Technological Evaluation and Optimization of E-Learning Systems Components

2011 ◽  
pp. 150-173 ◽  
Author(s):  
Eugenijus Kurilovas ◽  
Valentina Dagiene
Keyword(s):  
Quality Evaluation ◽  
Evaluation Criteria ◽  
Learning Objects ◽  
Learning Systems ◽  
Main Research ◽  
Evaluation Models ◽  
E Learning ◽  
Multiple Criteria Evaluation ◽  
Technological Evaluation ◽  
Learning Software

The main research objective of the chapter is to provide an analysis of the technological quality evaluation models and make a proposal for a method suitable for the multiple criteria evaluation (decision making) and optimization of the components of e-learning systems (i.e. learning software), including Learning Objects, Learning Object Repositories, and Virtual Learning Environments. Both the learning software ‘internal quality’ and ‘quality in use’ technological evaluation criteria are analyzed in the chapter and are incorporated into comprehensive quality evaluation models. The learning software quality evaluation criteria are further investigated in terms of their optimal parameters, and an additive utility function based on experts’ judgements, including multicriteria evaluation, numerical ratings, and weights, is applied to optimize the learning software according to particular learners’ needs.

scholarly journals HyCo – An Authoring Tool to Create Semantic Learning Objects for Web-Based E-learning Systems

2004 ◽  
pp. 344-348 ◽  
Author(s):  
Francisco J. García ◽  
Adriana J. Berlanga ◽  
Maria N. Moreno ◽  
Javier García ◽  
Jorge Carabias
Keyword(s):  
Learning Objects ◽  
Learning Systems ◽  
Authoring Tool ◽  
Web Based ◽  
Semantic Learning ◽  
E Learning

A Systematic Map of Evaluation Criteria Applicable for Evaluating E-Portfolio Systems

2016 ◽  
pp. 60-106
Author(s):  
Gary F. McKenna ◽  
Gavin J. Baxter
Keyword(s):  
Evaluation Criteria ◽  
Evaluation Methods ◽  
Extensive Literature ◽  
Design Development ◽  
Systematic Map ◽  
Portfolio Evaluation ◽  
Literature Searches ◽  
Starting Point ◽  
Evaluation Models ◽  
E Learning

This chapter examines the literature on evaluation methods within e-learning with respect to their applicability to evaluate e-portfolio systems within higher education as evaluation criteria for reviewing e-portfolio provisions do not currently exist in the literature. The appr­oach taken is to initiate two extensive literature searches and reviews. The first search was undertaken in 2009 involved reviewing over 600 articles by abstract dating from 1995 to 2010 to develop evaluation criteria suitable for Blackboard LMS e-portfolio systems evaluation. The second search undertaken in 2013 involved extending the search criteria to include further terminology and databases and returned over 4107 articles, which were read by title and abstract dating from 2009 to 2013, in order to systematically map evaluation methods used within e-learning to assess their quality and applicability for evaluating e-portfolio systems. The implications of the research undertaken provide a starting-point for further research into the development of robust e-portfolio evaluation models and frameworks. The lack of evidence uncovered in the 2009 and 2013 searches of the literature justify the need for further research into the design, development, and testing of evaluation methods for the evaluation of e-portfolio systems.

Indexing Serious Games to Meet Adaptive E-Learning System Needs

2020 ◽  
pp. 284-303
Author(s):  
Yassine El Borji ◽  
Mohammed Khaldi
Keyword(s):  
Serious Games ◽  
Main Idea ◽  
Learning Objects ◽  
Learning Systems ◽  
Learning System ◽  
The Other ◽  
E Learning ◽  
Technical Sense ◽  
Application Profile ◽  
Educational Field

This chapter aims to strengthen the integration of serious games in the educational field by providing tools to monitor and assist the progress of learners/players. The main idea is to address the integration aspects and the deployment of serious games in adaptive e-learning systems based on the automatic package and the export of serious games as reusable learning objects (LO). This integration will allow SGs to benefit from the tracking and support features offered by the LMS. On the other hand, LMS can supplement their training offer and reach a certain maturity. The approach aims to meet the specific needs of SGs in terms of metadata so that they can be described, indexed, and capitalized. This is a new application profile of the IEEE LOM standard entitled “SGLOM” integrating fields to describe SGs not only in a technical sense but also by examining the pedagogical and playful criteria. The authors also focus on the integration and extraction aspects of SGs in an LMS using the ADL SCORM 2004 data model that defines how content can be packaged as a SCORM PIF (package interchange file).

scholarly journals Design of an Adaptive e-Learning System based on Multi-Agent Approach and Reinforcement Learning

2021 ◽  
Vol 11 (1) ◽  
pp. 6637-6644
Author(s):  
H. El Fazazi ◽  
M. Elgarej ◽  
M. Qbadou ◽  
K. Mansouri
Keyword(s):  
Reinforcement Learning ◽  
Learning Style ◽  
Learning Process ◽  
Learning Experience ◽  
Personalized Learning ◽  
Learning Objects ◽  
Learning Systems ◽  
Learning System ◽  
E Learning ◽  
Multi Agent

Adaptive e-learning systems are created to facilitate the learning process. These systems are able to suggest the student the most suitable pedagogical strategy and to extract the information and characteristics of the learners. A multi-agent system is a collection of organized and independent agents that communicate with each other to resolve a problem or complete a well-defined objective. These agents are always in communication and they can be homogeneous or heterogeneous and may or may not have common objectives. The application of the multi-agent approach in adaptive e-learning systems can enhance the learning process quality by customizing the contents to students’ needs. The agents in these systems collaborate to provide a personalized learning experience. In this paper, a design of an adaptative e-learning system based on a multi-agent approach and reinforcement learning is presented. The main objective of this system is the recommendation to the students of a learning path that meets their characteristics and preferences using the Q-learning algorithm. The proposed system is focused on three principal characteristics, the learning style according to the Felder-Silverman learning style model, the knowledge level, and the student's possible disabilities. Three types of disabilities were taken into account, namely hearing impairments, visual impairments, and dyslexia. The system will be able to provide the students with a sequence of learning objects that matches their profiles for a personalized learning experience.

scholarly journals Research on learning objects quality and reusability

2010 ◽  
Vol 51 ◽  
Author(s):  
Elvyra Ignaško ◽  
Eugenijus Kurilovas
Keyword(s):  
Quality Evaluation ◽  
Evaluation Model ◽  
Evaluation Criteria ◽  
Learning Objects ◽  
Multiple Criteria ◽  
Multiple Criteria Analysis ◽  
Analysis Methods ◽  
Quality Evaluation Model

The paper is aimed to analyse the learning objects quality evaluation model taking into account learning objects reusability principles. Multiple criteria analysis methods and quality evaluation criteria identification principles are used to create the learning objects quality evaluation model. The portrait of the sets of the learning objects reusability principles and the learning objects quality evaluation criteria is presented in the paper. This portrait shows the bilateral cohesion of theseprinciples and criteria. The presented learning objects quality evaluation model is usable in education institutions while selecting learning objects in the market or free-of-charge repositories.

Standards? What and Why?

2011 ◽  
pp. 3433-3448
Author(s):  
Phil Long ◽  
Frank Tansey
Keyword(s):  
Systems Design ◽  
Building Blocks ◽  
Learning Systems ◽  
Next Generation ◽  
Complex Learning ◽  
E Learning ◽  
Learning Software

Specifications define the nature of the interconnections between the distinct parts of complex learning systems, but not their boundaries.  Next generation CMS tools are emerging from standards discussions that challenge current e-learning systems design boundaries. They raise the prospect of a complex but smoothly functioning set of components and services that aggregate in ways that best serve individual communities of users. Users need to engage in the process to express their requirements for e-learning software. These building blocks, produced by a small number of organizations, are establishing the framework that will enable CMS environments to become vastly different than the CMS you might now be using.

Interoperability Approach in E-Learning Standardization Processes

2012 ◽  
pp. 542-560 ◽  
Author(s):  
Carmen Bao ◽  
José María Castresana
Keyword(s):  
Learning Environments ◽  
Relational Databases ◽  
Learning Objects ◽  
Learning Technologies ◽  
Learning Systems ◽  
Learning Resources ◽  
Virtual University ◽  
Schema Mappings ◽  
Learning Standards ◽  
E Learning

Providing interoperability by using standards and specifications for E-learning resources is an important element of the virtual learning environments (VLEs). In this context, a large number of international organizations develop specifications that provide principles for reaching a common “language” to be used in exchanging resources among the virtual university. In this paper we turn your attention to an approach and reference for providing interoperability in different standards. The establishment of E-learning standards has promised to improve interoperability between E-learning systems, but can only be done through enforcement of these standards. Many existing E-learning systems are built on top of relational databases, and it is possible a framework which matches XML Schemas (from learning standards) and relational schemas semi-automatically. This type of framework can provide translation between learning objects and relational databases as well as an interface to manually refine existing schema mappings. The focus is E-learning standardization and synchronization in the international and national levels. The work presents a brief updated review and it presents some new challenges, concerning the E-learning standardization processes. This research is in the area of E-learning standardization and issue is one aspect of great interest for all organizations, authorities and experts working in the field of education. Moreover, the most recognized approaches are introduced in order to improve and optimize the management of the E-learning processes. While the establishment of E-learning standards has promised to improve interoperability between E-learning systems, and obviously, this can only be done through enforcement of E-learning standards and E-learning standardization processes. The aim of this work is to discover the useful E-learning technologies as technological tools for teaching. Therefore, teachers must keep in mind clearly that they must optimize teaching by means of them, such as an improvement of quality education for current society in terms of competences, as connections with the current reality that students spent long hours using them. It starts with a brief background to worldwide standardization activities in the field of educational technologies as means of enhancing the accessibility, interoperability, durability, reusability and efficiency of E-learning resources, but more important new demands and problems to be tackled are reviewed. Finally, experimental dates from studies have shown that it is useful a framework that also provides translation between learning objects and relational databases, as well as an interface to manually refine existing schema mappings.

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.

A Systematic Map of Evaluation Criteria Applicable for Evaluating E-Portfolio Systems

2014 ◽  
pp. 1-54 ◽  
Author(s):  
Gary F. McKenna ◽  
Gavin J. Baxter
Keyword(s):  
Evaluation Criteria ◽  
Evaluation Methods ◽  
Extensive Literature ◽  
Design Development ◽  
Systematic Map ◽  
Portfolio Evaluation ◽  
Literature Searches ◽  
Starting Point ◽  
Evaluation Models ◽  
E Learning

This chapter examines the literature on evaluation methods within e-learning with respect to their applicability to evaluate e-portfolio systems within higher education as evaluation criteria for reviewing e-portfolio provisions do not currently exist in the literature. The appr­oach taken is to initiate two extensive literature searches and reviews. The first search was undertaken in 2009 involved reviewing over 600 articles by abstract dating from 1995 to 2010 to develop evaluation criteria suitable for Blackboard LMS e-portfolio systems evaluation. The second search undertaken in 2013 involved extending the search criteria to include further terminology and databases and returned over 4107 articles, which were read by title and abstract dating from 2009 to 2013, in order to systematically map evaluation methods used within e-learning to assess their quality and applicability for evaluating e-portfolio systems. The implications of the research undertaken provide a starting-point for further research into the development of robust e-portfolio evaluation models and frameworks. The lack of evidence uncovered in the 2009 and 2013 searches of the literature justify the need for further research into the design, development, and testing of evaluation methods for the evaluation of e-portfolio systems.

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