Agostino Marengo

LIA: An Intelligent Advisor for E-Learning

Intelligent e-learning systems have revolutionized online education by providing individualized and personalized instruction for each learner. Nevertheless, until now very few systems were able to leave academic laboratories and be integrated into real commercial products. One of these few exceptions is the Learning Intelligent Advisor (LIA) described in this article, built on results coming from several research projects and currently integrated in a complete e-learning solution named Intelligent Web Teacher (IWT). The purpose of this article is to describe how LIA works and cooperates with IWT in the provisioning of individualized e-learning experiences. Defined algorithms and underlying models are described as well as architectural aspects related to the integration in IWT. Results of experimentations with real users are discussed to demonstrate the benefits of LIA as an add-on in online learning.

The OSEL Taxonomy for the Classification of Learning Objects

This project started from the necessity to create a taxonomic classification for the management of the Learning Objects (LO) repository used by the LCMS platforms. The classification obtained is now in use for the OSEL project (OSEL website – http://www.osel.it). The OSEL project is financed by the Statistics Department of the University of Bari. The aim is to analyze and to promote the introduction of blended elearning in the academic world. Many LCMSs Open-source platforms have been studied, tested and put at users’ disposal. The support to the ADL/SCORM (see http://www.adlnet.org) given by all the platforms has allowed the integration in the OSEL web of the repository service, along with the services already in use (forum, newsletter, glossary, database). The aim is to gather and to catalogue the LO products proposed in the various courses and managed by the learners on the web. Starting from Wiley’s (2000) and Redeker’s (2003) taxonomies, the research group studied the OSEL Taxonomy and presented the project of a web application able to classify the LO and to place them in order into the repository.

Ontological support for the creation of learning objects

This work belongs to a project in support of the semantic Web standard. The aim is to give an ontological support for the creation of e-learning courses. This will make a selection of learning objects according to semantic descriptors and in heterogeneous contexts, by means of a selective agent of didactic courses customized on the users preferences. This will also apply in the knowledge management systems where the time of answer to an informative need is a very critical aspect for the efficiency of the whole system

Adaptive learning: A new approach in student modeling

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.

Creation and Delivery of Complex Learning Experiences: The ELeGI Approach

The paper presents the main findings of the ELeGI project, namely its learning model and software architecture to support the creation and execution of complex learning processes.The learning model defined in ELeGI promotes and supports a learning paradigm centred on knowledge construction using experiential based and collaborative learning approaches in a contextualised, personalised and ubiquitous way.The software architecture has been designed and developed taking into account the learning model for the personalisation of complex learning experiences.In order to validate our results, the paper presents and describes a case study relating to the implementation of a Unit of Learning for explanation of the Torricellis law, and its execution on top of the Service Oriented Architecture.

An Open Source LMS Vision and Development. The Development of Innovative Web Technologies for E-Learning: The eLearning Portal Project

The aim of the project is the development of an inn ovative, Open Source-based eLearning portal, which provides high scalability and versatility, as well as it is easy to upgrade; it aims at meeting some changeable requirement in the field of distanc e learning (yearly or even monthly innovation). The modular structure and flexibility provided by t he portal makes this system adaptable to any kind of educational and/or academic situation, allo wing also the development in step with innovative and specific Web Technologies. The project has been developed thanks to the experi ence obtained in managing a postgraduate specialization course promoted by University of Bar i (www.comedudida.org ) and it keeps developing as suitable tools for proper online form ation are designed. This experience has been studied inside the OSEL research project by Univers ty of Bari (www.osel.it).

Evaluation of Student Performance in Adaptive E-Learning Processes with Active Tutorship

This paper describes the implementation of adaptive 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 given the opportunity to further develop a predicting tool based on data mining student modeling. This provides an efficient tool in tutorship activities. This paper describes some best practices developed during a Tempus IV Project granted by EU.

Data Mining Methods to Assess Student Behavior in Adaptive e-Learning Processes

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. The future implementation of this project is related to testing activities in order to prove the efficiency method in content and course delivery. This paper describes some best practices developed during a Tempus IV Project granted by EU.

An Assessment of Customer’s Preferences and Improve Brand Awareness Implementation of Social CRM in an Automotive Company

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.