become infused with traditional connotations of power and knowledge creation a la “one to many” (Hart-Davidson) being transferred within a hierarchy of primary to secondary, rather than a pattern which follows a more diffused set of relationships fostered by the sort of collaborative-centered design of a cMOOC (Cromier). Further, Gibson’s theory points out that “[t]he richest and most elaborate affordances of the environment” are not even non-human agents. In fact, they are “provided by other…people” whose “behavior affords behavior” (135).Bourelle et al. describe MOOCs in this way, with knowledge being created and transferred (learning) as much between students as between student to instructor. The disruption created by the affordances of the networked and massive space itself thereby resists a fixed nature of objects. So, what does this mean for this OoS?

"Finding Meaning In Networks"  (www.ysc.com)

“Finding Meaning In Networks” (www.ysc.com)

Knowledge is closely aligned with the concept of meaning. In Composition theory, this pairing is typically framed within key rhetorical concepts of audience and rhetor (writer). Gibson asserts that his theory of affordances provides “a new definition of what values and meaning are,” particularly in terms of how these affordances are directed. Gibson’s theory insists that (unlike neuronal pathways), an “affordance…points two ways, to the environment and to the observer” (140-41). Within the network of a Composition MOOC, such principles of meaning and knowledge allow the discourse to shift to the gap which commonly houses a “chicken or the egg” dilemma: is the MOOC environment to be seen as machine interface housing the human interface (the student-student or student-teacher connections), or are the human connections and interfaces transforming the physical network structure itself?

In short, when it comes to a Composition MOOC, what does it mean “to know” – for both teacher and student? These theorists take the discussion out of the realm of assessment, assignments, and the writing process, and shifts us into the realm of how we learnin a complex system of networked relationships. I deliberately do not refer to “networked space” as these four theories facilitate a move away from the structural configurations of boundaries, tools, and computer-mediated access, and into the realm of social networks.

Baseline Concept: The Locus or Framework of Learning

highed-mooc_475x300_0Of all these lenses, some are more useful than others when it comes to interrogating the MOOC space as a learning and teaching space. Gibson argues that “a place is not an object with definite boundaries” but is instead more of “a region” (136). Bateson famously observes that “the map is not the territory” (455). What do these mean for a new network theory meant to analyze a Composition MOOC? It is Bateson’s map/territory equation that may be most productive initially, as we endeavor to discuss a MOOC as uniquely networked on a level that must be theorized differently than a physical Composition classroom space filled with desks, one teacher, 20 students, textbooks (or even eBooks). When attempting to theorize a space as massive and open as a MOOC, it soon becomes clear that we cannot talk about its practices or its situatedness using the same framework and terms we use to analyze a traditional Composition course following traditional paradigms of f2f classroom theory. In fact, Bateson’s theory is predicated on the assumption that we must “change our whole way of thinking about mental and communicational process” (458). When Bateson notes that the “differences are the things that get onto a map” (457), it is a phrase remarkably reminiscent of Foucault’s differences, disruptions, and traces as the more productive locus of our attention when it comes to theorizing knowledge and networks within MOOCs. But just what does this mean – “the map is not the territory” – for MOOCs?

Neurobiology may help address this if seen as a metaphor for the type of learning that happens in a MOOC. 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.

Hart-Davidson’s article recently published in Invasion of the MOOCs: The Promise and Perils of Massive Open Online Coursesfocuses 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).

MOOC Web Wheel

MOOC Web Wheel

She asserts that one course failed because of its reliance on a pedagogy that had not adapted its methods to the characteristics that define the web space as a learning space. In particular, she argues that the failed course did so due to its reliance on a “learning model that most of higher education institutions follow – instructors direct the learning, learning is linear and constructed through prescribed course content featuring the instructor,” a method not unlike the way many face-to-face (f2f) Composition courses are conducted. Such methods, she argues, are unsuited for the ways in which the Web “as a platform for open, online, and even massive learning creates a different context for learning – one that requires different pedagogical methods.” Morrison’s observation may illustrate one of the limitations of the neurobiology thread because the metaphoric image of a neural network isolates the picture somewhat, “tuning out” the environmental influences surrounding the neural pathways. In other words, the neural network nodes are a very small part of a much larger system, equated only to the “basic cellular mechanism in the brain” (“Neurobiology”). The dilemma for this application is whether this “smallness” can correlate to the “bigness” and complexity of a MOOC. This gap may be usefully bridged by integrating Spinuzzi’s work with chained activity networks and the concept of “connectivism” as applied learning theory.

Spinuzzi defines Activity Theory (AT) as “a theory of distributed cognition” that “focuses on issues of labor, learning, and concept formation” (62). Further, this theory continues to evolve, moving “from the study of individuals and focused activities to the study of interrelated sets of activities” (62) – networks that may include collaborative learning and development, both of which play significant roles in Composition pedagogy and MOOC structural designs. Such concepts and terms create a framework with which to explore how using a network lens provides a means with which to locate this discussion in terms of borders. As Morrison observes, such concepts and terms create a framework with which to explore how using a network lens provides a means with which to locate this discussion in terms of borders. As Morrison observes, the nature of a MOOC space does not easily align with the nature of an f2f classroom space. While the basic principles of Composition pedagogical theory must ground both in terms of the aforementioned priorities of student learning (as outlined by the NCTE in “Beliefs About the Teaching of Writing”), the nature of the space – the networks that represent the physical, the theoretical, and what AT calls the “dialectical” qualities of that space – create tensions at those boundaries which represent how to implement that learning. Morrison refers to the importance of “connectivism” as a corollary to “social constructivism,” a thread woven into modern pedagogical theory (and connected to principles of Ecology as well as Neurobiology) that states “students learn more effectively” when they are actively involved in knowledge construction that includes their own knowledge bases.

Spinuzzi Structure of Activity, Networks

Spinuzzi Structure of Activity, Networks

Activity Theory as distributed cognition incorporates mediation as a key concept. Described by Spinuzzi as “tools, rules, and divisions of labor” (71), mediators are used by individuals within an activity system to “transform a particular object with a particular outcome in mind” in a way that is meaningful and connected to a (discourse) community (71-72). Composition MOOCs as networks are often seen through the filter of traditional f2f structural limitations, leading to concerns such as those described by Halasek et al., who assert that reflecting on “the MOOC learning environment” reveals the “ways we understood – and sometimes failed to understand – our roles as teachers of composition and our students’ roles as writers and learners” (156). Again, the example of the Discussion Boards serves as an example of how Activity Theory allows us to productively analyze the MOOC environment. Halasek et al. observe that Discussion Forums are typically conceptualized as nodes in which student participants depend on the “controlled exhanges…shaped and guided by teachers…and oriented toward assignment expectations” (159). In effect, these learning nodes are mediated in specific ways by a limited number of people who occupy academically hierarchical positions with relation to the student-to-teacher activity pathways. In the revised iteration of their MOOC class, Halasek et al. discovered that students “actively occupied” these learning spaces and mediated the activity as well as the flow of content when they “engaged and even tested the faculty team by making their needs explicit and articulating the problems the instructional context posed” (159). Such meta-participation is then makes students the mediators who transform the learning environment through their activity and co-creating of the space.

Finally, Activity Theory involves “chained activity systems,” a concept that may account for the sort of “organizational…boundaries” that create “informal linkages” between activities that could be interpreted as metacognitive nodes where transfer takes place (Spinuzzi “Networks” 74-77). As Spinuzzi explains, there are two types of work that takes place in systems: modular and net work (“How”). Complex tasks in Modular work is described as more compartmentalized and specialized, with clear boundaries and hierarchical orders of authority. Net work refers to the “coordinated work that holds” complex systems together (“How”). Foucault’s concepts of disruption and chaos as areas of transformation may fit here as Spinuzzi explains that modular work (a system of activity that emerged from the Industrial Revolution) has been “disrupted” or “destabilized” by technology’s impact. As a result, homogenous units of work gave way to “heterogenous networks…[that] form dense interconnections among people, texts, tools, etc.” (“How”).

Spinuzzi applies Activity Theory in terms of connected activity systems in which mediators – which in this case may be the digital space itself, the technology, or the pedagogical system that functions as a genre – provide the “tools, rules, and division of labor” (71) to create a system suited for “distributed cognition” (69). In terms of MOOCs, Spinuzzi’s characterization of “contradictions” as “engines of change” and transformation (a key component of Activity Theory) becomes a means of considering the impact of designers’ pedagogies as well as the agency afforded users in this learning space.

Further, Spinuzzi asserts that chained activities “don’t chain so much as they overlap and interfere with each other,” allowing the participants “to take on many functions” (“How”). This distinction is reminiscent of Syverson’s application of ecology to the Composition classroom in terms of how it allows us to treat a MOOC space as a “complex system” rather than a technology-mediated space. As a result of these theoretical combinations, discussions of the most productive teaching/learning models for a MOOC allow more credence to the “many-to-many” as opposed to one of “one-to-many” (Hart-Davidson).

For Composition, metacognitive transfer has become an increasingly foregrounded concept in discussions of student writing. For the Composition MOOC, AT becomes especially productive as a way to analyze it as a potentially viable mediator of student writing. It also offers a point of alignment with the neuronal metaphor (the way axons and dendrites constitute independent nodes of activity as part of the larger neuronal system that make up brain activity) as well as ecology theories.

But what of Agency within these complex systems? What of the students’ ability to co-create their learning and knowledge?

Baseline Concept: Agency

Foucault describes members of a discourse community as existing inside “a web of which they are not the Masters, of which they cannot see the whole, and of whose breadth they have a very inadequate idea” (126). These notions of control and scope are key to understanding and exploring the notion of agency in MOOC spaces, in particular how that impacts writing pedagogy. Because Foucault’s theories challenge the linear homogeneity of not only academic discourse but knowledge conventions as well, the notion of hierarchical agency as a power dichotomy comes under scrutiny.

As stated earlier, classrooms are often analyzed in terms of structural components: the mechanical, the hardware, the situatedness of student and teacher. In the case of any online classroom including MOOCs, it is easy to believe there is an individual mastery over the network, which Spinuzzi might refer to in terms of designer, as when the architects of that network exert an unseen filter in the form of a control system. Agency, then, within such networks must also be a point of analysis, and is a boundary where all four theories contribute to one degree or another.

Foucault’s Definition of Agency – Foucault resists essentialisms and absolutes. Therefore, his approach to agency is one that resists what he refers to as a “history of ideas” that promotes a linear approach to influences — a one-to-one, top-down hierarchy. Instead, he seems to locate that agency in moments of disruption and discontinuity, which networks facilitate in their “redistributions” (5). He argues that the “sovereignty of the subject” (12) is problematic, one fostered by the history of ideas. His assertion, through his archeology of knowledge, is to dethrone or decenter the subject. If we view “subject” as having the sort of primary agency as might a designer (Spinuzzi), a theory that decenters that subject’s hierarchical (and linear) primacy would fit a networked system in which agency is diffused. The MOOC’s essential networked structure can serve Foucault’s argument, but only if the hierarchical system of one teacher distributing knowledge to many students is disrupted. Some MOOCs, as Hart-Davidson points out, fail to operate in this way, but there are cases, such as the online classrooms cited by Bourelle et al. as well as Halasek et al., which operationalize a networked, student-prioritized course that diffuses the agencies of knowledge generation and transfer to tutors as well as students. Moreover, a consideration of how their online course failed to produce envisioned learning outcomes – a gap – served to focus their theorizing efforts to address these disruptions via a redistribution of agency. Foucault’s theory both frames the disruptive powers of networks as well as serving to illuminate the gaps where questions of agency may be asked.

Spunuzzi and Agency: Vygotsky’s theory of learning might locate agency in the relationship b/w nodes — teacher, student – which may be discussed in terms of scaffolding. The scaffolding, of course, takes on an entirely new location in a MOOC, but activity theory may allow this to be applied in a more decentered way than Vygotsky originally intended when he wrote about educational strategies for teaching children new concepts. While Vygotsky’s theories have been folded into Writing Center and even Composition theories, at their core is a collaborative activity. All too often, however, that collaboration still relies on a designer (tutor / teacher) who crafts the structure for that scaffolded behavior. In the case of MOOCs, the course design begins within the institutionalized origin of the course, but the networked system may allow designer agency to be diffused through the course through peerlearning nodes, some predesigned and others initiated and created by students (as in the composition MOOCs of Hart-Davidson and Bourelle et al.). As Downes observes, when MOOCs are designed following theories of Connectivism, students are empowered (i.e., are afforded agency) by the space itself to become “creators of learning” (Downes “Connectivism”). Teachers as well adopt “new roles” as “coaches and mentors” (Downes “Connectivism”). Due to this increased and diffused agency, learning then becomes “a network phenomenon” (Downes). 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.

Ecology and Agency: For Bateson, meaning is “projected” onto the world by the perceptions and subjectivity of the viewer. Dividing potential agents into “creatura” and “pleroma,” he sets up a binary of subject/object. To set up the question, “what does it mean to know,” Bateson’s agency is diffused, but not shared. It is still very much a human-centered approach to networks, knowledge, and agency, an approach which Spinuzzi might find appealing. Gibson’s theory pushes back against the worldview born of the Enlightenment that sees the world in terms of mechanical cause and effect. Affordances are potential activity that allow agency, but have no agency of their own per se. The environment is not a “cause” of action, but instead facilitates it. The interactivity of an environment’s connectivity is one of give and take, self-regulating. Non-human actors (animals) are not simply machine-like, responding to environmental stimuli. His concept of agency is a theoretical one meant to disrupt a subject-object / subjective-objective dichotomy. Most interestingly, “[a]n affordance points both ways, to the environment and to the observer” (129). This relationship or network, while still privileging the human actor, opens up a means of exploring the structural elements of a created structural network (a system of connections that afford students and instructors to create relationships one with the other) of a MOOC. Affordances themselves, therefore, seem to possess agency of a kind. Their existence does NOT depend on their perception. Actions, then, reveal how animals are using those affordances, which Foucault might see as a trace or gap that results in new possibilities for analysis (statements).

Neurobiology and Agency: 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 (“Neurobiology”). 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 as well as 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).

Summation: Syverson offers a justification for an ecological approach to Composition, one which translates over to this OoS as well. As she observes, the layering of theory is “crucial in developing new knowledge” (Syverson 2). As well, we might argue that, just as MOOCs should be seen and theorized as a complex system, these theories are part of that system. In the end, as a unifying element of this FrankenTheory, Ecology seems the most productive of the four in terms of framing discussions of MOOCs as spaces for teaching, learning, and practicing writing. Too often, MOOCs seem to be cast in terms of a “simple system” of teacher-student relationships, when in reality – and as Foucault, Spinuzzi, Neurobiology, Bateson, and Gibson all demonstrate – it is far more complicated than criticisms based on “mechanistic explanations” permit (Syverson 2).

Indeed, as Syverson posits, the cMOOC is a “meta-complex system,” one wherein Ecology Theory may productively integrate (subsume) Neurobiology, Activity Theory, even Foucault. As Syverson argues, such ecologies allow us to discuss “writers, readers, and texts” as part of a complex system that is composed of “self-organizing, adaptive, and dynamic interactions” (3). This system, as she envisions it, is built of “interrelated and interdependent complex systems and their environmental structures,” structures that include “theoretical frames, academic disciplines, and language itself” (3) along with – I argue — assumptions about knowledge and agency.

In Music, It’s Called A Deceptive Cadence: 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 simply 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 and new theories with which to best equip college-level writers for the demands of communication across disciplines and 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.

Coda: If our field approaches the Composition MOOC as an ecology, how might the conversation change? How will it reflect the “enunciative function” identified by Foucault (88)? What new threads, nodes, or means of transmission might emerge as part of the discourse if we apply theories of learning like Vygotsky through the lenses of Neurobiology and Activity Theories combined? How might the goals and motives of our pedagogy evolve if we treat the technology of MOOCs as having productive, rather than reductive, agency in the ways students learn to write in a massive digitally-mediated space?

When these digital spaces are built as adaptive, complex systems rather than static delivery systems based on one-to-many models like Coursera and eduX courses (Hart-Davidson), how will the conversation be transformed?

Questions aside, as important is how we as a field of study will frame this discussion of the MOOCs place in 21st century higher education. Syverson’s question seems productive to our response: “Can the concepts currently emerging in diverse fields on the nature of complex systems provide us with a new understanding of composing as an ecological system?” (5). Her question posits the very behavior itself – composing – as a system (Spinuzzi might call it a networked activity) itself, not a learned behavior designed to produce a product. The transformation of our field of view afforded by this proposed FrankenTheory may allow those of us in the field of Composition Studies to bring this question, and these three key areas of theoretical overlap, to the forefront of this discussion in an effort to move us forward.


 

Works Cited:

Barlow, Aaron. “Teachers and Students: Machines and Their Products?”Academe Magazine 26 May 2013. Web. 1 May 2014.

Bateson, Gregory. Steps To An Ecology of Mind. New Jersey: Jason Aronson Inc., 1987.

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

Bourelle, Tiffany, Sherry Rankins-Robertson, Andrew Bourelle, and Duane Roen. “Assessing Learning in Redesigned Online First-Year Composition Courses.” Digital Writing Assessment and Evaluation.  Eds. Heidi A. McKee and Danielle Nicole DeVoss. Logan, UT: Computers and Composition Digital Press/Utah State University Press, 2013. Web. 2 Feb. 2014.

Cormier, David. “Knowledge In A MOOC.” YouTube. 1 Dec. 2010. Web. 1 Feb. 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. < http://www.slideshare.net/Downes/the-connectivism-and-connective-knowledge-course>

Downes, Stephen and George Siemens. “Connectivism and Connective Knowledge: Getting Started.” MOOC course, University of Manitoba. 2009. Web. 30 Mar. 2014. <http://elearnspace.org/media/GettingStarted/player.html>

Foucault, Michel. The Archaeology of Knowledge and the Discourse on Language. New York: Vintage Books, 1972. Print.

Friend, Chris. “Will MOOCs Work For Writing?” Hybrid Pedagogy: A Digital Journal of Learning, Teaching, and Technology. 28 March 2013. Web.

Gardner, Traci. “The Misunderstood MOOC.” Bits: Ideas for Teaching Composition. Bedford / St. Martins. 5 June 2013. Web. 1 May 2014.

Gibson, J. J. “The Theory of Affordances.” In R. E. Shaw & J. Bransford (Eds.), Perceiving, Acting, and Knowing. Hillsdale, New Jersey: Lawrence Erlbaum, 1977. pp. 127-143.

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.

Mitrano, Tracy. “MOOCs as a Lightning Rod.” Inside Higher Education 31 May 2013. Web. 1 May 2014.

“Neurobiology.” Rediscovering Biology. Annenberg Foundation, 2013. Web. 31 Mar. 2014.

Norman, Don. “Affordances and Design.” jnd.org. 2004. Web. 18 Mar. 2014.

Spinuzzi, Clay. “How Are Networks Theorized?” Network: Theorizing Knowledge Work in Telecommunications. NY: Cambridge UP, 2008. 62-95.

Spinuzzi, Clay. Tracing Genres through Organizations. Cambridge: MIT Press, 2003.

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

“What You Need to Know About MOOCs.” The Chronicle of Higher Education: Technology. 1 May 2014. Web. 1 May 2014.

 

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.

Terminology

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.

http://www.psychologyinaction.org/2011/04/01/conventional-wisdom-upset-persistent-action-potential-firing-in-distal-axons/

Image of Neuron. The dendrites are in green; the axon is in blue. Taken from http://www.uic.edu/classes/bios/bios100/lectures/nervous.htm.

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.

http://www.learner.org/courses/biology/textbook/neuro/neuro_6.html

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. < http://www.slideshare.net/Downes/the-connectivism-and-connective-knowledge-course>

Downes, Stephen and George Siemens. “Connectivism and Connective Knowledge: Getting Started.” MOOC course, University of Manitoba. 2009. Web. 30 Mar. 2014. <http://elearnspace.org/media/GettingStarted/player.html>

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.

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 Alpha.org

The Borg, Star Trek: The Next Generation
from Memory Alpha.org

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.

http://www.learner.org/courses/biology/textbook/neuro/neuro_6.html

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).
http://www.psychologyinaction.org/2011/04/01/conventional-wisdom-upset-persistent-action-potential-firing-in-distal-axons/

The dendrites are in green; the axon is in blue. Taken from http://www.uic.edu/classes/bios/bios100/lectures/nervous.htm.

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.