Here is described the implementation of adaptivity in Moodle: a specific but very common Learning Management System. After a preliminary study about the adaptive built-in features in moodle learning management system, and the capabilities ready to perform a suitable student modeling, the research team extended Moodle capabilities with a specific data model, student model and tutoring engine to perform automatic monitoring and sequencing of learning objects for each particular learner. The future implementation of this project is related to testing activities in order to prove the efficiency method in content and course delivery. Keywords. Adaptive Learning, Intelligent Systems, learning management, moodle, student modelling, activity locking.

The huge amount of online conversations that arises from the new means of communication between users, if analyzed and capitalized, is an important resource for companies and brands alike. Thus, a fundamental tool for the management of the relationship with customers such as CRM seems to be exceeded. The concept of a Social CRM platform was born with the objective of filling the gap between brand and customers connected to various social networks, allowing both parties to achieve tangible benefits from active participation. The key objective of this research involves the implementation of a Social CRM system, which is not yet present on the automotive market. The work starts through the identification and implementation of an experimental prototype that can define and highlight a methodological and technological best practice in the integration of heterogeneous components of an information system composed of independent software and continues with the definition of an integrated system that allows innovative Business Intelligence activities.

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.