ABSTRACT

Learning analytics is developed within various disciplinary communities and is an instantiation of different ideas, each with its own long tradition. ‘Business analytics on e-learning’ is one such perspective; another one is ‘Web analytics on e-learning’. Other traditions are those of ‘learning analytics’, ‘knowledge analytics’ and ‘academic analytics’ developed in the field of Knowledge Management (see Siadaty, Gašević, Jovanović, Milikić, Jeremić & Ali, 2012 for a use of traditional Knowledge Management concepts in LA for workplace learning). A common theme in these fields is the detailed analysis of behavioural data describing the usage and production of knowledge resources. LA is also closely related to educational data mining (EDM). Both analyse learning data: EDM focuses on the data-mining models and fully automated modelling and personalisation, whereas LA draws on models from different disciplines. LA also applies modelling as well as personalising in a more semi-automated and interactive fashion (Siemens & Baker, 2012). Lastly, interactive LA, that is designed to be used by learners and others who are directly involved in the learning, are instances of feedback and awareness systems (Berendt, Clarke, De Wolf, Gao, Peetz, Pierson, J., 2012): systems that give a user feedback about her/his own behaviour, in an attempt to raise awareness about issues such as how one learns or how one learns in relation to what one thinks about how one learns.