Online Learning Platforms and the Confessional Subject

Abstract

Is there a connection between pedagogic practices of confessional reflectivity, online learning platforms, and the massively scaled surveillance of Higher Education student transactions via data analysis? It is the contention of this paper that there is an ideological and processual logic which connects these practices and platforms. It argues this logic has been benignly embedded in pedagogy, but has now become scaled via technologically deterministic paradigms, providing companies such as Pearson Ltd with monopolistic scope to dominate the epistemic foundations of teaching theory and practice. How these forces converge on the learning platform is the theme of this paper, which draws upon an arts and creative computation educational background rather than a specifically architectural context.

Keywords:

• online platforms
• pedagogy
• epistemology
• neoliberalism

Introduction

Changes to the United Kingdom’s Higher Education and Research Act, 2017, mean that students’ personal data is now “shared with other government departments, public authorities, councils trading standards, and with commercial companies explicitly named; Pearson Ltd and the Student Loans Company.”¹ This includes data about their debts as well as their online transactions, including those captured via interaction with online forums on learning platforms such as Moodle. According to Gary Hall at least one UK university, The Open University (OU), has created:

an algorithm capable of predicting a student’s final grade based on her performance during just the first week of a degree course. Significantly, it takes into account factors such as “how enthusiastically students participate in online learning forums to improve their results.”²

Such surveillant practices arguably make the virtual learning platform one which invokes an assimilation to space, a loss of subjectivity, paradoxically mediated by myriad technologies of the self, of self-confession and self-objectification, via forums, blogs and wikis and other confessional interfaces. Such is the intensity of datafication. Virtual learning environments are arguably now sites of a metaphoric flattening and absorption via similarity metrics, and clustering processes, in which individual personality attributes, as Katherine Behar puts it: “are a near perfect example of secondary qualities, attributes of objects that, in object-oriented theories like object-oriented feminism, become objects in their own right.”³ For Behar, the secondary qualities of online subjects are:

becoming detachable and remixable independent objects. And the same goes for qualities like personality types. They could be arranged in a formation that looks like or centers on a human individual. But they could just as easily be organized otherwise, taken on their own, without a person in their midst.⁴

So normalized are these processes that it is rare to encounter resistance to them within the academy, and to do so risks being accused of Luddism or digital illiteracy. In the author’s experience of working with Moodle (for both computing and arts education), it is seamlessly integrated into the everyday life of both university students and staff. It is worth breaking down a typical “day in the life” of a Moodle platform, though to do so necessitates a disruption of linear, “live” timings, as the whole point of Moodle is its asynchronous availability. Students are not tied to specific patterns of interaction but can access the platform whenever they wish.

Moodle is used as a repository for managing regulatory information, such as appeal procedures and referrals, it is also often used to book tutorials and workshops. “News blocks” can be added to provide institutional and course-specific communications, while a “forum” block can be deployed to engage students with a range of structured methods for online discourse, for example, thematic or free flowing, multi-threaded posts. Posts can also be constrained to one-per-person or constructed as once-only edicts, with no scope for reply. At the backend of Moodle sites, privileged administrators and super-users can view “reports” on each student’s activity, surveilling when, where and how they interacted with a given Moodle site. Alerts can be created so that lecturers are warned of low levels of interaction with each site and its specific activities, its sections and sub-sections. At the same time, senior managers can see how often staff interact with Moodle pages. In universities which specialize in online learning, and increasingly so since post pandemic all universities have shifted to more online learning, these metrics are routinely used to monitor both staff and students. They are used as staff performance indicators in the absence of qualitative indicators beyond student feedback. Staff are typically expected to respond rapidly to student posts and can end up finding themselves working far beyond their contracted hours to engage with online digital rather than face-to-face teaching. Further problems emerge in relation to normative validity.

Normative Validity

The embedding in digital platforms of normative validity – a shift in orientation and teleology which privileges the metrics generated by Big Data over qualitative, non-reductionist, enquiry – is also problematic because measuring quality becomes the definition of quality.⁵ Such a shift also maintains a power-relation that has arguably, always had its foundations in technologies of individual spatial domination. Indeed, Hall predicts:

the development of preemptive technologies means that in the future, the market may even be able to discipline and control you before you have done anything wrong – and, what’s more, without you knowing it’s doing so.⁶

The establishment of classroom or design studio “ground rules” is apparently benign, typically taught on in-house PGCEs (Postgraduate Certificates of Education), in which reflexive blogs, critical forums and the formation of “ground rules” with cohorts are an orthodox teaching approach. However, in retrospect, such practices appear to be aligned with the trajectory of surveillance capitalism, toward the goal of a near total subject tracking via ubiquitous “dataveillance.”

In art and design educational contexts, ground rules typically address what is expected from students within their studio spaces. I have usually taken this approach when there have been tensions between students, or issues about looking after equipment in studios. But what is the impact and meaning of establishing ground rules, and of using learning technologies to police students and ourselves? By learning technologies, I mean not only those we readily picture, such as computers, programming languages and Moodle sites, but Michel Foucault’s technologies of the self, or systems of self-regulation,⁷ in which issues of agency and control are always present.

Making Rules

In the past, I have had varied degrees of success trying to emphasize the ways students “should” be respectful and supportive of each other within our learning spaces, receptive to looking after equipment, listening to each other during group discussions and generally taking “ownership” of the studios or labs where we have worked. By facilitating students in the formulation of ground rules I have hoped to generate both a sense of cohesion and mutual respect among new cohorts. The results established by such sessions are typical of the ones illustrated below:

• equipment should be respected and put away properly;

• regular clean-up sessions should take place in the studio;

• lateness to workshops should be tolerated with a buffer zone of about 15 minutes and;

• beyond that students should take responsibility for their lateness and not expect a re-cap during the class.

The student defined solution is apparently simple and “fair”: students may be late but will take responsibility for that lateness in the sessions, instead of expecting a potentially disruptive catch-up session during the class, neither should the latecomers expect to be reprimanded. The student defined rules often show some insight into the impact of individual and social differences on educational processes. It would be facile, however, to idealize the scenarios I have outline here, or to neutralize them as existing outside of wider issues of power and control, gender, race and economics. This becomes explicitly contentious in the context of, for example, video camera use for students on Zoom and other such platforms, revealing the physical context of a student’s off-campus life (and, indeed, a lecturer’s living conditions) surfaces myriad issues of privilege and exclusion. The platforms we deploy therefore have a physical impact and are manifest in material phenomena. It is overly simplistic to claim such platforms are immaterial. Access to Wi-Fi and the fluctuations of such a service are also physical entities, with the potential to enable or constrain learning.

In terms of other cohort generated rules, the rule of lateness is one such real-world example which was not “fair” for students involved in managing morning childcare arrangements or the student who told me he cannot afford to take a train which runs into London seven minutes earlier, in the peak morning hours. Andrew Lambirth explains the dangers of presenting pedagogic theory and practice, especially the establishment of ground rules, as if it were ideologically neutral, and challenges the:

ahistorical and apolitical approach to learning theory that many writers adopt when recommending teaching methods, and how they fail to see how serious dilemmas over equality and alienation are not being addressed by their suggestions.⁸

Online practices are no more ideologically neutral. In my experience as both an online lecturer and an online student, online learning is even more reliant on technologies of the self, forms of self-surveillance channeled through reflective blogs and compulsory participation in forums, in which students reflect, not only on their own work and “attitudes,” but peer-review other student’s work, sometimes on a near constant basis. In these new and emerging contexts, we must understand: “Learning analytics are a structuring device, not neutral, informed by current beliefs about what counts as knowledge and learning, colored by assumptions about gender/race/class/capital/literacy and in service of and perpetuating existing or new power relations.”⁹ Indeed, one might ask: what came first, online pedagogy or the will to harvest transactional data? By gaining a near monopolistic access to student and staff transactions, courtesy of the Higher Education and Research Act:

Pearson’s hybrid science of data and learning, and the methods that enact it, are consequential to ways of conceptualizing learning processes, measuring learner progression and developing pedagogic products and practices. Through its methodological complex of psychological and data scientific ways of knowing and intervening in learning processes, Pearson is seeking to derive new classifications and standard definitions of learning itself that can then be relayed into practices by being coded into the e-learning software products that it inserts into the pedagogic routines of the classroom.¹⁰

Institutional surveillance has historically been overt, as Foucault has documented,¹¹ but within contemporary universities, these forms of control arguably now operate on two levels. First, through self-surveillance, or technologies of the self and second, via the more covert methods of data science. Foucault identified four major technologies of the self,¹² and it is the fourth one which relates to the processes described here, namely those technologies of the self which:

permit individuals to effect by their own means or with the help of others a certain number of operations on their own bodies and souls, thoughts, conduct, and way of being, so as to transform themselves in order to attain a certain state of happiness, purity, wisdom, perfection, or immortality.¹³

Foucault describes this form of self-regulation as a “strange discourse,”¹⁴ involving “the interaction between oneself and others and in the technologies of individual domination, the history of how an individual acts upon himself, in the technology of self.”¹⁵ Academic methodologies concerned with transformation, “self-realisation” and self-development are similarly embedded within a form of Foucauldian self-regulation¹⁶ including, for academics, our self-evaluation, our five-year plans, our course and self-appraisals, the:

audit culture’ with its attendant obligation to make everything “auditable,” rendered knowable and calculable in terms of quantifiable “outputs” (Power, 1994, Strathern, 2000)… new and emerging forms of discipline, which operate as technologies of selfhood that bring into being the endlessly self-monitoring, planning, prioritising “responsibilised” subject required by the contemporary University.¹⁷

For staff and students alike, there is a conflation of business-derived branding practices and technologies of the self, in which:

The platform capitalist sharing economy functions to transform us as citizens into connected yet atomized and dispersed individuals who develop our personalities as brands and endeavor to generate social, public, and professional value by acting as both microentrepreneurs and microentrepreneurs of our own selves and lives.¹⁸

Through reflective blogs, “co-defined” ground rules and online forums, it could be argued that, under the guise of benign liberality and inclusiveness, educators manage to get students to police themselves while artfully distancing their own agency in establishing such new regimes. By emphasizing the agency of students in defining what they want from their classes and studio spaces, these ground rules appear to reflect student’s own values and expectations. However, I am left with an uncomfortable feeling that I have deceived both myself and my students in using this self-surveillant technology. And, in a sense, I am doing the same to myself here now, but in pursuit, as Foucault wrote, of “another form of truth obligation different from faith” in which:

Each person has the duty to know who he is, that is, to try to know what is happening inside him, to acknowledge faults, to recognize temptations, to locate desires, and everyone is obliged to disclose these things to either to God or to others in the community and hence to bear public or private witness against oneself.¹⁹

The practice of establishing ground rules uncovers a recurring tension in teaching practice and in wider andragogic theory, that of exerting control (exercising a type of spatial, vocal and equipment management) while encouraging students to engage critically with their own meanings and “truth obligations.” While I have found reflective practice at times constructive (and obligatory for much off and online “learning”) it is important, to ask, as Foucault does, what kinds of knowledge we lose about ourselves in these processes of self-interdiction? On covert forms of control Larry Catá Backer writes:

It becomes most successful when it disappears into the background of cultural assumptions and expectations of the managed population. As culture rather than as regulation, the state can also appear more benign, and the iron fist of control covered in the velvet of management that is self-effected.²⁰

In critiquing the quantified academic self (staff or student), we must also critique the essentialist legacy which supports our student’s and our own reduction to discrete, quantifiable entitles. Since Foucault wrote Technologies of the Self, we have all become subject to an intensity of surveillance which was structurally and procedurally impossible before the rise of computer networks and machine learning. As Hall states, online quantification systems “are capable of exploiting our labor whether we consciously opt into them or not (just as we are all on Facebook, regardless of whether we have signed up to join its social network).”²¹

Pearson’s use of such digital methods, applied on a vast scale, “exemplifies a shift toward more software-based, computer-coded and algorithmically mediated techniques of educational governance.”²² Moreover, the problem of “normative validity” implied by such metrics, in which that which can be measured is valued, has myriad implications for the ontology and causality of educational theory and provision. The choice of algorithms, variables and interpretation of learning analytics are always, like all other technological processes, part of a social and economic imaginary.²³ They reflect the biases, fantasies and power imbalances of the cultures in which they are situated.

For large-scale online learning platforms, it is the millions of data points generated by each student’s interaction which educational corporations focus their energies on, so that many ‘large-scale online educational systems are designed to maximize the analytic potential of their data usage.”²⁴ Sal Khan, founder of Khan Academy is blunt in stating that Khan Academy’s educational materials are free because “Data is the real asset.”²⁵ As Neil Selwyn writes: “data are an ideal means of bringing market values and free market mechanisms into otherwise closed public education settings.”²⁶ The exploitation of student data, combined with the well documented biases generated by algorithmic evaluation of individuals raises urgent questions about discrimination within digital learning platforms, as analyzed in the following section.

Inequality on the Learning Platform

Figures from the UK Government do not suggest educational inequality or exclusion have been improved by the assimilation of a neoliberal business ontology into either the online learning platform or the on-campus university. Quite the opposite. We are now in a situation where disadvantaged males, are “five times less likely to go to university than those from the most advantaged backgrounds”²⁷ where universities are “being asked to reduce high drop-out rates among black students, who are 50% more likely to quit their studies than their peers.”²⁸ The politics of knowledge production converge upon the digital learning platform, amplified by the absorption of reductionist ontologies which “unmoor” data from the “social, cultural and political realities of what the data are supposed to represent.”²⁹ The algorithmic evaluation of exam results in the UK in August 2020, during the Covid-19 pandemic, further exposed the potential (and in that case the actuality) of discriminatory ontologies. The grades of students from poorer backgrounds were downgraded from the higher grades their teachers had predicted. Thankfully, those results were overturned, following protests by students, but the longitudinal impact of less visible algorithmic processes may come at great cost to those who already face disadvantage and discrimination within HE.

Conclusion

This paper was started many months before the Covid-19 pandemic unfolded in the UK in March 2020. It was written with the growing recognition that the arts and humanities are under threat, and that, at the same time, the STEM and STEAM agendas of successive neoliberal governments, in the UK and beyond, had the potential to converge upon the privatized sphere of online learning. Now, nearly a year later, the abrupt move to mass online learning feels like the beginning of the end for many of the analogue practices and pedagogies many of us value as academics, educators, practitioners, researchers and students. Rumors that the UK government will defund studio-based arts courses now seem more likely. Given that state funding for HE is already at a low level, this may mean the stalling or end of arts and humanities education as many of us know it. Anita Taylor, cited by Sam Philips, states: “If the funding is cut, there will be an impoverished learning experience, and many universities will no longer teach some subjects. The only ways we will survive as art schools will be to become small and bespoke, or very big – maybe delivering at a distance, because of the challenge for space.”³⁰ I have already experienced firsthand a growing sense of distance from students, with technologies and practices increasingly deployed by HE which do not allow for conversation or questioning, in which students are literally muted. At the same time, the neoliberal unbundling of the academy seems to be accelerating, meaning the fragmentation of education to more and more corporate and disparate digital platforms. Arguably this resembles a covert form of incremental privatization and the same technological ambitions applied in healthcare, such as the failed and spectacularly expensive UK Track and Trace technology.

Those of us who work with online learning platforms in Higher Education should consider the challenging assertion that “education is perhaps the most insidious and in some ways the most cryptic of colonialist survivals, older systems now passing, sometimes imperceptibly, into neocolonialist configurations.”³¹ The online learning platform has the potential to assimilate subjects into increasingly reductionist practices of knowledge, harvesting students for their analytic potential while insisting there is no alternative to neoliberal education and a neoliberal mode of working. In the words of Roopika Risam: “Those of us who are equipped with the capacity for humanities inquiry have a responsibility to intervene.”³² Such intervention, however, will only be meaningful if we challenge a pervasive business ontology which has been naturalized by the same technologically determinist ideology which threatens to transform students into commodities and disembodied data points. The mass move to online learning of art and design education risks a reversion to the pedagogy of the nineteenth century, disembodying and declarative, centered upon a world of facts and rules, which is accompanied by a loss of experiential and relational knowledge. Furthermore, this form of optimized learning, online education risks systemically disadvantaging and excluding already underrepresented students from art and design education. The form our resistance(s) might take is an expanding field of research. The Post Pandemic University (postpandemicuniversity.net) is one such initiative to explore the future and state of education post-pandemic. It is clear that we must try to resist the growing division between ourselves and students. At the best of times our shared embodiment and practices have the potential to bridge aspects of that separation, combined with an acknowledgement and analysis of systemic power disparities and the ways in which discrimination and exclusion are structurally entangled with HE campuses and so, inevitably, carried onto our online platforms and in many ways amplified.

Additional information

Notes on contributors

Eleanor Dare

Dr. Eleanor Dare’s research addresses technology, knowledge representation and digital media. Eleanor was formerly the Head of Programme for MA Digital Direction and Reader in Digital Media at the Royal College of Art (RCA). Eleanor is now a visiting lecturer and visiting practitioner at UAL (University of the Arts London), RCA and the Creative Computing Institute, where she teaches coding, spatial storytelling and critical themes.

Notes

1. Anon. “Student Data Rights Packaged Up for Pearson,” defendingdigitalme.com, https://defenddigitalme.com/2018/06/student-data-rights-packaged-up-for-pearson/ (accessed February 5, 2021).

2. Gary Hall, The Uberfication of the University (Minnesota, MN: University of Minnesota Press, 2016).

3. Katherine Behar, “Personalities without People/Anonymous Autonomous” What’s Next: Distributed Technology and the Technosphere (lecture at Royal College of Art, London, 2018).

4. Ibid.

5. Gert J. J. Biesta, “Education, Measurement and the Politics of Fear: Reclaiming a Democratic Space for the Educational Professional,” http://education.unimelb.edu.au/__data/assets/pdf_file/0008/908450/PESA_2013_Gert_Biesta_2013.pdf (accessed December 8, 2017).

6. Hall, The Uberfication of the University, 15.

7. Michel Foucault, “Technologies of the Self. Lectures at University of Vermont Oct. 1982,” in Technologies of the Self, ed. Michel Foucault (Amherst, MA: University of Massachusetts Press, 1988), 16–49.

8. Andrew Lambirth, “Challenging the Laws of Talk: Ground Rules, Social Reproduction and the Curriculum,” The Curriculum Journal 17, no. 1 (2006): 59–71.

9. Paul Prinsloo, “A Brave New World: Student Surveillance in Higher Education,” http://www.slideshare.net/prinsp/a-brave-new-world-student-surveillance-in-higher-education (accessed February 5, 2021).

10. Ben Williamson, “Digital Methodologies of Education Governance: Pearson Plc and the Remediation of Methods,” European Educational Research Journal 15, no. 1 (2016): 34–53.

11. Foucault, “Technologies of the Self.”

12. Ibid.

13. Ibid.

14. Ibid.

15. Ibid.

16. Refer Carl Rogers and Jerome H. Freiberg, Freedom to Learn, 3rd ed. (New York: Merrill, 1993); Jean Piaget, Construction of Reality in the Child (London: Routledge & Kegan Paul, 1954).

17. Rosalind Gill, “Breaking the Silence: The Hidden Injuries of Neo-liberal Academia,” in Secrecy and Silence in the Research Process: Feminist Reflections, ed. Roísín Ryan Flood and Rosalind Gill (London: Routledge, 2009), 231.

18. Hall, The Uberfication of the University, 18.

19. Foucault, “Technologies of the Self.”

20. Larry Catá Backer, “The University and the Panopticon: Naturalizing “New” Governance Forms for Behavior Control Beyond Law,” September 17, 2010, http://lcbackerblog.blogspot.com/2010/09/university-and-panopticon-naturalizing.html (accessed February 5, 2021).

21. Hall, The Uberfication of the University, 18.

22. Williamson, “Digital Methodologies of Education Governance,” 34–35.

23. Paul Prinsloo, “Decolonising the Collection, Analyses and Use of Student Data: A Tentative Exploration/Proposal,” November 14, 2016, https://opendistanceteachingandlearning.wordpress.com/2016/11/14/decolonising-the-collection-analyses-and-use-of-student-data-a-tentative-explorationproposal/ (accessed February 5, 2021).

24. Neil Selwyn, Is Technology Good for Education? (Cambridge: Polity Press, 2016), 88.

25. Ibid.

26. Ibid., 92.

27. Sally Weale, “Universities Told to Raise Numbers of Working-Class and Black Students,” The Guardian Online, February11, 2016, https://www.theguardian.com/education/2016/feb/11/universities-told-to-raise-numbers-of-working-class-and-black-students (accessed February 5, 2021).

28. Ibid.

29. Selwyn, Is Technology Good for Education?, 99.

30. Anita Taylor in Sam Phillips, “Art Under Threat: The Growing Crisis in Higher Education,” Royalacademy.org., 2019, https://www.royalacademy.org.uk/article/art-under-threat-crisis-britain-higher-education (accessed February 5, 2021).

31. Bill Ashcroft, Gareth Griffiths and Helen Tiffin, “Part XIII-Education: Introduction,” in The Postcolonial Studies Reader, ed. Bill Ashcroft, Gareth Griffiths and Helen Tiffin (London: Routledge, 1995), 425–427.

32. Roopika Risam, New Digital Worlds: Postcolonial Digital Humanities in Theory, Praxis and Pedagogy (Evanston, IL: Northwestern University Press, 2019), 139.