scholarly journals Mokymosi objektų metaduomenų analizė: valdomų žodynų reikšmės

2009 ◽  
Vol 50 ◽  
pp. 95-100
Author(s):  
Svetlana Kubilinskienė ◽  
Inga Žilinskienė
Keyword(s):  
Learning Objects ◽  
Controlled Vocabulary ◽  
The Other ◽  
Learning Object ◽  
Object Type ◽  
Controlled Vocabularies ◽  
Metadata Standard ◽  
Research Results ◽  
Learning Object Metadata ◽  
Search Systems

Pagrindinis straipsnio tikslas yra išanalizuoti mokymosi objektų (MO) metaduomenų standarto LOM (angl. Learning Object Metadata) edukacinės dalies 5.2 elementą (MO tipą) nagrinėjant stambiausius Europos mokslo ir technologijų projektus bei LOM standarto taikymo modelių valdomų žodynų reikšmes. Remdamosi MO metaduomenų standarto taikymo modelio elementų tobulinimo principais ir atliktos analizės rezultatais autorės siūlo originalų patobulintą ir praplėstą MO tipo valdomą žodyną, kuris remiasi LOM standarto ir kitais valdomais žodynais. Valdomo žodyno reikšmių tikslumas ir vienareikšmiškumas leistų naudotojams tiksliai rasti jiems tinkamus MO pagal jų tipą MO paieškos sistemose.Research of Learning Object Metadata: Values of the Controlled VocabularySvetlana Kubilinskienė, Inga Žilinskienė SummaryThe main aim of the article is to analyse the element 5.2 of the education part of the learning object metadata standard (LOM). The values of the controlled vocabularies of the largest European scientifi c and technological projects and LOM standard’s application profi les are analysed in the article. The authors propose the original improved and extended controlled vocabulary of the learning object type which is based on LOM standard and the other standards’ controlled vocabularies. These proposals are based on the scientifi c principles of improvement of the learning object metadata application profi les and the research results. The proposed accurate and unambiguous values of the controlled vocabulary give the users the possibility to precisely search and fi nd suitable learning objects in the search systems in conformity with their types.

Towards a holistic model for quality of learning object repositories

2017 ◽  
Vol 35 (5) ◽  
pp. 953-976
Author(s):  
Christian Vidal-Castro ◽  
Alejandra Andrea Segura Navarrete ◽  
Victor Menendez-Dominguez ◽  
Claudia Martinez-Araneda
Keyword(s):  
Learning Objects ◽  
Learning Object ◽  
Quality Level ◽  
Quality Model ◽  
Holistic Model ◽  
Metadata Standard ◽  
Content Type ◽  
Learning Object Metadata ◽  
Quality Of Learning

Purpose This paper aims to address the need to ensure the quality of metadata records describing learning resources. We propose improvements to a metadata-quality model, specifically for the compliance sub-feature of the functionality feature. Compliance is defined as adherence level of the learning object metadata content to the metadata standard used for its specification. The paper proposes metrics to assess the compliance, which are applied to a set of learning objects, showing their applicability and usefulness in activities related to resources management. Design/methodology/approach The methodology considers a first stage of metrics refinement to obtain the indicator of the sub-feature compliance. The next stage is the proposal evaluation, where it is determined if metrics can be used as a conformity indicator of learning object metadata with a standard (metadata compliance). The usefulness of this indicator in the information retrieval area is approached through an assessment of learning objects where the quality level of its metadata and the ranking in which they are retrieved by a repository are correlated. Findings This study confirmed that the best results for metrics of standardization, completeness, congruence, coherence, correctness and understandability, which determine the compliance indicator, were obtained for learning objects whose metadata were better labelled. Moreover, it was found that the learning objects with the highest level of compliance indicator have better positions in the ranking when a repository retrieves them through an exact search based on metadata. Research limitations/implications In this study, only a sub-feature of the quality model is detailed, specifically the compliance of learning object standard. Another limitation was the size of the learning objects set used in the experiment. Practical implications This proposal is independent from any metadata standard and can be applied to improve processes associated with the management of learning objects in a repository-like retrieval and recommendation. Originality/value The originality and value of this proposal are related to quality of learning object metadata considered from a holistic point of view through six metrics. These metrics quantify both technical and pedagogical aspects through automatic evaluation and supported by experts. In addition, the applicability of the indicator in recovery systems is shown, by example to be incorporated as an additional criterion in the learning object ranking.

Creating High Quality Learning Object Metadata Based on Web 2.0 Concepts

2010 ◽  
pp. 32-46
Author(s):  
Daniel Dahl ◽  
Gottfried Vossen
Keyword(s):  
Web 2.0 ◽  
Learning Objects ◽  
Learning Object ◽  
New Paradigm ◽  
High Quality ◽  
Metadata Standard ◽  
Electronic Learning ◽  
Learning Object Metadata ◽  
Learning Content ◽  
E Learning

When introducing the metadata standard LOM, objectives such as the ability to find or to reuse learning objects were followed. These objectives are actually achieved in LOM to a limited degree only, despite the designation as de-facto standard for description of electronic learning content. Based on the complexity of the standard, a high theoretical potential faces rejection in practice. One reason for this is that the process of metadata generation—for example, who creates which metadata attributes—is not defined in detail yet. This paper illustrates an approach which guarantees a high quantity as well as a high quality of learning object metadata records, bringing together known ways of metadata creation and the new paradigm of users describing content as implemented in recent Web 2.0 applications. In the context of a concrete e-learning platform, we exemplarily illustrate who creates which metadata records of LOM in which way at what time. Finally, we show why this approach of creating metadata matters as we measure our metadata quality and compare it with other’s findings.

Adaptation of Descriptive Metadata for Managing Educational Resources in the GREDOS Repository

2018 ◽  
pp. 2063-2085
Author(s):  
Erla M. Morales Morgado ◽  
Rosalynn A. Campos Ortuño ◽  
Ling Ling Yang ◽  
Tránsito Ferreras-Fernández
Keyword(s):  
Learning Styles ◽  
Mobile Apps ◽  
Learning Objects ◽  
Educational Resources ◽  
Learning Object ◽  
Institutional Repository ◽  
Dublin Core ◽  
Digital Repositories ◽  
Learning Object Metadata ◽  
Metadata Mapping

In this chapter the authors describe a Project entitled “Divulgación de Recursos Educativos Digitales (DIRED)” (Divulgation of Digital Educational Resources) addressed to promoting specific educational resources and mobile apps for educational proposals in order to manage them through the institutional repository of the Salamanca University (GREDOS). The authors present a proposal for describing learning objects based on pedagogical information, digital competences and learning styles. The authors also suggest educational information for classifying useful mobile apps. To achieve their suitable access and recovery, the authors focus on the use of Learning Object specific metadata in digital repositories such as LOM (Learning Object Metadata). The authors study the metadata mapping necessary to adapt from LOM to Qualified Dublin Core, because this is the standard used in the GREDOS repository built with a DSpace platform. Finally, the authors present their implementation of Learning Object Description in the GREDOS repository.

scholarly journals A Semantic Distances-Based Approach for a Deeply Indexing of Learning Objects

2019 ◽  
Vol 14 (06) ◽  
pp. 27 ◽  
Author(s):  
Kamal El Guemmat ◽  
Sara Ouahabi
Keyword(s):  
Search Engines ◽  
Learning Objects ◽  
Learning Object ◽  
Automatic Indexing ◽  
New Approach ◽  
Learning Object Metadata ◽  
Depth Extraction ◽  
Semantic Distances ◽  
Linguistic Structures

Educational search engines are important for users to find learning objects (LO). However, these engines have not reached maturity in terms of searching, they suffer from several worries like the deep extraction of notions which diminishes their performance. The purpose of this paper is to propose a new approach that allows depth extraction of LO’s notions to increase the relevance level of educational search engines. The proposed approach focuses on semi-automatic indexing of textual LO and more precisely the deeper relations of sentences that flesh out explanations. It based on linguistic structures and semantic distances between specific and generic notions according to OntOAlgO ontology. The notions obtained will be improved by learning object metadata (LOM) and will be represented semantically in final index. The tests performed on algorithmic LO, proving the usefulness of our approach to educational search engines. It increases the degree of precision and recall of notions extracted from LO.

scholarly journals Educational Resource Management in Grid Community Based on Learning Object Metadata Standard

2018 ◽  
Vol 13 (11) ◽  
pp. 130
Author(s):  
Yuhang Chen
Keyword(s):  
Resource Management ◽  
Information Diffusion ◽  
Educational Resources ◽  
Learning Object ◽  
Educational Resource ◽  
Community Group ◽  
Community Based ◽  
Metadata Standard ◽  
Learning Object Metadata ◽  
Peer Community

To manage the educational resources of the grid community based on the standard of learning object metadata, the resource classification standard of the learning object metadata standard is taken as the basis of the grid community division. According to the principle of the classification of educational resources, and based on the characteristics of the grid management system and the features of the grid community, the construction and internal structure of grid community are discussed, and the idea of constructing peer community group is proposed. In accordance with the idea of peer community, similar educational resources achieve a logical connection between peer communities. The results show that the mechanism of information sharing and information diffusion is established among communities, and the framework of educational resource management is constructed through simulation and evaluation.

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 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 Learning Object Repositories

10.28945/2908 ◽  
2005 ◽  
Author(s):  
Permanand Mohan
Keyword(s):  
Business Models ◽  
Learning Objects ◽  
Learning Object ◽  
Metadata Standard ◽  
Client Server ◽  
Digital Repositories ◽  
Advantages And Disadvantages ◽  
Learning Object Repository ◽  
Learning Object Repositories ◽  
Uniform Manner

In order to reuse learning objects created by others, they must be made available to potential users on the Web, and services must be provided to allow users to discover, obtain rights to, and use these learning objects in their own instructional scenarios. In the learning object economy, these services are typically provided by learning object repositories, which are collections of learning objects that are accessible to users via a network without prior knowledge of the structure of the collections. This chapter discusses the important role played by learning object repositories in the learning object economy. The success of the learning objects' approach depends on users worldwide (such as instructors, learners, and software agents) being able to access and search for learning objects in different repositories in a uniform manner. The first part of the chapter explains how this can be achieved using a standardized approach for accessing and describing learning objects in a repository. Standardized access and retrieval is facilitated by implementing a specification from the IMS known as the Digital Repositories Interoperability (DRI) specification, while standardized search and discovery is facilitated by implementing a metadata standard such as the IEEE Learning Object Metadata (LOM) standard, described earlier in the book. There are different architectural approaches and business models that can be employed when designing a learning object repository and these are discussed next in the chapter. Typical architectural choices include using a centralized repository based on the client/server approach versus using several local repositories connected in a peer-to-peer fashion. Typical choices for business models include using an online broker for advertising and receiving payment for learning objects versus making the learning objects freely available. The advantages and disadvantages of the different approaches and models are carefully examined, and concrete examples of research prototypes and real-world deployments are provided wherever appropriate.

Sign in / Sign up

Export Citation Format

Share Document