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Abstract
E-learning is nowadays recognized as one of the key components of Enterprise Knowledge Management platforms. Given a project specification, the platform should be able to suggest a project team, to measure human resources competence gaps and to contribute to reduce them by creating personalized learning paths. In this paper we propose an XML based Multi-Agent System to perform the following tasks: (i) supporting Chief Learning Officers in defining roles, associated competencies and knowledge level required; (ii) managing theskill map of the organization; (iii) measuring human resources competence gaps; (iv) supporting employees in filling their competence gaps as related to their roles; (v) enriching a given courseware or creating personalized learning paths according to feedbacks user provides in order to optimize the acquisition of needed competencies; (vi) assisting Chief Learning Offcers in choosing the most appropriate employee for a given role.
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Authors and Affiliations
D.E.I.S. - Università della Calabria, Via P. Bucci, 87030, Rende (CS), Italy
Alfredo Garro
D.I.M.E.T. - Università di Reggio Calabria, 89060, Reggio Calabria, Italy
Luigi Palopoli
- Alfredo Garro
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- Luigi Palopoli
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Editors and Affiliations
Carnegie Mellon University, Pittsburgh, PA, USA
Jaime G. Carbonell
University of Saarland, Saabrücken, Germany
Jörg Siekmann
CSIRO Mathematical and Information Sciences, 723 Swanston Street, Carlton, 3053, Victoria, Australia
Ryszard Kowalczyk
Siemens AG, CT IC 6, Munich, Germany
Jörg P. Müller
Department of Computing, Glasgow Caledonian University, City Campus, 70 Cowcaddens Road, G4 0BA, Glasgow, Scotland, UK
Huaglory Tianfield
Institute for Computer Science, University of Essen, 45117, Essen, Germany
Rainer Unland
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Garro, A., Palopoli, L. (2003). An XML Multi-agent System for E-learning and Skill Management. In: Carbonell, J.G., Siekmann, J., Kowalczyk, R., Müller, J.P., Tianfield, H., Unland, R. (eds) Agent Technologies, Infrastructures, Tools, and Applications for E-Services. NODe 2002. Lecture Notes in Computer Science(), vol 2592. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36559-1_21
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