When our Special Section “Towards a critical perspective on data literacy in higher education. Emerging practices and challenges” was accepted by ETHE in 2019, an advanced debate on the impact of datafication was already in place. Datafication is that particular digital technologies feature we were unaware of, namely, users’ data capture and commodification. That same year, a landmark book by Shoshana’s Zuboff was going to explain the dynamics of datafication through the theory of “Surveillance Capitalism” (here a book’s review I recommend). As the editors of the above-mentioned Special Section, we were five scholars committed to different facets of digital transformation in higher education. Stefania Manca had been actively working in the field of social media from a socio-technical perspective. Bonnie Stewart brought to the Special Section a relevant perspective on the evolution of the prosocial web, having developed her work in relation to media education and digital scholarship. Paul Prinsloo was (and is!) a key reference relating to the ethics of learning analytics, having produced several studies around the vulnerability of those whose data was being captured in higher education. Finally, Albert Sangrà had been analysing the problem of university rankings, considering the unfair practices in quantifying and marginalising the quality of online education. I was extremely lucky to have them in the same space of conversation around the problem of datafication in higher education, and, at the same time, to catch ETHE’s interest in our proposal.
ETHE’S attention on our ideas was situated, indeed. They had already been publishing Sections addressed to the critique of educational technologies’ narratives, claiming for a renewed vision of what we (academics, students, staff) were doing with edtech in Higher. My attention went particularly to the following Thematic Series More than tools? Critical perspectives and alternative visions of technology in higher education (Edited in 2018 by Linda Castañeda and Neil Selwyn whose scholarly work had been influential in the last decade at a global level, and in the Spanish speaking countries); Technology Enhanced Learning or Learning driven by Technology? (Edited in 2019 by an interdisciplinary and intercultural team: Denise Whitelock, Eric Ras, Nicola Capuano, Maria Jesús Marco Galindo and David Baneres); and Can artificial intelligence transform higher education? (Edited later in 2019 by: Tony Bates, Cristóbal Cobo, Olga Mariño and Steve Wheeler, again, an amazing group of scholars in the field of educational technologies).
Our Special Section attempted to contribute to the ideas above by considering the evolution of the digital landscape under data-intensive practices. We provided a purposely broad definition of data practices, aiming at exploring and discussing different perspectives, spanning from educational data mining to open research data for teaching as part of responsible research and innovation. In the end, the goal of the call for papers was to provide a description of ongoing data practices and narratives in higher education as far as making space for a critique of their limitations. We did not overlooked technological developments, but we discussed it under different lights, purporting that data practices required a situated understanding and deconstruction in order to achieve a fair, balanced, evolving approach. I had been considering the concept of “data culture” elsewhere and we all agreed that by supporting the development of critical data literacies in higher education, we might achieve fairer data cultures not only within the institutions, but also in society. It was just a concept to bring together the several perspectives and to try and frame our educational interventions against the dystopian scenarios of datafication.
We selected hence four works that shed light on these ideas through cases and studies with glances over data practices, dispositions, and literacies. Despite the nuances and differences in our positions, we converged on the compelling need to make more transparent the social and cultural structure motivating data production, elaboration, and usage. The cases composing the Special Section underlined the relevance of promoting practices such as uncovering the students’ vulnerability in the techno-structure; participating in the design of data practices to understand and discuss pedagogical and organisational interests and to evaluate the impact of data-driven operations; considering the social impact of data usages; and last, but not least, developing the literacies required not only to read or understand data as text, but to take an active part in the creative and participatory processes which use data as just a mediational artefact.
But as anyone in 2019, we were unaware of what was coming next: the COVID-19 pandemic. Initially seen as a “huge experiment” for online education (it was March 10 th when that was announced at the Chronicle of Higher Education), many discussed that such an assumption was just a naïve understanding of the “digital” as solution. In fact, the situation rapidly evolved towards an uneven landscape of practices and solutions. And rather than strengthening the merits of the digital (announced in the last three previous decades since the beginning of the Internet), the pandemic exacerbated the injustices just digital: lack of connectivity, access, devices availability, and the educators and students’ digital competences necessary to develop the educational activity (Williamson et al., 2020). Most importantly, the platformisation of education became extremely visible, as a sort of Trojan Horse entered in the public educational space. Having played an initial role as generous and even philanthropic provider of easy solutions for the locked-down students, Ed Tech industry revealed another face. It was because of a rapid response from social research that critique and deconstruction were applied to understand the problematic interests held by EdTech companies or even worst, sectors of the Big Tech industry rapidly evolving into educational providers. Tellingly, the free offering of digital platforms to deliver video lectures, to support virtual classrooms and social learning, all relevant elements during the pandemic and celebrated as approaches in educational research, were provided at the cost of extracting digital data. Such data would be further monetised by using it as the base to train the so-called AI-assisted classrooms tools (AIED) and to profile and offer the right solutions to the right audiences.
Nevertheless, this approach to digital data was already a trend already considered in critical and socio-technical studies in education before the pandemics (Anderson & Rivera-Vargas, 2020; Castañeda & Selwyn, 2018; Knox, 2017; Perrotta & Williamson, 2018; Selwyn, 2015; Shum, 2019; Williamson, 2017a, 2017b). In such a context our Special Section was also contributing not only through the critique and the deconstruction of educational technologies in higher education, but also through the idea of promoting data literacy as means to support a more reflective digital transformation of higher education. This entailed, for us, to rethink academics as more than passive objects of datafication, that is, as active subjects in building fairer data practices in teaching and research. We also brought to the fore the compelling need of acting together while dealing with the advances of data practices connected to artificial intelligence, in the terms adopted by Selwyn and Gašević (Selwyn & Gašević, 2020): by promoting a continuous interdisciplinary conversation to come to terms or, even better, to generate approaches which are aware of the agendas in education/social sciences and computer science.
Nonetheless, the pandemic put under our eyes the political problem relating to data practices and the need to move beyond the single institution, to discuss digital transformation at regional and national levels (Williamson & Hogan, 2021). By following the relevant ideas purported in the articles published as part of the “Platform Studies in Education” Symposium at the Harvard Educational Review, I reconsidered the role of developing data literacy and more participatory approaches to promote “fair data practices”. Instead, the data cultures are deeply entrenched with the digital infrastructures very often considered just “technical decisions” and not sufficiently discussed at regional, national and transnational level (Fiebig et al., 2021; Williamson et al., 2022). This is what this new strand of research on the platformisation is pointing at: there is a compelling need of considering the private platforms’ influence on the whole higher education system, how they constrain professional practices and identities, and how the political engagement to take decisions about the techno-structure is invisibilised by the “fast pace” of educational innovation “pushed by” the “needs” raised by the pandemic aftermath.
I said, by introducing ETHE’s Special Section, that “with the current state of affairs, it is not unusual to see ‘techno-solutionism’ around problems (…) The forms of de-responsibilization which the objectivist positionings around data practices create is a clear expression of the pressure on the system to produce results fast. The faster, the simpler, the better, which entails less attention to the need for complex interventions where data-driven practices are just another piece of the puzzle”.
Though formulating a critical approach to educational datafication and platformisation is (and has been) extremely relevant; and though reframing the literacies needed to thrive in this post-digital context have generated new spaces for the pedagogical practice… the critical perspective over data literacy is not enough!
Following other brilliant colleagues, starting by my co-editors’ subsequent research in the field, I’m still convinced that the ethics, the politics and even the narratives and their aesthetics are embedded in the materiality of data, and a crucial endeavor will be to embrace approaches that help deconstruct the techno-structure from diverse perspectives, like feminism (D’Ignazio & Klein, 2020) or the decolonial theory (Prinsloo, 2020; Ricaurte, 2019). For a fair data culture could not disregard the complex and political nature of data infrastructures (Kuhn & Raffaghelli, 2022).
Therefore, transforming the data infrastructures we live by will require active participation to rethink them democratically. To this regard, it will be necessary to discuss and experiment several approaches to support a sustainable distribution of power across better situated, local data ecosystems (see for example the XNet participation to the debate in the EU, and the declaration discussed at an independent congress on digital democratisation). Such ecosystems should be nurtured not only by technological development but also by participatory data practices, aimed at shared data futures, to express it in Selwyn terms (2021). And again, the research on educational technologies in higher education will be called to nurture new spaces for creativity and dialogue.
Anderson, T., & Rivera-Vargas, P. (2020). A critical look at educational technology from a distance education perspective. Digital Education Review, 0(37), 208–229. https://doi.org/10.1344/DER.2020.37.208-229
Castañeda, L., & Selwyn, N. (2018). More than tools? Making sense of the ongoing digitizations of higher education. International Journal of Educational Technology in Higher Education, 15(1), 22. https://doi.org/10.1186/s41239-018-0109-y
D’Ignazio, C., & Klein, L. F. (2020). Data Feminism. MIT Press. https://doi.org/10.7551/mitpress/11805.001.0001
Fiebig, T., Gürses, S., Gañán, C. H., Kotkamp, E., Kuipers, F., Lindorfer, M., Prisse, M., & Sari, T. (2021). Heads in the Clouds: Measuring the Implications of Universities Migrating to Public Clouds. ArXiv:2104.09462 [Cs]. http://arxiv.org/abs/2104.09462
Knox, J. (2017). Data Power in Education: Exploring Critical Awareness with the “Learning Analytics Report Card”. Television & New Media, 18(8), 734–752.
Kuhn, C., & Raffaghelli, J. (2022). Report for the project: Understanding data: praxis and politics. Bath Spa University. https://doi.org/10.5281/zenodo.6482614
Perrotta, C., & Williamson, B. (2018). The social life of Learning Analytics: Cluster analysis and the ‘performance’ of algorithmic education. Learning, Media and Technology, 43(1), 3–16. https://doi.org/10.1080/17439884.2016.1182927
Prinsloo, P. (2020). Data frontiers and frontiers of power in (higher) education: A view of/from the Global South. Teaching in Higher Education, 25(4), 366–383.
Ricaurte, P. (2019). Data Epistemologies, The Coloniality of Power, and Resistance. Television & New Media, 20(4), 350–365. https://doi.org/10.1177/1527476419831640
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Selwyn, N. (2021). Data futures. In The Sage Handbook for Digital Sociology.
Selwyn, N., & Gašević, D. (2020). The datafication of higher education: Discussing the promises and problems. Teaching in Higher Education, 25(4), 527–540.
Shum, S. J. B. (2019). Critical data studies, abstraction and learning analytics: Editorial toSelwyn’s LAK keynote and invited commentaries. Journal of Learning Analytics, 6(3), 5–10. https://doi.org/10.18608/jla.2019.63.2
Williamson, B. (2017a). Big Data in Education. The digital future of learning, policy and practice.
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Williamson, B., Eynon, R., & Potter, J. (2020). Pandemic politics, pedagogies and practices: Digital technologies and distance education during the coronavirus emergency. In Learning, Media and Technology (Vol. 45, Issue 2, pp. 107–114). Routledge. https://doi.org/10.1080/17439884.2020.1761641
Williamson, B., Gulson, K., Perrotta, C., & Witzenberger, K. (2022). Amazon and the New Global Connective Architectures of Education Governance. Harvard Educational Review, 92(2), 231–256. https://doi.org/10.17763/1943-5045-92.2.231
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