Semantic Web and e-Learning

As emerging technology that has given a new approach on how information in the Web is represented, SW has great potential to be implemented for enhancing the e-Learning system. Stojanovic et al. (Stojanovic et al. 2001) identified some of SW potentials for realizing the emerging e-Learning requirements (see Table 2-2).

Investigation on exploring Semantic Web for e-learning have been conducted by prior work such have been discussed in Journal of Educational Technology & Society special issues on Ontologies and the Semantic Web for e-Learning (Sampson et al. 2004). Table 2-3 is presented to sum the discussion on this special issues up and to highlight the prior works contribution.

Another suggestion come from Bony Consortium (elearningeurope 2008) that initiated SW potential to improve e-Learning process such as:

1. Ontological representation of content, SW-based approach for knowledge sharing, that allows collaborative creation and maintenance of educational contents.

2. User profiling and intelligent recommending systems, that allow automatic assessment of skills and competences into different areas of interest, so as the automatic definition of a formative path depending on trainees’ objectives and pre-existent knowledge.

3. Social network analysis finalized to the creation of a cooperative model in order to select automatically training or research partners from the established network. This analysis includes research in special algorithms elaboration, creating e- Learning Social Network keys features such as the “Expert Finding” and the “User Reputation system”.

Table 2- 2 Benefits of using Semantic Web as a technology for e-Learning (Stojanovic et al. 2001)

Dimension e-Learning Semantic Web

Delivery Pull – Student determines agenda. Knowledge items (learning materials) are distributed on the Web, but they are linked to

commonly agreed ontology(ies). This enables construction of a user specific course, by semantic querying for topics of interest.

Responsiveness Reactionary – Responds to problem at hand. Software agents on the Semantic Web may use commonly agreed service language, which

enables co ordination between agents and proactive delivery of learning materials in the context of actual problems. The vision is that each user has his own personalized agent that communicates with other agents.

Access Non-linear – access knowledge in whatever

sequence makes sense to the situation at hand.

User can describe situation at hand (goal of learning, previous knowledge) and perform semantic querying for the suitable learning material. The user profile is also accounted for. Access to knowledge can be expanded by semantically defined navigation.

Symmetry Symmetric – Learning occurs as an

integrated activity.

The Semantic Web (semantic intranet) offers the potential to become an integration platform for all business processes in an organization, including learning activities.

Modality Continuous – Learning runs in parallel and

never stops.

Active delivery of information (based on personalized agents) creates a dynamic learning environment.

Authority Distributed – Content comes from the

participants and the educators.

The Semantic Web will be as decentralized as possible. This enables an effective co-operative content management.

Personalization Personalized – Content is determined

by the individual user’s needs and aims to satisfy the needs of every user

A user (using personalized agent) searches for learning material customized for her/his needs. The Ontology is the link between user needs and characteristics of the learning material. Adaptivity Dynamic – Content changes constantly

through user input, experiences, new practices, business rules and heuristics.

The Semantic Web enables the use of knowledge provided in various forms, by semantically annotation of content. Distributed nature of the Semantic Web enables continuous improvement of learning materials.

Table 2- 3 Prior Work On Investigating Semantic Web for e-Learning

Prior Work Contribution

(Devedžic 2004) Exploiting SW, interm of Web Intelligent (WI) for tackling new and challenging research problems especially adaptivity and learner comfortability in AIED such as:

• Enabling course sequencing and material presentation not only according to the learner model, but also according to the most up-to-date relevant content from the Web.

• Automatic discovery, invocation, and composition of educational Web services can free the learner from many time-consuming activities that often disrupt the learning process itself.

• Ontology-supported learning process greatly increases automation of a number of learners', teachers', and authors' activities related to Web-based learning environments.

(Cristea 2004) A conversion method from Adaptive Hypermedia to the Semantic Web. It demonstrated how LAOS, an Adaptive Hypermedia (authoring) framework can be used in the context of the Semantic Web.

(Aroyo and Dicheva 2004)

• Identified state-of-the-art research a realistic approach towards the Educational Semantic Web.

• Proposed a modular semantic-driven and service-based interoperability framework and related ontology-driven authoring tools.

• Identified the challenge of the next generation web- based educational systems such as user-friendly, structured and automated authoring, balancing between

exploiting explicit semantic information for agreement and exchange of educational information, and on the other hand, collecting and maintaining the information semantics.

(Yang et al. 2004) Proposed a framework for ontology enabled annotation and knowledge management in collaborative learning environments that consisted of personalized annotation, real- time discussion, and semantic content retrieval.

(Henze et al. 2004) Framework for personalized e-Learning in the semantic web A logic-based approach to educational hypermedia using TRIPLE

(Abel et al. 2004) An ontology building process An Ontology-based Organizational Memory for e-learning

(Moreale and Vargas- Vera 2004)

Proposed an architecture for a student semantic portal providing semantic services, including a student essay annotation service.

(Papasalouros et al. 2004)

CADMOS-D: A Hypermedia Design Method Method for transformation of UML modeling to Semantic Description

Joint Information Systems Committee Centre for Educational Technology Interoperability Standards (JISC CETIS) University of Bolton, UK (Campbell and Currier 2005) in their research report gave recommendations to exploit the potential of SW technologies in e-Learning:

• Explore the applicability of various SW technologies including RDF, SKOS, OWL, TopicMaps, etc. to the teaching and learning domain.

• Establish links between the SW community within the UK and the JISC community of educational practitioners and e-Learning technologists.