AI- and IoT-Assisted Sustainable Education Systems during Pandemics, such as COVID-19, for Smart Cities

The integration of AI and the IoT in education has the potential to revolutionize the way we learn. Personalized learning, real-time feedback and support, and immersive learning experiences are some of the benefits that AI and the IoT can bring to the education system. In this regard, this research paper aims to investigate how AI and the IoT can be integrated into sustainable education in order to provide students with personalized and immersive learning experiences during pandemics, such as COVID-19, for smart cities. The study's key findings report that AI can be employed in sustainable education through personalized learning. AI-powered algorithms can be used to analyze student data and create personalized learning experiences for each student. This includes providing students with tailored content, assessments, and feedback that align with their unique learning style and pace. Additionally, AI can be used to communicate with students in a more natural and human-like way, making the learning experience more engaging and interactive. Another key aspect of the integration of AI and the IoT in education obtained from this research is the ability to provide real-time feedback and support. IoT-enabled devices, such as smart cameras and microphones, can be used to monitor student engagement and provide real-time feedback. AI algorithms can then use these data to adapt the learning experience in real time. IoT-enabled devices, such as tablets and laptops, can be used to collect and process student work, allowing for the automatic grading of assignments and assessments. Additionally, IoT technology can facilitate remote monitoring and grading of student work, which would be particularly useful for students who cannot attend traditional classroom settings. Furthermore, AI and the IoT can also be used to create intelligent personal learning environments (PLEs) that provide students with personalized, adaptive, and engaging learning experiences. IoT-enabled devices, such as smart cameras and microphones, combined with AI-powered algorithms, can provide real-time feedback and support, allowing the PLE to adapt to the student's needs and preferences. It is concluded that integrating AI and the IoT in sustainable education can revolutionize the way people learn, providing students with personalized, real-time feedback and support and opening up new opportunities for remote and disadvantaged students. However, it will be important to ensure that the use of AI and the IoT in education is ethical and responsible to ensure that all students have equal access to the benefits of these technologies.

Exploring the Factors Affecting Learners' Adoption Intention of MOOC in Higher Education during the COVID-19 Pandemic

The COVID-19 epidemic has had a huge impact on all education systems throughout the world. The lockdown policy caused higher education to find alternative teaching solutions to serve students' needs. Consequently, MOOCs have become a fascinating solution for several universities. However, the evidence from existing research still needs to be better understood by significant factors to support learners during COVID-19. This study examined the factors influencing students' adoption intention of MOOCs in developing countries during the coronavirus outbreak. This research reports the online survey of 1,384 university students enrolled in Thai MOOC as the primary part of the curriculum. The extended UTAUT2 was proposed and analyzed using a structural equation model to improve the comprehension of students' adoption intention on Thai MOOC. The result found Performance Expectancy, Hedonistic Motivation, Habit, and Local Language Support significantly influence MOOCs adoption intentions. While Habit was found to be the most significant to students' adoption intention, only gender had a moderating effect on the relationship between Habit and Adoption intention. The overall proposed model explained 84% of the variance in MOOC adoption intention of university students in Thailand during the COVID-19 pandemic. © 2023 IEEE.

Learning Management System: An Approach towards Virtual Education

With India's rapid educational growth towards virtual education, the education system has intensified. India has gone through critical condition like COVID-19. There is huge increment in the implementation of online learning management system. This helped the educational institutions to manage their education system without being physically present in the institution. This paper is presenting the challenges required by institutions to transform their manual education system into virtual/online education system. The online learning management system has enhanced the way of teaching and learning process of students. This study will tell us about how online LMS has speeding up the quality of education for the On-Campus enrolled students as well as distance learning students also. In general, LMS are built to provide the course material in a static way only. The modern LMS has the ability for the group discussion which is helping the student to achieve the qualities of team-working. © 2022 IEEE.

Students Experience Testing in the Implementation of the 'Gather Town' Meeting Platform as an Alternative Learning Media other than Zoom Cloud Meeting Application

The COVID-19 pandemic has limited the mobility of everyone in the world. Education is one of the most affected sectors because education systems have been done face to face. Most educational institutions switch to online learning by using online meeting platforms. We discovered an online meeting platform called 'Gather town' which looks more attractive in increasing learning motivation and may be an alternative solution for online education. This paper aims to test student experience using 'Gather Town' as a new learning medium and compare the effectiveness with Zoom Meeting Application. We compare the User Experience of both applications by letting respondents try the application and ask for feedback from our questionnaire. The result from the questionnaire shows that Gather Town has excellent potential as an alternative new learning media. © 2022 IEEE.

Contextual Academic Achievement Analysis Affected by COVID-19 Pandemic of Higher Education Learners in Thailand Using Machine Learning Techniques

This research aims to present the context and impact that the Thai education system has experienced from the COVID-19 pandemic in Thailand. It consists of three research objectives: (1) to study the context of the impact on academic achievement from the COVID-19 pandemic in higher education, (2) to develop a model for clustering the academic achievement of students in higher education during the COVID-19 pandemic in Thailand, and (3) to compare the academic achievement of students in higher education during the COVID-19 pandemic in Thailand. The research data were 43,230 transactions (1961 students) from four educational programs at the Faculty of Business Administration and Information Technology, Rajamangala University of Technology Tawan-ok, the results showed that the context of the impact on the education system among tertiary learners has decreased in the number of graduates during the COVID-19 pandemic. However, students graduating during the COVID-19 pandemic in Thailand had higher levels of academic achievement than those in normal circumstances. The findings reflect those learners who achieved academic achievement during the COVID-19 pandemic were more persevering and tolerant than those in the traditional system. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Observation of Online vs Offline Learning Experience

As the outbreak of COVID-19 increased in various countries. India is also majorly affected with the COVID-19 by that education system is affected, and it has transferred the traditional face-to-face teaching to online education platform. Considering student's perspective on both online and offline learning mode in India, we conducted a survey to collect the data. In that survey questionnaire, focus was on the factors and situation which can affect the education system. Using that data, we used Kruskal Wallis test to collect the evidence for which learning mode is better and Naive Bayes Algorithm, we were able to conclude the results. © 2022 IEEE.

Determinants of e-Learning user satisfaction at a South African University of Technology

This The COVID-19 and its safety precautionary protocols triggered an instantaneous transition to online learning in the higher education institutions (HEIs), to ensure the completion of academic calendars. However, the complexities associated with lingering digital divide in Sub-Saharan Africa and transition to virtual learning means learners from disadvantaged socio-economic backgrounds become more vulnerable and unlikely to benefit from the paradigm shift. Therefore, building a resilient education system through learning management systems (LMS) for remote learning, that is all-inclusive for students would be hampered by varied degrees of users' satisfaction. The objective of the study was to identify determinants of e-Learning user satisfaction for remote learning at a South African University of Technology. An online questionnaire was administered through a Microsoft form link. A sample of 40 participants were selected from the student population that have experienced blended and exclusive online learning. The data was analyzed to identify determinants of user satisfaction with LMS for learning within the context of study. An ethics clearance certificate was obtained from the relevant Faculty research ethics committee. Learners expressed positive experiences that LMS met their immediate academic needs. Challenges experienced during the learning process were not attributed to the LMS quality, but inadequate facilitating conditions and contextual peculiarities. The post-adoption success of online learning is critical towards building a resilient education system. The results from this study can help HEIs' management and LMS designers to make an informed decision on best practices for an inclusive virtual learning environment with peculiar contextual characteristics. © 2022 IEEE.

The good, the bad and the ugly: Reflections on obtaining a PhD in Healthcare Systems Design amid the COVID-19 pandemic

This paper presents a reflection on the experience of obtaining a PhD degree in Participatory Healthcare Systems amid the COVID-19 pandemic. The paper first introduces the PhD research and how the methodology was adjusted during the pandemic. Then, the reflections are presented considering the benefits/advantages (the good), the barriers/difficulties (the bad) and the struggles (the ugly). The topics presented show that positive aspects were overshadowed by the emotional burdens and increasing limitations of data collection and study design. Learnings from this experience indicate that designing a more resilient methodology that integrates creative methods, supporting PhD students to pause the research, fostering a culture of care that rethinks what a successful PhD is, and a greater focus on the Mental Health of PhD students is advisable. [ FROM AUTHOR] Copyright of Design for Health is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

The Evaluation of Cognitive Load Significance for Mobile Learning Application via User Interface Design Violations

COVID-19 has changed how the world operates, and education is one of the sectors that are highly affected by these changes. Previously, mobile learning is just an optional or a supplementary learning method. However, with the increased in the number of COVID-19 cases around the world, education system has switched from the traditional face-to-face mode in a classroom setting, to an online learning environment. Learning using a mobile device or mobile learning is a concept that is new to most learners, especially those who have never before experienced an online learning setting. One of the prevalent factors that leads to ineffective mobile learning process is badly designed user interfaces that will disengage learners from learning materials presented, and increase the cognitive load of the learners. Among the factors that results in bad user interface is the violation of a user interface guideline/framework. Therefore, the main objective of this research-work is to evaluate the learners' cognitive load significance for mobile learning application by identifying Nielsen's Heuristics' violation. By implementing this study, important user interface design (UID) attributes that increase learner's cognitive load can be identified. Understanding how UID can affect the learners' cognitive load can assist designers in deciding which user interface designs that can improve or minimize learners' cognitive load. The outcome of this research will enable mobile learning application designers, developers, educators, teachers and people who are interested in developing a mobile learning application to deliver an effective mobile learning experience to learners. © 2022 IEEE.

A System Design with Deep Learning and IoT to Ensure Education Continuity for Post-COVID

In this paper, an IoT and deep learning-based comprehensive study to reduce the effects of COVID-19 on the education system is presented. The proposed system consists of an edge device, IoT nodes, and a neural network that runs on a server. The purpose of the proposed system is to protect students and staff against infectious diseases and increase the students performance during classes by monitoring the environmental conditions via an IoT-based sensor network, during the current pandemic to ensure the use of masks in closed areas by training a customized deep learning model, and to monitor the student attendance data by deep learning and IoT-based solution. Furthermore, effective heating and cooling can be done to save energy by transmitting the environmental conditions of the indoor environment to the relevant destinations. The experiment is conducted with five different networks to classify the faces in the images as masked or unmasked, and their performances were examined. The networks were trained on the Face Mask Detection Dataset which contains a total of 7553 masked and unmasked images. The best results were obtained as 99.5% for the F1 Score and 99% for MCC by the model trained on the InceptionV3 network. IEEE

Analyzing Success Factors of E-Learning Effectiveness at Higher Education in Indonesia: A Review

E-learning is a student-centered education system which enables students to study anything from anywhere and anytime according to their learning goals. Since the COVID-19 pandemic constrained people to commute, e-learning has been massively implemented to enable educational activities. This study aims to investigate the e-learning success factors and its influence on e-learning effectiveness in higher education. The systematic Literature Review (SLR) has taken into account in order to identify e-learning success factors. Through analyzing the selected literatures, extraction of e-learning success factor domains has been attempted based on the influencing factors and its impact. As a result, seven success factors related to technology, learner, instructor, content, and institution's support, are identified as influential in the effectiveness of e-learning implementation. © 2022 IEEE.

Paying for inclusion and exclusion

Work by UNESCO (2009 and 2020a) has been framed by the argument that there are three main justifications for inclusive education: educational, social and economic. This paper aims to explore the economic justification that it is less costly to establish and maintain schools that educate all children together than to set up a complex system of different types of schools specializing in different groups of children. The paper examines the crucial role played by financing mechanisms in achieving more inclusive education systems. It provides an analytical discussion of key issues and findings emerging from international and European research and policy guidance. This paper also draws on 20 years of work by the European Agency for Special Needs and Inclusive Education with its 31 European countries, covering 35 jurisdictions, from across Europe. A consistent finding of European Agency work is that a higher amount of funding does not in itself guarantee better learning conditions and more inclusive schools. The successful implementation of inclusive education depends upon financing mechanisms and strategies that involve a range of stakeholders and take a preventative policy approach. Such financing mechanisms aim at paying for inclusion rather than paying for different forms of exclusion. The current impact of the COVID-19 pandemic is also considered as it further reinforces the need for prevention-based policy approaches. © 2023 Elsevier Ltd. All rights reserved.

Application of Deep Learning on Student Attendance Checking in Virtual Classroom

Due to the situation of the COVID-19 outbreak, the importance of both virtual and hybrid conferences has unexpectedly increased, especially for the education sector. Additionally, the virtual classroom is the only method to make the education system grow while the COVID-19 outbreak situation is currently spreading. However, class attendance checking is a time-wasting problem for various online classes, which have more than 50 students. This research aims to help the course instructor by adapting the use of intelligent technologies in order to save the time that has been spent on the class attendance checking method. The deep learning techniques together with automatic screen-capturing mechanisms have successfully been designed and developed with Python, Flask, Sqlite, Html, CSS, and Javascript. Therefore, our proposed approach for attendance checking can automatically check the attendance of the enrolled students that belong to that particular class. In addition, this research uses front-face photos to train a deep learning model and deal with face recognition and image analytics for the student attendance checking methods. Therefore, the highlight of the system is the ability to take attendance automatically and continuously throughout the learning period. As a result, the use of our proposed system efficiently saved the attendance checking time and the proposed deep learning model has practically achieved acceptable accuracy at 91.77. © 2022 IEEE.

Comprehensive Analysis of COVID-19's Effects on the Education System

COVID-19 has influenced all forms of degrees and training in higher education. An experimental structure for the analysis of information related to the education system was presented to measure the impact of the pandemic on university students' learning. The framework brings together the processes of analysing COVID-19's effects on the education system during the pandemic. Data were collected from 104 individuals via a survey w by circulating Google forms among teachers and students It has been put to the test by analysing data from a student survey done during the outbreak. The study's major goals are to analyse students' attitudes toward distant learning and their willingness to participate in it. In the context of the lockdown, to understand the struggles, and prospects of distance learning shortly, and to suggest changes and improvements for a higher quality academic experience. © 2022 IEEE.

A Systematic Literature Survey of Emotion Detection of Students in E-learning

Affective computing is a part of artificial intelligence, which is becoming more important and widely used in education to process and analyze large amounts of data. Consequently, the education system has shifted to an E-learning format because of the COVID-19 epidemic. Then, e-learning is becoming more common in higher education, primarily through Massive Open Online Courses (MOOCs). This study reviewed many prior studies on bolstering educational institutions using AI methods, including deep learning, machine learning, and affective computing. According to the findings, these methods had a very high percentage of success. These studies also helped academic institutions, as well as teachers, understand the emotional state of students in an e-learning environment. © 2022 IEEE.

COVID-19 and Shifting Paradigm in Asian Education System

COVID-19 has forced the paradigm shift in the education system.This study thoroughly examined the adopted virtual learning practices to understand the changing paradigm positively contributes or has adverse impacts on the education system.The study has found that technologies, devices, and internet access have become essential requirements for students to continue their education during this transition period.The study has also discussed how families' financial status influences the degree of learning attitude and the effectiveness of virtual learning of students.The literature reviewed for this study showed that students from higher-income countries have greater access to and command of technologies, while students from lower-income countries continue to struggle to meet the basic requirements for virtual learning.The study argues that virtual education cannot deliver comprehensive requirements of education as it lacks studenthood, classroom bonding between students and teachers, and a peer learning approach, which is significant in the holistic growth of individuals. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

The ELF Tribe: Redefining Primary Education in a Post-COVID Era

Coronavirus brought the entire world to a grinding halt, and it has still not recovered from the vandalization caused. Along with the dramatic loss of lives worldwide, the situation also proved to be disruptive in every sector of the economy. Education system also faced immense turbulence. It has impacted the younger children the most as the effectiveness of online classes is highly doubtful among them. Even the teachers are not able to deliver classes to their best ability. Keeping in mind the present circumstances and the return to state of normalcy, ‘The ELF Tribe' is designed as an educational tool for both teachers and students. There is substantial evidence in science to prove that kids learn better with hands-on experience but nothing can replace a good teacher. This application assists them in non-teaching tasks which, when blended with traditional schooling, has the potential to redefine meaningful schooling. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Difference between Online and On-site Mathematics Courses in Higher Education

As a result of the rapid spread of the Covid-19 virus, the education system has undergone many changes in order to avoid the spread of the disease. Educational institutions have moved from traditional pedagogy of teaching to the process of online learning. The purpose of this research is to estimate there are differences between learning mathematics online and on-site in Higher Education. To determine if there is a difference between learning math online and on-site, we first analyzed the results of students who have completed the same math course. Then we analyzed the results of students who have successfully completed this course. The students' academic results were measured by the final grade of the exams from the mathematics course, which were provided by the Department of Computer Science and Engineering at UBT University in Kosovo, where the students of this University were part of this study. This research study makes an important contribution to addressing the question of differences between online and on-site mathematics learning and achievement. The findings revealed that there are small differences between online learning outcomes and on-site. The outcomes demonstrated that online learners performed better than on-site learners in the arithmetic course. The results of this study will offer crucial information to higher education institutions looking to provide top-notch online courses that cater to students' and communities' requirements. Copyright © 2022 The Authors.

Feature Selection and Parameter Optimization of SVM by Using a Hybridization Model

The feature selection approach (FSA) has lately emerged as a critical method for enhancing accuracy in several disciplines, including e-learning. Since the emergence of the COVID-19 pandemic, the education system in Iraq has diversified its methods to cope with the circumstances, and thus, the positive and negative aspects of e-learning in Iraq are revealed. In this study, we developed a hybrid model that predicts how to rely on a blended learning system during and after the COVID-19 pandemic. A hybrid model was implemented in MATLAB environment that suggested to optimize the support vector machine algorithm in blended e-learning. This hybrid model combines neighborhood component analysis and chi-square statistic. The proposed model demonstrated that platform influence is the most important factor in the e-learning field. It includes high-ranking features, such as adequacy of the virtual environment, a platform that provides sufficient tools for the user, user interest to learn new platforms, obligating students to attend, and having computer skills. The current work was compared with [11], which employed the SVM classification method, using the same datasets. The prediction accuracy of proposed work was better than that of the previous finding. The main goal of proposed work is to obtain a better optimization model than pervious finding by decreasing model error. The Error results was successfully reduced to 0.00012294. © 2022 IEEE.

Assessment of the impact of ICT in the Digitalization Process in High Schools during the Covid-19

The research focus is on identifying and assessing the impacting factors to be measured in order to realize assessment of the impact of ICT in the Digitalization Process in private and public high schools during the Covid-19. These years, during the Covid 19 epidemic, evidenced was the problem of pandemic huge impact on every aspect of life. One of the most significant sectors affected and was a major problem was the educational system, especially high schools, were severely impacted. However, as a result of the conditions, most of the schools, confronted this challenge and started to implement ICT technology within their facilities to enable distance online learning. This research study's major objective is to investigate how the Covid 19 epidemic has affected the digitalization process and impact of ICT technology in high school's weather public or private, focusing on the impact on learning and the teaching process. Two of the largest private and public schools from the city of Prishtina from Kosovo have been chosen as case studies for investigation. A number of schools include administration representatives and teachers as their primary study subjects. A survey was conducted using a questionnaire, and the information from the responses was received, compiled, and analyzed. Analyses of the hypothesis as well as impacting factors has been realized, discussed and argumented. © 2022 IEEE.