DocumentCode :
1288446
Title :
Ontology for E-Learning: A Bayesian Approach
Author :
Colace, Francesco ; De Santo, Massimo
Author_Institution :
Dept. of Electr. & Inf. Eng., Univ. di Salerno, Fisciano, Italy
Volume :
53
Issue :
2
fYear :
2010
fDate :
5/1/2010 12:00:00 AM
Firstpage :
223
Lastpage :
233
Abstract :
In the last decade, the evolution of educational technologies has forced an extraordinary interest in new methods for delivering learning content to learners. Today, distance education represents an effective way for supporting and sometimes substituting the traditional formative processes, thanks to the technological improvements achieved in the field in recent years. However, the role of technology has often been overestimated. The amount of information students can obtain from the Internet is huge, and as a result, they can easily be confused. Teachers can also be disconcerted by this vast quantity of content and are often unable to suggest the correct content to their students. In the open scientific literature, it is widely recognized that an important factor for success in delivering learning content is related to the capability for customizing the learning process for the specific needs of a given learner. This task is still far from having been fully accomplished, and there is a real interest in investigating new approaches and tools to adapt the formative process to specific individual needs. In this scenario, the introduction of ontology formalism can improve the quality of the formative process, allowing the introduction of new and effective services. Ontologies can lead to important improvements in the definition of a course´s knowledge domain, in the generation of an adapted learning path, and in the assessment phase. This paper provides an initial discussion of the role of ontologies in the context of e-learning. The improvements related to the introduction of ontologies formalism in the e-learning field are discussed, and a novel algorithm for ontology building through the use of Bayesian networks is shown. Finally, the application of this algorithm in the assessment process and some experimental results are illustrated.
Keywords :
Internet; belief networks; computer aided instruction; distance learning; ontologies (artificial intelligence); Bayesian approach; Internet; adapted learning path; course knowledge domain; distance education; e-learning; educational technology; formative process quality; ontology formalism; Adaptive systems; Bayesian methods; Distance learning; Educational technology; Electronic learning; Helium; Intelligent systems; Internet; Ontologies; Standardization; Adaptive assessment tool; Bayesian network; adaptive hypermedia system; e-learning; learning technology; ontology;
fLanguage :
English
Journal_Title :
Education, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9359
Type :
jour
DOI :
10.1109/TE.2009.2012537
Filename :
5196690
Link To Document :
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