Abstract
Intelligent e-learning systems have revolutionized online education by providing individualized and personalized instruction for each learner. Nevertheless, till now very few systems were able to leave academic labs and be integrated 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 solution 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 personalized e-learning experience. Results of experimentations with real users coming from IWT customers are also presented and discussed in order to demonstrate the benefits of LIA as an add-on in on-line learning.
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References
MoMA, s.r.l.: IWT Intelligent Web Teacher, http://www.momanet.it/english/iwt_eng.html
Capuano, N., Marsella, M., Salerno, S.: ABITS: An Agent Based Intelligent Tutoring System for Distance Learning. In: Proceedings of the International Workshop on Adaptive and Intelligent Web-Based Education Systems held in Conjunction with ITS 2000, Montreal, Canada, June 19-23, pp. 17–28 (2000)
Capuano, N., Gaeta, M., Micarelli, A., Sangineto, E.: An Integrated Architecture for Automatic Course Generation. In: Petrushin, R.V., Kommers, P., Galeev, I. (eds.) Proceedings of the IEEE International Conference on Advanced Learning Technologies (ICALT 2002), Kazan, Russia, September 9-12, pp. 322–326. IEEE Computer Society, Los Alamitos (2002)
Capuano, N., Gaeta, M., Micarelli, A.: IWT: Una Piattaforma Innovativa per la Didattica Intelligente su Web. AI*IA Notizie XVI(1), 57–61 (2003)
IMS Learning Design Specification, http://www.imsglobal.org/learningdesign
Shmoys, D., Tardos, E., Aardal, K.: Approximation Algorithms for Facility Location Problems. In: Proceedings of the 29th Annual ACM Symposium on Theory of Computing, El Paso, Texas, United States, pp. 265–274 (1997)
Acanfora, G., Gaeta, M., Loia, V., Ritrovato, P., Salerno, S.: Optimizing Learning Path Selection through Memetic Algorithms. In: Proceedings of IEEE World Congress on Computational Intelligence, Hong Kong, June 1-6 (2008)
Albano, G., Gaeta, M., Ritrovato, P.: IWT: an innovative solution for AGS e-Learning model. Intl. Journal of Knowledge and Learning 3(2/3), 209–224 (2007)
Sangineto, E., Capuano, N., Gaeta, M., Micarelli, A.: Adaptive Course Generation through Learning Styles Representation. Universal Access in the Information Society International Journal 7(1/2), 1–23 (2008)
Capuano, N., Gaeta, M., Ritrovato, P., Salerno, S.: How to Integrate Technology Enhanced Learning with Business Process Management. Journal of Knowledge Management (to appear)
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© 2008 Springer-Verlag Berlin Heidelberg
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Capuano, N., Gaeta, M., Miranda, S., Orciuoli, F., Ritrovato, P. (2008). LIA: An Intelligent Advisor for e-Learning. In: Lytras, M.D., Carroll, J.M., Damiani, E., Tennyson, R.D. (eds) Emerging Technologies and Information Systems for the Knowledge Society. WSKS 2008. Lecture Notes in Computer Science(), vol 5288. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87781-3_21
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DOI: https://doi.org/10.1007/978-3-540-87781-3_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87780-6
Online ISBN: 978-3-540-87781-3
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