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Résumé : Four descriptions of learning analytics are widely cited.Siemens (2010) described learning analytics as and analysis models to discover information and socialThe website for the 1 st International Conference on Learning Analytics and Knowledge posted this de-1 Educause models to predict student progress and performance, modelling capacity of analytics: to predict behaviour, act on predictions, and then feed those results back into the process in order to improve the predictions These descriptions beg fundamental questions.What data should be gathered for input to methods that 1 https:/ /tekri.athabascau.ca/analytics/computations that underlie analytics and, second, what analytics can say about phenomena.For instance, ordinal (rank) data preclude using arithmetic operations on data, such as addition or division.If data are not ordinal, A cannot be described as greater than B, nor are transitive statements valid: if A > B and B > C, then A > C. What properties of data bear on the validity of interventions based on learning analytics developed from grounds for intervening without other data.None of these data classes are legitimately considered a with other courses or a job).And, notably, prediction does not supply valid grounds for inferring causality.Learning ecologies involve multiple actors.Authors of learners about how to study; font styles and formats Chapter 21: Learning Analytics for Self-Regulated Learning