Evaluation of Student Performance in adaptive e-learning processes with active tutorship

How could data mining help the development of e-learning methodologies? How could an instructional designer take benefit from the use of adaptive learning? How could adaptive learning be implemented in an Open Source platform? In this paper will be described the implementation of adaptivity technology in a specific, Open Source, Learning Management System (LMS). After a preliminary study about the adaptive features already built-in and the capabilities ready to perform a suitable student modeling, the research team extended those capabilities with a specific data model, student model and tutoring engine to perform automatic monitoring and sequencing of Learning Objects for each particular learner. Testing activities has proven the efficiency method in content and course delivery and give the opportunity to further develop a predicting tool based on data mining student modeling. This provides an efficient tool in tutorhisp activities. This paper describes some best practices developed during a Tempus IV Project granted by EU.