M.D. Lytras et al. (Eds.): WSKS 2008, LNAI 5288, pp. 187–196, 2008. © Springer-Verlag Berlin Heidelberg 2008 LIA: An Intelligent Advisor for e-Learning Nicola Capuano 1,2 , Matteo Gaeta 1 , Sergio Miranda 1 , Francesco Orciuoli 1,2 , and Pierluigi Ritrovato 1 1 University of Salerno, Department of Information Engineering and Applied Mathematics, via Ponte don Melillo, 84084 Fisciano (SA), Italy 2 CRMPA, Centro di Ricerca in Matematica Pura ed Applicata, via Ponte don Melillo, 84084 Fisciano (SA), Italy ncapuano@unisa.it, {gaeta,smiranda,orciuoli, ritrovato}@diima.unisa.it Abstract. Intelligent e-learning systems have revolutionized online education by providing individualized and personalized instruction for each learner. Nev- ertheless, till now very few systems were able to leave academic labs and be in- tegrated in real commercial products. One of this few exceptions is the Learning Intelligent Advisor (LIA) described in this paper, built on results coming from several research projects and currently integrated in a complete e-learning solu- tion named IWT. The purpose of this paper is to describe how LIA works and how it cooperates with IWT in the provisioning of an individualized and per- sonalized e-learning experience. Results of experimentations with real users coming from IWT customers are also presented and discussed in order to dem- onstrate the benefits of LIA as an add-on in on-line learning. Keywords: e-Learning, ITS, Knowledge Representation, Planning. 1 Introduction The Learning Intelligent Advisor (LIA) is an intelligent tutoring engine capable of integrating, in “traditional” e-learning systems, “intelligent” features like learner modelling and learning experience individualisation. LIA was born from the co- operation of an high-tech company named MoMA with the Research Centre in Pure and Applied Mathematics (CRMPA) and the Information Engineering and Applied Mathematics Dept. of the University of Salerno. It is currently included in a complete solution for e-learning named Intelligent Web Teacher (IWT) [1]. LIA is based on a set of models able to represent the main entities involved in the process of teaching/learning and on a set of methodologies, leveraging on such mod- els, for the generation of individualised learning experiences with respect to learning objectives, pre-existing knowledge and learning preferences. Models and methodolo- gies behind LIA integrate and extend results coming from several researches on knowledge representation and intelligent tutoring systems made by the authors, some of which partially founded by the European Commission.