ABSTRACT
COVID has made education shift towards online mode. In online mode, instructors have a hard time keeping track of their students. Students' performance in online classes falls considerably below the level of learning due to a lack of attention. This initiative aids in the supervision of students during online classes. Artificial Intelligence (AI) models are being developed to better recognize student activities during online sessions. Many applications rely on determining an individual's mental state. When evaluating which subtask is the most challenging, a quantitative measure of human activity while executing a task can be helpful. Thus, the goal of this research is to create an algorithm that uses EEG data gathered with a Muse headset to measure the amount of cognitive intelligence of students during online classes. The data collected by the Muse headset is multidimensional, and it is pre-processed before being fed into machine learning algorithms. Using feature selection, the dataset's dimension is now reduced. The model's precision and recall were calculated, and a confusion matrix was created. The Support Vector Machine produces better outcomes in the experiment. © 2022 IEEE.
ABSTRACT
For the past few years, the world has seen a paradigm shift in the way of life. Daily activities of working, learning, etc. were shifted to an online mode so that the spread of the covid virus can be contained. During this time, usage of social media apps was at an all-time high since it was the only way people could socialize. The clubhouse was one such social media app that gained popularity during the lockdown and showed exponential growth in terms of user engagement. But, it was observed that from the survey conducted among 33 users, almost 82% of users showed reluctance in using Clubhouse over time. 84.8% of users welcomed the need for a better User Experience for the platform. An average of 64.2% of users reported different User Experience (UX) related issues in the app. In this paper, the UX side of the app is studied and discussed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
From the last two years due to emergence of COVID-19, a first pandemic of the century, caused hard time to continuing normal lifestyle in all aspects including the campus lifestyle of students. All the academic activities such as classes, examinations, evaluations and placement are going as usual in online mode like earlier. In this regard, we have conducted a Web-based survey on students about their mental condition concerning corona anxiety, coping with stress, worry, and fear. In our survey, 620 students participated from different discipline and states to rejoin the campus either online or offline mode. 372 (60%) students want to attend offline classes while 248 (40%) students want online classes. Additionally, generating the rules using a rough set approach to identify corona anxiety in students. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
With the outbreak of COVID-19, several countries have requested the closure of all educational institutions;many universities have shifted to online mode during this period. Previous studies showed the need for a continuous assessment of student's satisfaction with the online delivery methods to improve the teaching and learning experience. This paper is framed with the motivational needs and social presence theories to review students' perceptions of various online learning environment tools, social presence, and satisfaction with online courses. 846 students in higher education institutes from different backgrounds and cultures participated in the online survey. Results show that the learning environment has a positive, substantial, and significant relationship with social presence. Moreover, factors influencing the learning environment that was significant to student satisfaction are presented. © 2022 IEEE.
ABSTRACT
This paper presents a new dataset for Kazakh-Russian Sign Language (KRSL) created for the purposes of Sign Language Processing. In 2020, Kazakhstan's schools were quickly switched to online mode due to COVID-19 pandemic. Every working day, the El-arna TV channel was broadcasting video lessons for grades from 1 to 11 with sign language translation. This opportunity allowed us to record a corpus with a large vocabulary and spontaneous SL interpretation. To this end, this corpus contains video recordings of Kazakhstan's online school translated to Kazakh-Russian sign language by 7 interpreters. At the moment we collected and cleaned 890 hours of video material. A custom annotation tool was created to make the process of data annotation simple and easy-to-use by Deaf community. To date, around 325 hours of videos have been annotated with glosses and 4,009 lessons out of 4,547 were transcribed with automatic speech-to-text software. KRSL-OnlineSchool dataset will be made publicly available at https://krslproject.github.io/online-school/. © European Language Resources Association (ELRA), licensed under CC-BY-NC 4.0.
ABSTRACT
From the last two years due to emergence of COVID-19, a first pandemic of the century, caused hard time to continuing normal lifestyle in all aspects including the campus lifestyle of students. All the academic activities such as classes, examinations, evaluations and placement are going as usual in online mode like earlier. In this regard, we have conducted a Web-based survey on students about their mental condition concerning corona anxiety, coping with stress, worry, and fear. In our survey, 620 students participated from different discipline and states to rejoin the campus either online or offline mode. 372 (60%) students want to attend offline classes while 248 (40%) students want online classes. Additionally, generating the rules using a rough set approach to identify corona anxiety in students. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
This study aims to identify the relationship between work stress, burnout and mental health of academic staff during the implementation of the Movement Control Order (MCO) when the only possible mode of teaching was the fully online mode. It has been hypothesized that there are significant relationships between work stress and mental health among academics;and work stress (work overload, role ambiguity, lack of autonomy) can predict a significant amount of the variance in mental health (anxiety/insomnia, social dysfunction) of academic staff during the online teaching, after taking the possible effect of burnout into consideration. This study involved 106 academic staff (73 females, 33 males) to complete an online survey which included the Work Stress Scale, Burnout Measure, and General Health Questionnaire 28. The findings of this study showed the significant positive relationships between all variables of work stress and mental health;work overload and burnout predicted anxiety/insomnia;lack of autonomy and burnout predicted social dysfunction. These findings have implications for Human Resources practices in efforts in reducing work stress and improving mental health of academic staff during these trying times. © 2022 ACM.
ABSTRACT
For the past few years, the world has seen a paradigm shift in the way of life. Daily activities of working, learning, etc. were shifted to an online mode so that the spread of the covid virus can be contained. During this time, usage of social media apps was at an all-time high since it was the only way people could socialize. The clubhouse was one such social media app that gained popularity during the lockdown and showed exponential growth in terms of user engagement. But, it was observed that from the survey conducted among 33 users, almost 82% of users showed reluctance in using Clubhouse over time. 84.8% of users welcomed the need for a better User Experience for the platform. An average of 64.2% of users reported different User Experience (UX) related issues in the app. In this paper, the UX side of the app is studied and discussed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
The outbreak of the deadly Covid-19 virus has snatched smiles from everyone’s face and now the entire world has been affected directly or indirectly by the effects of the virus, this virus keeps on mutating due to which there is no proper medicine or a final vaccine that assures it will curb the spread of the virus, major countries all over the world has lost more people than in a war and is still losing its people even after getting fully vaccinated. The horror is so much imbibed in each human it seems unrealistic to even think that the world will be normal ever again. This outbreak of the unknown virus is certainly a black-swan event that has annihilated people economically, emotionally, and socially and has made each individual realize the importance of one’s health and how to be a responsible person by taking care of whatever finances one has, as in unprecedented times savings are the only resort left with a person. It is a testing time and everyone is at war, we all are soldiers in this pandemic and our health care workers, administration, and government are trying their best to stop the spread of the disease as it has killed more than four lakh people in India only and in the world tally is more than forty lakhs with numbers increasing. In this appalling situation when everything has been shifted to online mode solutions must be looked at in more technologically driven methods, in today’s world due to rapid advancement in the IT and computer science sector there are ways to track the next rising hotspot of the virus and how it can be contained by taking swift actions if predicted within a particular time frame. Data collection, data analysis, and studying trends can help in assessing the upcoming threats, and in this manner, new job opportunities can also be created as it will involve people being prepared with limited medical knowledge to cure the people affected with the virus. In these times government and administration must adopt technologically backed solutions which will help the system to make accurate decisions based on real-time data-driven modeling capable of identifying the relevant information. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
This research paper describes a study of engineering students' perceptions of online classes in the time of COVID-19. In the engineering field, online classes were relatively uncommon prior to the pandemic due to the emphasis on field practice. The pandemic rapidly changed education in general to make online classes the norm-not as a means of assisting face-to-face classes but rather replacing them. The online mode of learning in engineering education holds tremendous promise for traditional and non-traditional students who wish to major in engineering. Therefore, this study explored how students evaluate online engineering classes to effectively implement them during the ongoing pandemic as well as in the post-pandemic era. Drawing from> the SERVQUAL model this paper determines which factors contributed to students' evaluation of the quality of online engineering classes and their perceptions of the benefits of such classes. Ultimately, 186 engineering students participated in this study. The results show that perceived suitability of the online format for teaching engineering courses was the strongest determinant of perceptions toward the quality and benefits of online engineering classes. In addition, how much the instructor knows about the course content and whether useful and accurate information is provided using appropriate multimedia on an e-learning site determine the perceived quality of online classes for students. The students also believed that instructors who showed more empathy generated more benefits for the class. Theoretical as well as practical implications are discussed in this paper. © American Society for Engineering Education, 2022.
ABSTRACT
Capstone Projects, CTC 490, is a mandatory course for all Civil Engineering Technology students during their senior year. This specific course is designed to apply cumulative experiences gathered from wide range of courses in the curriculum. The students analyze and design real life civil engineering project, write a written report followed by an oral presentation. However, during the COVID-19 pandemic, student learning outcomes were significantly disrupted as the plan of study changed to online mode from March 2020. The purpose of the current study is to document the students' learning experiences of the capstone design course during the pandemic year. As the course is so comprehensive in nature, wide range of student learning assessment is possible from this course. Data were collected from Fall 2020 and Spring 2021 semester to assess the student outcomes in the category of communication with the teammates, fulfill roles and responsibilities, and listening to the teammates. The scales of one to four (1-not acceptable, 2- below standards, 3- meets standards, 4- exemplary) were chosen so that the instructor had a clear view to make a decision whether the expectations were met or not. The measure of successful performance in each attribute was achieving a score of 3 or 4. A benchmark of 70% was selected to gage the level of success. The results showed that the student outcomes were impacted most in the communications category. The level of success in the capstone rubric were documented and connected with the related program outcomes of the ETAC/ABET criteria. Outcomes of this study will be helpful in planning to teach such kind of course in situation like pandemic or other situations out of our control. © American Society for Engineering Education, 2022
ABSTRACT
COVID pandemic has brought many changes in day to day working of almost every profession. Education is one such arena where switching to online mode of teaching and assessment was received by many educators as a paradigm shift in pedagogy. Conducting classes online was not a satisfying experience for many but was recognized as the need of the hour. But when it came to online assessment of work, the bright window of light generated an array of questions. Conducting online assessments using live online proctored test, or submissions of assessment sheets has become a new-normal. Many technology platforms provide solutions for online face-to-face meetings, Artificial intelligence based proctored examinations and online objective type assessment sheets with pre-assigned rubrics for marks and evaluation. Since there was a situation where the proctor needs to be present and observe the behaviour of the student, their movements and also the application is to check the face to be recognised with the data already entered, if there is any noise or if someone else if present in the room or not.All these features had made the online examination system little efficient and effective for the universities to conduct the exam hassle free and from remote access. This paper presents a study of various online assessment tools presented by technology companies for smooth conduct of examinations. This study also presents a comparative analysis of features of these tools and their utilization in different domains. © 2022 IEEE.
ABSTRACT
During the period of COVID-19, the national universities support the policy of "continuing teaching and learning while stopping the class", and fully apply the teaching advantage of "Internet +"to conduct the online teaching activity. "Technical Fundamentals of Web Front-end", as the main course of the major of financial science and technology, plays a significant role in cultivating professionals and improving the core competitiveness of students. During the epidemic period, the online teaching mode based on SPOC and WeChat, which coordinates the pre-class guidance, in-class research, after-class supervision and development, has been applied to complete the online teaching of 2019 and 2020 students. This paper not only shares the online teaching experience of the course, but also summarizes and discusses the advantages and disadvantages of online education, in order to provide reference for improving the quality of online teaching of financial technology courses. © 2022 ACM.
ABSTRACT
COVID-19 has induced the need of exercises and yoga among people. Yoga is now becoming a habit of everyone for staying fit and healthy through body and mind. Since, it was the period of complete lockdown, people started preferring online modes for the same. There are many different apps on the play store specifically for doing yoga. With the advent of artificial intelligence in various industries, it is also winning the hearts of the yoga enthusiasts too. The integration of AI in the fitness industry (AI enabled fitness trainers, smart wearables, AI based gym equipment to name a few) is gaining huge momentum among the health conscious. This paper walks through different yoga mobile applications that use the techniques of artificial intelligence to motivate their customers with personalized experience and positive feedback and introduces a new concept of AI based Yoga Trainer who reminds, instructs, guides, and motivates a user to do yoga or while doing yoga. © 2022 IEEE.
ABSTRACT
The demand for a smart classroom has been compounded by Covid-19, which allows students to have a meaningful learning experience while staying home. Students who join a classroom in online mode don't have the opportunity to experience a classroom setting because of the hybrid mode of teaching (both online and offline classes). As a result, they have problems such as not being able to see the board clearly, not being able to follow the lecturer because he or she is out of frame, and thus having difficulty learning. Furthermore, this results in lower interaction between the online students and the professor. To teach effectively, the professor is unable to use the entire length of the board as it would not be visible to students joining in online mode. As students and instructors, we identified the issue and developed a plug-and-play device which is portable to address the aforesaid problem during this testing and difficult period of time of the pandemic. The paper outlines the practical implementation of a plug-and-play device that meets the aforementioned requirements. The model also considers power usage, as it can dynamically control energy-consuming resources such as lighting and air conditioning in response to the environment and the presence of students. © 2022 IEEE.
ABSTRACT
Distance learning has dramatically increased in recent years because of advanced technology. In addition, numerous universities had to offer courses in online mode in 2020 and 2021 because of the COVID-19 pandemic. However, there are more challenges in distance learning than in the traditional learning method (e.g., feedback and interaction). Recently, researchers started using simple EEG headsets to identify confused students during online courses based on machine learning approaches. However, they faced unpleasant accuracy using traditional machine learning algorithms or nondeep neural networks. In this paper, we present a data-driven approach based on a multi-view deep learning technique called CSDLEEG to identify confused students. We employ the students' demographic information and EEG signals to feed our novel neural networks. The results show that our proposed approach is superior to state-of-the-art methods for 98% accuracy and 98% F1-score. © 2022 IEEE.
ABSTRACT
This article is focused on the subject Digital technique, which is lectured at the Faculty of Electrical Engineering of the CTU in Prague. The subject is intended for the students of the 2nd grade of their basic study and each year approx. 70 students participate in this subject. Our aim is to continually increase the quality of laboratory measurements by including up-to-date and modern resources (FPGA development boards and kits) as well as interesting and important achievements in this area in order to make the subject as much interesting and motivating for the students as possible. Unfortunately, the last academic year teaching was negatively influenced by COVID pandemic and by various restrictions it caused, especially unpredictable opening and closures of the university for students, which caused the teaching was mostly performed in the online mode. Due to that, we decided to essentially update and transform the content of the subject towards modern resources and with respect to the above-mentioned principles. The paper contains the description of these updates and upgrades we performed, especially focusing on the updates of laboratory tasks and experiments. The article describes the necessary prerequisites, restrictions and will focus deeper on laboratory tasks. © 2022 IEEE.
ABSTRACT
As a matter of fact the English language is considered as the language of global commerce, the role and outcomes of English language provision in English-medium higher education institutions in the Indian fronts and remained central to any discussion on graduate profile and the employability of graduates in the global marketplace. This present study entails its direction toward the learning process of English language after the completion of graduation and post-graduation in the crucial times of COVID-19, where the most of the educational and training institutes were running in online mode. Many of the job aspirants use to learn English from the private English learning centers, who are having different methodologies for teaching the language, but presently this scenario has changed to online mode of training. Using a mixed methods approach, data was gathered through telephone interviews, student workplace simulations and employer focus groups. Findings of the study focus on the increase in employability skills during pandemic period, channeled through English as a second or additional language, becoming confident, gaining knowledgeable, etc. © The Electrochemical Society
ABSTRACT
The COVID-19 pandemic has impacted the world severely. With the onset of lockdowns and restrictions, daily activities have been hindered, forcing humanity to adapt to this new reality. With new arising necessities, several advancements have been made to help bridge the gap in our old way of life and our new, albeit forced reality. Education has been revolutionized out of necessity as well. Schools and universities have shifted to online mode in order to continue educating the future generations. But this has had its limitations. The goal of our research is to enable educators to seamlessly communicate and learn like they would on through regular blackboard. We have actuated with the use of computer vision and camera to capture their ideas onto the computer screen. Our approach involves a virtual keyboard that can be interfaced with hand gesture for providing input onto the system at a desired text area. Also, a virtual drawing system is developed that can capture finger movement and accurately draw, thereby envisioning free hands teaching gestures onto the screen. © 2022 IEEE.
ABSTRACT
Depression is an unfamous mental health disorder that has affected half the population worldwide. In December 2019, the break of the COVID-19 pandemic was first spotted in Wuhan, China, and later spread to 212 countries and territories worldwide, impacting half the population. It took a significant toll on their physical health and their mental health. Many among the population lost their loved ones, businesses, and being in quarantine for years, completely shifted to the online mode made everyone's life miserable. Many may be dealing with escalated levels of alcohol and drug use, sleeplessness, and an anxious state of mind. So, the need to address this and help the severely affected ones is significant. Self-quarantine also causes additional stress and challenges the mental health of citizens. This paper intends to identify the people who were mentally affected by the pandemic using machine learning techniques. A survey was conducted among college-going students and professionals. The paper used classification techniques such as Naive Bayes, KNN, Random Forest, Logistic Regression, k-fold cross-validation to get results. Support Vector Machine gave the maximum accuracy of 99.35%. © 2022 IEEE.