Learning Systems
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Ouiame Filali Marzouki ◽  
Mohammed Khalidi Idrissi ◽  
Samir Bennani

The development of mobile technologies and wireless networks encourages more research on Mobile Learning. Reviewing irregular verbs on a bus or organizing a training schedule on a Smartphone is becoming more common today. Mobile learning complements and enhances existing learning systems. Its development has been slowed in the early 2000s by both technical limitations and lack of dedicated teaching models. This article focuses on educational issues and proposes a solution by adopting the Method for Engineering Learning Systems MISA. Our work aims to identify basic elements, key characteristics and dimensions for developing the appropriate content for mobility. These elements are the basis for customization of the MISA method. Indeed, the different steps of MISA are governed by operating principles which ensure greater consistency and flexibility. Taking into account the specifications of Mobile learning in the development of these principles, we can adapt MISA to design a mobile learning system.

2021 ◽  
pp. 85-92
Sigita Rackevičienė ◽  
Liudmila Mockienė ◽  
Andrius Utka ◽  
Aivaras Rokas

The aim of the paper is to present a methodological framework for the development of an English-Lithuanian bilingual termbase in the cybersecurity domain, which can be applied as a model for other language pairs and other specialised domains. It is argued that the presented methodological approach can ensure creation of high-quality bilingual termbases even with limited available resources. The paper touches upon the methods and problems of dataset (corpora) compilation, terminology annotation, automatic bilingual term extraction (BiTE) and alignment, knowledge-rich context extraction, and linguistic linked open data (LLOD) technologies. The paper presents theoretical considerations as well as the arguments on the effectiveness of the described methods. The theoretical analysis and a pilot study allow arguing that: 1) a combination of parallel and comparable corpora enable to considerably expand the amount and variety of data sources that can be used for terminology extraction; this methodology is especially important for less-resourced languages which often lack parallel data; 2) deep learning systems trained by using manually annotated data (gold standard corpora) allow effective automatization of extraction of terminological data and metadata, which enables to regularly update termbases with minimised manual input; 3) LLOD technologies enable to integrate the terminological data into the global linguistic data ecosystem and make it reusable, searchable and discoverable across the Web.

2021 ◽  
Vol 6 (2) ◽  
pp. 111-123
Ikhlas Zamzami ◽  

It is possible to learn more quickly and effectively with e-learning software development because it provides learners with convenient and flexible learning environments. This allows them to progress further in their careers. Reports on web-based e-learning systems for inservice education have frequently neglected to include the viewpoint of the instructor. In order to conduct quantitative research, a sample of 50 academic staff members was selected. The purpose of this study was to investigate various factors that influence the intention to use webbased e-learning, with the theoretical foundation being provided by university lecturers. According to the findings of the study, the intention to use web-based e-learning for in-service training is positively correlated with the motivation to use the Internet and the belief in one's own ability to use the Internet. In terms of intentions to use web-based e-learning in-service training, a statistically significant increase in computer anxiety had an impact. University lecturers embraced Web-based e-learning systems because they believed they would be beneficial and because they were eager to put them to use

2021 ◽  
Vol 2 (4) ◽  
pp. 248-262
Sisca Monita ◽  
Ilman Zuhri Yadi

E-learning is an electronic distance learning system that uses network and computer technology. There are many models of using e-learning, one of which is the use of e-learning at Bina Darma University during the COVID-19 pandemic, where more use of e-learning and online learning systems during the pandemic period, for this reason the quality of e-learning services can be measured using Webqual. Webqual is a method used to measure website quality based on end users. Webqual is structured in research on 3 dimensions, namely Usability, information, and service interaction. This study aims to determine the quality of the e-learning website of Bina Darma University as student learning taken by 101 students and to find out the most influential indicators in the quality of e-learning. If the alpha value is greater than the R table, then the consistency of the R table is declared valid. On the Likert test scale, it is known that the usability dimension or indicator gets the highest usability level, so the usability dimension has a positive effect on user satisfaction.

M. Kazakova ◽  
Tat'yana Selivanova

This article focuses on the implementation of the national programme "Digital Economy of the Russian Federation" and the federal project "Human Resources for the Digital Economy" in the organisation of the mining and metallurgical complex. The object of the study is e-learning systems. The subject of the study is the processes of using e-learning systems in the organization-basis of the study relating to the mining and metallurgical complex in Russia. The aim of the work is to develop recommendations for the management of organizations that are going to implement distance learning technology in the educational processes of staff. The methodology of the study includes a survey of employees of the organisation under study on the attitude and quality of training in an e-learning system. The experience of personnel training in enterprises with the help of different information systems is considered. The focus is on the analysis of the use of the training and control system "Olympox" in the organisation of the mining and metallurgy industry. The results of an employee survey are given to find out their attitude to the introduction of an electronic learning information system and to the organization of training processes in it. Recommendations on the improvement of information training systems used for personnel assessment and development are offered. Based on the results of the study, it was determined that the quality of personnel development depends on the competent combination of training in a face-to-face format with technology that allows you to practice theory in the form of tests and open questions and practice in the form of cases and exercises to practice working situations in conditions as close to the real.

2021 ◽  
Dun Li ◽  
Dezhi Han ◽  
Tien-Hsiung Weng ◽  
Zibin Zheng ◽  
Hongzhi Li ◽  

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0

E-Government in itself requires reorganizing of governance with institutions and organizations with the aim of running them more efficiently. This is done using various applications created specifically for actions in the fields of economics, health, safety, education, etc. These applications are products that are used directly by all citizens. In the field of e-Learning, in educational institutions such as universities, the users of these applications are lecturers and students who are considered to have the highest skills in Information and Communication Technologies (ICT). Based on this, e-Learning systems in educational institutions can be configured in such a way that tasks and responsibilities are divided into user levels. This would make the maintenance of system not dependent on the administrator only, but on all levels of users. Consequently this makes the whole system more sustainable, decentralized, with low-maintenance. Such a configuration has been running with the Moodle platform at Kadri Zeka University Kosovo (UKZ) for five year since 2016.

Khaled ELKarazle ◽  
Valliappan Raman ◽  
Patrick Then

Age estimation models can be employed in many applications, including soft biometrics, content access control, targeted advertising, and many more. However, as some facial images are taken in unrestrained conditions, the quality relegates, which results in the loss of several essential ageing features. This study investigates how introducing a new layer of data processing based on a super-resolution generative adversarial network (SRGAN) model can influence the accuracy of age estimation by enhancing the quality of both the training and testing samples. Additionally, we introduce a novel convolutional neural network (CNN) classifier to distinguish between several age classes. We train one of our classifiers on a reconstructed version of the original dataset and compare its performance with an identical classifier trained on the original version of the same dataset. Our findings reveal that the classifier which trains on the reconstructed dataset produces better classification accuracy, opening the door for more research into building data-centric machine learning systems.

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