[u' @inproceedings{orduna_learning_2014, title = {Learning {Analytics} on federated remote laboratories: tips and techniques}, abstract = {A remote laboratory is a software and hardware tool which enables students to use real equipment -located in an educational institution- through the Internet. This way, students can experiment as if they were using the laboratories with their own hands. And, depending on the design, instructors can later see the results of these students. During the last decade, federation protocols to share remote laboratories have emerged. The focus of these protocols is to be make remote laboratories of one institution available in other in an automated manner, through institutional contracts. And these federation protocols usually rely on existing Remote Laboratory Management Systems (RLMS), which usually provide APIs for tracking student usage. At the same time, the interest on Learning Analytics is increasing. Learning Analytics focuses on the measurement and analysis of data about learners in their context. In the particular context of federated remote laboratories, new challenges arise: on the one hand, remote laboratories must be prepared to track insightful information from the student session so as to extract patterns, and on the other hand, the usage of a federated environment requires different degrees of anonymity. This contribution describes the new Learning Analytics dashboard of WebLab-Deusto, detailing what information can be extracted and how the usage of a RLMS simplifies the development of such tools in a federated environment.}, author = {Ordu\xf1a, Pablo and Almeida, Aitor and L\xf3pez-De-Ipi\xf1a, Diego and Garc\xeda-Zubia, Javier}, month = apr, year = {2014}, note = {00000}, keywords = {Artificial Intelligence, Data analysis, ISI, Learning Analytics, Remote Laboratories, data mining, educational technology, la-weblab, learning technologies, machine learning, mcloud, social network analysis, social networks}, } ']