scholarly journals Creating an Advanced Web Based Environment using Semantic Web

2017 ◽  
pp. 38-44 ◽  
Author(s):  
Panchajanyeswari M Achar
Keyword(s):  
Learning Environment ◽  
Learning Objects ◽  
Learning Systems ◽  
Personalized Recommendation ◽  
Learning Material ◽  
Web Based ◽  
Learning Content ◽  
User Query ◽  
E Learning ◽  
Learner Profile

E-learning systems are of no help to the users if there are no powerful search engines and browsing tools to assist them. Most of the current web-based learning systems are closed systems where the courses and the learning material are fixed. The only thing that is dynamic is that the organization of the learning content is adapted to allow individualized learning environment. The learners of web-based e-learning systems belong to different categories based on their skills, background, preferences and learning styles. This paper focuses on personalized semantic search and recommending learning content that are appropriate to the learning environment. The semantic and personalized search of the learning content is based on comparison of the learner profile. The learner profile depends on re individual learning style of the user and learning objects’ metadata. This concept needs to be represented both in the learner profile as well as learning object description as certain data structures. Personalized recommendation of learning objects uses an approach to determine a more suitable relationship between learning objects and learning profiles. Thus, it may advise a learner with most suitable learning objects. Semantic learning objects search is based on the query expansion of the user query and by using the semantic similarity to retrieve semantic matched learning objects.

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

Securing the Infrastructure for Service-Based E-Learning Environments

2011 ◽  
pp. 1-24
Author(s):  
Simon Schwingel ◽  
Gottfried Vossen ◽  
Peter Westerkamp
Keyword(s):  
Web Services ◽  
Learning Environment ◽  
Learning Environments ◽  
User Authentication ◽  
Learning Objects ◽  
Learning System ◽  
Learning Material ◽  
Single Sign On ◽  
User Data ◽  
E Learning

E-learning environments and their system functionalities resemble one another to a large extent. Recent standardization efforts in e-learning concentrate on the reuse of learning material only, but not on the reuse of application or system functionalities. The LearnServe system, under development at the University of Muenster, builds on the assumption that a typical learning system is a collection of activities or processes that interact with learners and suitably chosen content, the latter in the form of learning objects. This enables us to divide the main functionality of an e-learning system into a number of stand-alone applications or services. The realization of these applications based on the emerging technical paradigm of Web services then renders a wide reuse of functionality possible, thereby giving learners a higher flexibility of choosing content and functionalities to be included in their learning environment. In such a scenario, it must be possible to maintain user identity and data across service and server boundaries. This chapter presents an architecture for implementing user authentication and the manipulation of user data across several Web services. In particular, it demonstrates how to exploit the SPML and SAML standards so that cross-domain single sign-on can be offered to the users of a service-based learning environment. The chapter also discusses how this is being integrated into LearnServe.

The DEKOR System

2011 ◽  
pp. 164-186 ◽  
Author(s):  
Christian Gütl ◽  
Victor Manuel García-Barrios
Keyword(s):  
Learning Environment ◽  
Learning Styles ◽  
Educational Systems ◽  
Learning Material ◽  
Learner Characteristics ◽  
Web Based ◽  
Learning Content ◽  
Support Students

Due to the wide diversity of learning styles and learner characteristics, delivering learning material from modern ICT-based learning must also be conducted in a diverse manner rather than with a “one-fitsall” approach. By focusing on content aspects, the majority of adaptive Web-based educational systems are only able to deal with closed repositories and therefore only pre-defined content alternatives for limited learner characteristics are manageable. One possible solution is to enable and technologically support students’ freedom to select appropriate learning content of their own choice. The WWW as an extensive repository of diverse content has gained considerable interest as an open-ended learning environment, but most students cannot cope well with such open accessibility. To overcome this, the authors have started research towards a system of personalized access to open repositories. In this book chapter, they introduce the evolution of their linked approaches and discuss the findings in the context of learner characteristics.

scholarly journals Design and Implementation of Adaptive Recommendation System

2018 ◽  
pp. 101-117
Author(s):  
MagedEla zony ◽  
Ahmed Khalifa ◽  
Sayed Nouh ◽  
Mohamed Hussein
Keyword(s):  
Semantic Web ◽  
Semantic Similarity ◽  
Recommendation System ◽  
Learning Objects ◽  
Just In Time ◽  
Web Based ◽  
Design And Implementation ◽  
Knowledge Based ◽  
E Learning ◽  
Learner Profile

E-learning offers advantages for E-learners by making access to learning objects at any time or place, very fast, just-in-time and relevance. However, with the rapid increase of learning objects and it is syntactically structured it will be time-consuming to find contents they really need to study.In this paper, we design and implementation of knowledge-based industrial reusable, interactive web-based training and use semantic web based e-learning to deliver learning contents to the learner in flexible, interactive, and adaptive way. The semantic and recommendation and personalized search of Learning objects is based on the comparison of the learner profile and learning objects to determine a more suitable relationship between learning objects and learner profiles. Therefore, it will advise the e-learner with most suitable learning objects using the semantic similarity.

scholarly journals ANALISIS DAN EVALUASI REKOMENDASI E-LEARNING BERBASIS OPEN SOURCE (STUDI KASUS: SMKN XYZ BANDUNG)

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
Arief Samuel Gunawan ◽  
Herastia Maharani ◽  
Karen K Tatuh
Keyword(s):  
Open Source ◽  
Online Discussion ◽  
Learning Systems ◽  
Learning System ◽  
Learning Activities ◽  
Learning Material ◽  
Web Based ◽  
Analysis And Evaluation ◽  
System Recommendation ◽  
E Learning

SMKN XYZ is a vocational institution located in Bandung. In performing learning activities, SMKN XYZ implemented e-learning systems, namely Edmodo and school website, to complement and support daily learning activities. E-learning system is used as a solution when teachers could not attend the class. But in reality, it was found that both Edmodo and school website have relatively similar features and functions in use. Furthermore, it was found from interviews and questionnaire results that both existing applications were lacking of several necessary features such as chatting and math equation features. Therefore, an analysis and evaluation of e-learning system recommendation will be conducted in this research. There are 5 main requirements of SMKN XYZ regarding e-learning implementation, which were found from the interviews and questionnaire, namely learning material online sharing, online discussion, online assignment, online quiz and online announcement. Moodle is a web-based open source e-learning application. Using Moodle could support online learning activities and meet the 5 main requirements of SMKN XYZ, by providing features such as access to learning materials, assignment, quiz, discussion and other important informations, including chatting and math equation features which were not available in Edmodo and school website.

Improving Personalization In E-Learning Systems

2014 ◽  
Vol 4 (2) ◽  
pp. 75-84
Author(s):  
Assma Bezza ◽  
Amar Balla ◽  
Farhi Marir
Keyword(s):  
Knowledge Management ◽  
Ad Hoc ◽  
Research Work ◽  
User Profile ◽  
Learning Systems ◽  
Learning Content ◽  
E Learning ◽  
Learner Profile ◽  
Knowledge Content ◽  
User Intervention

Individual learners have different requirements and characteristics, and as a result learning content should be able to be personalized and adaptable to the e-learner' profile. Little research work undertaken to tackle this issue, and it has been limited to ad-hoc work on personalizing, and adapting learning content in e-Learning. This paper presents two methods for modeling user profile and for personalizing and adapting a given content to match that profile: inductive (without user intervention) and deductive (with user intervention). These methods will be used as a base to review and classify research work undertaken on personalizing content in the domain of knowledge management and e-learning systems. Based on these reviews, especially those undertaken in personalizing knowledge content in knowledge management systems, the paper proposes a comprehensive approach for personalizing learning content.

Learning Object Model for Online Laboratories

2011 ◽  
pp. 514-527
Author(s):  
Habib Mir M. Hosseini ◽  
Keck Voon Ling ◽  
Bing Duan
Keyword(s):  
Learning Objects ◽  
Learning Systems ◽  
Learning Object ◽  
Object Model ◽  
Web Based ◽  
Course Content ◽  
Online Laboratories ◽  
E Learning ◽  
Text Images ◽  
Learning Concept

Online learning environments provide the students access to the course content at any time and from anywhere. Most of the existing e-Learning systems are designed for content-based subjects that deliver course content such as text, images, video, audio, and simulation to the student through the Internet. In recent years, several online or remote laboratories have been developed to bring the e-Learning concept to the lab-based courses. These systems, mainly web-based, allow students to conduct real laboratory experiment, as opposed to computer simulations, from anywhere and at any time. In this chapter, we introduce a model for providing lab-based lessons as Learning Objects. The Learning Object model has been widely used in content-based e-Learning systems. We then propose a learning management system framework which helps students to remotely access the lab-based learning objects. We will also present some experimental results and implementations.

Towards Best Practices in Web-Based Learning and Teaching

2016 ◽  
pp. 317-332
Author(s):  
Mercy A. Iroaganachi
Keyword(s):  
Best Practices ◽  
Learning Environment ◽  
Learning Styles ◽  
Learning Style ◽  
Learning Objects ◽  
Web Based ◽  
Learning And Teaching ◽  
Web Based Learning ◽  
E Learning ◽  
Level Of Knowledge

The chapter explored best practices in web-based learning and teaching with a view to discover trends and provide valuable information for all in the e-learning environment. It affirms that paradigms in Web-based education have shifted from teacher-centered to learner-centered but basically it remains synchronous or asynchronous. This requires Learning Objects (LOs) to be pedagogically efficient, designed to standard (Multimodal) with designers bearing in mind the varied population and learning styles. LOs are to be personalized thereby creating adaptive content based on learner's abilities, learning style, level of knowledge and preferences. It is recommended that educators have requisite background knowledge and competencies in technology such as hardware, software, and course management systems etcetera. Instructors, designers and all interested persons should consult a checklist of best practices, for assessing learning object repositories. More so, there is need to incorporate hands-on component into the e-learning environment. The chapter provides Indicators for best practices.

Learning Object Model for Online Laboratories

2011 ◽  
pp. 768-784 ◽  
Author(s):  
Habib Mir M. Hosseini ◽  
Keck Voon Ling ◽  
Bing Duan
Keyword(s):  
Learning Objects ◽  
Learning Systems ◽  
Learning Object ◽  
Object Model ◽  
Web Based ◽  
Course Content ◽  
Online Laboratories ◽  
E Learning ◽  
Text Images ◽  
Learning Concept

Online learning environments provide the students access to the course content at any time and from anywhere. Most of the existing e-Learning systems are designed for content-based subjects that deliver course content such as text, images, video, audio, and simulation to the student through the Internet. In recent years, several online or remote laboratories have been developed to bring the e-Learning concept to the lab-based courses. These systems, mainly web-based, allow students to conduct real laboratory experiment, as opposed to computer simulations, from anywhere and at any time. In this chapter, we introduce a model for providing lab-based lessons as Learning Objects. The Learning Object model has been widely used in content-based e-Learning systems. We then propose a learning management system framework which helps students to remotely access the lab-based learning objects. We will also present some experimental results and implementations.

scholarly journals CrowdLearn: Crowd-sourcing the Creation of Highly-structured E-Learning Content

2015 ◽  
Vol 5 (4) ◽  
pp. 47 ◽  
Author(s):  
Darya Tarasowa ◽  
Ali Khalili ◽  
Soeren Auer
Keyword(s):  
Data Model ◽  
Content Management ◽  
Learning Objects ◽  
Learning Material ◽  
Crowd Sourcing ◽  
Assessment Tests ◽  
Learning Content ◽  
E Learning ◽  
The Creation ◽  
Entity Relationship

While nowadays there is a plethora of Learning Content Management Systems, the collaborative, community-based creation of rich e-learning content is still not sufficiently well supported. Few attempts have been made to apply crowd-sourcing and wiki-approaches for the creation of e-learning content. However, the paradigm is only applied to unstructured, textual content and cannot be used in SCORM-compliant systems. To address this issue we developed the CrowdLearn concept to exploit the wisdom, creativity and productivity of the crowd for the creation of rich, deep-semantically structured e-learning content. The CrowdLearn concept combines the wiki style for collaborative content authoring with SCORM requirements for re-usability. Therefore, it enables splitting the learning material into Learning Objects (LOs) with an adjustable level of granularity. In order to realize the CrowdLearn concept, a novel data model called WikiApp is devised. The WikiApp data model is a refinement of the traditional entity-relationship data model with further emphasis on collaborative social activities and structured content authoring. We implement and evaluate the CrowdLearn approach with SlideWiki – an educational platform dealing with presentations and assessment tests. The article also comprises results of a usability evaluation with real students.

Sign in / Sign up

Export Citation Format

Share Document