E-learning System Architecture Research Articles

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

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.

Cloud Computing-Based E-Learning System Architecture in Education 4.0

E-learning architecture based on Cloud Computing is an implementation of the E-learning System by utilizing the benefits of Cloud Computing. Furthermore, the E-learning system will experience a change with the emergence of the Education 4.0 era which is an adaptation of the development of Industry 4.0. Therefore the writer try to review the architecture of the e-learning system based on cloud computing in relation to Education 4.0 era. In this paper, the authors propose a concept of cloud computing-based e-learning system architecture at Education 4.0. The aim is to produce architecture that can be used as a guideline in developing cloud computing-based e-learning systems that answer the needs of Education 4.0. For this reason, in this paper, the author reviews the papers that review the architecture of cloud-based e-learning systems and also papers on Education 4.0.

Integration of Data Mining Clustering Approach in the Personalized E-Learning System

Educational data-mining is an evolving discipline that focuses on the improvement of self-learning and adaptive methods. It is used for finding hidden patterns or intrinsic structures of educational data. In the arena of education, the heterogeneous data is involving and continuously growing in the paradigm of big-data. To extract meaningful information adaptively from big educational data, some specific data mining techniques are needed. This paper presents a clustering approach to partition students into different groups or clusters based on their learning behavior. Furthermore, the personalized e-learning system architecture is presented, which detects and responds to teaching contents according to the students’ learning capabilities. The primary objective includes the discovery of optimal settings, in which the learners can improve their learning capabilities. Moreover, the administration can find essential hidden patterns to bring the effective reforms in the existing system. The clustering methods K-Means, K-Medoids, Density-based Spatial Clustering of Applications with Noise, Agglomerative Hierarchical Cluster Tree and Clustering by Fast Search and Finding of Density Peaks via Heat Diffusion (CFSFDP-HD) are analyzed using educational data mining. It has been observed that more robust results can be achieved by the replacement of existing methods with CFSFDP-HD. The data mining techniques are equally effective in analyzing the big data to make education systems vigorous.

Smart E-Learning System Architecture based on Cloud Computing

With the advent of new technologies, companies and academic institutions are striving to keep pace with the advancement in Information and Communication Technologies and to streamline the way to manage or upgrade their IT resources. Cloud Computing provides an alternative solution to achieve these objectives within budget. A number of colleges and universities all over the world are implementing cloud infrastructure to reduce the IT operational cost and increasing the effectiveness and convenience of educational services. Cloud computing can play an important role in the education sector in providing ubiquitous access (anytime, anywhere, independent of device) to the learning material. This approach provides a new way to design and manage IT resources in an efficient manner not only by increasing the user’s productivity and hardware utilization but also decreasing infrastructure cost through virtualization. This research paper presents a smart e-learning system based on cloud platform in delivering and sharing e-learning resources. The authors also discuss the features of the smart E-Learning system over the traditional system and propose architecture of smart e-learning system for the education institutions.

An Adaptable E-Learning Architecture Based on Learners' Profiling

These days modifications and supplements to e-learning are not enough to make them successful since flexibility and adaptability is missing. Different e- Learning architecture provide different kinds of learning experience to the learners. The lack of adaptive system is due to ―One size fits for all‖ concept. Currently the research is towards to learner oriented platforms putting student motivation, habits, expectations and learning styles (additional Koper, R.; Burgos, D (2005)). The concept of adaptation has become a prominent issue in e- learning. Systems allow the users to change some system parameters and adapt their behavior accordingly is known as adaption process. Systems that adapt based on the systems assumption are called as adaptive systems (additional santally mohammed issack). Since the system adapts to a person and personalizes the learning process it can be also known as personalized system (additional Paramythis, A.; Loidl-Reisinger). So to serve the learning community better there was a necessity to profile them and identify their requirements and provide an adaptive e- learning architecture which suits the individuals needs better. So the main objective of this research was to provide an adaptive e-learning system architecture which satisfies Felder Silverman learning style. Felder- Silverman's learning model (FSLM) was chosen since FSLM synthesis of these theories can be designed to easily translate them into strategies into a university setup. Index Terms—Learning, e-Learning, Virtual Learning, e- Learning Standards, Adaptive e-learning systems.

E-Learning And Instructional Management System Based On Local Computer Networks And Internet

This article describes the educational efforts invested at Wasit University (WU), in Wasit, Iraq, in order to make WU the first university in that country to implement campus-wide e-learning, which is essential for any country aiming for progress through the essential goal of “Education For All”; e-learning being economic, far-reaching, and relatively simple to implement. These efforts have materialized in an integral e-system that performs and manages a complete educational process that can be used by any educational organization (schools, colleges, or continuing education centers) in a highly flexible, reliable, and secure manner. The e-learning management system architecture consists of three layers: user’s interface layer, middle layer, and server layer. The user interface layer is composed of four modules: user interface module, teacher module, student module, and administrator module. Each module has several sub-modules that are described in detail throughout the paper. Our proposed e-learning system has been successfully tested on some courses in the Electrical Engineering Department at WU. Our primary objective is to implement it department-wide, evaluate it, and refine it. Once satisfactory and efficient, the goal is to expand its use throughout WU, and eventually to all other institutions of learning in Iraq.

E-learning system design with the focus on knowledge flows and learning objects

The aim of the paper is to propose an e-learning system architecture integrating knowledge flows. Our motivation is to provide the user with some intelligent possibilities of the learning environment used. This could be fulfilled using knowledge management at the operational level. Knowledge management should be a fundamental objective of any educational institution, as learning is its core function and should be reflected in how the organisation operates. In the academia environment, knowledge management and e-learning represent a substantial tuple for distance form of education. For e-learning method, heterogeneous and distributed architecture is one of the most prominent features. In a learning environment, different kinds of information resources are shared. Its demands can be fulfilled by means of local intelligence using multi-agent systems. This paper presents a layered multi-agent architecture of e-learning system including basics of its implementation. Learning objects and learning objects repositories are used for facilitating intended learning outcomes, and can be extracted and reused in other learning environments. Agent structure, general framework and workflow were designed in order to simplify information and knowledge flows with the aim to keep system overhead as low as possible.

PELS: A Noble Architecture and Framework for a Personal E-Learning System (PELS)

This article presents a personal e-learning system architecture in the context of a social network environment. The main objective of a personal e-learning system is to develop individual skills on a specific subject and share resources with peers. The authors' system architecture defines the organisation and management of a personal learning environment that aids in creating, verifying and sharing learning artefacts, and making money at the same time. In their research, they also focus on one of the most interesting arenas in digital content or document management – digital rights management – and its application to e-learning.

Security and Privacy Preservation for Mobile E-Learning via Digital Identity Attributes

This paper systematically discusses the security and privacy concerns for e-learning systems. A five-layer architecture of e-learning system is proposed. The security and privacy concerns are addressed respectively for five layers. This paper further examines the relationship among the security & privacy policy, the available security & privacy technology, and the degree of e-learning privacy & security. The digital identity attributes are introduced to e- learning portable devices to enhance the security and privacy of e-learning systems. This will provide significant contributions to the knowledge of e-learning security & privacy research communities and will generate more research interests.

EduComponents

We present the eduComponents, a component-based approach to e-learning system architecture. In contrast to typical "integrated" platforms, the eduComponents are implemented as extension modules for a general-purpose content management system (CMS). The components can be used individually, together, and in combination with other modules. The use of a general-purpose (i.e., note-learning-specific) CMS means that a single platform can be used for e-learning and other Web content, providing the advantages of a uniform user interface, reduced system administration overhead, and extensive code reuse.

An Architecture for Online Laboratory E-Learning System

Internet-based learning systems, or e-learning, are widely available in institutes, universities, and industrial companies, hosting regular or continuous education programs. The dream of teaching and learning from anywhere and at anytime becomes a reality due to the construction of e-learning infrastructure. Traditional teaching materials and methods are shifting to the new paradigm. In higher education, laboratory work is playing an important role in the area of training students and helping students to absorb more knowledge. With the goal of bringing e-learning to the traditional laboratory experiment, in this article, we present an architecture for an online laboratory e-learning system to facilitate the design and deployment of lab-based courses for e-education. The article provides an overall view of the system design and implementation so the Internet-based laboratory can be easily integrated with the e-learning infrastructure.

Process-oriented e-learning architecture in supporting mastery learning

Instructional strategy plays a prominent role in traditional classrooms, but it is not widely noticed in e-learning environments. This study adopts the widespread pedagogical method of mastery learning and proposes an e-learning system architecture that considers the concept of process management and applications of mobile device. This study also offers several scenarios to explain how to use this kind of system. The proposed system could assist teachers to manage their students more easily and it can streamline the teaching processes. It could also make personalised teaching more popular and easier.