A Reference Model for Learning Analytics

Recently, there is an increasing interest in learning analytics in Technology Enhanced Learning (TEL). Generally, learning analytics deals with the development of methods that harness educational data sets to support the learning process. Learning analytics (LA) is a multi-disciplinary field involving machine learning, artificial intelligence, information retrieval, statistics, and visualization. LA is also a field in which several related areas of research in TEL converge. These include academic analytics, action research, educational data mining, recommender systems, and personalized adaptive learning. In this paper, we investigate the connections between LA and these related fields. We describe a reference model for LA based on four dimensions, namely data and environments (what?), stakeholders (who?), objectives (why?), and methods (how?). We then review recent publications on LA and its related fields and map them to the four dimensions of the reference model. Furthermore, we identify various challenges and research opportunities in the area of LA in relation to each dimension.