Building Interoperable Learning Objects Using Reduced Learning Object Metadata

2005 ◽  
Vol 2 (3) ◽  
pp. 299-313
Author(s):  
Mostafa S. Saleh
Keyword(s):  
Semantic Web ◽  
Learning Community ◽  
Learning Objects ◽  
Web Technology ◽  
Learning Object ◽  
Learning Standards ◽  
Semantic Web Technology ◽  
Learning Object Metadata ◽  
E Learning ◽  
Learning Object Repositories

The new e-learning generation depends on Semantic Web technology to produce learning objects. As the production of these components is very costly, they should be produced and registered once, and reused and adapted in the same context or in other contexts as often as possible. To produce those components, developers should use learning standards to describe these objects in order to support interoperability. IEEE Learning Object Metadata (LOM) is the most dominant standard for describing learning objects, in which 76 different elements are used to describe the different aspects of e-learning. Nonetheless, it will still be time consuming to build these learning objects. This paper introduces a model for building Global Interoperable Learning Objects (GILO) for the e-learning community. This is achieved by using a reduced set of the LOM elements, and giving a unique global ID to the learning object. This will enable software agents to query these learning object repositories, to automatically deliver the required material to the e-learning consumer.

scholarly journals A Metadata Model Proposal for Simulation Based E-learning

2017 ◽  
Vol 5 (1) ◽  
pp. 16
Author(s):  
El Hassan Laaziz ◽  
Elmustapha Elkhouzai
Keyword(s):  
Learning Objects ◽  
Learning Object ◽  
Web Technologies ◽  
Learning Standards ◽  
Metadata Model ◽  
Learning Object Metadata ◽  
Learning Content ◽  
Simulation Based ◽  
E Learning ◽  
On Line

<p class="Abstract">Existing E-learning standards and specifications present a great basis for the development of E-learning, on line and distance learning contents that are accessible, interoperable, durable and reusable.  E-learning contents are supported by these standards as well as by the LMS (Learning Management System)   or web technologies compliant to them. However, simulation based contents or learning objects are less integrated in the E-learning contents than other learning objects, partially because standards and specification don’t pay much attention to more specify them in term of metadata requirements.</p>The main objective of this paper is the elaboration of a new Metadata model on the basis of Learning Object Metadata (LOM) with a wider scope that could support more easily simulation objects, especially in experiential E-learning content in which simulation activity should be executed by the learner, monitored and tracked by the tutor completely on the LMS.

scholarly journals The Integrated Environment for Learning Objects Design and Storing in Semantic Web

2018 ◽  
Vol 13 (1) ◽  
pp. 39
Author(s):  
Valentina Dagiene ◽  
Daina Gudoniene ◽  
Reda Bartkute
Keyword(s):  
Semantic Web ◽  
Learning Objects ◽  
Learning Systems ◽  
Learning Object ◽  
Learning Methods ◽  
Integrated Learning Systems ◽  
Integrated Environment ◽  
E Learning ◽  
Learning Object Repositories ◽  
Effective Design

There is a variety of tools and environments for Learning Objects (LOs) design and delivery as well as learning object repositories (LOR) but the researchers could not find a repository that includes both functions: creation and storing of LOs. A number of different integrated learning systems are suggested for users that demonstrate the variety of e-learning methods and semantic capabilities. LO repository oer.ndma.lt/lor, that we are going to present, is very friendly and interoperable to use and assure LO design, search in semantic web, adaptation of the re-used objects and storing. There are no more existing LO repositories with the functionality presented by researchers. Transformation of closed education into open one without existence of well-structured, multifunctional and integrated environment becomes problematic. Authors will present an integrated environment for the LO design, search in semantic web, adaptation and storing of newly designed or re-designed LO. Measures will support the transformation of closed education into open and will assure effective design, re-usability and adaptation of LO in the integrated environment.

M-Learning through Semantically Annotated Learning Objects and Ontologies

2015 ◽  
Vol 3 (2) ◽  
Author(s):  
Reshmy Krishnan
Keyword(s):  
Semantic Web ◽  
Learning Process ◽  
Rapid Development ◽  
Learning Objects ◽  
Learning System ◽  
Learning Object ◽  
Mobile Technologies ◽  
Rich Medium ◽  
Object Structure ◽  
E Learning

Number of mobile subscriptions has increased tremendously due to rapid development of mobile technologies. The performance and accessibility of the e-learning process can be enhanced through mobile devices which is called m-learning. M-learning makes learning resources available anywhere and anytime, provide strong search capabilities, and offers easy interaction features to the learners. M-learning also points the opportunity for interoperability than existing e-learning system. The integration of semantic web in m-learning can improve the efficiency of searching for learning objects and reduce the time and cost of learning process. Semantic web can be integrated with the help of ontologies and learning objects in semantic web. They offer rich medium to assist m-learning via semantic annotated learning objects and shared repositories. Two types of ontologies, such as learning object content ontology and learning object structure ontology are used in this system. These ontologies facilitate the reuse, sharing and retrieval of relevant learning objects which are the backbone of m-learning.

Ontologies in Intelligent Learning Systems

2012 ◽  
pp. 31-48
Author(s):  
Boryana Deliyska ◽  
Peter Manoilov
Keyword(s):  
Semantic Web ◽  
Learning Process ◽  
Learning Objects ◽  
Learning Systems ◽  
Learning Object ◽  
Structural Learning ◽  
Principal Role ◽  
Web Resources ◽  
Human Tutor ◽  
E Learning

The intelligent learning systems provide a direct customized instruction to the learners without intervention of human tutor on the base of Semantic Web resources. The principal role ontologies play in these systems is as an instrument for modeling learning process, learner, learning objects, and resources. In the chapter, a variety of relationships and conceptualizations of ontologies used in the intelligent learning systems are investigated. The utilization of domain and application ontologies in learning object building and knowledge acquisition is represented. The conceptualization of domain ontologies in e-learning is presented by the upper levels of its taxonomies. Moreover, a method and an algorithm intended for generation of application ontologies of structural learning objects (curriculum, syllabus, topic plan, etc.) are developed. Examples of curriculum and syllabus application ontologies are given. Further these application ontologies are used for structural learning object generation.

On the Convergence of Formal Ontologies and Standardized E-Learning

2011 ◽  
pp. 3401-3415
Author(s):  
Miguel-Ángel Sicilia ◽  
Elena García Barriocanal
Keyword(s):  
Learning Objects ◽  
Learning Object ◽  
Learning Resources ◽  
Knowledge Representations ◽  
Learning Object Metadata ◽  
Organizational Issues ◽  
Formal Ontologies ◽  
E Learning ◽  
Ontology Languages ◽  
Effective Integration

Current efforts to standardize e-learning resources are centered on the notion of a learning object as a piece of content that can be reused in diverse educational contexts. Several specifications for the description of learning objects — converging in the LOM standard — have appeared in recent years, providing a common foundation for interoperability and shared semantics. At the same time, the Semantic Web vision has resulted in a number of technologies grounded in the availability of shared, consensual knowledge representations called ontologies. As proposed by several authors, ontologies can be used to provide a richer, logics-based framework for the expression of learning object metadata, resulting in the convergence of both streams of research towards a common objective. In this article, we address the practicalities of the representation of LOM metadata instances into formal ontologies, discussing the main technical and organizational issues that must be addressed for an effective integration of both technologies, and sketching some illustrative examples using modern ontology languages and a large knowledge base.

scholarly journals Panel Discussion: Learning Object Definitions, Metadata, Instructional Design, and Repositories

10.28945/2904 ◽  
2005 ◽  
Author(s):  
Jacques du Plessis ◽  
Alex Koohang ◽  
Jared Schaalje ◽  
Xiangming Mu ◽  
Johannes Britz
Keyword(s):  
Higher Education ◽  
Learning Community ◽  
Panel Discussion ◽  
Personalized Learning ◽  
Learning Objects ◽  
Learning Object ◽  
Quality Instruction ◽  
Learning Instruction ◽  
E Learning ◽  
The Many

The many promises of learning objects (readily available quality instruction, reducing cost of production, personalized learning, interoperability, reusability, discoverability/accessibility, scalability, durability, content customization, and many more) have been the talk of the e-learning community in recent years. Higher education institutions have begun to capitalize on these promises by adopting, developing, and deploying learning objects in e-learning instruction.

scholarly journals Interoperability Gap Challenges for Learning Object Repositories & Learning Management Systems

10.28945/3079 ◽  
2007 ◽  
Author(s):  
Robert Mason
Keyword(s):  
Reference Model ◽  
Learning Management Systems ◽  
Learning Objects ◽  
Learning Object ◽  
Management Systems ◽  
Assessment Data ◽  
Learning Object Metadata ◽  
Metadata Standards ◽  
Learning Object Repositories ◽  
Learning Management

An interoperability gap exists between Learning Management Systems (LMS) and Learning Ob ject Repositories (LOR). LORs are responsible for the storage and management of Learning Objects and the associated Learning Object Metadata (LOM). LOR(s) adhere to various LOM standards depending up the requirements established by user groups and LOR administrators. Two common LOM standards found in LORs are CanCore (Canadian LOM standard) and the Sharable Content Object Reference Model (SCORM) Content Aggregation Model (CAM). In contrast, LMSs are independent computer systems that manage and deliver course content to students via a web interface. This research addresses three important issues related to this problem domain: (a) a lack of metadata standards that define the format of how assessment data should be communicated from Learning Management Systems to Learning Object Repositories, (b) a lack of Information Engineering (IE) architectural standards for the transfer of data from Learning Management Systems to Learning Object Repositories, and (c) a lack of middleware that facilitates the movement of the assessment data from the Learning Management Systems to Learning Object Repositories. Thus, the three goals of this research are: (a) make recommendations for extending the CanCore and SCORM CAM LOM standards to facilitate the storage of assessment and summary assessment data, (b) define the foundation for an IE architectural standard based on an Access Control Policy (ACP) and Data Validation Policy (DVP) using a reliable consensus of experts with the Delphi technique, and (c) develop a middleware prototype that transfers learning assessment data from multiple Learning Management Systems into the Learning Object Metadata of Learning Objects that are stored within a CanCore or SCORM compliant Learning Object Repository.

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