scholarly journals INTEGRATING SEMANTIC SEARCH IN E-LEARNING TECHNOLOGIES: THE ELSE SYSTEM

2020 ◽  
Vol 78 (4) ◽  
pp. 237-248
Author(s):  
Анна Форміка ◽  
Алессія Барбагалло
Keyword(s):  
Semantic Web ◽  
Health Professionals ◽  
Learning Objects ◽  
Learning Preferences ◽  
Learning Technologies ◽  
Semantic Search ◽  
Medical Education Program ◽  
User Request ◽  
E Learning ◽  
Definition Of

The integration of semantic web methodologies and e-learning technologies is a challenge that has attracted a lot of attention for a decade. Given this, the purpose of this paper is the definition of a new e-learning semantic web methodology for the development of courses for health professionals in both distance and residential learning modes. ELSE is an ontology-based system which allows the construction of customized e-learning courses according to the needs and learning preferences of the user. It integrates semantic search methodologies and e-learning technologies. The underlying methodology relies on a reference domain ontology and teaching multimedial interactive modules, referred to as Reusable Learning Objects (RLOs), which are annotated according to the concepts of the ontology. The user can specify his/her training needs by selecting a set of concepts from the ontology, and the SemSim semantic search engine allows the identification of the set of RLOs that satisfy the user request at best, in efficient way. SemSim is a semantic similarity method which has been extensively experimented with and shows a higher correlation with human judgment with respect to the most relevant similarity methods defined in the literature. The set of RLOs is successively reorganized according to the learning preferences of the user. ELSE has been developed within a project of the CME (Continuing Medical Education) program - ECM for Italian participants - whose goal is the introduction of new methodologies and tools to keep updated health professionals and, in particular, medical specialists, in order to ensure effectiveness, safety, and efficiency of the national health service. ELSE has been tested and validated in the domain of osteoporosis, and the overall judgment about the system is very positive, both in terms of usability and effectiveness of customization. The system has been developed in cooperation with the ECM provider SPES S.c.p.A., accredited by the Italian Ministry of Health.

scholarly journals The Model for Learning Objects Design Based on Semantic Technologies

2017 ◽  
Vol 12 (2) ◽  
pp. 227
Author(s):  
Daina Gudoniene ◽  
Rytis Maskeliunas ◽  
Danguole Rutkauskiene
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Learning Environments ◽  
Information And Communication Technologies ◽  
Learning Objects ◽  
Semantic Web Services ◽  
Innovative Learning ◽  
Modern Learning ◽  
E Learning ◽  
Integration Of Learning

The paper presents a comparison of state of the art methods and techniques on implementation of learning objects (LO) in the field of information and communication technologies (ICT) using semantic web services for e-learning. The web can serve as a perfect technological environment for individualized learning which is often based on interactive learning objects. This allows learners to be uniquely identified, content to be specifically personalized, and, as a result, a learner’s progress can be monitored, supported, and assessed. While a range of technological solutions for the development of integrated e-learning environments already exists, the most appropriate solutions require further improvement on implementation of novel learning objects, unification of standardization and integration of learning environments based on semantic web services (SWS) that are still in the early stages of development. This paper introduces a proprietary architectural model for distributed e-learning environments based on semantic web services (SWS), enabling the implementation of a successive learning process by developing innovative learning objects based on modern learning methods. A successful technical implementation of our approach in the environment of Kaunas University of Technology is further detailed and evaluated.

Generational Learners & E-Learning Technologies

2010 ◽  
pp. 76-92 ◽  
Author(s):  
Ke Zhang ◽  
Curtis J. Bonk
Keyword(s):  
Learning Preferences ◽  
Learning Technologies ◽  
Learning Design ◽  
Learner Characteristics ◽  
Attitudes Towards Technology ◽  
E Learning ◽  
Practical Implications

This chapter reviews the characteristics of learners of different generations. In particular, it compares their differences in terms of learning preferences as well as their typical skills and attitudes towards technology in e-learning. In addition, it discusses the impacts of these shared and varied learner characteristics on e-learning and provides suggestions and recommendations on how to address generational learning diversity in e-learning design and delivery. In responding to the emerging learning technologies, this chapter specifically analyzes generational learners’ preferences and characteristics regarding learning technologies, and the practical implications for designers and educators working on e-learning for highly diversified audiences representing various generations.

A Review of Emerging Technological Trends in E-Learning

2011 ◽  
pp. 729-740
Author(s):  
Furkan Tari
Keyword(s):  
Information Technology ◽  
Semantic Web ◽  
Learning Outcomes ◽  
Learning Process ◽  
Learning Outcome ◽  
Learning Technologies ◽  
Web Content ◽  
Holistic View ◽  
Behavioral Issues ◽  
E Learning

Advances in information technology and the redefined web trigger a holistic view of learning process. The objective of this study is to provide a conceptual view of how various technologies can be used to maximize learning outcomes through e-learning. Among the trends investigated in this study are, XML and semantic Web, content-based video indexing, personalized, intelligent Web tutoring, and m-learning. In addition to these technologies, a brief review of some of the key behavioral issues is presented. For researchers and developers interested in maximizing the learning outcome through e-learning technologies, the paper provides a taxonomy of these trends along with a framework for future designs.

A Semantic Web Service Architecture for Learing Object Repositories

2011 ◽  
pp. 141-158 ◽  
Author(s):  
José-Manuel Lopez-Cobo ◽  
Sinuhé Arroyo ◽  
Miguel-Angel Sicilia ◽  
Salvador Sanchez
Keyword(s):  
Semantic Web ◽  
Web Service ◽  
Learning Objects ◽  
Learning Object ◽  
Learning Technology ◽  
Computational Semantics ◽  
Semantic Web Service ◽  
Service Architecture ◽  
Develop Technology ◽  
Definition Of

The evolution of learning technology standards has resulted in a degree of interoperability across systems that enable the interchange of learning contents and activities. Nonetheless, learning resource metadata does not provide formal computational semantics, which hampers the possibilities to develop technology that automates tasks like learning object selection and negotiation. In this paper, the provision of computational semantics to metadata is addressed from the perspective of the concept of Semantic Web service. An architecture based on the specifications of the WSMO project is described, including the definition of an ontology for learning object metadata, and issues of mediation, all under the perspective of the learning object repository as the central entity in learning object reuse scenarios. The resulting framework serves as a foundation for advanced implementations that consider formal metadata semantics as a mechanism for the automation of tasks related to the interchange of learning objects.

M-Learning through Semantically Annotated Learning Objects and Ontologies

2015 ◽  
Vol 3 (2) ◽  
Author(s):  
Reshmy Krishnan
Keyword(s):  
Semantic Web ◽  
Learning Process ◽  
Rapid Development ◽  
Learning Objects ◽  
Learning System ◽  
Learning Object ◽  
Mobile Technologies ◽  
Rich Medium ◽  
Object Structure ◽  
E Learning

Number of mobile subscriptions has increased tremendously due to rapid development of mobile technologies. The performance and accessibility of the e-learning process can be enhanced through mobile devices which is called m-learning. M-learning makes learning resources available anywhere and anytime, provide strong search capabilities, and offers easy interaction features to the learners. M-learning also points the opportunity for interoperability than existing e-learning system. The integration of semantic web in m-learning can improve the efficiency of searching for learning objects and reduce the time and cost of learning process. Semantic web can be integrated with the help of ontologies and learning objects in semantic web. They offer rich medium to assist m-learning via semantic annotated learning objects and shared repositories. Two types of ontologies, such as learning object content ontology and learning object structure ontology are used in this system. These ontologies facilitate the reuse, sharing and retrieval of relevant learning objects which are the backbone of m-learning.

SWELS

2010 ◽  
pp. 120-145
Author(s):  
Gianluca Elia ◽  
Giustina Secundo ◽  
Cesare Taurino
Keyword(s):  
Semantic Web ◽  
Learning Environments ◽  
First Generation ◽  
Learning Technologies ◽  
Learning Systems ◽  
Learning System ◽  
E Learning ◽  
Distance Learning Technologies ◽  
Traditional Approaches ◽  
New Generation

This chapter presents a prototypal e-learning system based on the Semantic Web paradigm, called SWELS (Semantic Web E-Learning System). The chapter starts by introducing e-learning as an efficient and just-in-time tool supporting the learning processes. Then a brief description of the evolution of distance learning technologies will be provided, starting from first generation e-learning systems through the current Virtual Learning Environments and Managed Learning Environments, by underling the main differences between them and the need to introduce standards for e-learning with which to manage and overcome problems related to learning content personalization and updating. Furthermore, some limits of the traditional approaches and technologies for e-learning will be provided, by proposing the Semantic Web as an efficient and effective tool for implementing new generation e-Learning systems. In the last section of the chapter, the SWELS system is proposed by describing the methodology adopted for organizing and modeling its knowledge base, by illustrating its main functionalities, and by providing the design of the tool followed by the implementation choices. Finally, future developments of SWELS will be presented, together with some remarks regarding the benefits for the final user in using such system.

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.

An Adaptive e-learning Platform for Personalized Course Generation

2008 ◽  
pp. 262-282 ◽  
Author(s):  
Enver Sangineto
Keyword(s):  
Learning Styles ◽  
Learning Objects ◽  
Learning Preferences ◽  
Domain Specific ◽  
Learning Platform ◽  
E Learning ◽  
Funded Project ◽  
Learning Platforms ◽  
Didactic Material ◽  
Methodological Aspects

In this chapter we show the technical and methodological aspects of an e-learning platform for automatic course personalization built during the European funded project Diogene. The system we propose is composed of different knowledge modules and some inference tools. The knowledge modules represent the system’s information about both the domain-specific didactic material and the student model. By exploiting such information the system automatically builds courses whose didactic material is customized to meet the current student’s degree of knowledge and her/his learning preferences. Concerning the latter, we have adopted the Felder and Silverman’s pedagogical approach in order to match the student’s learning styles with the system Learning Objects’ types. Finally, we take care to describe the system’s didactic material by means of some present standards for e-learning in order to allow knowledge sharing with other e-learning platforms and knowledge searching by means of possible Semantic Web information retrieval facilities.

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.

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