Management Of Learning Objects Research Articles

Design matters: How a course review informed online teaching best practices

This paper discusses how an Applying the Quality Matters (QM) Rubric for Higher Education workshop had an impact on the online teaching practice of three academic librarians. The QM Rubric was used to review and update a credit-bearing information literacy course taught by the authors’ department. The authors reflect on how this training influenced their relationship to online teaching during the COVID-19 pandemic (and beyond), using examples from their own experiences to demonstrate how instruction librarians contributed to online education during this period and how they used sustainable teaching practices to lessen the workloads of their teaching colleagues. Future steps include improved documentation, assessment, management and maintenance of digital learning objects used in online teaching.

The management of Digital Learning Objects of Natural Sciences and Digital Experiment Simulation Tools by teachers

In the present study, we tried to find possible obstacles that Primary and Secondary education teachers face when managing Digital Learning Objects (DLOs) and/or Digital Simulation Tools (DST) in Science. One hundred seventy-six teachers from all over Greece answered the questionnaire. The results showed that the main reason for refusing to deal with DLOs and DSTs is the technological equipment. Also, the lack of adequate training level B 'results in about 25% of teachers not knowing the DSTs and 30% not knowing the DLOs. Factors such as the teaching experience, the specialty, the Pan-Hellenic examinations, the classes they teach, and the number of students they have per class negatively affect the teachers' attitude to get involved with the DLOs the DSTs. Finally, the negative attitude seems to be related to the lack of trust in the curriculum content as teachers prefer to search DLOs and DSTs on the internet connection. Further research with mixed methods of analysis would help to obtain satisfactory results.

Adaptive learning objects in the context of eco-connectivist communities using learning analytics

Eco-connectivist communities are groups of individuals with similar characteristics, which emerge in a connectivist learning process within a knowledge ecology. ARMAGAeco-c is a reflexive and autonomic middleware for the management and optimization of eco-connectivist knowledge ecologies using description, prediction and prescription models. Adaptive Learning Objects are autonomic components that seek to personalize Learning Objects according to certain contextual information, such as learning styles of the learner's, technological restrictions, among other aspects. MALO is a system that allows the management of Adaptive Learning Objects. One of the main challenges of the connectivist learning process is the adaptation of the educational context to the student needs. One of them is the learning objects. For this reason, this work has two objectives, specifying a data analytics task to determine the learning style of a student in an eco-connectivist community and, adapting instances of Adaptive Learning Objects using the learning styles of the students in the communities. We use graph theory to identify the referential member of each eco-connectivist community, and a learning paradigm detection algorithm to identify the set of activities, strategies, and tools that Adaptive Learning Objects instances should have, according to the learning style of the referential member. To test our approach, a case study is presented, which demonstrates the validity of our approach.

Integration of learning objects for adaptative learning

The integration of learning management systems with learning object management systems allows to increase the availability, reuse, integration and adaptability of educational contents according to the characteristics and preferences of the clients. However, given the new trends in the integration of learning objects, software architectures and recommendation systems, it is of high added value to optimize the services offered to customers through an integrated learning management system aimed at the automatic construction of Adaptive training processes in higher education. The main result is the description of an integral system of virtual education based on the competences required by the students, which integrates learning objects (OA) through a semantic OA recommender system and then the system sequencing the OAs to respond to the required competences. The software architecture of the system is structured in two layers: The layer of OA discovery and adaptability and the layer of generation of adaptive training processes, which have as a design principle the web services in order to guarantee the interoperability of the layers.

Hypermedia Driven Application Programming Interface for Learning Object Management

The research purpose is to create a hypermedia driven API for learning object management. The research focuses on conception, design, implementation and evaluation of the learning object management hypermedia API. The hypermedia API was designed based on learning object models, hypermedia concepts, and related studies. Learning object model can be represented and manipulated as a hypermedia resource. It contains page resources with text and links to multimedia elements. The hypermedia API was designed using UML and represented in HTML5 because of its rich affordance. The implementation and evaluation phase were conducted by testing the API using three different client’s software to prove the concept of hypermedia as the engine of application state for managing learning objects. The results show that the hypermedia API for learning object management is accessible, consistent, and discoverable by heterogonous client applications.

Towards a holistic model for quality of learning object repositories

PurposeThis 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/approachThe 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.FindingsThis 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/implicationsIn 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 implicationsThis 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/valueThe 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.

Multicriteria Decision Making for Evaluation of e-Learning Tools

This document is in the required format. This work shows a benchmark of e-Learning tools including an approach for comparing them based on histogram specification concepts. The analysis is based on the definition of a set of criteria which are useful and desirable characteristics of learning management systems. The final results show the evaluation from different views including the approach based on their histograms. The evaluation of each e-Learning tool is based on the use of a three-dimensional model which organizes the criteria in three different axes according to their functionality inside the model, namely: Management, Technological and Instructional. With the application of the evaluation methodology we can assess the tools from different points of view. One of the main objectives of this work is to help users and developers of e- Learning tools to make good decisions about which tool have the best features for developing training and learning systems and for development and management of resources, courses and learning objects.

Learning Objects Recommendation System: Issues and Approaches for Retrieving, Indexing and Recomend Learning Objects

This paper discusses some important issues regarding the the management of Learning objects covering searching over repositories and different approaches of recommendation systems and presents a multiagent system based application model for indexing, retrieving and recommending learning objects stored in different and heterogeneous repositories. The objects within these repositories are described by filled fields using different metadata (data about data) standards. The searching mechanism covers several different learning object repositories and the same object can be described in these repositories by the use of different types of fields. Aiming to improve accuracy and coverage in terms of recovering a learning object and improve the relevance of the results we propose an information retrieval model based on a multiagent system approach and an ontological model to describe the covered knowledge domain.

An investigation on the correlation of learner styles and learning objects characteristics in a proposed Learning Objects Management Model (LOMM)

The issues of accessibility, management, storage and organization of Learning Objects (LOs) in education systems are a high priority of the Thai Government. Incorporating personalized learning or learning styles in a learning object management system to improve the accessibility of LOs has been addressed continuously in the Thai education system. A proposed Learning Object Management Model (LOMM) is discussed in this paper which aims to adapt and optimize the learning process based on characteristics of the individual learners. This study aims to find the correlation between learning styles and LOs characteristics in the LOMM. Decision Tree and Apriori algorithms were used to generate a predictive model for the classification of learners. Development of the predictive model was based on survey results from 1,586 high school students in Nakhon Ratchasima province, Thailand. The diverse LOs characteristics were analyzed in order to find the correlation with learning styles of the learners. The classification model consists of 24 sub-models used to predict a learner’s class based on 8 groups of LOs characteristics. The best accuracy obtained in the study was 80.23%. Finally, for the next phase this approach has been designed to support the proposed LOMM and it is expected that it could be readily applied to other e-learning systems and digital repositories.

Модели и стандарты электронного обучения

The paper is a review of models and standards used in modern e-learning systems. The general concept model of e-learning environment is considered. The review also regards these topics: the data model for interaction with learning objects; the content aggregation model which describes the structure of learning objects, the ways of searching, packing and transmitting them between different learning systems; the run-time environment model, which defines an API for learning objects management; the sequencing model for learning content; the competency model, which is used to specify knowledge, skills and abilities in e-learning systems. The paper also reviews SCORM, which integrates a system of e-learning models.

Evaluation Models for Building Learning Content Management System (LCMS) in Riyadh City Universities

paper proposes evaluation model based Learning Content Management System (LCMS) in the university city of Riyadh. The survey was conducted literature and practical web development methodologies to determine the readiness of LCMS University in the city of Riyadh. Framework is evaluated by a valuation model of e-learning anti-hunger program, proposed by Francesco Colace in 2006. Evaluation model was evaluated four main features (management and collaborative approach, interactive learning objects management and adaptation of the path of education). Involves every feature, in their determination, some sub- features. The results of the evaluation model as follows: The sum of the weights of the framework proposed in management feature is 16.7/25, collaborative feature is 9/10, in the adaptive learning path is a 5.5/10 in interactive learning object is 5/5. Sum of the weights of all the features are 36.2/50. Then, the results were compared with each other. Weighs the sum of all of King Saud University and the University of Prince Sultan was 41. While the total weights of King Faisal University, IMAMU, YU and NAUSS was 40, 37.36 and 32, respectively. The evaluation process shows that the proposed framework satisfied with the objectives and tasks required for this work.

Web‐based learning design tool

PurposeThe purpose of this paper is to propose a web‐based tool that enables the development and provision of learning designs and its reuse and re‐contextualization as generative learning objects, aimed at developing educational materials.Design/methodology/approachThe use of learning objects can facilitate the process of production and delivering of educational material and their reuse and re‐contextualization in different scenarios – such process is due to the current development stage of information and communication technologies (ICTs), which allow easy access to products and services related to them. ICTs combined with instructional design theories, lead to the emergence of new generations of distance learning, which add educational content to web‐based services. From this combination rises a hybrid mode of education, which combines tools for face‐to‐face and distance learning (blended learning).FindingsThe use of the web as a platform for production and management of learning objects comes as a solution for storage and sharing. The utilization of objects is justified when its reusability is facilitated. This gives rise to possibilities in a client‐server environment, where information is centralized and available anywhere in the network.Research limitations/implicationsThe combination of ICT and instructional design theories has potential and could result in hybrids which are yet to be fully understood and explored. This can enhance blended learning provision.Originality/valueThe paper presents a tool in which the learning designs work as structures built on XML, based on concept maps, which act as an interaction layer between the learning objects, organizing the content to be available.

Gestión de objetos de aprendizaje a través de la red, basado en el desarrollo de competencias

Hoy en día existen una gran cantidad de bibliotecas virtuales y repositorios de recursos en general, donde es posible acceder a diverso tipo de información, destinado a múltiples áreas de conocimiento. 
 Uno de esos tipos de información corresponde a los Objetos de Aprendizaje (OAs), los cuales a través de sus metadatos pueden ser localizados y recuperados según necesidades educativas específicas de los usuarios. 
 Los objetivos educativos están claramente orientados al desarrollo de competencias, por tanto, es importante tener en cuenta materiales que puedan potenciarlas. Debido a la caracteristica de los OAs, como unidades independientes que puedan ser reutilizadas, se propone un modelo de diseño que oriente la creación de estos recursos según niveles de conocimiento necesarios para el desarrollo de competencias.
 Para promover la búsqueda de estos recursos en base a niveles de conocimiento, se presenta una propuesta para su catalogación a través de metadatos, que considere además de los niveles de conocimiento, su clasificación por competencias.

Digital content creation: A global view on curriculum design

Digital content creation: A global view on curriculum design

Promoting quality during learning-object management through experts and users

Like any digital resource, learning objects are managed in different stages: design, creation, delivery and evaluation. However, it is not very clear how their quality can be strengthened to obtain optimum functionality. This means that there is no clear definition as to the stages in which learning objects need to be evaluated and neither are there any specific models that can help in the design of learning objects to meet different kinds of targets and tools for their evaluation. This paper presents a proposal for learning objects design and evaluation during their management in the four stages proposed by the context, input, process, and product (CIPP) model.

ONTOLOGY-BASED LEARNING OBJECTS SEARCH AND COURSES GENERATION

Learning objects paradigm is widely adopted in e-learning environments. Learning objects management can be improved using semantic technologies from ontology engineering and the semantic web. In this article we use a semantic model of the repository to improve both learning objects retrieval and composition. The use of domain knowledge enables automatic reasoning and makes the system able to import new domain models and use them to interrogate the repository (Arrigoni Neri 2005). Learning objects composition is one of the main challenges in e-learning management systems and can be improved exploiting ontological reasoning. The building of a course can be carried out in two phases, in the first phase we compose concept level entities to obtain an outline of the course, then we fill the outline with actual resources from the repository. Both phases can use ontology-based models to capture specific domain knowledge (Arrigoni Neri 2006). In order to provide an intuitive and expressive ontology representation, we briefly propose a graphical syntax for the well-known ontology web language (OWL).

The Open Learning Object model to promote Open Educational Resources

<div class="abstract_container"> In this paper we present the results of research work, that forms part of the activities of the EU-funded project SLOOP: Sharing Learning Objects in an Open Perspective, aimed at encouraging the definition, development and management of Open Educational Resources based on the Learning Object paradigm (Wiley, 2000). We present a model of Open Learning Object (OpenLO) for a greater awareness in the use of LOs by teachers, giving them a more active role in the evolution of educational resources; the OpenLO model extends the concept of reusability, providing pedagogical sustainability. Moreover, we compare FreeLOms, a Learning Object Management System that implements the proposed OpenLO model, to traditional tools for handling LOs. </div> <p class="editors_container"><strong>Editors:</strong> Patrick McAndrew (Open University, UK). <p class="reviewers_container"><strong>Reviewers:</strong> Anonymous Review (Anonymous) and Patrick McAndrew (Open University, UK).

Introduction to the IEEE Transactions on Learning Technologies

Welcome to the fi rst issue of the IEEE Transactions on Learning Technologies. The IEEE Transactions on Learning Technologies will publish archival research papers focusing on all kinds of modern e-learning technologies. The new journal will emphasize the technology side of learning and instruction, as opposed to the majority of existing journals focusing solely on instructional and pedagogical issues. The new title will cover all advances in learning technologies, including but not limited to innovative online learning systems, intelligent tutors, educational software applications and games, simulation systems for education and training, collaborative learning tools, devices and interfaces for learning, interactive techniques for learning, personalized and adaptive learning systems, tools for formative and summative assessment, ontologies for learning systems, standards and Web services that support learning, authoring tools for learning materials, computer support for peer tutoring, learning via discovery, field, and lab work, learning with mobile devices, social learning techniques, social networks and infrastructures for learning and knowledge sharing, and the creation and management of learning objects. In order to best serve the community, the IEEE Transactions on Learning Technologies is published online, four issues per year, using a delayed open-access policy under which paying subscribers and per-article purchasers have access to newly published content, and 12 months after the publication of each issue, all readers have access to the content free of charge. We expect papers which either describe original research or offer a critical review of the state of the art in a particular area. Papers concerned with the evaluation of technology are only appropriate if the technology itself is novel or if significant insights for advancing the technology are provided.

Content Management Systems For E-learning:An Application

This paper discusses our approach to the tailoring of an open source Content Management System to use it as a Learning Content Management System, by providing modules for the management of Learning Objects and for their retrieval and indexing via Metadata. Both the description of what a Content Management System is and the key requirements that a Learning Content Management System must posses will be presented in the paper. Then, a working definition of Learning Object will be provided, and finally we will show how this model can be implemented using MD-PRO.

CanCore: Metadata for Learning Objects

The vision of reusable digital learning resources or objects, made accessible through coordinated repository architectures and metadata technologies, has gained considerable attention within distance education and training communities. However, the pivotal role of metadata in this vision raises important and longstanding issues about classification, description and meaning. The purpose of this paper is to provide an overview of this vision, focusing specifically on issues of semantics. It will describe the CanCore Learning Object Metadata Application Profile as an important first step in addressing these issues in the context of the discovery, reuse and management of learning resources or objects.