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After two years of online learning, minor changes happened in some tiny places which we may not always notice. These changes may impact the school management, education arrangement, and curriculum design: what do students expect from their teachers, and the school? Are they expecting forever online learning, and getting their degree completely online? In this study, we examined 93 final-year students from the school of computing science which mainly used work-based learning applied to learn pedagogy. We analyze their viewpoint on how COVID-19 changed their understanding of teaching and learning: what is the role of teachers and students? And how do they see the arrangement for the internship program? We found that over 92% of students agree that a creditable degree can better secure a job;over 68% of the students believed that face-to-face teaching is still a better choice, but at the same time, over 73% wish to have the materials recorded so that they can access them at their convenience time. We also examined some of the course design elements, especially those related to the internship program, to achieve a possible curriculum improvement for the students in the Asia Pacific region. © 2022 ACM.
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This study explores the online education action for defeating COVID-19 in China from the perspectives of the system, mechanism and mode. In particular, the policy development of online education in China during the epidemic includes the education informatization policy, the online education system, and the online education mechanism in China. The online education and teaching mode during the epidemic involve the synchronous live class-based teaching mode, asynchronous recording and broadcasting teaching mode, online flipped classroom teaching mode, and online tutoring-based teaching mode. Both characteristics and trends of online education in China during the epidemic have been explored in this study. In addition, the problems, discussions and remarks are also offered.
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An outbreak of a respiratory sickness started in Wuhan, China in December 2019 and the causative agent was found be a novel betacoronovirus of the same subgenus as SARSCoV and named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Coronavirus disease 2019 (COVID-19) quickly spread around the world, with clinical signs ranging from mild respiratory symptoms to severe pneumonia and a fatality rate estimated around 2%. Lower respiratory tract infections can occur in immunocompromised subjects and the elderly persons. Respiratory droplets are the causative agent for the person-to-person spread of the disease resembling the spread of influenza. Individual to individual spread turned into the primary mode of transmission. The transmission of the disease might be more likely in the earlier stage of infection as the viral RNA levels appear to be higher. Accurate diagnosis in the early stages of the epidemic helps control the spread of the disease. [ FROM AUTHOR] Copyright of Indian Drugs is the property of Indian Drug Manufacturers' Association (IDMA) 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.)
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The increasing use of online surveys (CAWI) is a trend that became more pronounced in the wake of the COVID-19 pandemic. The switch from face-to-face interviews to online surveys raises the question of mode effects. Do the results of online surveys differ from those based on telephone interviews? This study examines this question using data from the AKCOVID Panel Survey, which has a mixed-mode design and was conducted in the first year of the COVID-19 pandemic. The results of regression analyses for 46 different variables controlling for the sample characteristics of CAWI and CATI show that mode effects are topic-specific. For some topics, significant and substantial mode effects are estimated (social trust, worries about the future, financial problems and health). When people are interviewed by telephone, they answer more socially desirable, express worries less strongly, assess their financial situation, social status and health better, report more trust in other people, and present themselves as more prosocial than in CAWI interviews. Not or less affected by mode effects are 'factual' questions about crisis-related changes in income without reference to one's financial situation, questions about working conditions, family relations, or a range of political attitudes. The paper concludes that results of interviewer-led surveys from pre-pandemic times can often not be directly compared with current results based on online surveys and points to the importance of heterogeneous mode effects that are hitherto under-researched. © 2023, The Author(s).
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Online shopping has revolutionized our daily lives in the modern era. We can purchase needed goods on mobile shopping applications (apps) anytime and anywhere without leaving home. Especially during the COVID-19 pandemic, we have become increasingly dependent on various mobile shopping activities. However, the visual design of the shopping app interface often affects the user's interactive experience and the efficiency of browsing product information. In addition, gender differences are also worth being considered in the shopping interface design process. To achieve the goal, the research conducted a user study (N=40) of a 2× 2 x 2 mixed factorial design (i.e., information layout x display mode x gender difference). Each participant performed four tasks during the experiment. The authors measured the task completion time, collected the subjective responses from the SUS and the 7-point Likert scale questionnaire, and interviewed participants. The results revealed that: (1) females perform faster in lighter mode when searching for information location, while males perform faster in darker mode. (2) The information layout affects the user's visual search performance and subjective evaluation;females prefer the list style, but men prefer the matrix style. (3) Participants (both males and females) perceived matrix style as more popular than list style in dark mode;however, the result was reversed in light mode. The findings generated from the research can serve as a good reference for the development of user experience in the user interface design of mobile shopping apps. © 2013 IEEE.
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Travel choices in terms of means of transport and frequencies have changed during the recent pandemic period due to mobility restrictions, the growing fear of contagion and, especially in some months, the reduction of public transport capacity during the phases of the pandemic (especially for low demand areas). These trends must be analysed in order to optimize the implementation of possible complementary solutions to fill the deficit of local public transport (TPL) by introducing for example the Demand Responsive Transport services (DRT). A preliminary analysis is useful to identify the most efficient, effective and sustainable solutions in the various contexts, taking into account users and their motivation to travel. A growing need for "on-demand" mobility is linked to the increase in the number of elderly and disabled people. With a lack of alternative services and a reluctance to bear the burden and cost of ownership of vehicles, transport infrastructure will be particularly important to this aging population. Therefore, the improvement of transport services must consider some main characteristics of this modal choice are: being user-oriented;guarantee the accessibility of the service via the web, on specific platforms available on fixed and mobile devices and also enjoy the versatility of use with reference to the areas and users to be served. The present work, therefore, focuses on an evaluation of the literature, defining the main characteristics of DRT in Europe over the last twenty years. The results lay the foundations for a better planning of the service in the post-pandemic phase and a diffusion of bottom-up approaches for the calibration of the service itself through the dissemination of survey campaigns. © 2023 The Authors. Published by ELSEVIER B.V.
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Novel coronavirus disease (COVID-19), caused by the virus (SARS-CoV-2), has drastically impacted human beings' lives since early 2020. The virus is constantly changing, and with mutations, it becomes diverse and spreads more easily. Several automatic COVID-19 diag-nostic tools are proposed that emphasize feature extraction mechanism from radiographical images using modern deep learning technology. The general idea is to leverage smart solutions of pre-trained networks for deep-feature processing. However, all the extracted features may not essentially contribute to the performance of the COVID-19 diag-nostic model, and hence an optimal subset of features must be discov-ered. Motivated by this, we propose a novel feature selection method based on multi-operator differential evolution (MODE), which helps to acquire optimal feature-subset. To show the efficacy of the proposed algorithm, we focus on applying the COVID-19 classification model through medical imaging. Eight advanced pre-trained architectures have been selected for COVID-19 feature extraction from CT-scan medi-cal imaging. After that, the proposed feature selection technique based on MODE is applied. A customized SVM kernel is implemented that supports feature classification. The result analysis shows the perfor-mance of the existing COVID-19 designs with the proposed feature selection technique, MODE, integrated with a customized SVM kernel. It even beats the existing state-of-the-art frameworks carried forward for COVID-19 diagnosis. We have observed that MODE feature selec-tion is suitable for fast COVID-19 detection, having overall accuracy of 85.27%.
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OBJECTIVES: During the first 3 months of the coronavirus disease 2019 (COVID-19) pandemic, our hospital's quality management team determined a decline in the rate of cesarean deliveries (CD). Thus, in this study we examined both the factors associated with this decrease as well as neonatal outcomes. METHODS: This was a retrospective observational cohort study comparing deliveries (n=597) between March and May 2020 (first nationwide "lockdown" in Switzerland) with those during the same period in 2018 and 2019 (n=1,063). A multivariable logistic regression analysis was used to examine the association between CD and the pandemic, adjusting for relevant risk factors for CD. RESULTS: The overall rate of CD during the pandemic period was lower (30.0%), than during the pre-pandemic period (38.7%, unadjusted odds ratio 0.68, 95% confidence interval [95%CI]: 0.55 to 0.84, p=0.0004) a result that was supported by the adjusted odds ratio (0.73, 95%CI: 0.54 to 0.99, p=0.04). CONCLUSIONS: The results of this study confirmed a significant reduction in the rate of CD in early 2020, during the first lockdown period due to COVID-19, but without major differences in maternal and infant health indicators or in obstetric risk factors than before the pandemic. These results may have been due to a difference in the composition of the obstetric team as well as the behavior of the obstetrics team and in the patients during the pandemic, given the burden it placed on healthcare systems. However, this hypothesis remains to be tested in further research.
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Growing Up in Ireland (GUI) is the national longitudinal study of children and young people in the Republic of Ireland and has followed two cohorts for over ten years to date: Cohort '98 who were recruited into the study at age nine years and Cohort '08, recruited at age nine months. The study aims to describe the lives of Irish children and young people in terms of their development, with a view to positively affecting policies and services available for them. Traditionally, data collection involved in-home visits from an interviewer who conducted face-to-face interviews, recorded physical measurements of study participants and administered cognitive assessments. However, with the onset of the COVID-19 pandemic and the associated restrictions, significant adaptations were required to these methods to ensure data collection for the pilot and main fieldwork for Cohort '08 at age 13 could continue to the expected timeline. Face-to-face interviews with participants were replaced with telephone and web-based modes, interviewer training was conducted online, online resources were made available for interviewers and participants and COVID-19 related items were added to questionnaires. In addition to the scheduled data collection, a special COVID-19 survey was also conducted on both GUI cohorts in December 2020 to explore the impact of the pandemic on participants' lives. This paper outlines the adaptations made to traditional data collection methods in GUI, highlighting the challenges that were met, but also the benefits of some changes that may be worth incorporating into future waves of GUI.
Subject(s)
COVID-19 , Child , Humans , Adolescent , Infant , COVID-19/epidemiology , Cohort Studies , Pandemics , Longitudinal Studies , Ireland/epidemiology , Surveys and QuestionnairesABSTRACT
Awarding gaps between various groups of students persist across the Higher Education sector, yet the responses designed to address the contributors remain localised. The sudden spread of COVID-19 led to various responses across the University sector creating an unprecedented natural experiment and offering the opportunity to compare outcomes from these measures with prior cohorts. This study seeks to investigate the effects of two COVID-19 interventions on students' performance in the Business and Management discipline at a UK university. The specific COVID-19 measures considered here are the move to online assessments and the new grade policy to ensure the pandemic did not affect students' outcomes adversely. We use a Kernel Propensity Score and a Quantile Difference in Differences models to estimate the treatment effect of the two COVID interventions on the treated group, namely term two students' performances of the academic year 2019/20. Our results indicate that the effects of both COVID interventions supported the outcomes of international students, thereby narrowing the awarding gap. Findings suggest firstly that institutional policies adopted in crises should seek to address potential adverse effects on student outcomes for the period of disruption, indicating that significant care should be taken in their drafting. The policy, in this case, was found to have achieved its aim. Secondly, the move to new modes of assessment combined with detailed briefings from faculty may have served to uncover aspects of the hidden curriculum for this group, contributing to a narrowing of awarding gaps between different groups of students.
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PurposeThis paper investigates the probable differential impact of the confirmed cases of COVID-19 on the equities markets of G7 and Nordic countries to ascertain possible interdependencies, diversification and safe haven prospects in the era of the COVID-19 pandemic over the short-, intermediate- and long-term horizons.Design/methodology/approachThe authors apply a unique methodology in a denoised frequency-domain entropy paradigm to the selected equities markets (Li et al. 2020).FindingsThe authors' findings reinforce the operability of the entrenched market dynamics in the COVID-19 pandemic era. The authors divulge that different approaches to fighting the pandemic do not necessarily drive a change in the deep-rooted fundamentals of the equities market, specifically for the studied markets. Except for an extreme case nearing the end (start) of the short-term (intermediate-term) between Iceland and either Denmark or the US equities, there exists no potential for diversification across the studied markets, which could be ascribed to the degree of integration between these markets.Practical implicationsThe authors' findings suggest that politicians should pay closer attention to stock market fluctuations as well as the count of confirmed COVID-19 cases in their respective countries since these could cause changes to market dynamics in the short-term through investor sentiments.Originality/valueThe authors measure the flow of information from COVID-19 to G7 and Nordic equities using the entropy methodology induced by the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN), which is a data-driven technique. The authors employ a larger sample period as a result of this, which is required to better comprehend the subtleties of investor behaviour within and among economies - G7 and Nordic geographical blocs - which largely employed different approaches to fighting the COVID-19 pandemic. The authors' focus is on diverging time horizons, and the ICEEMDAN-based entropy would enable us to measure the amount of information conveyed to account for large tails in these nations' equity returns. Furthermore, the authors use a unique type of entropy known as Renyi entropy, which uses suitable weights to discern tailed distributions. The Shannon entropy does not account for the fact that financial assets have fat tails. In a pandemic like COVID-19, these fat tails are very strong, and they must be accounted for.
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Change in activity patterns and travel behaviour were seen worldwide as a response to the COVID-19 pandemic. This is mainly due to the restrictive measures imposed by the government and perception of own safety or commitment in reducing the spread of the disease. However, with or without the restrictive measures, people still have various needs to travel. Thus, this study was initiated to understand the changes in travel behaviour due to the COVID-19 pandemic. An online questionnaire survey, including questions related to purpose of travel, transport mode choice, distance and frequency of trip was conducted. Findings from this study revealed that there is a significant change in activity pattern and travel behaviour, before and during the COVID-19 pandemic. Based on the 460 responses received, it is known that mode shifts, from public transportation to private vehicles, occurred mainly due to pandemic related concerns. This study reveals that people perceived public transportation as a potential risk for exposure of the COVID-19 virus, while private vehicles, bicycles and walking are viewed as the safest mode of transport during the pandemic. Gender, age group, vehicle ownership, marital status and purpose of travelling had significant impact on the mode choice during the pandemic. Based on these findings, it is hoped that rail and bus transport service providers will be able to plan measures and further encourage the usage of the rail and bus transport services post-pandemic.
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Currently, society is entering a new crisis in the historical phase of society namely post-truth reality. The crisis arises when the mixing of real and fake information is reproduced through social media by the digital actors. It has put new problems of social analysis particularly to understand the meaning and direction of social actions. This article aims at answering the crisis of the digital society with the elaboration of theoretical discourse of interest. Social scientists from various schools have placed interest as the basic concept to analyze social life. However, the sociological elaboration of the theory of interest stops among the great edifices of all schools of social theory. Therefore, this article is a proposal for developing a theory of interest to track the mode of reality, particularly in the digital society. The research method of this study is an eclectic literature review of interest theories and participative observation in Indonesia's digital society during 2019-2021. This study finds that digital actors produce and reproduce symbolic language on social media by confounding true and false information or post-truth in the dynamics of the COVID-19 pandemic policy. The symbolic language of digital actors does not only mean violating the rules in a digital society, but also expresses certain social interests including certain needs or aspirations.
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The global tourism industry is struggling to recover from the COVID-19 pandemic. During the COVID-19 pandemic, daily tourism forecasting is more critical than ever before in supporting decisions and planning. Considering the changes in tourist psyche and behaviour caused by COVID-19, this study attempts to investigate whether the statistical modelling methods can work reliably under the new normal when travel restrictions are eased or lifted. To this end, we first compare the predictivity of daily tourism demand data before and during COVID-19, and observe heterogeneous impacts across different geographical scales. Then an improved multivariate & multiscale decomposition-ensemble framework is proposed to forecast daily tourism demand. The empirical study indicates the superiority and practicability of the proposed framework before and during COVID-19. Finally, we call for more research on the comparability of tourism demand forecasting.
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Mingling, the activity of ad-hoc, private, opportunistic conversations ahead of, during, or after breaks, is an important socializing activity for attendees at scheduled events, such as in-person conferences. The Covid-19 pandemic had a dramatic impact on the way conferences are organized, so that most of them now take place in a hybrid mode where people can either attend on-site or remotely. While on-site attendees can resume in-person mingling, hybrid modes make it challenging for remote attendees to mingle with on-site peers. In addressing this problem, we propose a collaborative mixed-reality (MR) concept, including a prototype, called HybridMingler. This is a distributed MR system supporting ambient awareness and allowing both on-site and remote conference attendees to virtually mingle. HybridMingler aims to provide both on-site and remote attendees with a spatial sense of co-location in the very same venue location, thus ultimately improving perceived presence. © 2023 Owner/Author.
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This research regards the COVID-19 pandemic as a major life event with the ability to affect daily activity-travel behavior, and investigates if specific activity participation (work/study, shopping, social contact, free time) is associated with different travel modes (walk, cycle, car, public transportation), with attention paid to residential neighborhood using survey data (n = 854) in Flanders, Belgium. Through mean-comparison tests and regression analyses, evidence was found of (1) compensation for changed working/studying time with walking time, (2) compensation for changed social contact with cycling, and (3) similarly affected travel behavior regardless of residential neighborhood, though suburban residents may have more mode-resilience and less reliance on public transportation. Further evidence indicate that those working/studying may have taken advantage of decreased traffic and congestion with an increase in car and public transportation use and that older respondents may be more likely to hold flexible, teleworkable jobs and treat the pandemic with greater caution. Some travel behavior changes are expected to persist post-pandemic, therefore understanding which life domains are associated with which travel modes can inform policy aiming to decrease motorized and increase active mode use (e.g., for health or sustainability goals). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
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The COVID-19 pandemic has relatively affected the Norwegian context and other Nordic countries (except for Sweden), considering the prudential authorities and policies adopted during the various waves of the virus. The capacity for remote working and high flexibility of working (already observed before the pandemic) have contributed to adapt to the changes. In this context, the study aims to explore the ways of working and living during the Corona Times and the implications for planning and mobility in Norway, considering the short-medium and long-term effects of the pandemic. First, the study presents an overview of the main impacts of the pandemic in the Nordic countries (such as mortality, labour market and absence from work, including the closure of workplaces), and second, it focuses on Norway, in light of the national measures. Then, the working related trends (for example, growth of demand of new working spaces and the increased number of workers in the public libraries) are discussed, as well as the major implications for our cities, such as new housing demands, commuting habits and transportation modes. Finally, an overview of the current debate within the Norwegian society shows the high interests of planners, other experts, and media in understanding the future of work, such as hybrid forms, new jobs, working remotely (but from where?). © 2023, The Author(s).
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Travel choices in terms of means of transport and frequencies have changed during the recent pandemic period due to mobility restrictions, the growing fear of contagion and, especially in some months, the reduction of public transport capacity during the phases of the pandemic (especially for low demand areas). These trends must be analysed in order to optimize the implementation of possible complementary solutions to fill the deficit of local public transport (TPL) by introducing for example the Demand Responsive Transport services (DRT). A preliminary analysis is useful to identify the most efficient, effective and sustainable solutions in the various contexts, taking into account users and their motivation to travel. A growing need for "on-demand" mobility is linked to the increase in the number of elderly and disabled people. With a lack of alternative services and a reluctance to bear the burden and cost of ownership of vehicles, transport infrastructure will be particularly important to this aging population. Therefore, the improvement of transport services must consider some main characteristics of this modal choice are: being user-oriented;guarantee the accessibility of the service via the web, on specific platforms available on fixed and mobile devices and also enjoy the versatility of use with reference to the areas and users to be served. The present work, therefore, focuses on an evaluation of the literature, defining the main characteristics of DRT in Europe over the last twenty years. The results lay the foundations for a better planning of the service in the post-pandemic phase and a diffusion of bottom-up approaches for the calibration of the service itself through the dissemination of survey campaigns. © 2023 The Authors. Published by ELSEVIER B.V.
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In 2019, a pandemic of the so-called new coronavirus (SARS-COV-II) began, which causes the disease COVID-19. In a short time after the first case appeared, hundreds of countries began to register new cases every day. Mapping and analyzing the flow of people, regardless of the mode of transport, can help us to understand and prevent several phenomena that can affect our society in different ways. Graphs are complex networks made up of points and edges. The (geo)graphs are graphs with known spatial location and, in the case of our study, the edges represent the flow between them. The (geo)graphs proved to be a promising tool for such analyses. In the study region, municipalities that first registered their COVID-19 cases are also municipalities that have the highest mobility indices analyzed: degree, betweenness and weight of edges. © 2022 National Institute for Space Research, INPE. All rights reserved.
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The COVID-19 pandemic led to a sudden shift to virtual work and events, with the last two years enabling an appropriated and rather simulated togetherness - the hybrid mode. As we return to in-person events, it is important to reflect on not only what we learned about technologies and social justice, but about the types of events we desire, and how to re-design them accordingly. This SIG aims to reflect on hybrid events and their execution: scaling them across sectors, communities, and industries;considering trade-offs when choosing technologies;studying best practices and defining measures of "success"for hybrid events;and finally, identifying and charting the wider social, ethical, and legal implications of hybrid formats. This SIG will consolidate these topics by inviting participants to collaboratively reflect on previous hybrid experiences and what can be learned from them. © 2023 Owner/Author.