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The quick technological evolution of the last decades has also reached learning environments, where the use of networked computing devices such as laptops, smartphones, tablets, IoT devices, servers, etc. is continuously growing. In particular, those computerized learning environments have the potential to track the activity of teachers and students in them, which enables the development of innovative applications that enrich the learning process by analyzing the collected data. The majority of related work in this field has been centered on batch gathering and analysis of the data. However, in order to integrate more reactive applications, there is a need for an infrastructure that enables the real-time collection and analysis of data in learning environments. Such an infrastructure should be scalable and flexible enough to cope with heterogeneous data coming from different types of learning settings. This paper presents Lostrego, a stream-based, modular, scalable and flexible distributed infrastructure that allows the gathering and analysis of educational data from heterogeneous data sources in a real-time fashion. Lostrego applications are composed by interconnected services that can be reused in different courses. The results of the evaluation of Lostrego in two editions of a computer programming course with 233 students and 384,702 gathered events are also reported.
Educational systems Learning analytics Data streaming Publish subscribe infrastructure Service-oriented Real-time learning analytics