Quality in Learning Objects: Evaluating Compliance with Metadata Standards

Vidal, Christian; Segura, N. Alejandra; Campos, Pedro G.; Sánchez‐Alonso, Salvador

doi:10.1007/978-3-642-16552-8_31

Cited by 4 publications

(6 citation statements)

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“…Moreover, the evaluation can be either quantitative or qualitative. In a later work, the authors detail the form as determining the compliance sub-characteristic (part of the functionality characteristic) through six indicators (Vidal et al, 2010). The indicators are metadata standardization, completeness, correctness, clarity, congruence and pedagogical coherence.…”

Section: Learning Object Repositoriesmentioning

confidence: 99%

“…The proposal made by Tabares et al (2013) defined the quality of the metadata by using completeness, consistency and coherence metrics. The first two metrics are similar to those proposed by Vidal et al (2010), but coherence is defined from the correlation between metadata, which should be drawn from a well-labelled significant set of objects. Coherence is defined as an narray relationship between the learning object metadata with a pedagogical sense.…”

Section: Learning Object Repositoriesmentioning

confidence: 99%

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Towards a holistic model for quality of learning object repositories

Vidal‐Castro

Navarrete

Domínguez

et al. 2017

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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.

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Section: Learning Object Repositoriesmentioning

confidence: 99%

Section: Learning Object Repositoriesmentioning

confidence: 99%

Towards a holistic model for quality of learning object repositories

Vidal‐Castro

Navarrete

Domínguez

et al. 2017

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“…Es la institución propietaria del ROA quien debe definir el perfil de los expertos y el momento de la evaluación. En la tabla IV se presenta el instrumento propuesto con las variables evaluadas, las preguntas y su respectiva codificación, que servirá para entender el cálculo de las métricas, el cual se basa en propuestas de diferentes autores (Bruce y Hillmann, 2004;Massa, 2012;Morales et al, 2007;Nesbit et al, 2003;Vidal, Segura, Campos y Sánchez-Alonso, 2010).Modelo por capas para evaluación de la calidad de objetos de aprendizaje en repositorios En qué nivel la estructura y contenido apoyan el aprendizaje del tema. …”

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Modelo por capas para evaluación de la calidad de Objetos de Aprendizaje en repositorios

Morales

Méndez

Carranza

2017

REDIE

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ResumenLos Objetos de Aprendizaje (OAs) son recursos digitales utilizados para apoyar los procesos de enseñanza y aprendizaje almacenados en Repositorios de OAs (ROAs), facilitando su búsqueda y recuperación. Sin embargo, en la mayoría de los casos es difícil determinar la calidad de estos recursos, por ello en este trabajo se presenta un modelo por capas para la evaluación de la calidad de OAs que identifica las principales características que deben cumplir estos recursos y la forma de determinar su cumplimiento a través de la especificación de diferentes métricas. Los resultados de la aplicación de la propuesta en la evaluación de los OAs de la Federación de Repositorios de Objetos de Aprendizaje (FROAC) demostraron la existencia de problemas en la calidad de estos recursos educativos, la importancia de la aplicación del modelo para apoyar el proceso de entrega de mejores objetos a partir de las búsquedas y su utilidad como herramienta de gestión en los ROAs.Palabras clave: Objetos de Aprendizaje, Repositorios de Objetos de Aprendizaje, Evaluación de Objetos de Aprendizaje, Tecnología educativa. AbstractLearning objects (LOs) are digital resources used to support teaching and learning processes and stored in learning object repositories (LORs), making them easier to search for and retrieve. However, in most cases it is difficult to determine the quality of these resources, and as a result this study presents a layered model for quality assessment of LOs that identifies the main conditions these resources must fulfill and a way to determine fulfillment by specifying various metrics. The results obtained from applying the proposal to the assessment of LOs in the Federation of Learning Object Repositories (FROAC) revealed problems in the quality of these educational resources, the importance of applying the model to support the delivery of better objects from searches and its usefulness as a management tool in LORs.Modelo por capas para evaluación de la calidad de objetos de aprendizaje en repositorios I. IntroducciónEl e-learning se ha posicionado como uno de los principales esquemas de educación; ha cambiado los procesos tradicionales de enseñanza y aprendizaje, y proporcionado numerosas ventajas de carácter pedagógico y de acceso. Este esquema genera nuevas necesidades, tales como el desarrollo y mejora de materiales educativos, de donde surgen los Objetos de Aprendizaje (OAs) definidos como entidades digitales que pueden ser utilizadas es procesos de aprendizaje, generalmente entregados a través de Internet y diseñados con el fin de que sean utilizados y reutilizados en múltiples contextos educativos (Learning Technology Standards Committe, 2002;Wiley, 2001). Para facilitar su reutilización, los OAs deben ser unidades independientes con un objetivo de aprendizaje claro y un contenido autónomo que no dependa de otros objetos (Chiappe, 2006;Morales, García, Barrón, Berlanga y López, 2005). Una característica distintiva de los OAs es que contienen metadatos que los describen, facilitando su búsqueda, evaluación...

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“…Besides the quality metrics defined by some of the above evaluation models, more metrics have been developed to evaluate various aspects of Learning Objects such as metadata quality [26], [288], popularity [219], [221], effectiveness [289], [290] or cost of reuse [192].…”

Section: Learning Object Evaluationmentioning

confidence: 99%

“…Vidal, Segura, Campos and Sánchez-Alonso [288] proposed a set of quality metrics for Learning Object metadata in order to evaluate metadata standardization, completeness, correctness, understandability, coherence and congruence. Some of these metrics can be calculated automatically by software systems while others require expert evaluations.…”

Section: Learning Object Evaluationmentioning

confidence: 99%

Contribution to the authoring, distribution, evaluation and integration of learning objects

Gordillo¹

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Learning Objects have emerged in recent years in the field of educational technology as a key strategy for creating and delivering digital educational resources. The fundamental idea behind them is that educational content can be broken down into small chunks that can be independently created and reused in different contexts and e-Learning systems.Learning Objects are educational resources that aim to improve reusability in order to minimize production cost, save time and provide better learning experiences. Various benefits of using Learning Objects have been exposed by several studies that have examined their acceptance and effectiveness as well as their capacity to be reused. Nevertheless, and in spite of the immense amount of work done in this research field, there are still several barriers hampering the use and adoption of Learning Objects. To overcome these barriers and fully exploit the potential of Learning Objects, various challenges must be addressed at different stages of their life cycle. This thesis encompasses the design, development and evaluation of various systems, metrics and models in order to address and overcome several of the main barriers that hamper the authoring, distribution, evaluation and integration of Learning Objects. Moreover, the use of Learning Objects in various educational environments is studied. The thesis starts with the identification of the main barriers that hamper the use and adoption of Learning Objects along the different stages of their life cycle. Thereafter, an e-Learning platform that supports the whole Learning Object life cycle is presented. Then, results of the design, implementation and evaluation of an authoring tool to create Learning Objects are reported. Next, the thesis presents the first system designed to provide systematic evaluation of Learning Objects and generation of quality scores to e-Learning systems according to multiple Learning Object evaluation models and quality metrics. Furthermore, two new evaluation models and several new quality metrics for Learning Objects are proposed. One of these metrics is based on learning analytics and allows to estimate the quality of Learning Objects based on learners' interactions. This thesis also presents a hybrid Learning Object recommendation model for Learning Object Repositories and two recommender systems implemented based on this model. After that, three integration models are detailed: a model to allow e-Learning authoring tools to assemble Learning Objects by integrating and combining other ones, a model to enable the integration of Learning Objects into web videoconferencing services, and a model to integrate Learning Objects into web games in order to create educational web games. Afterwards, several projects and learning experiences in which different contributions have been validated are described. Finally, the thesis concludes with answers to the stated research questions, a summary of the main contributions and some suggestions for further research.

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Quality in Learning Objects: Evaluating Compliance with Metadata Standards

Cited by 4 publications

References 11 publications

Towards a holistic model for quality of learning object repositories

Towards a holistic model for quality of learning object repositories

Modelo por capas para evaluación de la calidad de Objetos de Aprendizaje en repositorios

Contribution to the authoring, distribution, evaluation and integration of learning objects

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