Frameworks for the Automatic Indexation of Learning Management Systems Content into Learning Object Repositories

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Semelhante a Frameworks for the Automatic Indexation of Learning Management Systems Content into Learning Object Repositories

D04 06 2438

International Journal of Engineering Inventions www.ijeijournal.com

Although of the semantic web technologies utilization in the learning development field is a new research area, some authors have already proposed their idea of how an effective that operate. Specifically, from analysis of the literature in the field, we have identified three different types of existing applications that actually employ these technologies to support learning. These applications aim at: Enhancing the learning objects reusability by linking them to an ontological description of the domain, or, more generally, describe relevant dimension of the learning process in an ontology, then; providing a comprehensive authoring system to retrieve and organize web material into a learning course, and constructing advanced strategies to present annotated resources to the user, in the form of browsing facilities, narrative generation and final rendering of a course. On difference with the approaches cited above, here we propose an approach that is modeled on narrative studies and on their transposition in the digital world. In the rest of the paper, we present the theoretical basis that inspires this approach, and show some examples that are guiding our implementation and testing of these ideas within e-learning. By emerging the idea of the ontologies are recognized as the most important component in achieving semantic interoperability of e-learning resources. The benefits of their use have already been recognized in the learning technology community. In order to better define different aspects of ontology applications in e-learning, researchers have given several classifications of ontologies. We refer to a general one given in that differentiates between three dimensions ontologies can describe: content, context, and structure. Most of the present research has been dedicated to the first group of ontologies. A well-known example of such an ontology is based on the ACM Computer Classification System (ACM CCS) and defined by Resource Description Framework Schema (RDFS). It’s used in the MOODLE to classify learning objects with a goal to improve searching. The chapter will cover the terms of the semantic web and e-learning systems design and management in e-learning (MOODLE) and some of studies depend on e-learning and semantic web, thus the tools will be used in this paper, and lastly we shall discuss the expected contribution. The special attention will be putted on the above topics.

Applying Semantic Web Technologies to Services of e-learning System

International Journal of Engineering Inventions www.ijeijournal.com

The world is witnessing the electronic revolution in many fields of life such as health, education, government and commerce. E-learning is considered one of the hot topics in the e-revolution as it brings with it rapid change and greater opportunities to increase learning ability in colleges and schools. The fields of Learning Management Systems (LMS) and Learning Content Management Systems (LCMS) are full of open source and commercial products, however LCMS systems in general inherit the drawbacks of information system such as weakness in user expected information retrieval and semantic modelling and searching of contents & courses. In this paper, we propose a new prototype of LCMS that uses the Semantic Web technologies and Ontology Reasoner with logical rules, as an inference engine to satisfy the constraints and criteria specified by a user, and retrieves relevant content from the domain ontology in an organized fashion. This enables construction of a user-specific course, by semantic querying for topics of interest. We present the development of an Ontology-oriented Inference-based Learning Content Management System OILCMS, its architecture, conception and strengths.

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The Semantic Web provides a common framework that allows data to be shared and reused across applications, enterprises, and community boundaries. The existing web applications need to express semantics that can be extracted from users' navigation and content, in order to fulfill users' needs. Elearning has specific requirements that can be satisfied through the extraction of semantics from learning management systems (LMS) that use relational databases (RDB) as backend. In this paper, we propose transformation rules for building owl ontology from the RDB of the open source LMS Moodle. It allows transforming all possible cases in RDBs into ontological constructs. The proposed rules are enriched by analyzing stored data to detect disjointness and totalness constraints in hierarchies, and calculating the participation level of tables in n-ary relations. In addition, our technique is generic; hence it can be applied to any RDB.

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B04 3-1121

International Journal of Engineering Inventions www.ijeijournal.com

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In the LMS or CMS environment, content management frequently translates into single-purpose allocation of content resources, with cataloging and meta tagging being a haphazard affair. This results in potential duplication of content and significant time loss associated with asset retrieval for incorporation into new curricula. Because content is created with the notion that all contributors have knowledge of the underlying taxonomies or common vernacular that information is based upon, it is difficult for organizations to survey their content universe for existing objects that can be incorporated into emerging workflows or to assess relationships between content across disciplines.

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The e-learning contained many educational resources are generally used in learning systems like Moodle, It’s free open source software packages designed and flexible platform to create Learning Objects (LOs) and users’ accounts. The author demonstrates how to use semantic web technologies to improve online learning environments and bridge the gap between learners and LOs. The ontological construction presented here helps formalize LOs context as a complex interplay of different learning-related elements and shows how we can use semantic annotation to interrelate diverse between learner and LOs. On top of this construction, the author implemented several feedback channels for educators to improve the delivery of future Web-based learning. The particular aim of this paper was to provide a solution based in the Moodle Platform. The main idea behind the approach presented here is that ontology which can not only be useful as a learning instrument but it can also be employed to assess students’ skills. For it, each student is prompted to express his/her beliefs by building own discipline-related ontology through an application displayed in the interface of Moodle. This paper presents the ontology for an e-Learning System, which arranges metadata, and defines the relationships of metadata, which are about learning objects; belong to academic courses and user profiles. This ontology has been incorporated as a critical part of the proposed architecture. By this ontology, effective retrieval of learning content, customizing Learning Management System (LMS) is expected. Metadata used in this paper are based on current metadata standards. This ontology specified in human and machine-readable formats. In implementing it, several APIs were defined to manage the ontology. They were introduced into a typical LMS such as Moodle. Proposed ontology maps user preferences with learning content to satisfy learner requirements. These learning objects are presented to the learner based on ontological relationships. Hence it increases the usability and customizes the LMS. In conclusion, ontologies have a range of potential benefits and applications in further and higher education, including the sharing of information across e-learning systems, providing frameworks for learning object reuse, and enabling information between learner and system parts.

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Semelhante a Frameworks for the Automatic Indexation of Learning Management Systems Content into Learning Object Repositories (20)

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