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Digital technological innovations have the potential to improve higher education and bring benefits to students, academics, and university administrators. They also bring new monetisation opportunities. Indeed, the education technology market is worth $187bn with 15% growth rate as estimated by IBIS Capital [1]. Investment in education technology is unprecedented, including the capitalisation of companies. As of October 2020, there are already 20 identified education technology unicorns in the world, i.e. companies valued over $1bn, as reported by HolonIQ [2]. Who are the actors in this fast-expanding market and who profits, what kind of monetisation models are being developed, and why does it matter?

Universities around the world are increasingly digitalising all of their operations, with the current COVID-19 pandemic speeding up otherwise steady developments. Using virtual learning environments and digital communication platforms for teaching and learning, applying learning and business analytics for decision-making, and turning university campuses smart, are only a few examples of the fast-expanding global digital ecosystem in higher education.

There is ample research on digital technology in relation to teaching and learning processes, including the impact of particular software or applications. There is far less research on the issues around privatisation, monetisation, and new forms of value related to higher education digitalisation. Research on these questions is only just emerging. Yet, analysing these processes is crucial in understanding the contemporary digitalisation dynamics in the sector.

In my article " The future of value in digitalised higher education: why data privacy should not be our biggest concern", I propose the empirical, theoretical, and political moves for higher education researchers. They are equally relevant for higher education policymakers and stakeholders.

Empirical move

We cannot understand the digitalisation of higher education as separate from the globally expanding digital economy. The defining element of the digital economy is business models focussed on digital goods and services enabled by digital platforms. Platforms are socio-technical intermediaries, which act as infrastructure at the same time. This way, they record and extract all data on users’ actions and interactions, as well as metadata on users’ location, machines they use, and their click-through behavior. The collected digital data is then made valuable by enclosure, storage, aggregation, analysis, and transformation into intelligence. Education technology industry (EdTech) is a good proxy for the presence of the digital economy in the education sector. As mentioned above, the growth of EdTech is impressive.

There are many different platforms present in the higher education sector. Some are developed by universities alone. Most are proprietary, and universities either act as users, such as with the proprietary virtual learning environment platforms; or as partners, such as with the Online Programme Management companies with which they deliver programmes online and share profits. Finally, some platforms target individual students and staff directly. In the article, I start examining the types of actors who are part of digitalisation processes in higher education, what is being digitalised, and various monetisation models. The commonality among the different models that I identify is that they are not selling a commodity, but are charging rent in the form of subscription fees, fees per click, time spent on a platform, and so forth. We do not know much about the relations between these different actors in various business and monetisation arrangements. These need to be analysed in-depth on a case-to-case basis.

Theoretical move

Most research on the intersection of digitalisation and marketisation of higher education thus far employs a theory of markets as institutions exchanging commodities. Commodification and commodity form are in the analytical foreground. However, the expanding digital economy is marked with the rise of rentiership, i.e. the appropriation of value through ownership and control rights, as Kean Birch [3] argues. Instead of entrepreneurial strategies based on commodity production, there is a focus on financial strategies of turning things into assets. Birch proposes a theory of rentiership consisting of three steps: ‘thingification’ of knowledge, turning things into assets, and capturing economic rents.

Assets come in different sizes, forms, and shapes. The kinds of assets relevant in the digitalisation of higher education are intangible assets, and the main governing mechanisms become contracts in the form of copyright issued and patents secured by platform owners. In the theoretical move, I suggest that higher education researchers employ rentiership theory and study assetisation processes. I propose they identify and follow various data rent models, which are being developed in the sector as we leave behind our digital traces.  It is safe to assume that there are different ways of governing extracted digital data in higher education. Again, not much is known. From this perspective, data access, ownership, and control become crucial questions.

Political move

The way how the digital economy more broadly has been developing so far is marked with a particular form of rentiership based on the established intellectual property rights regime. Practice superseded theory and policy. UNCTAD [4] cautions that the direction in which it is developing is marked by the digital divide, inequality, and uneven development. It calls for global policy coordination and regulation. It is not known how constructing value has been developing specifically in higher education. We thus urgently need research, as well as political action.

There are various relations existing in the digitalised higher education ecology. The first is between platform companies and individual users, which are governed by terms of use issued by platform owners. The second is between platform companies and universities, which are governed by contracts they negotiate. The third is outsourced third party services by either platform companies or universities, governed by contracts between them. In some of these relations, students and staff as individual users of platforms become subject to nested data and privacy policies. We do not know if students and staff as users, in fact, know where the data they produce is going, and if they agree with these practices. Giving consent to terms of use unilaterally issued by platform owners is by some authors seen as disempowering individuals. Moreover, they might be indicative of a potential shift in the higher education governance from public law to contract law and commercial sensitivity. This again deserves much-needed research attention.

The only regulation existing thus far is on data privacy, with the GDPR seen as the most developed framework in the world. Data privacy is immensely important, especially in the light of surveillance. However, regulation on data privacy only applies to parts of the world. Also, it does not tackle the question of data ownership and control beyond personally identifiable information. The questions of monetising de-identified and aggregated data are not tackled. The issue becomes normative and political. Who should benefit from the extracted data, and how? Are the ways how the economic value is captured now legitimate? Is the way how value is managed in digital higher education socially just? We are still to hold a debate on what kind of political economy of education technology we want, which needs to be organised at the international level.

Note:The forthcoming article mentioned above is titled ‘The future of value in digitalized higher education: why data privacy should not be our biggest concern’ (DOI: 10.1007/s10734-020-00639-7). It will be available as open source.

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References

[1] IBIS Capital, a specialist investment and corporate finance advisory group focused on media, education, and healthcare sectors: http://www.ibiscap.com/index.php/insights-research/(Accessed 18 September 2020).

[2] https://www.holoniq.com/edtech-unicorns/

[3] Birch, K. (2020). Technoscience Rent: Toward a Theory of Rentiership for Technoscientific Capitalism. Science, Technology, & Human Values, 45(1), 3–33.

[4] UNCTAD. (2019). Digital Economy Report: Value Creation and Capture—Implications for Developing Countries. Geneva: United Nations Conference on Trade and Development.