Fuzzy predictive models to help teachers in e-learning courses

e-Learning comprises the use of electronic devices for learning, including the delivery of content via electronic media such as Internet/Intranet/Extranet, audio or video, satellite broadcast, interactive TV, and so on. Initially, e-learning was presented as the best solution to cover the needs and requirements of remote students, but also as a helping tool in the teaching-learning process, reinforcing or replacing face-to-face education. However, many real projects have failed, or have performed below expectations, due to the fact that a huge amount of time is required just in the process of providing feedback to the virtual learners, resulting in an increasing demand of teachers and, therefore, of the educational costs. This research is focused on the development of fuzzy inductive models to predict dynamically students´ performance in e-learning courses, with the goal to help teachers to give feedback to the students easily and efficiently, enhancing student´s learning behaviour.