A generic framework for the development of standardised learning objects within the discipline of construction management

E-learning has occurred in the academic world in different forms since the early 1990s. Its use varies from interactive multimedia tools and simulation environments to static resources within learning management systems. E-learning tools and environments are no longer criticised for their lack of use in higher education in general and within the construction domain in particular. The main criticism, however, is that of reinventing the wheel in order to create new learning environments that cater for different educational needs. Therefore, sharing educational content has become the focus of current research, taking e-learning into a whole new era of developments. This era is enabled by the emergence of new technologies (online and wireless) and the development of educational standards, such as SCORM (Sharable Content Object Reference Model) and LOM (Learning Object Metadata) for example. Accordingly, the broad definition of the construction domain and the interlocking nature of subjects taught within this domain, makes the concept of sharing content most appealing. This paper proposes a framework developed to describe the various steps required in order to enable the application of e-learning metadata standards and ontology for sharable learning objects to serve the construction discipline. The paper further describes the application of the proposed framework to a case study for developing an online environment for learning objects that are standardised, sharable, transparent and that cater for the needs of learners, educators and curricula developers in Construction Management. Based on the framework, a learning objects repository is developed incorporating educational and web standards. The repository manages objects as well as metadata using ontology and offers a set of services such as storing, retrieving and searching of learning objects using Semantic Web technologies. Thus, it increases the reusability, sharability and interoperability of learning objects

Ontology technology for the development and deployment of learning technology systems - a survey

The World-Wide Web is undergoing dramatic changes at the moment. The Semantic Web is an initiative to bring meaning to the Web. The Semantic Web is based on ontology technology – a knowledge representation framework – at its core. We illustrate the importance of this evolutionary development. We survey five scenarios demonstrating different forms of applications of ontology technologies in the development and deployment of learning technology systems. Ontology technologies are highly useful to organise, personalise, and publish learning content and to discover, generate, and compose learning objects

Context and Keyword Extraction in Plain Text Using a Graph Representation

Document indexation is an essential task achieved by archivists or automatic indexing tools. To retrieve relevant documents to a query, keywords describing this document have to be carefully chosen. Archivists have to find out the right topic of a document before starting to extract the keywords. For an archivist indexing specialized documents, experience plays an important role. But indexing documents on different topics is much harder. This article proposes an innovative method for an indexing support system. This system takes as input an ontology and a plain text document and provides as output contextualized keywords of the document. The method has been evaluated by exploiting Wikipedia's category links as a termino-ontological resources

A structured model metametadata technique to enhance semantic searching in metadata repository

This paper discusses on a novel technique for semantic searching and retrieval of information about learning materials. A novel structured metametadata model has been created to provide the foundation for a semantic search engine to extract, match and map queries to retrieve relevant results. Metametadata encapsulate metadata instances by using the properties and attributes provided by ontologies rather than describing learning objects. The use of ontological views assists the pedagogical content of metadata extracted from learning objects by using the control vocabularies as identified from the metametadata taxonomy. The use of metametadata (based on the metametadata taxonomy) supported by the ontologies have contributed towards a novel semantic searching mechanism. This research has presented a metametadata model for identifying semantics and describing learning objects in finer-grain detail that allows for intelligent and smart retrieval by automated search and retrieval software

E-Learning and microformats: a learning object harvesting model and a sample application

In order to support interoperability of learning tools and reusability of resources, this paper introduces a framework for harvesting learning objects from web-based content. Therefore, commonly-known web technologies are examined with respect to their suitability for harvesting embedded meta-data. Then, a lightweight application profile and a microformat for learning objects are proposed based on well-known learning object metadata standards. Additionally, we describe a web service which utilizes XSL transformation (GRDDL) to extract learning objects from different web pages, and provide a SQI target as a retrieval facility using a more complex query language called SPARQL. Finally, we outline the applicability of our framework on the basis of a search client employing the new SQI service for searching and retrieving learning objects

THE ISSUE OF SEMANTIC MODELING OF THE LEARNING ORGANIZATIONAL MEMORY FOR E-LEARNING

The development of open and long-distance learning – within universities but also withingeographically distributed enterprises –has led to the development of researches focusing on modeling onsemantic bases the learning organizational memory of an e-learning type. This paper reviews the literaturein the field, focusing on defining a generic template of semantic modeling of the content of the learningorganizational memory of the e-learning type, by proposing a study case of semantic representation oflearning objects applied to the economic-financial analysis. The research is both theoretic and applied-deductive in character, starting from a general background regarding learning in general and reachingparticularity by providing an ontology specific to the economic-financial analysis.learning organizational memory, learning object, ontology, metadata, indexing, e-learning,modeling standards, economical and financial analysis.

Formalization of higher-level intelligence through integration of intelligent tutoring tools : a thesis presented in partial fulfilment of the requirements for the degree of Master of Information Systems, Department of Information Systems, Massey University, Palmerston North, New Zealand

In contrast with a traditional Intelligent Tutoring System (ITS), which attempts to be fairly comprehensive and covers enormous chunks of a discipline's subject matter, a basic Intelligent Tutoring Tool (ITT) (Patel & Kinshuk, 1997) has a narrow focus. It focuses on a single topic or a very small cluster of related topics. An ITT is regarded as a building block of a larger and more comprehensive tutoring system, which is fundamentally similar with the emerging technology "Learning Objects" (LOs) (LTSC, 2000a). While an individual ITT or LO focuses on a single topic or a very small cluster of knowledge, the importance of the automatic integration of interrelated ITTs or LOs is very clear. This integration can extend the scope of an individual ITT or LO, it can guide the user from a simple working model to a complex working model and provide the learner with a rich learning experience, which results in a higher level of learning. This study reviews and analyses the Learning Objects technology, as well as its advantages and difficulties. Especially, the LOs integration mechanisms applied in the existing learning systems are discussed in detail. As a result, a new ITT integration framework is proposed which extends and formalizes the former ITT integration structures (Kinshuk & Patel, 1997, Kinshuk, et al. 2003) in two ways: identifying and organizing ITTs, and describing and networking ITTs. The proposed ITTs integration framework has the following four notions: (1) Ontology, to set up an explicit conceptualisation in a particular domain, (2) Object Design and Sequence Theory, to identify and arrange learning objects in a pedagogical way through the processes of decomposing principled skills, synthesising working models and placing these models on scales of increasing complexity, (3) Metadata, to describe the identified ITTs and their interrelationships in a cross-platform XML format, and (4) Integration Mechanism, to detect and activate the contextual relationship

Digital Repositories and the Semantic Web: Semantic Search and Navigation for DSpace

4th International Conference on Open RepositoriesThis presentation was part of the session : DSpace User Group PresentationsDate: 2009-05-21 08:30 AM – 10:00 AMIn many digital repository implementations, resources are often described against some flavor of metadata schema, popularly the Dublin Core Element Set (DCMES), as is the case with the DSpace system. However, such an approach cannot capture richer semantic relations that exist or may be implied, in the sense of a Semantic Web ontology. Therefore we first suggest a method in order to semantically intensify the underlying data model and develop an automatic translation of the flatly organized metadata information to this new ontology. Then we propose an implementation that provides for inference-based knowledge discovery, retrieval and navigation on top of digital repositories, based on this ontology. We apply this technique to real information stored in the University of Patras Institutional Repository that is based on DSpace, and confirm that more powerful, inference-based queries can indeed be performed