ABSTRACT
This research aims to grasp the evolution of consumer demand and improve the resilience of the hotel industry under the public health crisis (COVID-19). Online reviews of 7,679 hotels in 10 cities were collected from Ctrip, China's major online hotel platform. Then, we applied opinion mining and time evolution to mine the change in consumer demand before, during, and after the COVID-19 pandemic. Findings show that some consumer demands (e.g. epidemic safety) will change during the outbreak period. However, during the nonoutbreak period, users were more concerned about their own check-in experience (e.g. hotel facilities, front desk services). This article provides new ideas for identifying the dynamic value of online reviews. We suggest that businesses focus on ensuring hotel safety during the crisis period. The results contribute essential theoretical and practical significance to the hotel industry's crisis management during public health crises.
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In automated scientific fact-checking, machine learning models are trained to verify scientific claims given evidence. A major bottleneck of this task is the availability of large-scale training datasets on different domains, due to the required domain expertise for data annotation. However, multiple-choice question-answering datasets are readily available across many different domains, thanks to the modern online education and assessment systems. As one of the first steps towards addressing the fact-checking dataset scarcity problem in scientific domains, we propose a pipeline for automatically converting multiple-choice questions into fact-checking data, which we call Multi2Claim. By applying the proposed pipeline, we generated two large-scale datasets for scientific-fact-checking: Med-Fact and Gsci-Fact for the medical and general science domains, respectively. These two datasets are among the first examples of large-scale scientific-fact-checking datasets. We developed baseline models for the verdict prediction task using each dataset. Additionally, we demonstrated that the datasets could be used to improve performance measured by weighted F1 on existing fact-checking datasets such as SciFact, HEALTHVER, COVID-Fact, and CLIMATE-FEVER. In some cases, the improvement in performance was up to a 26% increase. The generated datasets are publicly available. © 2023 Association for Computational Linguistics.
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Background: On-line education in a way was a forced introduction in our education system in wake of COVID-19 pandemic. Teachers as well as students became a part of this shift in education delivery mostly by force and rather by choice. However, in the short run itself it was realised that while shifting to this new-medium has its own challenges it also comes with its own set of advantages. Background: This research paper attempts to study and analyse the perception of teachers in hospitality education towards on-line education. Objective of study is to identify the major challenges and benefits of hospitality education as perceived by faculty members. Methodology: Descriptive research design was employed. The study was conducted by administering a structured questionnaire among faculty members of various IHMs and analysis of data was done. Locale is pan-India reached through google questionnaire method with a sample size of 50 faculty members from different IHMs in the country. Data was analysed with the help of excel tools, bar diagrams and graph. Results: Research revealed that in spite of the sudden paradigm shift in the macro environment faculty members responded well to the challenge of optimising learning for students in an on-line mode. Initially 80% faculty members found this shift challenging but now 80 percent believe that blended learning is future. Assessments and sustaining interest of students however are major challenges with 82 and 84 percent of faculty members respectively agreeing to this being a major issue. Conclusion: Teachers perceive blended learning to be a norm in future. It is perceived that while it's very difficult to impart skill training in an on-line mode, for theoretical classes this could be a preferred mode.
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The COVID-19 pandemic had a significant impact on medical care and medical education in Peru. In response, the Peruvian American Medical Society (PAMS), a charitable medical organization based in the USA, pursued its medical and educational missions in Peru by adopting virtual learning technology. We developed closer collaborative relationships with several medical schools and the Peruvian Association of Medical Schools (ASPEFAM) while offering a faculty panel of twenty-four members to provide lectures and multidisciplinary webinars in Spanish. We conducted 19 webinars including COVID -19 and non-COVID-19 related topics that over the last two years attracted 14,489 participants from 23 countries. They were the foundation for twenty publications in Peruvian medical journals. Our clinical investigations competition was positively received as was our pilot project on research mentorship. The COVID -19 pandemic had a positive effect on the educational mission of PAMS in Peru.
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The widespread of (covid-19) has become the major reason for many physical illnesses in addition to psychological encounters to the whole world. The psychological challenges brought in due to the Covid-19 pandemic have resulted in decrease in the learning curve of students to a very large extent risking the academic ability of students due to psychological/mental health. Hence it is a challenge to identify valid cues for disorientation in the learning ability of the student at the right time and to suggest necessary support and guidance. This paper aims to describe about the work done so far and analyzes the future challenges to be addressed based on the learning curve of a student and gives an insight of how a student can be identified to be psychologically disturbed. © 2023 IEEE.
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Online teaching management has been widely used during the COVID-19 pandemic situation and it has a direct impact on practical teaching management because students do not have access to equipment, chemicals, and tools. This study's purpose is to evaluate practical learning instruction management and student satisfaction with "photocolorimetric methodology platform for measuring egg yolk color" during the COVID-19 pandemic. This study compared the student satisfaction and effectiveness of a learning instruction platform for measuring egg yolk color using a laboratory machine and an online teaching management platform using photocolorimetric methodology. The results of this experiment revealed that the two platforms evaluated yolk colors L*, a*, and b* similarly (P > 0.05). Furthermore, the students were satisfied with the learning instruction with the photocolorimetric methodology platform for measuring egg yolk color at 4.76 points or the most level.
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In this paper, we investigate the problems of the behavior of social media within the framework of reliable and unreliable information that they offer, as well as the issue of the security of certain distributed and mobile online systems in the era of the COVID 19 virus pandemic. In the wake of coronavirus disease (COVID-19), many turned to social media for information and guidance. There are both positive and negative aspects to this behavior. These range from the spread of misinformation to the indispensable role social media has played in the dissemination of accurate information and mental health education. This article looks at both the challenges and benefits, considering who is potentially more likely to use social media and thus be impacted by the information imparted on the digital platforms that are now an integral part of our daily lives.
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The application and effects of the project-based learning (PBL) model have been carried out in various majors and courses, and the results analysed in several studies. This study was focused on the Covid-19 pandemic period from 2020 to 2022 to discuss lessons and effects of applying an on-line and off-line PBL model to engineering economics courses for engineering students in 2021 and 2022 compared with a simple on-line course in 2020 without PBL. Project teams consisting of three-four students carried out on-line collaborative learning to solve open-ended problems through a four-step PBL procedure including presentation of the final result. Except for this PBL application in 2021 and 2022, textbooks, lecture contents, assignments and tests were implemented in the same way for each semester over these three years. Through lecture evaluation and a simple survey for students, the semesters with PBL showed higher effects in inducing student-led learning and lecture satisfaction compared to the semesters without it. Further, it was established that the PBL application to the course and the evaluation method were more appropriate than the approach in other semesters. It is expected that the PBL method and operation procedure outlined in this article could be utilised as a best practice for various on-line and mixed courses in student-led collaborative learning activities to achieve better educational effects and satisfaction. © WIETE 2023.
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With rapid proliferation of digitalization and compulsion by COVID-19 pandemic, learning formats have been changing from face-To-face to online. Online education enables learners to take courses from anywhere, anytime, but it can also cause some problems for learners who struggle to maintain motivation. In addition, for STEAM education, it is important to engage in hands-on activities, but the ongoing pandemic has made it difficult for students to gather in one place to perform such activities. Incorporating gamification into online education can potentially motivate students and make STEAM education more interactive. On this premise, we have developed PhyGame as a learning system to help high-school students learn Physics. The system includes common game elements such as badges and leaderboards, and interactive simulation of Physics concepts embodying game-like charm. It also includes three modes of learning that allow students to adjust the difficulty according to their own learning levels, and a function that automatically saves learning log. For evaluation, PhyGame was used by students (N=23) at a high school in central Tokyo. The students rated the system on a scale of 1 to 10, and the main results are as follows: (1) Using PhyGame made learning enjoyable (mean score: 7.74);(2) PhyGame provided a good UI/UX (mean score: 7.83);(3) The overall experience with PhyGame was satisfactory (mean: 7.00). Our evaluation results show that interactive and gamified learning systems like PhyGame have a positive impact on user engagement and motivation. © 2023 IEEE.
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For a better understanding of the COVID-19 pandemic impact over the medical education methods used by medical personnel, we have made a study using a standard form in which we have applied targeted questions regarding the methods used in medical education before and after the pandemic. This study followed the motivation and selection criteria of medical education forms before and after the pandemic, the advantages and disadvantages noed by attendees through onsite and online, also including suggestions for the future of medical education. The number of participans in online courses and the time assigned for online medical education has increased, compared to the period before pandemic. During the pandemic, has been recoreded a reorientation of participans on online platforms, following the utilization of those platforms which allow uploading files as well as free interaction between students and lecturer. The advantages and disadvantages, noted in medical personnel training, are counterbalanced in both of education online - onsite forms (exemple: the interaction with the lecturer and also between the students at medical meetings, has been the main advantage of medical education onsite and the major disadvantage of online education). The majority of study participants consider, for the futere, the combined use of both online and onsite professional training methods, and, therefore the participans can decide on what method of education should use.
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Supportive digital technologies for the community practice of Faith remain relatively under-explored in Human Computer Interaction (HCI). We report on interviews with 12 members of a Buddhist community in the UK who self-organized and used video-conferencing tools to remain connected to their faith community during the COVID-19 pandemic, aiming to understand how they adopted online tools for their practice while shaping new collective experiences. Findings from Reflexive Thematic Analysis were combined with autoethnographic insights from the first author, also a community member. We evidence qualities of the practice that were valued by participants before and during the pandemic, and the limitations of existing tools and screen-based interactions. We contribute empirical insights on mediated religious and spiritual practice, advancing HCI discourses on Techno-Spirituality, Tangible Embodied Interaction, Soma Design and More-than-Human Worlds. We further develop design considerations for enriching spiritual experiences that are meaningful to practitioners in communities of faith. © 2023 Owner/Author.
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Online banking has been proven to be an effective and convenient way of providing banking services anywhere and has been a necessity since the COVID-19 pandemic has affected the Philippines. Alongside this fact, people have been victims of scams involving these online services. Therefore, this paper aimed to analyze reports of online banking scams reported on social media using content analysis. The 26 filtered posts are labeled with 27 codes generated, and the top six were discussed. Specifically, scam (88.46%) was the most common code, followed by phone calls (57.69%) and impersonation (53.84%). Benefits, verifying personal information, and social engineering all had 46.15% occurrences. It is recommended for potential online banking scams to verify with the bank before giving away information, and to raise awareness on the possible technique's scammers use. © 2023 ACM.
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Machine learning extracts models from huge quantities of data. Models trained and validated over past data can be deployed in making forecasts as well as in classifying new incoming data. The real world which generates data may change over time, making the deployed model an obsolete one. To preserve the quality of the currently deployed model, continuous machine learning is required. Our approach retrospectively evaluates in an online fashion the behaviour of the currently deployed model. A drift detector detects any performance slump, and, in case, can replace the previous model with an up-to-date one. The approach experiments on a dataset of 8642 hematochemical examinations from hospitalized patients gathered over 6 months: the outcome of the model predicts the RT-PCR test result about CoViD-19. The method reached an area under the curve (AUC) of 0.794, 6% better than offline and 5% better than standard online-binary classification techniques. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR Workshop Proceedings (CEUR-WS.org)
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The COVID-19 pandemic caused several short- and mid-term disruptions, to which businesses must adapt. The main goal of this research is to investigate the impact of e-traders response to Covid-19 challenges on online growth. Using existing survey data results linear multiply regression was performed and statistically significant results confirmed that online growth during the Covid-19 emergency was higher in the companies that undertake marketing and delivery adaptation. Further, it was confirmed that e-traders that were selling traditionally and online made higher online growth. Companies with fewer employees were more adaptable to reach higher online growth. Online growth obviously was affected by online sales, and online visits do not statistically significantly influence online growth. The e-traders that believe in the potential for e-commerce in North Macedonia have achieved higher online growth. The timing of the start of the online business does not affect the online growth of e-traders.
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The present study is related to the problem associated with student assessment with online examinations at higher educational institutes (HEIs). With the current COVID-19 outbreak, the majority of educational institutes are conducting online examinations to assess their students, where there would always be a chance that the students go for malpractice. It is difficult to set a question paper for any technical course with great novelty. Under these circumstances, safeguarding academic integrity has become a challenge for HEIs. This study is aimed at improving the quality of questions for online exams to increase the accountability of HEIs by proper evaluation of their students. A detailed procedure with suggestions for setting the questions for technical courses, in the format of assertion and reason, matching, multiple select types, etc., has been discussed with adequate examples. It deals with a strategy for ensuring that all the students are held to the standards that are reflected in their grades. The proposed evaluation method has been implemented on a test batch and presented the results along with a comparison with that of traditional question papers. It is witnessed that there is a simultaneous enhancement of students'learning as an additional benefit of implementing the proposed learning-oriented assessment method. IEEE
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A survey of UK fertility counsellors' experiences of the impact on their service, including its availability, during the first phase of the COVID-19 pandemic in the spring of 2020 received 64 responses. Fifty three respondents had continued to provide a service. Forty now worked from a wholly/substantially different location to normal but many clinics provided no practical support for this (n = 17), or remote access to relevant clinic (n = 17) or client information (n = 12) and twenty five respondents reported reduced multi-disciplinary involvement. Few received regular information updates. Some whose service was stopped (n = 11) abruptly lost income and/or were unsure whether they could or would resume working. Increased remote counselling proved crucial for accessibility and could be effective. Concerns included fatigue, technical and practical challenges, confidentiality, lowered therapeutic effectiveness. Respondents supported patients having choice over how to receive counselling in the future but a third (n = 21) had not been included in such planning. These findings suggest the need for increased involvement and support of fertility counsellors in the event of a future waves, other pandemic or healthcare crisis. More needs to be understood about why clinic responses varied; how to improve the safety and efficacy of remote counselling; and how to accommodate future needs for face-to-face contact.
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This paper analyzes the role of Canadian online news media in framing travel during the pandemic. The article applies Altheide's concept of the problem frame to reflect how news media contribute to the emergence of a highly rationalized problem that, in turn, generates a discourse of fear. While the impacts of COVID-19 on tourism have been extensively examined within tourism scholarship, less attention has been devoted to the impact of news media. Because travel and the pandemic are heavily intertwined, discourse analysis can help process media narratives, furthering our understanding of their role in influencing perceived risk of travel. A critical discourse analysis of over 100 online news articles was conducted using thematic analysis to uncover themes in Canadian media sources and to explore how the media have framed travel during the pandemic. The role of online news media in promoting fear was communicated through the themes of anxiety, antitrust, avoidance, and animosity. The role of the media in producing the problem frame in the context of travel was examined as well as its implications for perceived travel risk and tourism demand. The power dynamics between media, government, and the citizens it serves are also discussed.
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The changes forced by the COVID-19 pandemic, have made educational institutions adopt new practices in the use of VLEs platforms and, one of these is to homogenize virtual classrooms, for which this study aims to diagnose how effective are the digital resources for cloned courses, taking as a pilot the subject of Linear Algebra. The development of this research is longitudinal, empirical-analytical, and quantitative. The study is carried out in two periods, from October 2021 to September 2022, at the Salesian Polytechnic University in the city of Guayaquil, Ecuador, with a total of 944 first year students of engineering careers. As a result, fewer courses for academic risk monitoring were obtained, as well as a higher satisfaction among students and professors involved. It is concluded that the cloned classrooms are a factor of improvement in the learning results to be achieved. © 2023 IEEE.
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With the onset of the COVID-19 pandemic, online education has become one of the most important options available to students around the world. Although online education has been widely accepted in recent years, the sudden shift from face-to-face education has resulted in several obstacles for students. This paper, aims to predict the level of adaptability that students have towards online education by using predictive machine learning (ML) models such as Random Forest (RF), K-Nearest-Neighbor (KNN), Support vector machine (SVM), Logistic Regression (LR) and XGBClassifier (XGB).The dataset used in this paper was obtained from Kaggle, which is composed of a population of 1205 high school to college students. Various stages in data analysis have been performed, including data understanding and cleaning, exploratory analysis, training, testing, and validation. Multiple parameters, such as accuracy, specificity, sensitivity, F1 count and precision, have been used to evaluate the performance of each model. The results have shown that all five models can provide optimal results in terms of prediction. For example, the RF and XGB models presented the best performance with an accuracy rate of 92%, outperforming the other models. In consequence, it is suggested to use these two models RF and XGB for prediction of students' adaptability level in online education due to their higher prediction efficiency. Also, KNN, SVM and LR models, achieved a performance of 85%, 76%, 67%, respectively. In conclusion, the results show that the RF and XGB models have a clear advantage in achieving higher prediction accuracy. These results are in line with other similar works that used ML techniques to predict adaptability levels. © 2023, International Journal of Advanced Computer Science and Applications. All Rights Reserved.
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This research examines the effect of digital innovation on the competitiveness and performance of hospitality businesses in Indonesia. This research was conducted with a quantitative research approach. Participants in this study are managers of hotel companies that implement online systems in Indonesia. The samples in this study were 218 respondents. Hypotheses are tested using the Structural Equation Modeling method and processed using Amos Software Version 23. The results show that there is a positive and significant effect between digital innovation on competitiveness, digital innovation and competitiveness also effect hotel business performance positively and significantly. We also found that competitiveness can mediate the effect of digital innovation on business performance. Therefore, we suggest improving business performance with enhancing competitiveness, to improve competitiveness can be done by increasing the implementation of digital innovation.