I pinned this cartoon to Pinterest because it made me think about learning analytics and its requirement to model the student and map the knowledge domain against which she might be measured. Williamson emphasises the importance of modelling,
complex human and social activities – and the values and assumptions held about them – are operationalized by being translated into a functional interaction of models, goals, data, variables, indicators, and outcomes. The algorithm itself, in this sense, may not be as important an object of inquiry as the underlying ‘models’
(Williamson, 2017, p.84)
Does modelling de-humanise the student by reducing her to data and, even if that is the case, are hitherto unrealised patterns of behaviour revealed which might help her? The more detailed and recursive the modelling, employing techniques of machine learning, the more faithful the model and potentially, the more useful a prediction or prescription. However, as Siemens (2013) admits, analytics is “about identifying and revealing what already exists” (p.1395), leaving little scope to unearth the accidents and epiphanies of learning.
Just Pinned to Education and Digital Cultures: Data dehumanises? http://ift.tt/2mJqI2u