Understanding MOOCs from the perspective of Actor Network Theory (ANT): Refraiming pedagogy and unmasking power

(Nach zwei erfolglosen Versuchen, das Paper bei einer Zeitschrift zu platzieren, stelle ich es nun hier zur Verfügung.)
 

Understanding MOOCs from the perspective of Actor Network Theory (ANT)

Refraiming pedagogy and unmasking power

Massively Open Online Courses (MOOCs) are without any doubt currently one of the hottest developments in open and flexible learning as indicated by a broad mass media coverage and several scholarly events (conferences, special issues in academic journals etc). Many of the aspects that are on top of controversial debates (drop-out rates, accreditation, quality) re-echo claims and arguments being made over forty years during the time when distance education hit the educational landscape (Peters, 2010). Yet, little reference is made to this academic tradition. On the other hand, research investigating the effects and impacts of MOOCs on learning processes and outcomes has started which is however limited to a learner-centred approach. This pertains both to research conducted around MOOCs based on connectivism and around so called xMOOCs (cf. Liyanagunawardena, Adams, & Williams, 2013). For instance, Breslow and colleagues (2013) studied learners‘ behaviour in a large edX MOOC using, among other things, predictive modelling to determine factors that influence student success. In a similar vein, Cross (2013) reports on an evaluation of the Open Learning Design Studio MOOC (OLDS MOOC) based on participation rates, use of course space and technologies and effectiveness by collaborative group working. The research strategy follows a subjective-oriented view as indicated by the statement “(…) how participants understood and used the series of nine badges on offer” (p. 1).
In this sense, MOOCs are portrayed as a “closed technological offering” to be utilized and acted upon according to personal learning goals. From a purely pedagogical standpoint, MOOCs are thus the latest materialisation of personal learning environments with a high degree of self-regulation and autonomy. Moreover, MOOCs, at least the cMOOCs, resonate well with the Open Education movement, i.e. opening up education for all has a long history and has culminated for instance in the foundation of the Open University UK or in the dissemination of Open Educational Resources world wide. In all these cases, the primary goal was to empower and liberate the individual by providing a broad variety of tools and resources (Deimann & Farrow, 2013; Peter & Deimann, 2013).
Against this background, the present paper argues that while the primacy of the individual is in favour of humanistic pedagogy (e.g., Freire, 1996), it does underestimate the importance of technology and fails to grasp its specific role for networked learning in a digital age.
In order to better understand the effects of digital technologies and its capabilities to connect learners all over the world, Actor Network Theory (ANT) (Latour, 1987) provides a different approach because it goes beyond the human-centred perspective and postulates non-human actors as equal entities:

“Whereas social network adds information on the relations of humans in a social and natural world which is left untouched by the analysis, ANT aims at accounting for the very essence of societies and natures. It does not wish to add social networks to social theory but to rebuild social theory out of networks. It is as much an ontology or a metaphysics, as a sociology”. (Latour, 1996, p. 371)

With regards to MOOCs, ANT offers a tool to understand how the social and technological are embedded in each other. More importantly, it helps to analyse how a MOOC network functions and what factors facilitate of impede success. This means, however, that the paper is not interested in the way an individual or a group of learners benefit from a MOOC and how the design might be didactically improved to better underachiever but in the network specific factors that contribute to the emergence and evolvement of a MOOC. For instance, the process of translation, describes in a series of steps (problematisation, interessement, enrolment, and mobilisation) how a network is formed (Callon, 1986).
Introduction
Massively Open Online Courses (MOOCs) are without any doubt currently one of the hottest developments in open and flexible learning as indicated by a broad mass media coverage and several scholarly events (conferences, special issues in academic journals etc). With much enthusiasm reflecting a relatively short-term educational innovation, the New York Times coined 2012 “The Year of the MOOC” (Pappano, 2012)

“MOOCs have been around for a few years as collaborative techie learning events, but this is the year everyone wants in. Elite universities are partnering with Coursera at a furious pace. It now offers courses from 33 of the biggest names in postsecondary education, including Princeton, Brown, Columbia and Duke.” (Pappano, 2012)

It seems as MOOCs have been wondrously hit the educational landscape causing the public to shake its head in great astonishment. Literally out of the blue a “MOOC mania” broke out with a clear statement: Top-tier universities have the capital (financially, socially) to offer world class online lectures at virtually no costs to the entire world. With these automated “assets”, “mediocre” universities can improve their quality and education is now available for everybody on the planet. However, even at this early phase in development, MOOCs have been evolved in two distinct models: the “original” cMOOC which is based on the notion of connectivism (Siemens, 2005) and the much hyped xMOOC which some refer to as Massive Open Animated Textbooks (Reich, 2013) and basically transfer the process of lecturing to the digital space.
Many of the aspects that are on top of controversial debates (drop-out rates, accreditation, quality) re-echo claims and arguments being made over forty years during the time when distance education hit the educational landscape (Peters, 2010). Yet, little reference is made to this academic tradition. On the other hand, research investigating the effects and impacts of MOOCs on learning processes and outcomes has started which is however limited to a learner-centred approach. This pertains both to research conducted around MOOCs based on connectivism and around so called xMOOCs (cf. Liyanagunawardena, Adams, & Williams, 2013). For instance, Breslow and colleagues (2013) studied learners‘ behaviour in a large edX MOOC using, among other things, predictive modelling to determine factors that influence student success. In a similar vein, Cross (2013) reports on an evaluation of the Open Learning Design Studio MOOC (OLDS MOOC) based on participation rates, use of course space and technologies and effectiveness by collaborative group working. The research strategy follows a subjective-oriented view as indicated by the statement “(…) how participants understood and used the series of nine badges on offer” (p. 1).
In this sense, MOOCs are portrayed as a “closed technological offering” to be utilized and acted upon according to personal learning goals. From a purely pedagogical standpoint, MOOCs are thus the latest materialisation of personal learning environments with a high degree of self-regulation and autonomy. Moreover, MOOCs, at least the cMOOCs, resonate well with the Open Education movement, i.e. opening up education for all has a long history and has culminated for instance in the foundation of the Open University UK or in the dissemination of Open Educational Resources world wide. In all these cases, the primary goal was to empower and liberate the individual by providing a broad variety of tools and resources (Peter & Deimann, 2013).
Consequently, most educators would certainly subscribe to the liberating effects of MOOCs and keep on working to fulfil its ultimate mission “affordable, high-quality education for all around the world”. However, MOOCs are not the “end of the history” but just another instance of a (relatively) stabilised network of technologies, principles, norms, educators and policy makers. Thus, instead of taking the MOOC or some of its derivatives for granted and to use it as an “input” for research¹ (Breslow et al., 2013) and policy making , this paper opens another approach by opening the “black box” and unreal its network effects. As has recently been claimed, we are already in a post-MOOC phase² which is not only a desperate attempt to keep up with the immense pace but also an indicator of the limitation of a foundationalist ontology based on a priori distinctions. The danger of a linear ordering of time phases (pre- and post-MOOCs) is that they draw the curtain over the complexity of the underlying network processes and let us believe that things happen because of causal relationships. Latour (1993) has coined a phrase that might seem at first glance pretty awkward but actually reflects in a most condensed way the fundamental different way of his thinking: “We have never been modern”.
Therefore, to fully understand what a MOOC is and how it works, it is necessary to open the black box and demystify the “legend of the phoenix”. It is argued that MOOCs – because of their very nature – should not be taken as a strapped entity with witchery or revolutionary power but rather as a complex set of technologies, practices, tools, norms, principles etc. that are interwoven and embedded in each other thereby creating one certain form of certain reality. Thus, large scale adoptions of MOOCs, e.g. in the context of universities, should be informed by a close inspection and interpretation of the different threads and the processes that may eventually generate a version of a MOOC.
Thus, the intend of the following paper is to familiarise the reader with the language of ANT, to provide an example of re-reading the story of the MOOC through the lens of ANT, and finally to start a discussion that is grounded on a way of thinking very much akin to the hybrid character of MOOCs.
Actor-network Theory as a model for framing MOOCs
Key ideas of ANT
Originally originated in the field of Science and Technology Studies and based largely on the work of French sociologist and philosopher Bruno Latour, actor-network theory (ANT) has started to make an impact on educational research (Fenwick & Edwards, 2010). As Edwards (2011) points out, ANT uptake has so far been piecemeal because it challenges core assumptions of education, first and foremost its human-centred approach. Instead of traditional or distance teaching models of education³, ANT does not privilege either human or non-human (technological) artefacts but focuses on hybrids networks which emerged through a complex process of translation and mobilisation. Thus, its account goes beyond because “(…) emphasis on personal and social processes, as important as these appear to be in constituting the cultural, emotional, political and psychological relations at work in education, completely ignores the material presences that exert force and are entwined with what appears to be human intention, engagement, resistance and change (Fenwick, 2011, p. 116).
Moreover, ANT is non-deterministic, i.e. there is no direct cause-and-effect relation neither n the human nor in the technological. Consequences, i.e. learning, are the result of a series of translations aimed at building a stable network and can include strategies such as negotiation, persuasion, seduction, bargaining, and violence. A translation is thus dynamic as different actors compete for allies and by which they pass a series of four steps (Callon, 1986; Rhodes, 2009):

1. Problematization: the first moment in the translation process is to set defines identities and interests of other actors with similar interests. A so-called obligatory passage point (OPP) is established, i.e. a certain way of solving the problem is created.
2. Interessment: a group of actions by which an actor attempts to impose and stabilize the identity of other actors. This is accomplished by convincing actors to accept the definition of a macro-actor. It includes using devices to detach actors from other networks (translation).
3. Enrolment: A successful outcome of the previous steps as the networks grows by enrolments. Translations, strengthening connections, and maintaining stability are important processes in this respect. Both human and non-human actors can be used to enrol other actors.
4. Mobilization: The final step is about commitment to the cause of action and about establishing a spokesperson (i.e. who speaks in the name of whom?). Latour (1987, p. 172) describes it as “(…) the ability to make a configuration of a maximal number of allies act as a single whole in one place”.

In the beginning the focus of ANT has been on describing success and failures of large inventions such as Thomas Edison’s electricity supply network in New York or Renault’s “electric vehicle” as systems of complex technological and human conditions that played out to work because, as in the case of Edison, single elements have been engineered together and subordinated to the logical of the network. In the opposite case, ambitious plans stranded because elements “behaved” in a different way than the developers (e.g. Renault) had fancied. A key term in pointing out the specific notions of networks is “translation” which is defined as follows: “To translate is to make two words equivalent. But since no two words are equivalent, translation also implies betrayal:traduction, trahision. So translation is both about making equivalent, and about shifting. It is about moving terms around, about linking and changing them” (Law, 2009, p. 144, emphasis in the original). A good way to understand the meaning of translation is to contrast it with diffusion which holds that ideas and objects stay the same as they move from one context to another, .i.e. translation implies that ideas and objects change.
In many empirical case studies, such as the Portuguese expansion in the 15th and 16th century (Law, 1986) or the scallops in the bay of St. Brieuc (Callon, 1986), it became clear how a precarious web emerged and how the process of translation gave each component a certain shape or form that was to hold together for an extended period. The success of the network depends on the “willingness” of each actor and as has been shown in the case of the fishermen, when a single translation fails, so does the whole web (Callon, 1986).
In the next section, the paper takes on an ANT-inspired inspection regarding (a) how MOOCs have emerged as (relatively) stabilised forms of massive open online courses – with a focus on people (xMOOCs) and on artefacts (cMOOCs) – and (b) how major claims being made by MOOC advocates relate to ANT terminology (i.e. to what extend do they bear a MOOC- or network-specific understanding in mind?).
Opening the Black Box: The MOOC spaceship has landed
The emergence of the xMOOCs
For most part of the general public, it must have seem as a spaceship has landed in 2012 given the tremendous coverage by mass media including various actors (political stakeholders, economic organisations, educational institutions). All together have worked on the construction of the narrative “education is broken”. Prominent examples of such kind of news coverage are the articles “The Campus Tsunami” (Brooks, 2012) and “Come the Revolution” (Friedman, 2012) which both were issued by the New York Times in a way to propel the third major MOOC provider edX against Coursera and Udacity. What has been labelled as “tsunami” and “revolution” was the fact that magically over 100,000 students participated in a course on machine learning and instructor Andrew Ng could not help but relate this to traditional instruction: “To reach that many students before, I would have had to teach my normal Stanford class for 250 years.” In a quite similar vein, his colleague Peter Norvig (2012) claims in his TED Talk “The 100,000-student classroom” that for over 600 years we have basically relied on the same technologies for teaching. While the content of teaching has advanced and is now “modern”, the delivery mode is still the “sage on the stage”, i.e. lecturing with the media of speech and textbook. For the Stanford professor it is then very clear to proclaim that given the tremendous advancements of digital technologies we have entered a “new era of learning”. Together with his co-worker Sebastian Thrun, he attempted to emulate Benjamin Bloom’s (1984) principle “one-on-one-tutoring” and to solve the “two sigma problem” which states that while it has been proven that students working with human tutors obtain average achievement levels two standard deviations higher than students in conventional instruction, it has not yet been doable to design educational environments that are as effective as individual human tutors and affordable enough to scale up.
The plan of the researchers suggested short videos (2-6 minutes) followed by a quiz to make it “feel like one-on-one-tutoring”. However, the actual tutoring is delegated to the masses of fellow students because they are better teachers anyway.
Whereas in most of the media coverage the Stanford MOOC appears in light of a technological determinism, i.e. learning is framed in terms of what technology allows and permits (Oliver, 2011), an ANT inspired account goes beyond not only by describing it as a network of a massive amount of people (<100k), a set of video-based lectures, teaching practice (short quizzes) and a set of technological specification (IP protocol) but also by describing the processes of translation. One of such translation is that traditional face-to-face lectures in front of a student population whose motivation depends, among other things, on the time of the lecture and on environmental conditions (e.g. noise level) is transformed into canned on-demand videos. Student motivation is thus much less dependent on exterior factors. Instead motivation becomes a factor used to advertise and promote the separation of student and teacher (Carr, 2012) (“human translation”). Concerning the modes of instruction, translation takes place, too, but into a regressive pedagogical direction. Although oral presentations for one and a half hour might seem questionable given the availability of sophisticated technologies for recording and distributing lectures (and this is one of the key arguments for “innovative” forms such as “flipped classroom”), it should not be forgotten that they constitute only one element or “quasi-object” of Higher Education and are usually complemented by other, more student centred forms. For xMOOCs, it is envisioned that both elements (lecture and student-focussed forms of learning) are distributed and offered online. This, however, means that teacher-student interactions are translated into semi-automated and pre-defined quizzes or highly structured discussion forums and as many critics have claimed stands in stark contrast to the revolutionary vision pictured by Norvig (see footnote 5). Yet, such an argumentation is flawed from an ANT standpoint because of the asymmetry between human and non-human actants, i.e. the translation has not yet compromised learners‘ reactions towards the translation of the teaching process. In this process, the xMOOC changes and creates realities every time students and teachers work with it within certain contexts (e.g. on a for-profit MOOC platform). This means that even though xMOOCs have often been blamed for notoriously high drop-out rates, this should not be interpreted as an evidence for or a logical consequence of a deficient instructional design but rather that an actor-network has not yet emerged corresponding to the ambitious goals of the providers.
In contrast to Distance Education (DE) – which is indisputable the form of instruction xMOOCs emulate to be – there has yet not been a symmetrical transaction, i.e. there is a disequilibrium between the social and the material world. Instead what occurred was that technology has been utilized top-down following the pre-determined and inscribed needs for end-users – which is according to a recent meta-analysis a stable development trend (Hsu, Hung, & Ching, 2013) – without accounting for the “real” requirements of the learner. In this vein, it is not much of a surprise that a MOOC which allows to transfer credit to Colorado State University/Global Campus failed in attracting any students despite an enormous financial discount (Kolowich, 2013) because, to put it simply, the actant “MOOC” could not persuade the actant “campus learner” to form an alliance. It would be a challenging research project to map out the various actants which underlie “MOOC” and “campus learner” and to trace the ways in which they influence each other and shape actions.
Another example for weak linkages and failed mobilisations is the refusal of San Jose State University’s philosophy department to adopt a MOOC on social justice (sic!) produced by non-profit provider edX. The university has signed a contract with edX to use the MOOC in undergraduate class. However, this decision was met with a refusal by several philosophers and in an open letter they argued: “Should one-size-fits-all vendor-designed blended courses become the norm, we fear two classes of universities will be created: one, well-funded colleges and universities in which privileged students get their own real professor; the other, financially stressed private and public universities in which students watch a bunch of video-taped lectures.” (The Department of Philosophy, 2013) Thus, a hitherto unconnected actant is being translated which means that “(..) at once offering new interpretations of (…) interests and channelling people in different directions” (Latour, 1987, p. 117). More precisely, moral values (e.g. education as a common good) are introduced as an important lens through which the “public private partnership”, i.e. the network of traditional university and commercial/non-commercial MOOC providers, should be judged. Subsequent discussions were then engaged with this new actor-network (Ginsberg, 2013).
When it comes to the notion of “MOOCs are a disruptive force that will ultimately revolutionise Higher Education”, one could argue that many of the visionary claims have already been fulfilled within Distance Education. And in fact an inspection of the literature on its history reveals many examples for the emergence of stabilised actor-networks (Lease & Brown, 2009). Basically, technological means (e.g. postal service) are approached and convinced to join the network of separated teachers and learners. The enrolment quickly succeeded, i.e. producer of written learning materials, accrediting bodies and information clearing houses were woven into the network and eventually the DE-model spread throughout Europe. The network became stabilised as soon as DE-institutions were allowed to award degrees. Thus, the ability to accredit student learning constitute the obligatory passage point through which all relations in the network must flow at some time. This pertains to learners who are typically unable to attend campus-based universities and for whom the DE-institution is a “university of second chance” as it offers a degree for personal and/or professional promotion, to governments who decide whether to cut or increase the funding for the DE-institution and base that decision on the amount of certificates awarded within a semester or to the textbook industry who produce and distribute content that is of most relevance for the students. Moreover, a new actor comes into the play which is about verifying learners‘ identity.
Does this mean that xMOOCs will come close to building a stabilised network once they are allowed to offer credits – which is indeed currently being negotiated? At the one hand there is a rush demand for affordable high-quality education so that, for instance, UK-MOOC provider FutureLearn had to capped its initial student quota at 10,000 (Parr, 2013). But notwithstanding that some courses can now be used to transfer credit points to regular degree programmes – which is another example for opening a black box as described in the case of the University of Osnabrück (Küchemann, 2013) – there are some linkages missing, e.g. it is yet unclear how to provide adequate student support that is needed to cope with the affordances of online learning and which has for a long time proven to be a valuable actor (Tait, 2003).
Moreover, it seems that an actor-network is emerging as a recent EDUCAUSE report reveals: “But the MOOC is teaching us about all the reasons that students engage in the learning process. In many ways it’s a vehicle for just-in-time learning, allowing students to participate at select points in the course and then depart when they have met their goals.” (Diaz, Brown, & Pelletier, 2013, p. 2f.). In this regard, Coursera’s move towards short classes (between three and six weeks) could be very well conceived as “education’s future” (Anders, 2013) but actually it is a translation (actor “organisational structure” is convinced to accept the definition of the macro actor; interessement) into the above described network. In the currently ongoing process of stabilisation it is yet unclear how the rigid structure of certain MOOCs might jeopardise the overall commitment of the actor-network.
What kind of impact a strong emphasis on “openness” can have will be discussed in the next section when the emergence of cMOOCs is analysed.
The evolution of cMOOCs
From a rather different angle, a type of MOOC has evolved which place much emphasize on the notion of “connectivism” as a “learning theory for the digital age” (Siemens, 2005). which lays claim to a natural connection between theoretical assumptions of learning and technological advancements by arguing that: “(…) Over the last twenty years, technology has reorganized how we live, how we communicate, and how we learn. Learning needs and theories that describe learning principles and processes, should be reflective of underlying social environments.” Siemens frames technology-facilitated learning in terms of “connectivism” based on the idea that knowledge is not only “inside” humans but also distributed across an information network and stored in a variety of digital formats. With his colleague Stephen Downes, connectivism is envisioned as a four-step activity : (1) aggregation (collection of various digital artefacts using tools such as RSS-feed reader), (2) relation (relating content to prior knowledge and experiences), (3) creation (based on step number 2, a new product is created), and (4) sharing (feed the created content back into the digital world so that other can benefit from that). This last step is, according to Kop (2011, S. 21), “vital to learning” as it ensures that there is enough “backflow” to the network. In order to bring the concept of connectivism into being, Downes and Siemens developed a course at the University of Manitoba to “(…) facilitate the transition from a neat, constrained and centralized learning management system to a distributed environment in which students and instructors employ multiple online services and applications” (Downes, 2010, p. 29). This course was run in 2008 and 2009 and defined what was later to become the cMOOC.
A clear picture of the core elements of the cMOOC was given in the 2011 course #change11 that predefined a set of learning activities, i.e guidelines set up by the “facilitators” to ensure that participant benefit from the MOOC-experience (Downes, 2011):

1. Aggregate: (…) You are NOT expected to read and watch everything. Even we, the facilitators, cannot do that.
2. Remix: Once you’ve read or watched or listened to some content, your next step is to keep track of that somewhere. (…) You can keep a document on your own computer listing all the things you’ve accessed. Or, better yet, you can keep a record online somewhere. That way you will be able to share your content with other people (…).
3. Repurpose: We don’t want you simply to repeat what other people have said. We want you to create something of your own. (…).
4. Feed Forward: We want you to share your work with other people in the course, and with the world at large. Now to be clear: you don’t have to share. You can work completely in private, not showing anything to anybody. Sharing is and will always be YOUR CHOICE (…).

With the strong emphasis on the notion of openness, cMOOCs are in perfect line with the tradition of Open Education as a reform movement aimed at liberating learners from social, political, economical or educational barriers (Deimann, 2013). Or to use the language of ANT, it can be argued that “openness” defines the obligatory passage point of the actor-network cMOOC through which the actors open source software tools, freely licensed material and “open minded” learners must pass.
However, the latter has been identified as a rather weak link, i.e. participation is to a large degree constrained by the ability to self-organize the learning process (Kop, Fournier, & Mak, 2011). Moreover, there is a serious mismatch between the claims put forward by advocates of open MOOCs and the practices, rules and practices utilized to facilitate the process. By promoting a virtually boundless digital space filled with an abundance of materials and combined with a diversity of fellow learners, there is not only a “new era of learning” emerging but also a dark side with excluding mechanisms and policies. In fact, there is a Janus-faced network that bears a striking resemblance to the arguments laid out by Foucault (1977) in his book Discipline and Punishment. As in the “positive” network, openness is the OPP through which the actors “facilitator” who candidly proclaim that being open and willing to share everything with others is beneficial for everybody, “learners” who are actually left with no choice but to obey to the MOOC-rules, and “materials” which do not entail any inherent means to measure one’s progress must go. This kind of actor-network exerts a disciplinary power as it is concerned with disciplinary technologies aimed at producing a “regime of openness”. For Foucault society is to a large extend based on the logic of disciplinary power and its mechanism to normalise individual behaviour by analysing and breaking down individuals, places, time, movements, actions and operations. In this regard, the classroom is a paradigm for disciplinary power: “Learners are ’seen‘ and ‚modified‘ and ‚broken down‘ by age and sometimes by gender, by ability, by ’need‘ in relation to talents and other forms of speciality of abnormality. Schools are broken down into houses, the school day into a timetable and a curriculum (…) and into specialist locations; pupil movements are broken down within and into lessons, they are allocated to seats, organized onto tables or in rows, labelled, tested, measured and calculated by the techniques of examination” (Ball, 2013, p. 46f.). Following this line of argument, a cMOOC as exemplified above, breaks down and analyses learners‘ behaviour such as in step 2 “remix” which suggests to “keep track”of one’s action, preferably “online”, i.e. behaviour is normalised against the default “open”. Deviating behaviour (keeping one’s product under lock and key) is discouraged although it is stressed that “you can work completely in private, not showing anything to anybody”. However, Foucault never tires insisting that disciplinary power is not a commodity commanded by individuals or groups but an entity that produces reality. That is, it is not the question whether individuals such as the MOOC facilitators attempt to de- or increase power by adopting certain guidelines (MOOC principles) but it is rather the concept of openness that functions as a dispositif, i.e. an arrangement of various elements (technological, legal, educational) with formative power and embedded in social assumptions (education as a common good to which everybody should have open access so that the entire society will benefit). From this it follows that the deliberate attempt to free learners from repressing burdens, e.g. learning management systems that function as “walled gardens”, actually creates a new form of oppression (“the regime of openness”).
Although the cMOOC protagonists most probably reject any form of exclusion constituted by the practices of sharing and keep on portraying MOOCs as the ultimate form of personalised learning, the problematic “side effects” should be taken much more seriously. In this regard, the flawed understanding of the concept “network” is the crux of the matter because it oversimplifies the complexity of the underlying processes. Although it is acknowledged that human and non-human entities account for a network, as stated by Siemens: “Computer networks, power grids, and social networks all function on the simple principle that people, groups, systems, nodes, entities can be connected to create an integrated whole” (Siemens, 2005), it privileges human actions above non-human actors thus underestimating the various translations that occur once a network is in place. Moreover, Latour (1996, p. 371) explicitly rejects the notion of “computer networks” as a common misunderstanding of ANT: A technical network in the engineer’s sense is only one of the possible final and stabilized state of an actor-network. An actor-network may lack all the characteristics of a technical network – it may be local, it may have no compulsory paths, no strategically positioned nodes.”
Conclusions
Against the background of the increasing proliferation of Massive Open Online Courses that has caused lively debates around fundamental topics of pedagogy (how to learn and teach in/with MOOCs?), economy (how can free online courses be transformed into a valid business model?), and politics, the present paper introduces actor-network theory as a critical lens through which these grand narratives can be critically analysed. It is argued that ANT enables the researcher to open the black box as which the initial appearance of MOOCs have often been portrayed. By doing so, it has been demonstrated how the two major stories (c and xMOOCs) can be re-read in terms of defining actors and typical translations. Moreover, it became clear that the history of Distance Education has not been a linear and progressive development which has culminated in the MOOC but rather a spiral form with various processes of translation and mobilisation such as the opening of lectures from Ivy-League universities to the world. The ambitious visions of xMOOC providers indicate how a macro actor attempts to define roles (e.g. video lectures as an instrument to provide high quality education for everybody) and actions (e.g. access to video is linked to multiple choice tests). In order to realise the project of “revolutionising education” new actors are approached and enrolled such as technological means to verify users‘ identify for learning in a MOOC.
As regards the cMOOCs it has been shown how the concept of openness has been “black boxed” thus veiling deeper contradictions. On the one hand the radical approach to realise the promises of Open Education portrayed as the collective attempt to liberate suppressed masses by opening up and sharing materials and ideas which has on the other hand generated a form of disciplinary power on the body of the individual. Borrowing from Foucault it has been claimed that this disciplinary power has two sides, on the one hand it creates a MOOC reality with enormous options for formal and informal education, but on the other hand it exerts a form of regulation and normalisation (being open as the default). Framing cMOOCs with ANT thus allows to understand how the advocates define and allocate roles according to their vision of Open Learning and set up the obligatory passage point “openness”. Consequently, the stability of the actor-network depends on each actor’s commitment to openness and as has become apparent with the emergence of commercial MOOC providers, seduction of one actor (“open formats”) undermines the entire network.
Although many commentators have begun to declare that the hype is over, MOOCs may indeed have a “bright” future that can leverage educational systems to another level. Yet, it is of crucial importance to know the identities, actions and principles of actors that are played out in complex networks.
References
Anders, G. (2013, October 10). Coursera’s online insight: Short classes are education’s future. Forbes. Retrieved from http://www.forbes.com/sites/georgeanders/2013/10/10/courseras-online-insight-short-classes-are-educations-future/
Ball, S. (2013). Foucault, power, and education. New York: Routledge.
Bloom, B. S. (1984). The 2 sigma Problem: The search for methods of group instruction as effective as one-to-one tutoring. Educational Researcher, 13(6), 4–16.
Breslow, L., Pritchard, D. E., DeBoer, J., Stump, G., Ho, A. D., & Seaton, D. T. (2013). Studying Learning in the Worldwide Classroom. Research into edX’s First MOOC. Research and Practice in Assessment, 8, 13–25.
Brooks, D. (2012). The Campus Tsunami. New York Times. New York.
Callon, M. (1986). Some elements of a sociology of translation: domestication of the scallops and the fishermen of St Brieuc Bay. In J. Law (Ed.), Power, action and belief: a new sociology of knowledge? (pp. 196–223). London: Routledge.
Carr, N. (2012, September 27). The crisis in higher education. MIT Technology Review. Retrieved from http://www.technologyreview.com/featuredstory/429376/the-crisis-in-higher-education/
Cross, S. (2013). Evaluation of the OLDS MOOC curriculum design course: participant perspectives, expectations and experiences. Milton Keynes: Open University UK. Retrieved from http://oro.open.ac.uk/37836/
Deimann, M. (2013). Open Education and Bildung as kindred spirits. E-Learning and Digital Media, 10(2), 190–199.
Deimann, M., & Farrow, R. (2013). Rethinking OERs and their use: Open Education as Bildung. International Review of Research in Open and Distance Learning, 14(3), 344–360.
Diaz, V., Brown, M., & Pelletier, S. G. (2013). Learning and the massive open online courses: A report on the ELI focus session (ELI White Papers). Washington: Educause. Retrieved from http://net.educause.edu/ir/library/pdf/ELI3029.pdf
Downes, S. (2010). New technology supporting informal learning. Journal of Emerging Technologies in Web Intelligence, 2(1), 27–33.
Downes, S. (2011). How this course works. change.mooc.ca. Retrieved from http://change.mooc.ca/how.htm
Edwards, R. (2011). Translating the prescribed into the enacted curriculum in college and school. Educational Philosophy and Theory, 43(S1), 38–54.
Envisioning a “Post-MOOC” era. (2013, August 13). edSurge. Retrieved from https://www.edsurge.com/n/2013-08-13-envisioning-a-post-mooc-era
Fenwick, T. (2011). Reading educational reform with actor network theory: Fluid spaces, otherings, and ambivalences. Educational Philosophy and Theory, 43(S1), 114–134.
Fenwick, T., & Edwards, R. (2010). Actor-network theory in education. New York: Routledge.
Foucault, M. (1977). Discipline and punish: The birth of the prison. New York: Pantheon Books.
Freire, P. (1996). Pedagogy of the oppresed. London: Penguin.
Friedman, T. (2012, May 15). Come the revolution. New York Times. New York. Retrieved from http://www.nytimes.com/2012/05/16/opinion/friedman-come-the-revolution.html
Ginsberg, B. (2013, June 26). Who’s afraid of the big bad MOOC? (Me.). Minding the Campus. Retrieved from http://www.mindingthecampus.com/originals/2013/06/whos_afraid_of_the_big_bad_moo.html
Hsu, Y.-C., Hung, J.-L., & Ching, Y.-H. (2013). Trends of educational technology research: More than a decade of international research in six SSCI-indexed refereed journals. Educational Technology Research and Development, 61(4), 685–705. doi:10.1007/s11423-013-9290-9
Kolowich, S. (2013). A University’s Offer of Credit for a MOOC Gets No Takers. The Chronicle of Higher Education. Retrieved from http://chronicle.com/article/A-Universitys-Offer-of-Credit/140131/
Kop, R. (2011). The challenges to connectivist learning on Open Online Networks: Learning experiences during a Massive Open Online Course. International Review of Research in Open and Distance Learning.
Kop, R., Fournier, H., & Mak, J. S. F. (2011). A pedagogy of abundance or a pedagogy to support human beings? Participant support on massive open online courses. International Review of Research in Open and Distance Learning, 12(7).
Küchemann, F. (2013, October 22). Im Sog der Moocs. Hochschulen experimentieren mit freien Online-Kursen. Frankfurter Allgemeine Zeitung. Frankfurt am Main. Retrieved from http://www.faz.net/aktuell/feuilleton/forschung-und-lehre/im-sog-der-moocs-hochschulen-experimentieren-mit-freien-online-kursen-12627870.html
Latour, B. (1987). Science in action: How to follow scientists and engineers through society. Cambridge, MA: Harvard University Press.
Latour, B. (1993). We have never been modern. Cambridge: Harvard University Press.
Latour, B. (1996). On actor-network theory. A few clarifications plus more than a few complications. Soziale Welt, 47, 369–381.
Law, J. (1986). On the methods of long distance control: Vessels, navigation, and the Portuguese route to India. In J. Law (Ed.), Power, action and belief: A new sociology of knowledge? (pp. 234–263). Henley: Routledge.
Law, J. (2009). Actor network theory and material semiotics. In The New Blackwell Companion to Social Theory (pp. 141–158). New York: Wiley-Blackwell.
Lease, A. J., & Brown, T. A. (2009). Distance learning past, present and future. International Journal of Instructional Media, 36(4), 415–426.
Liyanagunawardena, T. R., Adams, A. A., & Williams, S. A. (2013). MOOCs: A systematic study of the published literature 2008-2012. International Review of Research in Open and Distance Learning, 14(3), 202–227.
Moore, M., & Kearsley, G. (1996). Distance education : a systems view. Belmont, CA: Wadsworth Pub. Co. Retrieved from http://www.worldcat.org/isbn/9780534506889
Norvig, P. (2012). The 100,000-student classroom. Retrieved from http://www.youtube.com/watch?v=tYclUdcsdeo
Oliver, M. (2011). Technological determinism in educational technology research: some alternative ways of thinking about the relationship between learning and technology. Journal of Computer Assisted Learning, 27(5), 373–384. doi:10.1111/j.1365-2729.2011.00406.x
Pappano, L. (2012, February 11). The year of the MOOC. The New York Times. New York. Retrieved from http://www.nytimes.com/2012/11/04/education/edlife/massive-open-online-courses-are-multiplying-at-a-rapid-pace.html?_r=1&
Parr, C. (2013, October 24). FutureLearn is go, but it is not quite the finished article. Times Higher Education. Retrieved from http://www.timeshighereducation.co.uk/news/futurelearn-is-go-but-it-is-not-quite-thefinished-article/2008347.article
Peter, S., & Deimann, M. (2013). On the role of openness in education: A historical reconstruction. Open Praxis, 5(1), 1–8.
Peters, O. (2010). Distance education in transition: Developments and issues. Oldenburg: Bis.
Reich, J. (2013, May 19). Is a MOOC a textbook or a course? Education Week. Retrieved from http://blogs.edweek.org/edweek/edtechresearcher/2013/05/is_a_mooc_a_textbook_or_a_course.html
Rhodes, J. (2009). Using actor-network theory to trace an ICT (telecenter) implementation trajectory in an African women’s micro-enterprise development organization. Information Technologies & International Development, 5(3).
Siemens, G. (2005). Connectivism: A Learning Theory for the Digital Age. International Journal of Instructional Technology and Distance Learning, 2(1).
Tait, A. (2003). Reflections on student support in open and distance learning. International Review of Research in Open and Distance Learning, 4(1).
The Department of Philosophy. (2013, February 5). An Open Letter to Professor Michael Sandel from the Philosophy Department at San José State University. Retrieved from http://chronicle.com/article/The-Document-an-Open-Letter/138937/

1Latour (1987) refers to this as “ready made science” (as opposed to “science in action”) highlighting the merging of content and context and the importance of social aspects (e.g. controversies concerning the “right” approach for a scientific problem).

2Harvard Professor Robert Lue, for instance, makes the case the MOOCs do not have to be massive course but instead “online learning activities” (“Envisioning a ‘Post-MOOC’ era,” 2013)