ABSTRACT
The numerous emerging applications of learning analytics aim to improve various aspects of educational provision. For many people and institutions, though, learning analytics is synonymous with predictive analytics, in particular with determining how students are likely to perform academically and whether they are at risk of failure or dropping out. These predictions can then be used to determine which students may benefit from an intervention, either automated or human mediated.
