Ontology for e‐learning: a case study

Author:

Colace Francesco,De Santo Massimo,Gaeta Matteo

Abstract

PurposeThe development of adaptable and intelligent educational systems is widely considered one of the great challenges in scientific research. Among key elements for building advanced training systems, an important role is played by methodologies chosen for knowledge representation. In this scenario, the introduction of ontology formalism can improve the quality of formative process, allowing the introduction of new and effective services. Ontology can lead to important improvements in the definition of courses knowledge domain, in the generation of adapted learning path and in the assessment phase. The purpose of this paper is to provide an initial discussion of the role of ontology in the context of e‐learning. It seeks to discuss the improvements related to the introduction of ontology formalism in the e‐learning field and to show a novel algorithm for ontology building through the use of Bayesian networks. Finally, it aims to illustrate its application in the assessment process and some experimental results.Design/methodology/approachA novel method for learning ontology for e‐learning is illustrated, using an approach based on Bayesian networks. Thanks to their characteristics, these networks can be used to model and evaluate the conditional dependencies among the nodes of ontology on the basis of the data obtained from student tests. An experimental evaluation of the proposed method was performed using real student data.FindingsThe proposed method was integrated in a tool for the assessment of students during a learning process. This tool is based on the use of ontology and Bayesian network. In particular through the matching between ontology and Bayesian network, it was found that our tool allows an effective tutoring and a better adaptation of learning process to demands of students. The assessment based on Bayesian approach allows a deeper analysis of student's knowledge.Research limitations/implicationsThe proposed approach needs more experimentation with other domains and with more complex ontology.Originality/valueThis paper provides an initial discussion of the role of ontology in the context of e‐learning. The improvements related to the introduction of ontology formalism in the e‐learning field are discussed and a novel algorithm for ontology building through the use of Bayesian Networks is showed. Finally, its application in the assessment process and some experimental results are illustrated.

Publisher

Emerald

Subject

Education,Computer Science (miscellaneous)

Reference35 articles.

1. ACM (2001), “ACM computing curricula 2001 for computer science”, available at: www.acm.org/education/curricula.html (accessed 25 October 2006).

2. Aroyo, L., et al. (2002a), “A layered approach towards domain authoring support”, Proceedings of the International Conference on Artificial Intelligence (ICAI'02), Las Vegas.

3. Aroyo, L., et al. (2002b), “Courseware authoring tasks ontology”, Proceedings of the International Conference on Computers in Education (ICCE'02), Auckland.

4. Bechhofer, S., Horrocks, I., Patel‐Schneider, P. and Tessaris, S. (1999), “A proposal for a description logic interface”, Proceedings of the International Workshop Description Logics, pp. 33‐6.

5. Bisson, G. and Nedellec, C. (2000), “Designing clustering methods for ontology building: the Mo'K workbench”, in Staab, S., Maedche, A., Nedellec, C. and WiemerHasting, P. (Eds), Proceedings of the 14th European Conference Artificial Intelligence Workshop Ontology Learning (ECAI'00).

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