Abstract:

There is a pervasive, increasingly globalized discourse around learning analytics in higher education. Jisc, a UK-based higher education non-profit enterprise defines learning analytics as “the measurement, collection, analysis and reporting of data about the progress of learners and the contexts in which learning takes place. Using the increased availability of big datasets around learner activity and digital footprints left by student activity in learning environments, learning analytics take us further than data currently available can” (Jisc, 2016).

This definition links more localised course-level data to larger “big datasets” across courses, programmes, faculties and entire institutions. Conversely, the New Media Consortium (NMC) have more comprehensively define learning analytics as “an educational application of web analytics, a science that is commonly used by businesses to analyze commercial activities, identify spending trends, and predict consumer behavior. Education is embarking on a similar pursuit into data science with the aim of learner profiling, a process of gathering and analyzing large amounts of detail about individual student interactions in online learning activities.” (NMC, 2016).

NMC’s linking of business analytics to learning analytics is important: it frames learning in higher education as commodified, which position learners as consumers and institutions as vendors. In this paper, I problematize this increasingly pervasive discourse around learning analytics as an hegemonic “régime of thought” (Foucault, 1980, p. 81), offering a “local character of criticism” (p. 81) to disrupt this ostensive hegemony.

My criticism has three foci. First,: there are multiple ways an LMS can be deployed to support teaching as a digital repository for classes taught face-to-face, where nothing is taught online; a platform to wholly deliver classes online, where nothing is taught face-to-face; or an extension into blended classes, where elements are taught online and face-to-face. Therefore, a broad spectrum of activity occurs within an LMS. However, most of what is captured amounts to user behaviours rather than learning activities—or evidence of learning. Second, scant equivalent data on face-to-face teaching-related learner behaviours exist: there is no analogue to LMS data for face-to-face teaching. Finally, academic analytics, upon which many higher education leaders focus, are not data derived from teaching and learning. Rather, variables such as socio-economic status, ethnicity, region, gender, secondary school grades, and parental educational attainment are sometimes better systemic predictors of student performance.

The learning analytics discourse cannot serve the interests of teaching quality: the data captured are exclusive of face-to-face teaching. In whose interests, therefore, are such data? This “régime of thought” (Foucault, 1980, p. 81) has utility for managing and disciplining actors in an institution. We at the fore of higher education must problematize this discourse through scholarship and advocacy and offer substantive, purposeful local criticism. Most importantly, given that F2F teaching remains the most common—ostensibly preferred—delivery mode, this discursive shift towards learner analytics is a distraction.