“Conscious Linkage”

Higher education “reformers” are fond of mocking higher education faculty as the “sage on the stage,” while pushing to transform us into the “guide on the side.” Such language is illustrative of the continuing effort to transform higher education faculty from teachers to deliverers of skill-based “competencies” in the completion of tasks along a “guided pathway.” Preceded by various forms of “distance learning” by mail, video, and other forms (Noble 2004), the attempt to deskill teaching in higher education is hardly new. As Karl Marx observed of the automaton and the worker in the Grundrisse (1857–58), technology is being used to transform the academic worker into a “conscious linkage” of the machine.

The 2020 COVID-19 pandemic has accelerated the integration of educational technologies, or “edtech,” into not only the administration of higher education, but also teaching itself. As self-isolation and quarantines have suppressed the transmission of the virus, the turn toward remote work using new learning management system (LMS) and teleconferencing technologies also threatens to sweep away many of the barriers to the spread of another epidemic: the digital automation, deskilling, and proletarianization of teaching in higher education. Though this project has been underway for the past decade, the pandemic has created the ideal circumstances for edtech venture capitalists, textbook publishers, LMS companies like the owners of Blackboard, Canvas, and Classroom, and online education (OLE) advocacy groups to extend their reach into colleges and universities (Ovetz 2020). Similarly, widespread reliance on teleconferencing platforms such as Zoom has rapidly sped up the reorganization, and rationalization, of the academic work of higher education.

The mass collection of online data (Marachi and Quill 2020) has expanded the use of predictive data analytics to surveil, self-discipline, and increase the productivity of the academic labor of students and faculty. To counter these dangerous developments, faculty and other academic workers must shift our organizing tactics, strategies, and objectives. Indeed, organized academic workers are the only protection against the rapidly spreading virus of online education.

The Rationalization of Academic Labor

The accelerated reliance on conferencing platforms like Zoom, and LMSs such as Canvas that drive OLE, is not a neutral process. The emergence of OLE coincides with decades of relentless neoliberal assaults on higher education to increase the efficiency, productivity, and “work readiness” of students. The result has been a strategy of adjunctification, austerity, privatization, and entrepreneurization, and an effort to shift rising costs to students and their families through skyrocketing tuition and fees, paid for by massive personal debt. These external factors place relentless pressure on higher education to become a more effective producer of self-disciplined labor.

For the past few decades, neoliberal edtech “disruptors” have been pushing the “unbundling” (i.e., breaking up into component parts) of higher education—at the levels of systems, institutions, non-academic services, and instructional and professional roles—into separate “primary” (teaching and research) and “support” activities (administrative services). Today, all but the professional and instructional components have already been largely unbundled, leaving teaching and other academic services such as counseling, advising, financial aid, tutoring, library support, LMS tech support, and admissions as current targets for rationalization. Moreover, we now see relentless pressure to unbundle teaching itself through the expansion of OLE and integration of telecommunications and artificial intelligence (AI) in the form of grading chatbots. And this is only one example among many of the effort to physically unbundle higher education from a place-based site of learning to a virtual delivery of skills competency.

The current, second phase uses the technologies of OLE, including LMSs, AI, and teleconferencing technologies to rationalize academic labor and subtly shift the assessment of the comprehension of content knowledge to the measurement of proficiency in task completion.

The rationalization of faculty labor essentially seeks to break up and redistribute its three key elements—design, delivery, and assessment of teaching—into as many as nine components no longer under the control of faculty. Higher education researchers Sean Gehrke and Adrianna Kezar (2015) describe this unbundling of teaching as “the differentiation of instructional duties that were once typically performed by a single faculty member into distinct activities performed by various professionals, such as course design, curriculum development, delivery of instruction, and assessment of student learning.” This has only been made easier by the near-complete dismantling of the three pillars of faculty academic labor—research, service, and teaching—through the transformation of the majority of faculty into contingent, “just in time” adjuncts like myself. Now mostly contingent, faculty labor is being proletarianized.

“Unbundling” is in itself a problematic term that mystifies and deflects from the intended strategy of those that use it. Instead, The Analogue University (2019) suggests we understand the rationalization of teaching as a strategy to discipline and better control faculty academic labor, in order to produce a greater number of unwaged, self-disciplined students, while ensuring the productivity of waged labor. Productive, self-disciplined students are destined, as labor power, to meet the growing demand for precarious “platform” or “gig” work organized around algorithmic management.

OLE is misleadingly advocated as a cost-effective method of delivering “equitable” “access” to higher education. However, the American Council on Education has found insufficient evidence of the purported “cost savings” used to justify OLE, once fixed technology and staffing costs are included. A 2020 study by Education International found that LMS companies are preempting opposition to the high capital costs by covering the start-up costs in exchange for half or more of students’ fees. In fact, OLE is increasingly populated by a growing proportion of poor and non-white students for whom support services are automated, outsourced, inaccessible, inadequate, or lacking, amounting to what Michelle Alexander called a kind of “new Jim Crow” that we can also see in higher education (Ovetz 2015).

Tactical Defiance and Strategic Rigidity

OLE is the latest strategy in a decades-long program of corporate pressure to make students more efficient, productive, and “work ready” while forcing them onto “guided pathways” to speed them through higher education. The rationalization of academic labor is the flip side of platform/gig work where the worker is remotely managed by the algorithmic “black box” that functions as the relentless gaze of the panopticon (to use the French philosopher Michel Foucault’s term). Such “dataveillance” (Williamson 2020) subjects the worker to the ubiquitous potential of always being seen, without knowing when they are actually actively monitored. All the while, this Odin’s eye continues to generate a relentless data stream, detailing their every move.

In this way, the labor of faculty and students are closely interconnected. As David Harvie (2006) argues, teaching faculty’s labor is intended to produce disciplined student labor power for exploitation in the capitalist system. To the degree that faculty refuse to discipline and students refuse to be disciplined, teaching becomes unproductive to capital and ruptures the circuit of the reproduction of labor power.

Understanding this productive relationship of higher education in capitalism helps connect struggles over the faculty’s paid academic labor with those of students’ unpaid labor of schoolwork and of many students’ (similarly contingent) service jobs. Thus, the effort to identify the commonalities of precarious academic labor between the supermajority of the professorate and students is also the first step toward the recomposition of the power of all academic labor.

These connections need to be informed by an analysis of the role of higher education in capitalism, in which faculty academic workers, according to Harvie (2006), “co-produce new labor power” of new waged workers who “will in turn be employed to produce value and surplus value.” Harvie uses a class analysis that makes explicit how reforms such as “datafication,” OLE, and performance measurements are each “a concrete expression of capital’s social drive to enhance the quality of human labor power” while driving down the costs to reproduce it. The shift to OLE, datafication, and other performance-based measurements, such as student opinion surveys of faculty, are in reality a shift to continuous assessment and control of work both inside and outside of higher education.

Rather than situate our understanding of higher education in its productive relations, we have instead continued to mourn worsened academic working conditions, overcrowded classes, the lack of available courses, the rise in tuition, fees, and housing costs, and the push to online-ify more and more of higher education, against the wishes of faculty and students. The predominant strategy has been to attack the neoliberal program that channels the tax burden downward while increasing the costs to students, recouped by ever-expanding debt that they must work to repay.

But this strategy has failed us for decades, and it is likely to continue to do so until we carry out a workers’ inquiry (Ovetz 2020) of the current technical composition of what Sheila Slaughter and Larry Leslie (1999) call “academic capitalism.” Such an inquiry will inform new tactics, strategies, and objectives that can be circulated among a growing number of academic workers. Because there has been little attempt to assess the current composition of academic labor to date, the outcome is as yet uncertain. With the arrival of the COVID-19 pandemic and global online-ification, OLE has now become central to the struggle over academic labor.

Academic workers need to identify new forms of tactical defiance and strategic rigidity (Ovetz 2017; 2022, 233-237) that can develop into various forms of organization and refusal, complementing the organizing of adjunct faculty. For example, at the level of governance, faculty have immense power to diffuse, disrupt, or slow online-ification by “rebundling” academic labor such that faculty remain in charge of design, delivery, and assessment of their own unique, yet limited, OLE courses.

Academic worker struggles can no longer ignore the threat of rationalization. A vivid illustration of the way in which algorithmic management has been deployed against organized faculty and student academic labor is seen in Mariya P. Ivancheva et al.’s 2020 study of South Africa. During the #FeesMustFall and #RhodesMustFall student strikes in that country in 2015–16, administrators used OLE systems to keep universities open. South Africa was thus a local trial run for the global shift from in-person teaching to OLE that occurred during the COVID-19 pandemic, a shift that was nearly instantaneous in the Northern Hemisphere during spring 2020, when academic workers’ organized struggles underwent severe decline. Organizing technical non-teaching staff, such as course designers who build and service the algorithmic management infrastructure, is critically necessary to avoid a repeat of such defeats.

As long as academic governance bodies and faculty unions still retain powerful roles in campus governance, numerous tactics could be used to expand faculty intransigence and rigidity to slow down the process of online-ification and proletarianization. Edtech ideologues admit that deeply entrenched faculty resistance (Young 2018) is the greatest threat to further expansion and openly call for removing faculty control over OLE either by breaking shared governance and faculty unions or coopting faculty through stakeholder engagement and professional development. Faculty should be escalating their tactics and deploying strategies to make this potential impediment a reality.

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