EAI Endorsed Transactions on e-Learning https://publications.eai.eu/index.php/el <p>EAI Endorsed Transactions on e-Learning is open access, a peer-reviewed scholarly journal focused on topics belonging to the variegated and engaging e-Learning landscape, ranging from various types of distance learning (e.g., online, mobile, cloud, hybrid) to virtual laboratory environments supported by sound pedagogies, cutting-edge technologies and much more. The journal publishes research, review, commentaries, editorials, technical articles, and short communications with a triannual frequency. Authors are not charged for article submission and processing.</p> en-US <p>This is an open-access article distributed under the terms of the Creative Commons Attribution <a href="https://creativecommons.org/licenses/by/3.0/" target="_blank" rel="noopener">CC BY 3.0</a> license, which permits unlimited use, distribution, and reproduction in any medium so long as the original work is properly cited.</p> publications@eai.eu (EAI Publications Department) publications@eai.eu (EAI Support) Wed, 03 Aug 2022 09:49:54 +0000 OJS 3.3.0.12 http://blogs.law.harvard.edu/tech/rss 60 The Twenty First Century E- Learning Education Management & Implication for Media Technology Adoption in the Period of Pandemic https://publications.eai.eu/index.php/el/article/view/2342 <p>INTRODUCTION:&nbsp; The relevance of multimedia electronic learning(e-learning) education in the ongoing COVID-19 pandemic in the developing nations are justifiable on the pedagogical connections between the twenty first century digital automation and education itself. Multimedia is a creative combination of computer hardware , software and lifeware that allows for integration of video, animation, audio, graphical information and text resources in an interactive engagement , in which information are accessed interactively with any information processing devices.</p><p>OBJECTIVES: To enable personalizable and autonomous learning accomplishments when multimedia educational tools are merged , which allows for diversity in curriculum presentation.</p><p>METHODS: The current research investigated 400 postgraduate students of faculty of computer science and information technology who adopted the multimedia e-learning education approach to ensure that the&nbsp; expected date of graduation was not extended during the recent institution lock .</p><p>RESULTS :The research observed that out of six multimedia e-learning education tools&nbsp; used, e-mail functionalities, chat apps, audio/video computing application and discussion forum were mostly used to provide meaningful interactive engagement&nbsp; while blogs and webcast were less utilized.</p><p>CONCLUSION:&nbsp; The research proposed an enhanced level electronic participation, electronic readiness and e-learning education framework that matched the standards for the smartest educational reform that will enable regular and consistent educational accomplishment without disruptions of academic workflow in the global&nbsp; educational business ,notwithstanding the severity of any future pandemic similar to ongoing COVID-19.</p> Ugochukwu O. Matthew, Jazuli S. Kazaure, Ado Saleh Kazaure, Ogechukwu N. Onyedibe, Abraham N. Okafor Copyright (c) 2022 EAI Endorsed Transactions on e-Learning https://creativecommons.org/licenses/by/3.0/ https://publications.eai.eu/index.php/el/article/view/2342 Wed, 03 Aug 2022 00:00:00 +0000 Covid-19 Diagnosis by Gray-level Cooccurrence Matrix and Genetic Algorithm https://publications.eai.eu/index.php/el/article/view/2344 <p class="ICST-abstracttext"><span lang="EN-GB">Currently, improving the identification of COVID-19 with the help of computer vision and artificial intelligence has received great attention from researchers. This paper proposes a novel method for automatic detection of COVID-19 based on chest CT to help radiologists improve the speed and reliability of tests for diagnosing COVID-19. Our algorithm is a hybrid approach based on the Gray-level Cooccurrence Matrix and Genetic Algorithm. The Gray-level Cooccurrence Matrix (GLCM) was used to extract CT scan image features, GA algorithm was used as an optimizer, and a feedforward neural network was used as a classifier. Finally, we use 296 chest CT scan images to evaluate the detection performance of our proposed method. To more accurately evaluate the accuracy of the algorithm, 10-run 10-fold cross-validation was introduced. Experimental results show that our proposed method outperforms state-of-the-art methods in terms of Sensitivity, Accuracy, F1, MCC, and FMI.</span></p> Xiaoyan Jiang, Mackenzie Brown, Zuojin Hu, Hei-Ran Cheong Copyright (c) 2022 EAI Endorsed Transactions on e-Learning https://creativecommons.org/licenses/by/3.0/ https://publications.eai.eu/index.php/el/article/view/2344 Wed, 03 Aug 2022 00:00:00 +0000 COVID-19 Diagnosis by Wavelet Entropy and Extreme Learning Machine https://publications.eai.eu/index.php/el/article/view/2504 <p>In recent years, COVID-19 has spread rapidly among humans. Chest CT is an effective means of diagnosing COVID-19. However, the diagnosis of CT images still depends on the doctor's visual judgment and medical experience. This takes a certain amount of time and may lead to misjudgment. In this paper, a new algorithm for automatic diagnosis of COVID-19 based on chest CT image data was proposed. The algorithm comprehensively uses WE to extract image features, uses ELM for training, and finally passes k-fold CV validation. After evaluating and detecting performance on 296 chest CT images, our proposed method is superior to state-of-the-art approaches in terms of sensitivity, specificity, precision, accuracy, F1, MCC and FMI.&nbsp;</p> Xue Han, Zuojin Hu, William Wang Copyright (c) 2022 EAI Endorsed Transactions on e-Learning https://creativecommons.org/licenses/by/3.0/ https://publications.eai.eu/index.php/el/article/view/2504 Thu, 11 Aug 2022 00:00:00 +0000 A Concept Map based Teaching of Compiler Design for Undergraduate Students https://publications.eai.eu/index.php/el/article/view/2550 <p>In undergraduate engineering, most of the subjects do not have the open visibility of the Industry and Research requirements. Students are interested mostly on subjects which are useful for Industry placement. They do not show interest in non-open visibility subjects if an instructor teaches by simply following the textbook. Considering this, we presented a concept map based teaching methodology with Research and Industry assignments and problems. The proposed methodology focus on improving the teaching quality and students’ understanding level. In this paper, we have taken the Compiler Design subject and presented the concept map. To understand the eectiveness of the proposed methodology, the students feedback was collected and evaluated using the sign-test and the students’ submitted problems and assignments were evaluated to understand their level. The analysis results show that most of students studied Compiler Design with interest as a result of proposed teaching methodology.</p> Venkatesan Subramanian, Kalaivany Karthikeyan, Pallapa Venkataram Copyright (c) 2022 EAI Endorsed Transactions on e-Learning https://creativecommons.org/licenses/by/3.0/ https://publications.eai.eu/index.php/el/article/view/2550 Wed, 17 Aug 2022 00:00:00 +0000