Learning analytics and AI: Politics, pedagogy and practices

It is arguably human nature—and most certainly bureaucratic nature—to want to quantify our successes and failures. The ability to calculate a numerical value to represent the progress of an individual or an institution, a country even, is now central to evidence-based policy and practice. The counterpoint to “treasuring what we measure,” is of course, “what counts can’t always be measured, and what’s measurable doesn’t always count.” All institutions, education being no exception, have long wrestled with the tension that the powerful abstractions afforded by quantitative analysis also lose vital detail as context is stripped out. This is what makes the design of metrics to gauge the quality of nuanced human processes and outcomes (such as teaching and learning) so controversial. Across society, we see this debate now playing out in all spheres of human life, with ethical frameworks and professional codes of practice proliferating (eg, Asilomar, 2017; Floridi et al., 2018; IEEE, 2017; Montreal, 2017; Partnership on AI PAI, 2018)—although it is not clear that these are making much impact yet on computing companies (Whittaker et al., 2018, Section 2.3). How this debate should unfold in education and lifelong learning is the focus of this special issue, which brings together leading scholars in the field of Learning Analytics (LA) and Artificial Intelligence in Education (AIED)—fields that are viewed with varying degrees of excitement and suspicion by parents, students, teachers, journalists and scholars. The fears are reasonable: that quantification and autonomous systems provide a new wave of power tools to track and quantify human activity in ever higher resolution—a dream for bureaucrats, marketeers and researchers—but offer little to advance everyday teaching and learning in productive directions. This fear is justified in our post-Snowden era of pervasive surveillance, and post-Cambridge Analytica data breaches. Partly however, this fear is also born of lack of awareness about the diverse forms that LA/AIED take, which is equally understandable—to outsiders, these are new and opaque technologies. It follows that if we do not want to see concerned students, parents and unions protesting against AI in education, we need urgently to communicate in accessible terms what the benefits of these new tools are, and equally, how seriously the community is engaging with their potential to be used to the detriment of society. Politics, Pedagogy and Practices cannot, of course, be neatly split into separate analytical threads: they are mutually constitutive. Building on the critical analyses of information infrastructures (Bowker Star Edwards et al., 2013), we may now be seeing the emergence of “educational knowledge infrastructures” (Buckingham Shum, 2018)—these only exert political power through practices (in policy and design), which translate educational worldviews (whether implicitly or explicitly recognised: Knight, Buckingham Shum, Prinsloo, 2019; Williamson, 2019), and the design methodologies employed to make design decisions (Buckingham Shum, Ferguson, Richards Mavrikis, Geraniou, Gutierrez Santos, Luckin Richards Rosé et al., 2019). With respect to pedagogy, we anticipated critical narratives that explain how the use of quantification does not need to equate to the implementation of behaviourist or instructivist approaches to teaching and learning (du Boulay, 2019; Mavrikis et al., 2019). Finally, within the theme of politics, our goal was to garner accounts that recognise the political significance and the potential for power and influence that the intelligence infrastructure constructed through the use of big data, AI and analytics brings to the world. Accounts that would help us to be appropriately vigilant and judiciously embracing with respect to these technologies and the quantifiable approaches they can bring to education (Kitto Prinsloo, 2019; Richards Tsai et al., 2019; Williamson, 2019). We were also keen for clarifications of the that the three of our Politics, Pedagogy and Practices are deeply and Johanes Kitto & a of politics, pedagogies and practices that would it is only a of before LA/AIED to other pedagogies (eg, see the examples in 2019), concerns around and scientific always be In is a we all see and LA/AIED must recognise and value this as we into an future. we are to develop the Politics, Pedagogy and Practices that can us through the next we must to design that are and human These are not yet as visible as they could be in the LA/AIED community, but they are those that us from