Using Logical Sensors Network to the Accurate Monitoring of the Learning Process in Distance Education Courses

There are several systems to help monitoring the learning process in Learning Management System (LMS). Most of them are based on a post evaluation of data in logs and databases. Also, they are not accurate enough to detect users´ more complex actions. This paper introduces a logical sensors network-based system to support the accurate monitoring of learning process in Distance Education courses. For that, logical sensors are deployed in an LMS to detect relevant information, as far as the application is concerned, about a user. A user can be a student, a tutor, a teacher or a pedagogical coordinator. For a student, this information can vary from those taken directly in LMS to users´ interaction intentions, such as the attempts to access or to perform a task, which combined with other indicators of participation can help identifying problems in the learning process related to the course design. Simple logic, ontologies and fuzzy logic are used for the user´s context interpretation. The main objectives of this system are: (1) to contribute to mitigate problems such as poor school performance, low participation of students and tutors and high dropout rates, and (2) to create a basis for personalized education.