scholarly journals Deep-Sequence–Aware Candidate Generation for e-Learning System

Processes ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 1454
Author(s):  
Aziz Ilyosov ◽  
Alpamis Kutlimuratov ◽  
Taeg-Keun Whangbo

Recently proposed recommendation systems based on embedding vector technology allow us to utilize a wide range of information such as user side and item side information to predict user preferences. Since there is a lack of ability to use the sequential information of user history, most recommendation system algorithms fail to predict the user’s preferences more accurately. Therefore, in this study, we developed a novel recommendation system that takes advantage of sequence and heterogeneous information in the candidate-generation process. The principle underlying the proposed recommendation model is that the new sequence based embedding layer in the model catches the sequence pattern of user history. The proposed deep-learning model may improve the prediction accuracy using user data, item data, and sequential information of the user’s profile. Experiments were conducted on datasets of the Korean e-learning platform, and the empirical results confirmed the capability of the proposed approach and its superiority over models that do not use the sequences of the heterogeneous information of users and items for the candidate-generation process.

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Luyan Teng ◽  
Qinyi Tan ◽  
Ali Ehsani

PurposeOne of the most significant threats of COVID-19 in the world is the closure of universities, schools, training courses and even companies and organizations. In such a situation and with the free time that has arisen, this threat of education closure can become a golden opportunity for learning and progress in virtual education. E-learning uses information technology (IT) to distribute knowledge and information for training and education. Also, cloud computing is a technology utilized in the IT domain. It can be employed in performing e-learning. Therefore, the main goal of this study is to assess the impact of cultural characteristics, economic situations, skills and knowledge on the development and success of CELS in the COVID-19 era.Design/methodology/approachCloud-based e-learning system (CELS) provides all e-learning requirements like software and hardware resources to promote conventional e-learning technologies. The CELS stands on several factors of diverse aspects that have been of high significance in CELS success. So, these systems must be checked to analyze their significance rate and successfully carry out their effectiveness. On the other hand, these days, the 2019 coronavirus disease (COVID-19) changes our daily lifestyles. Therefore, the present investigation provides a new model investigating the development and success of CELS in the COVID-19 era. Also, an online questionnaire was used to gather the data. The content validity of the questionnaire was obtained by applying the opinions of ten experts from e-learning specialists. The collected data are analyzed using LISREL and Smart PLS software.FindingsThe results from the path coefficient and the sample t-test have implied that skills and knowledge positively influence CELS in the COVID-19 era. In addition, the relationship between cultural characteristics and CELS in the COVID-19 era has been positive and significant. The relationship between the economic situations and the CELS in the COVID-19 era is positive and significant.Practical implicationsThe proposed model helps managers get a big picture of CELS necessities and more effectively in the COVID-19 era. This research has a unique impact on universities to develop an e-learning platform to facilitate the education process in the COVID-19 era. It provides guidelines for educational institutions to effectively implement the learning management system to facilitate students' education.Originality/valueCELS are getting increasingly essential to offer training courses more efficiently in educational institutions. Although the intersection between cloud computing and e-learning has increasingly grown in both practical and academic contexts, few studies on the impact of cultural characteristics, economic situations, skills and knowledge on the development and success of CELS in the COVID-19 era. This paper explores the ignored but critically important subject of CELS. This paper's main contribution is to present a new and integrated model containing the essential aspects of the development and success of CELS in the COVID-19 era. The proposed framework comprises cultural characteristics, economic situations, skills and knowledge aspects simultaneously, as well as sub-criteria denoting each element.


Author(s):  
A. A. Azeta ◽  
Charles K. Ayo ◽  
Aderemi Aaron Anthony Atayero ◽  
Nicholas Ikhu-Omoregbe

Government establishments are most times highly involved in different reorganization programs. The processes in e-Government are diversified and complex, hence the need for an appropriate training and learning strategy for governmental employees. Changing business processes and organizational structures always mean that the personnel have to be familiar with the changed procedures. Consequently, the employees need to be trained to develop capacity for new responsibilities. Existing methods of learning and training do not make provision for certain category of employees such as the visually impaired. They do not provide an alternative learning platform for government of employees that are not physically challenged. Many studies have demonstrated the value of several learning platforms, including mobile learning (m-Learning) but with the problems of access barriers and streamlined participation of most learners. The purpose of this chapter is to propose a voice-based e-Learning system, also known as voice-learning (v-Learning) as a variant of the m-Learning with particular relevance for the visually and mobility impaired learners. V-Learning makes possible ubiquitous learning in e-Government and provides additional capacity and speed of response to help facilitate change. Cost reduction is also achieved and there is no shortage of teachers.


Author(s):  
Zameer Gulzar ◽  
L. Arun Raj ◽  
A. Anny Leema

Data mining approaches have been tried in e-learning systems for information optimization and knowledge extraction to make decisions. In recent years, the recommendation system has gained popularity in every field be it e-commerce, entertainment, sports, healthcare, news, etc. However, in e-learning system, the recommender systems were not effectively utilized in comparison to other domains and thus emerged as a bottleneck for almost all e-learning systems for not offering flexible delivery of the learning resources. Current e-learning systems lack personalization features, and the information is presented in a static way despite their varying learning objectives and needs. The aim of recommender system is to personalize the information with respect to learner interest. The objective of this study is to highlight various algorithmic techniques that can be used to improve information retrieval process to provide effective recommendations to learners for improving their performance and satisfaction level.


Symmetry ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 1798 ◽  
Author(s):  
Zeinab Shahbazi ◽  
Yung Cheol Byun

Electronic Learning (e-learning) has made a great success and recently been estimated as a billion-dollar industry. The users of e-learning acquire knowledge of diversified content available in an application using innovative means. There is much e-learning software available—for example, LMS (Learning Management System) and Moodle. The functionalities of this software were reviewed and we recognized that learners have particular problems in getting relevant recommendations. For example, there might be essential discussions about a particular topic on social networks, such as Twitter, but that discussion is not linked up and recommended to the learners for getting the latest updates on technology-updated news related to their learning context. This has been set as the focus of the current project based on symmetry between user project specification. The developed project recommends relevant symmetric articles to e-learners from the social network of Twitter and the academic platform of DBLP. For recommendations, a Reinforcement learning model with optimization is employed, which utilizes the learners’ local context, learners’ profile available in the e-learning system, and the learners’ historical views. The recommendations by the system are relevant tweets, popular relevant Twitter users, and research papers from DBLP. For matching the local context, profile, and history with the tweet text, we recognized that terms in the e-learning system need to be expanded to cover a wide range of concepts. However, this diversification should not include such terms which are irrelevant. To expand terms of the local context, profile and history, the software used the dataset of Grow-bag, which builds concept graphs of large-scale Computer Science topics based on the co-occurrence scores of Computer Science terms. This application demonstrated the need and success of e-learning software that is linked with social media and sends recommendations for the content being learned by the e-Learners in the e-learning environment. However, the current application only focuses on the Computer Science domain. There is a need for generalizing such applications to other domains in the future.


2020 ◽  
Vol 17 (9) ◽  
pp. 4585-4592
Author(s):  
Nidhi Gupta ◽  
Neeraj Sharma ◽  
Sanjay Sood

The teaching-learning process, especially in higher education has always been a matter of great concern in developing countries as it makes the nation’s youth capable and is a mainstay towards its development. With the introduction of ICT, it has become even more important to change the learning methodology using the latest technologies like e-Learning, m-Learning, Cloud Computing etc., to match with the education standards of developed countries. This aim of this paper is to provide an insight about the use of e-Learning and cloud computing in HEIs. The paper also discusses the various cloud based adoption technologies used for HEIs and illustrates the comparative analysis of the web based and cloud based e-Learning system.


Techno Com ◽  
2021 ◽  
Vol 20 (4) ◽  
pp. 518-526
Author(s):  
Remuz Maurenz Bertho Kmurawak ◽  
Samuel Alexander Mandowen

E-learning is one of the revolutions in the education system that encourages the acceleration of quality learning. The Covid-19 pandemic has become a catalyst for accelerating the implementation of e-learning in Jayapura, Papua. Teachers are required to be able to adapt to this rapid change. Thus, E-learning becomes essential amid the pandemic, yet the ICT indicators reveal many barriers to implementing it. This study aims to assess the level of readiness of the teachers in implementing the e-learning system. Data was collected by distributing questionnaires to the teachers from elementary to high school in Jayapura City. Technology infrastructures, human resources, and e-learning content were the main variables to measure. This study indicated that based on teachers' perceptions, more than 70 percent were using google classroom as an e-learning platform. The level of readiness was level 3 (ready with minor improvements). Infrastructures, internet access, and e-learning content availability are the indicators that needed extra attention for improvement


2021 ◽  
Vol 16 (02) ◽  
pp. 12-32
Author(s):  
Giorgi Abashishvili Giorgi Abashishvili

E-learning has an increasingly important role within the ever-growing tertiary education system in many developed countries. While the research on e-learning is still relatively a novel discipline, with even a universally accepted definition being absent, there are numerous indications pointing to its increasing importance. For example, in the US alone, some 35% of university students take at least one online degree, while the ratio has been steadily increasing in the recent years. There are numerous underlying factors which support the intensification of e-learning. Most countries cannot keep up with the increasing demand for tertiary education by merely expanding their traditional universities – be it because of high needed fixed investments, or because or elevated costs of engaging the relatively scarce teaching staff. In the same time, the ICT revolution – as well as the ongoing COVID outbreak – both facilitate and require shifts to a delocalized contact between students and the teaching staff. In sum, this provides many developing countries with a mechanism of provision of tertiary education to large masses of prospective students without having to invest in physical infrastructure. However, this is not a process without challenges. Regulation in many countries is only yet to cope with these technology and demography-induced shifts in education. Some academic fields are not yet appropriate for distance learning. Cheating and plagiarism could be widespread if not tackled with appropriate strategies and technological solutions. This document examines these elements by providing an overview of the experiences in some of the countries where the e-learning system already took deep roots. Georgia has much to gain if it includes e-learning in its tertiary education system. Georgia at this moment is, seemingly, one of the few relatively developed countries which still do not have a fully-fledged and accredited e-learning platform within its tertiary education system. However, as World Bank data show, some 64% of Georgia’s high school graduates successfully enroll to a university, which is approx. 10 percentage points lower than OECD average, or as much as 25-30 percentage points lower than some of the world’s top education performers, such as Finland, the Netherlands or South Korea. While this gap needs to be bridged if Georgia is to tap the potential of the ongoing technological revolution, introduction of e-learning to its system may be of significant help, while it would not incur large additional costs. Indeed, numerous international examples show that in many countries, the number of students enrolled to universities soared following the introduction of e-learning, while the quality of education has not declined. In terms of increasing the base of potential enrollments, in Georgia’s case it is important to underline that e-learning may also be a mean of reaching out and connecting with members of the numerous Georgian diaspora. Also, setting up an e-learning platform also helps the universities to engage top lecturers in many educational domains at relatively low cost, meaning that more students may be given a higher quality education. COVID-19 outbreak is a case in point. The ongoing pandemics outbreak has shown, among other, that true business continuity for many education institutions, at all education levels, could have only been reached by employing adequate e-learning procedures. This means that those who have already instituted some forms of e-learning had fewer difficulties in overcoming the operative issues, while continuing to deliver education. Keywords: Higher education, E-lerning.


2021 ◽  
Author(s):  
Vinay Kumar Yadav ◽  
Sanjeev Yadav

Abstract Learning through the Web or training via e-learning is rising exponentially and is gradually preferred by conventional ways of education and training. This massive change is directly related to digital computer technological advancement. The transformation driven by innovation in computer technology has enhanced the reach of e-learning and education, making the process of sharing knowledge easy, clear, and efficient. The E-learning system relies on various success factors from several viewpoints, such as framework, organisational alignment, instructor, and student support. This paper aims to identify the critical barriers to the Internet of Thing implementation in e-learning and to establish a relational relationship between identified barriers using the Interpretive Structural Modelling approach. This paper has established some primary barriers that are useful for Internet of Things implementation in E-learning by research scholars and industrial practitioners. For the study of the driving force and dependency power of the E-learning barrier, Interpretive Structural Modelling methodology was used to classify interrelationships between barriers for improved understanding and relationships between these barriers, and Management Cross Impact Multiplications were conducted to estimate the magnitude of these relationships. Applied to classification analysis, which is used for analysing the driving power and dependence power of E-learning barriers.


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