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

Author(s):  
Yuhang Chen

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.

2018 ◽  
pp. 2063-2085
Author(s):  
Erla M. Morales Morgado ◽  
Rosalynn A. Campos Ortuño ◽  
Ling Ling Yang ◽  
Tránsito Ferreras-Fernández

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.


2017 ◽  
Vol 35 (5) ◽  
pp. 953-976
Author(s):  
Christian Vidal-Castro ◽  
Alejandra Andrea Segura Navarrete ◽  
Victor Menendez-Dominguez ◽  
Claudia Martinez-Araneda

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.


Open educational resources just supply potentials to help equalize the access to worldwide knowledge and education, but themselves alone do not cause effective learning or education. How to make effective use of the resources is still a big challenge. In this study, a technical mode is proposed to collect the open educational resources from different sources on the Internet into a campus-network-based resource management system. The system facilitates free and easy access to the resources for instructors and students in universities and integrates the resources into learning and teaching. The technical issues regarding the design the resource management system are examined, including the structure and functions of the system, metadata standard compatibility and scalability, metadata file format, and resource utilization assessment. Furthermore, the resource collecting, storage and utilization modes are also discussed so as to lay a technical basis for extensive and efficient sharing and utilization of the OER in Chinese universities.


Author(s):  
Daniel Dahl ◽  
Gottfried Vossen

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.


2014 ◽  
Vol 10 (4) ◽  
pp. 50-72 ◽  
Author(s):  
Erla M. Morales Morgado ◽  
Rosalynn A. Campos Ortuño ◽  
Ling Ling Yang ◽  
Tránsito Ferreras-Fernández

In this paper 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.


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