scholarly journals An E-learning System Architecture Based on Web Services and Intelligent Agents

2009 ◽  
Author(s):  
Xu Wei ◽  
Jun Yan
Keyword(s):  
Web Services ◽  
System Architecture ◽  
Intelligent Agents ◽  
Learning System ◽  
Learning System Architecture ◽  
E Learning

MULTI‐LAYERED KNOWLEDGE‐BASED ARCHITECTURE OF THE ADAPTABLE DISTANCE LEARNING SYSTEM

2009 ◽  
Vol 15 (2) ◽  
pp. 229-244 ◽  
Author(s):  
Dalė Dzemydienė ◽  
Lina Tankelevičienė
Keyword(s):  
Distance Learning ◽  
Intelligent Agents ◽  
Research Work ◽  
Learning System ◽  
Conceptual Approach ◽  
Knowledge Based ◽  
Distance Learning System ◽  
Learning System Architecture ◽  
Service Oriented ◽  
E Learning

The quality of the distance learning courses is largely influenced by competently prepared educational resources and an effective study support system. One of the possible ways to improve distance learning infrastructure and increase its effectiveness is to extend the architecture of present e‐learning systems by the components for adaptable and sustainable learning. This research work is devoted to developing the service‐oriented distance learning environment adaptable to the user's needs. The proposed adaptable communication environment of distance learning is constructed by integration of new components of communication scenarios generation, adaptable for student's goals, multilayered domain ontology of learning subject and forming intelligent agents’ framework possible. The paper presents the knowledge‐based component architecture of the distance learning system, which enables a better adaptation of learning resources to students. The paper analyses the possibilities of integrating ontology into the e‐learning system. The issues of decomposing ontology into different levels of understanding are discussed in order to adapt to learner's tasks and goals. A conceptual approach is proposed for extending the existing distance learning system architecture by intelligent and deeper knowledge layers. Santrauka Nuotolinių studijų kokybė daugiausia priklauso nuo kompetentingai parengtų mokomųjų priemonių ir veiksmingai veikiančios studijų paramos sistemos. Ieškant priemonių, kaip pagerinti nuotolinių studijų sistemos infrastruktūrą ir padidinti jos darbo efektyvumą, nagrinėjamos galimybės praplėsti tradicinės nuotolinio mokymo sistemos architektūrą komponentėmis, kurios leistų išplėtoti adaptuotą ir darnų mokymosi procesą. Šio tyrimo uždaviniai skirti paslaugoms, skirtoms išvystyti nuotolinio mokymo aplinką. Siekiant sukurti tinkamą kompiuterizuotą bendradarbiavimo aplinką, lanksčiai prisitaikoma prie kintančių vartotojo poreikių studijų procese. Architektūra projektuojama integruojant naujas komponentes bendravimo scenarijams generuoti, daugelio lygių dalykinės srities ontologijai naudoti ir sudarant sąlygas automatizuotam intelektinių agentų bendravimui. Straipsnyje nagrinėjamos galimybės integruoti dalykinės srities ontologiją į tradicinės nuotolinio mokymo sistemos aplinką. Ontologijos detalizavimo pagal studento supratimo lygmenis klausimai nagrinėjami siekiant pateikti koncepcinį tokios nuotolinės adaptuotos sistemos darbo modelį.

scholarly journals ARTIFICIAL INTELLIGENCE INFLUENCE IN EDUCATION 4.0 TO ARCHITECTURE CLOUD BASED E-LEARNING SYSTEM

2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Purwono Hendradi
Keyword(s):  
System Architecture ◽  
Learning System ◽  
Application Layer ◽  
Artificial Intelligent ◽  
Business Application ◽  
Learning System Architecture ◽  
E Learning ◽  
Education Today ◽  
System Architecture Design

Business Application Layer in the Architecture of E-learning cloud is an important part, because it is the part that differentiates it from the application of cloud in other fields. The development of education today recognizes the term Education 4.0 which is an adaptation of the Industrial era 4.0 where in this era the role of Artificial Intelligent is important. In this paper the author will review a part of the cloud-based architecture of E-Learning which will correspond with Education 4.0. The aim will be to produce a Cloud-Based E-learning system Architecture design that can be used as a guideline in the direction of Education 4.0.

scholarly journals Personalized E-Learning System Architecture Using Data Mining Approach

2018 ◽  
Author(s):  
Samina Kausar ◽  
Huahu Xu ◽  
Iftikhar Hussain ◽  
Wenhau Zhu ◽  
Misha Zahid
Keyword(s):  
Data Mining ◽  
System Architecture ◽  
Educational Data Mining ◽  
Learning System ◽  
Data Mining Techniques ◽  
Learning Capabilities ◽  
Learning System Architecture ◽  
E Learning ◽  
Hidden Patterns ◽  
Using Data

Educational data mining is an emerging discipline that focuses on development of self-learning and adaptive methods. It is used for finding hidden patterns or intrinsic structures of educational data. In the field of education, the heterogeneous data is involved and continuously growing in the paradigm of big data. To extract meaningful knowledge adaptively from big educational data, some specific data mining techniques are needed. This paper presents a personalized e-learning system architecture which detects and responds teaching contents according to the students’ learning capabilities. Furthermore, the clustering approach is also presented to partition the students into different groups based on their learning behavior. The primary objective includes the discovery of optimal settings, in which learners can improve their learning capabilities to boost up their outcomes. Moreover, the administration can find essential hidden patterns to bring the effective reforms in the existing system. The various clustering methods K-means, Clustering by Fast Search and Finding of Density Peaks (CFSFDP), and CFSFDP via Heat Diffusion (CFSFDP-HD) are also analyzed using educational data mining. It is observed that more robust results can be achieved by the replacement of K-means with CFSFDP and CFSFDP-HD. The proposed e-learning system using data mining techniques is vigorous compared to typical e-learning systems. The data mining techniques are equally effective to analyze the big data to make education systems robust.

scholarly journals Gamification of learning activities with the Odin service

2016 ◽  
Vol 13 (3) ◽  
pp. 809-826 ◽  
Author(s):  
José Paiva ◽  
José Leal ◽  
Ricardo Queirós
Keyword(s):  
Formative Assessment ◽  
System Architecture ◽  
Management System ◽  
Learning System ◽  
Learning Activities ◽  
Learning Tools ◽  
Hybrid Courses ◽  
Learning Game ◽  
Learning System Architecture ◽  
E Learning

Existing gamification services have features that preclude their use by e-learning tools. Odin is a gamification service that mimics the API of state-of-theart services without these limitations. This paper presents Odin as a gamification service for learning activities, describes its role in an e-learning system architecture requiring gamification, and details its implementation. The validation of Odin involved the creation of a small e-learning game, integrated in a Learning Management System (LMS) using the Learning Tools Interoperability (LTI) specification. Odin was also integrated in an e-learning tool that provides formative assessment in online and hybrid courses in an adaptive and engaging way.

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.

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