A business intelligence model for online tutoring process

This work aims to implement business intelligence strategies in an educational institution based on the distance education, particularly in the online tutoring process. In this paper we propose to use the business intelligence paradigm to analyze the online tutoring process, based on the data collected on the interactions of students and teachers in a virtual learning environment, and the results recorded in the institutional academic system of evaluations. This analysis should answer the following questions: 1) Can we define a model of online tutoring that can adapt to each student profile? 2) Can we predict the success of an online tutoring process for a course and a student given? To this purpose, this paper presents three aspects: characterize and determine the key elements in an online tutoring process, build a descriptive model of the online tutoring process, and build a predictive model of the success of the online tutoring process. The models to be defined will be based on data mining techniques, and will be obtained from the current data stored in transactional databases of the University. This data is preprocessed with ETL techniques to build a multidimensional model, and the key elements are obtained through operations OLAP.