International Journal of Human-Computer Studies
Data mining in course management systems: Moodle case study and tutorial
Computers & Education
Proceedings of the 1st International Conference on Learning Analytics and Knowledge
1st International Conference on Learning Analytics and Knowledge
iSpot analysed: participatory learning and reputation
Proceedings of the 1st International Conference on Learning Analytics and Knowledge
Dataset-driven research for improving recommender systems for learning
Proceedings of the 1st International Conference on Learning Analytics and Knowledge
Variable construction for predictive and causal modeling of online education data
Proceedings of the 1st International Conference on Learning Analytics and Knowledge
Usage contexts for object similarity: exploratory investigations
Proceedings of the 1st International Conference on Learning Analytics and Knowledge
Learning analytics: drivers, developments and challenges
International Journal of Technology Enhanced Learning
Supporting action research with learning analytics
Proceedings of the Third International Conference on Learning Analytics and Knowledge
Dependencies between E-Learning Usage Patterns and Learning Results
Proceedings of the 13th International Conference on Knowledge Management and Knowledge Technologies
Towards a script-aware monitoring process of computer-supported collaborative learning scenarios
International Journal of Technology Enhanced Learning
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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 datasets to support the learning process. Learning analytics LA is a multi-disciplinary field involving machine learning, artificial intelligence, information retrieval, statistics and visualisation. LA is also a field in which several related areas of research in TEL converge. These include academic analytics, action analytics and educational data mining. 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.