IMS Compliant Ontological Learner Model for Adaptive E-Learning Environments

It has been proven that adopting the “one size fits one” approach has better learning outcomes than the “one size fits all” one. A customized learning experience is attainable with the use of learner models, the main source of variability, in adaptive educational hypermedia systems or any intelligent learning environment. While such a model includes a large number of characteristics which can be difficult to incorporate and use, several standards that were developed to overcome these complexities. In this paper, the proposed work intents to improve learner’s model representation to meet the requirements and needs of adaptation. We took IMS-LIP, IMS-ACCLIP and IMS-RDCEO standards into consideration and incorporated their characteristics to our proposed learner model so that it conforms to international standards. Moreover, the suggested learner model takes advantage of the semantic web technologies that offer a better data organization, indexing and management and ensures the reusability, the interoperability and the extensibility of this model. Furthermore, due to the use of ontologies, the metadata about a learner can be used by a wide range of personalization techniques to provide more accurate customization.

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A Cloud-Based Learning Platform

Advances in Educational Technologies and Instructional Design - Handbook of Research on Cloud-Based STEM Education for Improved Learning Outcomes ◽

10.4018/978-1-4666-9924-3.ch008 ◽

2016 ◽

pp. 106-122 ◽

Cited By ~ 3

Author(s):

Rocael Hernandez Rizzardini ◽

Christian Gütl

Keyword(s):

Web 2.0 ◽

Web Application ◽

Learning Experience ◽

Semantic Web Technologies ◽

Web 2.0 Tools ◽

Web Technologies ◽

Massive Open Online Course ◽

Learning Platform ◽

Wide Range ◽

Application Programming

A wide range of innovative Web 2.0 tools can be used for STEM education; however, learning orchestration issues arise in terms of management, adaption, and intervention. These issues can be solved through the manipulation of the tools' Web application programming interfaces (APIs) in order to orchestrate the learning experience. In this chapter, the authors present a learning platform that is capable of orchestrating learning activities through Web interoperability with Web 2.0 tools. This interoperability is realized through advanced Semantic Web technologies such as JSON-LD and Hydra, and a specialized architecture to automatically recognize, process, and use the tools' Web APIs. Finally, an evaluation of the architecture in a Massive Open Online Course is presented which reveals satisfactory usability and emotional evaluation results.

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Semantic Web Technologies for e-Learning: Models and Implementation

Informatica ◽

10.15388/informatica.2015.46 ◽

2015 ◽

Vol 26 (2) ◽

pp. 221-240 ◽

Cited By ~ 2

Author(s):

Valentina Dagienė ◽

Daina Gudonienė ◽

Renata Burbaitė

Keyword(s):

Semantic Web ◽

Learning Models ◽

Semantic Web Technologies ◽

Web Technologies ◽

E Learning

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Intelligent Agents for E-Learning

Intelligent Information Technologies and Applications - Advances in Intelligent Information Technologies ◽

10.4018/978-1-59904-958-8.ch002 ◽

2011 ◽

pp. 25-42

Author(s):

Ralf Bruns ◽

Jürgen Dunkel

Keyword(s):

Web Sites ◽

Intelligent Agents ◽

Domain Knowledge ◽

Multi Agent Systems ◽

Semantic Web Technologies ◽

Private Data ◽

Intelligent Software Agents ◽

E Learning ◽

The One ◽

New Generation

We propose the software architecture of a new generation of advisory systems using Intelligent Agent and Semantic Web technologies. Multi-agent systems provide a well-suited paradigm to implement negotiation processes in consultancy situations. Intelligent software agents act as clients and advisors using their knowledge in order to assist human users. In the proposed architecture the domain knowledge is semantically modeled by means of XML-based ontology languages such as OWL. Using an inference engine the agents reason on base of their knowledge to make decisions or proposals. The agent knowledge consists of different types of data: on the one hand private data, which has to be protected against unauthorized access, and on the other hand publicly accessible data spread over different web sites. Comparable to a real consultancy situation, an agent only reveals sensitive private data if it is indispensable for finding a solution. In addition, depending on the actual consultancy situation each agent dynamically expands its knowledge base by accessing OWL knowledge sources from the Internet. The usefulness of our approach is proved by the implementation of an advisory system whose objective is to develop virtual student advisers that render support to university students in order to successfully organize und perform their studies.

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Towards a Flexible Cloud Education Environment

Advances in Civil and Industrial Engineering - Handbook of Research on Applied E-Learning in Engineering and Architecture Education ◽

10.4018/978-1-4666-8803-2.ch007 ◽

2016 ◽

pp. 133-158

Author(s):

Rocael Hernandez Rizzardini ◽

Christian Gütl

Keyword(s):

Cloud Services ◽

Semantic Web Technologies ◽

Holistic Model ◽

Web 2.0 Tools ◽

Web Technologies ◽

Education Environment ◽

E Learning ◽

Definition Of ◽

And Training ◽

Semantic Definition

Web 2.0 tools offer innovative technologies for learning and training, and it exists a strong pedagogical foundation to include such tools in education. As a consequence of its more widespread usage arise issues in the context of managing these cloud services, such as to create adapted instances tool resources, to assign such resources to teachers and learners, and others. Web and educational interoperability technologies have provided initial paths toward building this type of e-Learning 3.0 cloud education environments, however, fundamental challenges remain such as granular tool resources management, and the lack of use of Semantic Web technologies to leverage automatic machine-processable tool API. To overcome these issues, an holistic model for flexible interoperability is contributed in this chapter. Covered aspects includes a semantic definition of tools' API, an interoperability service framework capable to automatically process APIs, a semantic proxy that enables usage of current APIs, and a system for learning activities orchestration using these tools. Furthermore, advanced semantic technologies to support the model for flexible interoperability are analyzed.

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Enhancing e-Learning Content by Using Semantic Web Technologies

IEEE Transactions on Learning Technologies ◽

10.1109/tlt.2016.2629475 ◽

2017 ◽

Vol 10 (4) ◽

pp. 544-550 ◽

Cited By ~ 6

Author(s):

Herminio Garcia-Gonzalez ◽

Jose Emilio Labra Gayo ◽

MPuerto Paule-Ruiz

Keyword(s):

Semantic Web ◽

Semantic Web Technologies ◽

Web Technologies ◽

Learning Content ◽

E Learning

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Applications, Methodologies, and Technologies for Linked Open Data

International Journal on Semantic Web and Information Systems ◽

10.4018/ijswis.2020070104 ◽

2020 ◽

Vol 16 (3) ◽

pp. 53-69

Author(s):

Cecilia Avila-Garzon

Keyword(s):

Semantic Web ◽

Open Data ◽

Linked Open Data ◽

Business Culture ◽

Semantic Web Technologies ◽

Web Technologies ◽

Wide Range ◽

Research And Education ◽

User Friendly ◽

Culture Education

Advances in semantic web technologies have rocketed the volume of linked data published on the web. In this regard, linked open data (LOD) has long been a topic of great interest in a wide range of fields (e.g. open government, business, culture, education, etc.). This article reports the results of a systematic literature review on LOD. 250 articles were reviewed for providing a general overview of the current applications, technologies, and methodologies for LOD. The main findings include: i) most of the studies conducted so far focus on the use of semantic web technologies and tools applied to contexts such as biology, social sciences, libraries, research, and education; ii) there is a lack of research with regard to a standardized methodology for managing LOD; and iii) a plenty of tools can be used for managing LOD, but most of them lack of user-friendly interfaces for querying datasets.

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Applying Semantic Web Technologies to Car Repairs

Web Technologies ◽

10.4018/978-1-60566-982-3.ch050 ◽

2011 ◽

pp. 924-942

Author(s):

Martin Bryan ◽

Jay Cousins

Keyword(s):

Semantic Web ◽

Single Point ◽

Online Resources ◽

Semantic Web Technologies ◽

Web Technologies ◽

European Single Market ◽

Wide Range ◽

Shared Language ◽

Information Sets ◽

Multiple Languages

Vehicle repair organizations, especially those involved in providing roadside assistance, have to be able to handle a wide range of vehicles produced by different manufacturers. Each manufacturer has its own vocabulary for describing components, faults, symptoms, etc, which is maintained in multiple languages. To search online resources to find repair information on vehicles anywhere within the European Single Market, the vocabularies used to describe different makes and models of vehicles need to be integrated. The European Commission MYCAREVENT research project brought together European vehicle manufacturers, vehicle repair organisations, diagnostic tool manufacturers and IT specialists, including Semantic Web technologists, to study how to link together the wide range of information sets they use to identify faults and repair vehicles. MYCAREVENT has shown that information sets can be integrated and accessed through a service portal by using an integrated vocabulary. The integrated vocabulary provides a ‘shared language’ for the project, a reference terminology to which the disparate terminologies of organisations participating in the project can be mapped. This lingua franca facilitates a single point of access to disparate sets of information.

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An Ontology-Based e-Learning Scenario

Methods and Applications for Advancing Distance Education Technologies ◽

10.4018/978-1-60566-342-5.ch005 ◽

2011 ◽

pp. 63-71

Author(s):

WenYing Guo

Keyword(s):

Semantic Web ◽

Relevant Information ◽

Learning System ◽

Semantic Mapping ◽

Application Domain ◽

Semantic Web Technologies ◽

Web Technologies ◽

Mapping Approach ◽

E Learning ◽

Heterogeneous Knowledge

Selecting appropriate learning services for a learner from a large number of heterogeneous knowledge sources is a complex and challenging task. This chapter illustrates and discusses how Semantic Web technologies can be applied to e-learning system to help learner in selecting appropriate learning course or retrieving relevant information. It firstly presents the main features of e-learning scenario and the ontology on which it is based; then illustrates the scenario ontology with the training domain and the application domain. Finally, it presents Semantic Querying and Semantic Mapping approach.

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