Because of the need of college education, some new methods have been adopted. One of them is e-learning system. So how to design a powerful e-learning system is the main concern of the authors. This paper first discus...Because of the need of college education, some new methods have been adopted. One of them is e-learning system. So how to design a powerful e-learning system is the main concern of the authors. This paper first discusses the EJB component mechanism and the J2EE multi-tiered model, and then applies them to an e-learning system. The J2EE framework makes the e-learning system easier be developed and be of better performance.展开更多
Currently,the majority of institutions have made use of information technologies to improve and develop their diverse educational methods to attract more learners.Through information technologies,e-learning and learni...Currently,the majority of institutions have made use of information technologies to improve and develop their diverse educational methods to attract more learners.Through information technologies,e-learning and learning-on-the go have been adopted by the institutions to provide affordability and flexibility of educational services.Most of the educational institutes are offering online teaching classes using the technologies like cloud computing,networking,etc.Educational institutes have developed their e-learning platforms for the online learning process,through this way they have paved the way for distance learning.But e-learning platform has to face a lot of security challenges in terms of cyberattacks and data hacking through unauthorized access.Fog computing is one of the new technologies that facilitate control over access to big data,as it acts as a mediator between the cloud and the user to bring services closer and reduce their latency.This report presents the use of fog computing for the development of an e-learning platform.and introduced different algorithms to secure the data and information sharing through e-learning platforms.Moreover,this report provides a comparison among RSA,AES,and ECC algorithms for fog-enabled cybersecurity systems.These Algorithms are compared by developing them using python-based language program,in terms of encryption/decryption time,key generations techniques,and other features offered.In addition,we proposed to use a hybrid cryptography system of two types of encryption algorithms such as RSA with AES to fulfill the security,file size,and latency required for the communication between the fog and the e-learning system.we tested our proposed system and highlight the pros and cons of the Integrated Encryption Schemes by performing a testbed for e-learning website scenario using ASP.net and C#.展开更多
This paper describes the implementation of the e-learning system at the School of Mathematics and Computer Science, National University of Mongolia. The paper includes in-house development of Edunet 1.0 e-learning sys...This paper describes the implementation of the e-learning system at the School of Mathematics and Computer Science, National University of Mongolia. The paper includes in-house development of Edunet 1.0 e-learning system, comparative analysis on LMS, evaluation methodology, selection of e-learning systems, and comparative analysis on implementation of Edunet, Moodle and Canvas systems.展开更多
With the advent of computing and communication technologies,it has become possible for a learner to expand his or her knowledge irrespective of the place and time.Web-based learning promotes active and independent lea...With the advent of computing and communication technologies,it has become possible for a learner to expand his or her knowledge irrespective of the place and time.Web-based learning promotes active and independent learning.Large scale e-learning platforms revolutionized the concept of studying and it also paved the way for innovative and effective teaching-learning process.This digital learning improves the quality of teaching and also promotes educational equity.However,the challenges in e-learning platforms include dissimilarities in learner’s ability and needs,lack of student motivation towards learning activities and provision for adaptive learning environment.The quality of learning can be enhanced by analyzing the online learner’s behavioral characteristics and their application of intelligent instructional strategy.It is not possible to identify the difficulties faced during the process through evaluation after the completion of e-learning course.It is thus essential for an e-learning system to include component offering adaptive control of learning and maintain user’s interest level.In this research work,a framework is proposed to analyze the behavior of online learners and motivate the students towards the learning process accordingly so as to increase the rate of learner’s objective attainment.Catering to the demands of e-learner,an intelligent model is presented in this study for e-learning system that apply supervised machine learning algorithm.An adaptive e-learning system suits every category of learner,improves the learner’s performance and paves way for offering personalized learning experiences.展开更多
Advancements in Information Communication Technology (ICT) have led to several opportunities especially the ones provided by the Internet. Several people are now taking advantage of distance learning courses and in th...Advancements in Information Communication Technology (ICT) have led to several opportunities especially the ones provided by the Internet. Several people are now taking advantage of distance learning courses and in the past few years huge research efforts have been dedicated to the development of distance learning systems. So far, many e-learning systems are proposed and used practically. This paper focused on the development of an asynchronous and interactive Web-based e-learning system. Its primary objective is to develop a fast, reliable, effective and efficient web-based e-learning system that will address the problems associated with the traditional learning system. Succinctly, the paper discusses the design of a system that enhances e-learning where course lecturers can set their courses, tests and quizzes at their convenient time and can track the activities and performance of their students and guide them to acquire knowledge without being obliged to be physically present on the institution campus. The system was designed using PHP as the scripting language, Macromedia Dreamweaver for the web page, MySQL as the database and Apache as the web server. The system was implemented using real data and the result was successful. This system is no doubt a solution to the constraints of the classical learning system and can be used successfully in distance learning, training, and various educational institutions.展开更多
To solve the irregular, poor efficiency and lowly reusable of resource, the hierarchy model of the ontology-based E-learning system is proposed. Some key techniques in the process of the project are also discussed in ...To solve the irregular, poor efficiency and lowly reusable of resource, the hierarchy model of the ontology-based E-learning system is proposed. Some key techniques in the process of the project are also discussed in this paper, such as the ontology construction, the content ontology for describing the semantics of the learning materials.展开更多
In most developing countries, governments attempt to enforce the movement from analogue to digital for all their sectors, from public to private. These technological advancements have been noted to bring necessary and...In most developing countries, governments attempt to enforce the movement from analogue to digital for all their sectors, from public to private. These technological advancements have been noted to bring necessary and unavoidable changes to businesses and learning environments. Higher learning institutions have adopted various e-learning systems to support learning, research, and publication activities to stay competitive in global academic systems. However, most public higher learning institutions in Tanzania lag behind in the adoption of these systems. Thus, research shows a failure of these institutions in utilising the full benefit that today’s Information and Communication Technology (ICT) can offer in learning environments. Thus, this study examines factors affecting the adoption of such a system in developing countries like Tanzania, taking the Institute of Accountancy Arusha (IAA) as a case study. The study used a mixed methodology where thematic and descriptive analysis was used to analyse both qualitative and quantitative research data. The study population was 187 teaching staff, a sample size of 126 was obtained, and 157 study participants were involved in the study. The study found that factors affecting the adoption of e-learning systems in public higher learning institutions in Tanzania include lack of ICT infrastructure, lack of technical and managerial support and lack of computers and e-learning knowledge among facilitators. Thus, the study recommended investments in adequate and reliable ICT facilities, high intermate speed and bandwidth, and policies that support e-learning and training programs about e-learning knowledge and use. Also, this study recommends the use of the Multi-Factors Adoption Model (MFAM11) for the successful adoption of an e-learning system in public higher learning institutions in Tanzania.展开更多
After the spread of COVID-19,e-learning systems have become crucial tools in educational systems worldwide,spanning all levels of education.This widespread use of e-learning platforms has resulted in the accumulation ...After the spread of COVID-19,e-learning systems have become crucial tools in educational systems worldwide,spanning all levels of education.This widespread use of e-learning platforms has resulted in the accumulation of vast amounts of valuable data,making it an attractive resource for predicting student performance.In this study,we aimed to predict student performance based on the analysis of data collected from the OULAD and Deeds datasets.The stacking method was employed for modeling in this research.The proposed model utilized weak learners,including nearest neighbor,decision tree,random forest,enhanced gradient,simple Bayes,and logistic regression algorithms.After a trial-and-error process,the logistic regression algorithm was selected as the final learner for the proposed model.The results of experiments with the above algorithms are reported separately for the pass and fail classes.The findings indicate that the accuracy of the proposed model on the OULAD dataset reached 98%.Overall,the proposed method improved accuracy by 4%on the OULAD dataset.展开更多
E-learning behavior data indicates several students’activities on the e-learning platform such as the number of accesses to a set of resources and number of participants in lectures.This article proposes a new analyt...E-learning behavior data indicates several students’activities on the e-learning platform such as the number of accesses to a set of resources and number of participants in lectures.This article proposes a new analytics systemto support academic evaluation for students via e-learning activities to overcome the challenges faced by traditional learning environments.The proposed e-learning analytics system includes a new deep forest model.It consists of multistage cascade random forests with minimal hyperparameters compared to traditional deep neural networks.The developed forest model can analyze each student’s activities during the use of an e-learning platform to give accurate expectations of the student’s performance before ending the semester and/or the final exam.Experiments have been conducted on the Open University Learning Analytics Dataset(OULAD)of 32,593 students.Our proposed deep model showed a competitive accuracy score of 98.0%compared to artificial intelligence-based models,such as ConvolutionalNeuralNetwork(CNN)and Long Short-TermMemory(LSTM)in previous studies.That allows academic advisors to support expected failed students significantly and improve their academic level at the right time.Consequently,the proposed analytics system can enhance the quality of educational services for students in an innovative e-learning framework.展开更多
文摘Because of the need of college education, some new methods have been adopted. One of them is e-learning system. So how to design a powerful e-learning system is the main concern of the authors. This paper first discusses the EJB component mechanism and the J2EE multi-tiered model, and then applies them to an e-learning system. The J2EE framework makes the e-learning system easier be developed and be of better performance.
基金This work was supported at Taif University by TRUSP(2020/150).
文摘Currently,the majority of institutions have made use of information technologies to improve and develop their diverse educational methods to attract more learners.Through information technologies,e-learning and learning-on-the go have been adopted by the institutions to provide affordability and flexibility of educational services.Most of the educational institutes are offering online teaching classes using the technologies like cloud computing,networking,etc.Educational institutes have developed their e-learning platforms for the online learning process,through this way they have paved the way for distance learning.But e-learning platform has to face a lot of security challenges in terms of cyberattacks and data hacking through unauthorized access.Fog computing is one of the new technologies that facilitate control over access to big data,as it acts as a mediator between the cloud and the user to bring services closer and reduce their latency.This report presents the use of fog computing for the development of an e-learning platform.and introduced different algorithms to secure the data and information sharing through e-learning platforms.Moreover,this report provides a comparison among RSA,AES,and ECC algorithms for fog-enabled cybersecurity systems.These Algorithms are compared by developing them using python-based language program,in terms of encryption/decryption time,key generations techniques,and other features offered.In addition,we proposed to use a hybrid cryptography system of two types of encryption algorithms such as RSA with AES to fulfill the security,file size,and latency required for the communication between the fog and the e-learning system.we tested our proposed system and highlight the pros and cons of the Integrated Encryption Schemes by performing a testbed for e-learning website scenario using ASP.net and C#.
文摘This paper describes the implementation of the e-learning system at the School of Mathematics and Computer Science, National University of Mongolia. The paper includes in-house development of Edunet 1.0 e-learning system, comparative analysis on LMS, evaluation methodology, selection of e-learning systems, and comparative analysis on implementation of Edunet, Moodle and Canvas systems.
文摘With the advent of computing and communication technologies,it has become possible for a learner to expand his or her knowledge irrespective of the place and time.Web-based learning promotes active and independent learning.Large scale e-learning platforms revolutionized the concept of studying and it also paved the way for innovative and effective teaching-learning process.This digital learning improves the quality of teaching and also promotes educational equity.However,the challenges in e-learning platforms include dissimilarities in learner’s ability and needs,lack of student motivation towards learning activities and provision for adaptive learning environment.The quality of learning can be enhanced by analyzing the online learner’s behavioral characteristics and their application of intelligent instructional strategy.It is not possible to identify the difficulties faced during the process through evaluation after the completion of e-learning course.It is thus essential for an e-learning system to include component offering adaptive control of learning and maintain user’s interest level.In this research work,a framework is proposed to analyze the behavior of online learners and motivate the students towards the learning process accordingly so as to increase the rate of learner’s objective attainment.Catering to the demands of e-learner,an intelligent model is presented in this study for e-learning system that apply supervised machine learning algorithm.An adaptive e-learning system suits every category of learner,improves the learner’s performance and paves way for offering personalized learning experiences.
文摘Advancements in Information Communication Technology (ICT) have led to several opportunities especially the ones provided by the Internet. Several people are now taking advantage of distance learning courses and in the past few years huge research efforts have been dedicated to the development of distance learning systems. So far, many e-learning systems are proposed and used practically. This paper focused on the development of an asynchronous and interactive Web-based e-learning system. Its primary objective is to develop a fast, reliable, effective and efficient web-based e-learning system that will address the problems associated with the traditional learning system. Succinctly, the paper discusses the design of a system that enhances e-learning where course lecturers can set their courses, tests and quizzes at their convenient time and can track the activities and performance of their students and guide them to acquire knowledge without being obliged to be physically present on the institution campus. The system was designed using PHP as the scripting language, Macromedia Dreamweaver for the web page, MySQL as the database and Apache as the web server. The system was implemented using real data and the result was successful. This system is no doubt a solution to the constraints of the classical learning system and can be used successfully in distance learning, training, and various educational institutions.
文摘To solve the irregular, poor efficiency and lowly reusable of resource, the hierarchy model of the ontology-based E-learning system is proposed. Some key techniques in the process of the project are also discussed in this paper, such as the ontology construction, the content ontology for describing the semantics of the learning materials.
文摘In most developing countries, governments attempt to enforce the movement from analogue to digital for all their sectors, from public to private. These technological advancements have been noted to bring necessary and unavoidable changes to businesses and learning environments. Higher learning institutions have adopted various e-learning systems to support learning, research, and publication activities to stay competitive in global academic systems. However, most public higher learning institutions in Tanzania lag behind in the adoption of these systems. Thus, research shows a failure of these institutions in utilising the full benefit that today’s Information and Communication Technology (ICT) can offer in learning environments. Thus, this study examines factors affecting the adoption of such a system in developing countries like Tanzania, taking the Institute of Accountancy Arusha (IAA) as a case study. The study used a mixed methodology where thematic and descriptive analysis was used to analyse both qualitative and quantitative research data. The study population was 187 teaching staff, a sample size of 126 was obtained, and 157 study participants were involved in the study. The study found that factors affecting the adoption of e-learning systems in public higher learning institutions in Tanzania include lack of ICT infrastructure, lack of technical and managerial support and lack of computers and e-learning knowledge among facilitators. Thus, the study recommended investments in adequate and reliable ICT facilities, high intermate speed and bandwidth, and policies that support e-learning and training programs about e-learning knowledge and use. Also, this study recommends the use of the Multi-Factors Adoption Model (MFAM11) for the successful adoption of an e-learning system in public higher learning institutions in Tanzania.
文摘After the spread of COVID-19,e-learning systems have become crucial tools in educational systems worldwide,spanning all levels of education.This widespread use of e-learning platforms has resulted in the accumulation of vast amounts of valuable data,making it an attractive resource for predicting student performance.In this study,we aimed to predict student performance based on the analysis of data collected from the OULAD and Deeds datasets.The stacking method was employed for modeling in this research.The proposed model utilized weak learners,including nearest neighbor,decision tree,random forest,enhanced gradient,simple Bayes,and logistic regression algorithms.After a trial-and-error process,the logistic regression algorithm was selected as the final learner for the proposed model.The results of experiments with the above algorithms are reported separately for the pass and fail classes.The findings indicate that the accuracy of the proposed model on the OULAD dataset reached 98%.Overall,the proposed method improved accuracy by 4%on the OULAD dataset.
基金The authors thank to the deanship of scientific research at Shaqra University for funding this research work through the Project Number(SU-ANN-2023017).
文摘E-learning behavior data indicates several students’activities on the e-learning platform such as the number of accesses to a set of resources and number of participants in lectures.This article proposes a new analytics systemto support academic evaluation for students via e-learning activities to overcome the challenges faced by traditional learning environments.The proposed e-learning analytics system includes a new deep forest model.It consists of multistage cascade random forests with minimal hyperparameters compared to traditional deep neural networks.The developed forest model can analyze each student’s activities during the use of an e-learning platform to give accurate expectations of the student’s performance before ending the semester and/or the final exam.Experiments have been conducted on the Open University Learning Analytics Dataset(OULAD)of 32,593 students.Our proposed deep model showed a competitive accuracy score of 98.0%compared to artificial intelligence-based models,such as ConvolutionalNeuralNetwork(CNN)and Long Short-TermMemory(LSTM)in previous studies.That allows academic advisors to support expected failed students significantly and improve their academic level at the right time.Consequently,the proposed analytics system can enhance the quality of educational services for students in an innovative e-learning framework.
