User Modeling and User-Adapted Interaction
Mining LMS data to develop an "early warning system" for educators: A proof of concept
Computers & Education
Networks: An Introduction
Attention please!: learning analytics for visualization and recommendation
Proceedings of the 1st International Conference on Learning Analytics and Knowledge
Discourse-centric learning analytics
Proceedings of the 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
A unified framework for multi-level analysis of distributed learning
Proceedings of the 1st International Conference on Learning Analytics and Knowledge
Cultural considerations in learning analytics
Proceedings of the 1st International Conference on Learning Analytics and Knowledge
Learning analytics as a "middle space"
Proceedings of the Third International Conference on Learning Analytics and Knowledge
Proceedings of the Third International Conference on Learning Analytics and Knowledge
STEMscopes: contextualizing learning analytics in a K-12 science curriculum
Proceedings of the Third International Conference on Learning Analytics and Knowledge
An evaluation of policy frameworks for addressing ethical considerations in learning analytics
Proceedings of the Third International Conference on Learning Analytics and Knowledge
Data wranglers: human interpreters to help close the feedback loop
Proceedings of the Fourth International Conference on Learning Analytics And Knowledge
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Learning analytics are rapidly being implemented in different educational settings, often without the guidance of a research base. Vendors incorporate analytics practices, models, and algorithms from datamining, business intelligence, and the emerging "big data" fields. Researchers, in contrast, have built up a substantial base of techniques for analyzing discourse, social networks, sentiments, predictive models, and in semantic content (i.e., "intelligent" curriculum). In spite of the currently limited knowledge exchange and dialogue between researchers, vendors, and practitioners, existing learning analytics implementations indicate significant potential for generating novel insight into learning and vital educational practices. This paper presents an integrated and holistic vision for advancing learning analytics as a research discipline and a domain of practices. Potential areas of collaboration and overlap are presented with the intent of increasing the impact of analytics on teaching, learning, and the education system.