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.

International students face unique challenges in pursuing higher education in a foreign country. To address these challenges and enhance their academic experience, higher education institutions are increasingly exploring the use of artificial intelligence (AI) applications. This research essay aims to investigate the impact of AI on the education of international students. Instead of a traditional literature review, it employs a research approach to examine the potential applications of AI and discuss associated concerns. The research paper explores various AI applications, such as personalized learning experiences, adaptive testing, predictive analytics, and chatbots for learning and research. By analyzing the role of AI in education for international students, this research paper sheds light on how AI can improve learning efficiency and provide customized educational support. Additionally, it identifies significant risks and limitations, including privacy concerns, cultural differences, language proficiency, and ethical implications, which must be effectively addressed. The findings contribute to a better understanding of the potential impact of AI on international students’ educational experiences and offer insights into the integration of AI into educational administration and learning processes.

Executive SummaryThe aim of this paper is to transform the necessity for "integrated ICT training" in study courses within universities into a possible action plan which indicates both the pros and cons of the use of IT in the strategies, services and products to be used from a cost point of view.This will enable an evaluation of the Return On Investment (ROI) using the new concept of Yield Index "e-lYI" (e-learning Yield Index), introduced in this study. The Yield Index "e-lYI" suggests an original way to evaluate the implementation of e-learning methodologies into campus based environments; still, the new index will help professionals involved in the management of the transition from the "classical" university structure to the innovative structure needed by the elearning implementation. These results should interest any Faculty or University which is planning to introduce e-learning methodology to its didactic organization.In this study, a Pilot Course, delivered in "Blended" learning model, will be taken into consideration to estimate the costs. In the subsequent phase the ROI will be assessed for the Pilot course and compared to the ROI of a classical course by the use of "e-lYI".Furthermore, it would therefore be extremely interesting to consider the "e-lYI" in a University administration that decided to adopt an Open Source Learning Management Systems. Open Source, therefore, will be the final element of innovation and experimentation in the evaluation process.Keywords: e-lYI, ROI, e-learning, costs, evaluation, open source. Introduction -The ContextIn the last five years, European Public Administration, in particular that within universities, has shown renewed interest in applications geared to information technology training. Its subsequent rapid development has helped accelerate and optimize knowledge of IT, overcoming the barriers of time and space which are characteristic of traditional training.The European Union Council, during a meeting in Lisbon in 2000, recommended that national governments organize a rapid acceleration in IT training to adopt the levels necessaryMaterial published as part of this journal, either on-line or in print, is copyrighted by the publisher of the Journal of Information Technology Education. Permission to make digital or paper copy of part or all of these works for personal or classroom use is granted without fee provided that the copies are not made or distributed for profit or commercial advantage AND that copies 1) bear this notice in full and 2) give the full citation on the first page. It is permissible to abstract these works so long as credit is given. To copy in all other cases or to republish or to post on a server or to redistribute to lists requires specific permission and payment of a fee. Contact Editor@JITE.org to request redistribution permission. Measuring the Economic Benefits of E-Learning 330for the European society of the third millennium.Following this recommendation, the European Community Commission adopted an initiative entitled "e-Learning -consid...

The COVID-19 pandemic marked an important breakthrough in human progress: from working habits to social life, the world population’s behaviours changed according to the new lifestyle requirements. In this changing environment, university courses and learning methods evolved along with other “remote” working activities. For this quasi-experimental study, we discuss the effectiveness of the changes made by the LUMSA University in Rome, comparing two different groups of students who attended a master’s course with blended and fully remote methodologies. Here, we focused our attention on the paradigm shift, comparing the data gathered during the blended course in the 2019/2020 academic year with data gathered during the same course, but conducted fully online, in the academic year 2020/2021. Considering the sample size and type, the group comparison was made using a non-parametric test (U-test). The statistical analysis results suggest that there was no substantial difference between the students’ performance, confirming that the course changes made to adapt to the pandemic situation were successful and that learning effectiveness was preserved.

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.