DocumentCode :
111183
Title :
S-WOLF: Semantic Workplace Learning Framework
Author :
Gaeta, Matteo ; Loia, Vincenzo ; Orciuoli, Francesco ; Ritrovato, Pierluigi
Author_Institution :
Dipt. di Ing. dell´Inf., Ing. Elettr. e Mat. Appl., Univ. of Salerno, Fisciano, Italy
Volume :
45
Issue :
1
fYear :
2015
fDate :
Jan. 2015
Firstpage :
56
Lastpage :
72
Abstract :
Workplace learning can be conceived as the set of processes related to learning and training activities at work. Typically, workplace learning includes formal, informal, and non-formal learning activities. Having a control on the whole learning process of each worker is a complex task. Indeed we have to align individual learning paths, real workers´ needs (for instance in terms of tasks or projects to accomplish), career plans, and other organizational needs to activate virtuous knowledge flows. In order to accomplish this complex task a comprehensive framework is needed. This paper provides the definition of the aforementioned framework by exploiting semantic technologies in order to model (by means of Ontologies), represent, extract, and share knowledge within organizations. Although the proposed framework allows a wide range of workplace learning experiences, it mainly focuses on informal learning, on the ways it can be sustained by exploiting organizational resources, and on the capability of linking individual and organizational learning in the context of a widely accepted knowledge flow model like socialization, externalization, composition, and internalization.
Keywords :
computer aided instruction; knowledge management; ontologies (artificial intelligence); organisational aspects; semantic Web; S-WOLF; informal learning activity; knowledge flow model; learning process; nonformal learning activity; ontology; organizational learning; organizational need; organizational resources; semantic technology; semantic workplace learning framework; training activity; virtuous knowledge flow; Context; Electronic learning; Employment; Ontologies; Organizations; Semantics; Training; Fuzzy formal concept analysis; linked data; semantic web; workplace learning;
fLanguage :
English
Journal_Title :
Systems, Man, and Cybernetics: Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
2168-2216
Type :
jour
DOI :
10.1109/TSMC.2014.2334551
Filename :
6866223
Link To Document :
بازگشت