Breaking the Ice with Group Flow: A Collaborative VR Serious Game for Relationship Enhancement

It is usually hard for unfamiliar partners to rapidly 'break the ice' in the early stage of relationship establishment, which hinders the development of relationship and even affects the team productivity. To solve this problem, we proposed a collaborative serious game for icebreaking by combining immersive virtual reality (VR) with brain-computer interface based on the team flow framework. We designed a multiplayer collaboration task with the theme of fighting COVID-19 and proposed an approach to improve empathy between team members by sharing their real-time mental state in VR;in addition, we propose an EEG-based method for dynamic evaluation and enhancement of group flow experience to achieve better team collaboration. Then, we developed a prototype system and performed a user study. Results show that our method has good ease of use and can significantly reduce the psychological distance among team members. Especially for unfamiliar partners, both functions of mental state sharing and group flow regulation enhancement can significantly reduce the psychological distance. © 2023 IEEE.

How to find undetected cases of dementia in care homes: A new approach to dementia diagnosis using a diagnostic tool with five criteria to check and specialist nurses going into care homes and assessing residents could improve detection rates

The pandemic took its toll on memory clinics with many forced to close or scale back their services. This led to lengthening waits for dementia assessment and left many without a diagnosis.

Covid-19 Vaccination Stance Detection Using Natural Language Processing and Machine-Learning Algorithms

The coronavirus outbreak has resulted in unprecedented measures, forcing authorities to make decisions related to establishing lockdowns in areas most affected by the pandemic. Social Media have supported people during this difficult time. On November 9, 2020, when the first vaccine with an efficacy rate over 90% was announced, social media reacted and people around the world began to express their feelings about this vaccination. This paper aims to analyze the dynamics of opinion on COVID-19 vaccination, in which the civil society is highly manifested in the vaccination process. We compared classical machine learning algorithms to select the best performing classifier. 4,392 tweets were collected and analyzed. The proposed approach can help governments create and evaluate appropriate communication tools to provide clear and relevant information to the general public, increasing public confidence in vaccination campaigns. © 2022 Copyright for this paper by its authors.

Kaleidoscope: A Reflective Documentation Tool for a User Interface Design Course

Documentation can support design work and create opportunities for learning and reflection. We explore how a novel documentation tool for a remote interaction design course provides insight into design process and integrates strategies from expert practice to support studio-style collaboration and reflection. Using Research through Design, we develop and deploy Kaleidoscope, an online tool for documenting design process, in an upper-level HCI class during the COVID-19 pandemic, iteratively developing it in response to student feedback and needs. We discuss key themes from the real-world deployment of Kaleidoscope, including: tensions between documentation and creation;effects of centralizing discussion;privacy and visibility in shared spaces;balancing evidence of achievement with feelings of overwhelm;and the effects of initial perceptions and incentives on tool usage. These successes and challenges provide insights to guide future tools for design documentation and HCI education that scaffold learning process as an equal partner to execution. © 2023 Owner/Author.

Integrating deep learning algorithms for the lung segmentation and body-part-specific anatomical classification with Medical Imaging and Data Resource Center (MIDRC)

Medical Imaging and Data Resource Center (MIDRC) has been built to support AI-based research in response to the COVID-19 pandemic. One of the main goals of MIDRC is to make data collected in the repository ready for AI analysis. Due to data heterogeneity, there is a need to standardize data and make data-mining easier. Our study aims to stratify imaging data according to underlying anatomy using open-source image processing tools. The experiments were performed using Google Colaboratory on computed tomography (CT) imaging data available from the MIDRC. We adopted the existing open-source tools to process CT series (N=389) to define the image sub-volumes according to body part classification, and additionally identified series slices containing specific anatomic landmarks. Cases with automatically identified chest regions (N=369) were then processed to automatically segment the lungs. In order to assess the accuracy of segmentation, we performed outlier analysis using 3D shape radiomics features extracted from the left and right lungs. Standardized DICOM objects were created to store the resulting segmentations, regions, landmarks and radiomics features. We demonstrated that the MIDRC chest CT collections can be enriched using open-source analysis tools and that data available in MIDRC can be further used to evaluate the robustness of publicly available tools. © 2023 SPIE.

The impact of confinement by COVID-19 on the academic year. Case study: Gypsy pupils

The urgent virtualisation of academic activity in educational centres forced by the confinement decreed in Spain between the months of March and May 2020 posed a challenge previously unknown to the entire educational community. Information and communication technologies became essential tools to guarantee the continuity of the course. This situation highlighted the lack of technological equipment for the most vulnerable groups of the population and further increased the << digital divide >>, putting at risk the monitoring and school performance of pupils in these sectors. Among the most affected groups is that of gipsy students, as demonstrated in schools such as CEIP Nueva Segovia, (Segovia, Spain). This paper is the result of a qualitative and quantitative research carried out in this school, which has made it possible to identify and analyse the technological devices available to gipsy students, the perception of the different members of the educational community on the use of technologies and, finally, the training of these members in relation to new technologies. The results reveal the needs not only for equipment, but also for training in new technologies that both families and students have. These results show the importance of a new curricular approach for pupils with educational compensation needs to eliminate this situation of inequality.

Student-teacher out-of-class communication on engineering courses during the COVID-19 pandemic: from face-to-face to videocalls

Out-of-class communication between teachers and students is essential throughout university engineering courses for in-depth explanations of the concepts covered in class. This study evaluates this aspect throughout the COVID-19 pandemic. Thus, a survey that addressed this issue was administered to students at the beginning (March 2020) and at the end (May 2020) of the COVID-19 lockdown in Spain, and at the end of each semester of the 2020/21 and 2021/22 academic years. The results were analyzed with statistical, qualitative, and mixed methods. E-mail usage was widely observed at the beginning of the pandemic, while the use of online videoconferencing tools progressed during that time, thanks to their temporal and spatial flexibility, and the direct and personal nature of student-teacher contact through those channels. Its success was linked to the prior training of teachers in the use of videoconferencing, the establishment of fixed schedules for the meetings, and the use of digital whiteboards that instantaneously display writing when discussing problems. According to the opinions of students, videocalls could be used for questions on theoretical and easy practical aspects despite the resumption of out-of-class face-to-face meetings. Videoconferencing tools for educational communication between engineering students and teachers seem to be here to stay. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

Digital Transformation of Education Toward Successful Internships: A Methodology Developed Over Seven Years and Tested During COVID-19

Contribution: This article provides a teaching methodology which combines project-based learning, self-regulated learning (SRL), and design projects (DPs) to improve the preparedness of students for computing science-related internships. The methodology is supported by the implementation of the educational technology that transforms the way teaching and learning is transformed to benefit on-campus and off-campus students equitably, during the COVID-19 pandemic. Background: Success in the workspace is governed by the ability of an individual to learn on-the-job and independently. Online learning has led to a shift from instructor-led learning to SRL. This requires individuals to discipline themselves, and be in control of their learning and education. Outcome: The success of internships is improved with skills learnt in class through hands-on real-world projects. Both on/off-campus students gain equitable relevant experience. The teaching methodology developed over several years combines project-based learning, SRL, and DPs. Application Design: The methodology was applied using a flipped classroom approach. The educational technology was used to enhance SRL before in-class learning. This way, in-class rote learning was replaced with hands-on projects. Exam assessments were replaced with DPs where soft skills and technical skills are applied. Findings: The effectiveness of the developed methodology is measured through quantitative and qualitative evaluation tools. The evaluation demonstrates that combining well-designed education technology for SRL, with in-class project-based learning and DPs, can improve students' chances in getting high-impact internships.

ASSOCIATION RULE MINING FOR PREDICTION OF COVID-19

COVID-19 is a raging pandemic that has created havoc with its impact ranging from loss of millions of human lives to social and economic disruptions of the entire world. Therefore, error-free prediction, quick diagnosis, disease identification, isolation and treatment of a COVID patient have become extremely important. Nowadays, mining knowledge and providing scientific decision making for diagnosis of diseases from clinical datasets has found wide-ranging applications in healthcare sector. In this direction, among different data mining tools, association rule mining has already emerged out as a popular technique to extract invaluable information and develop important knowledge-base to help in intelligent diagnosis of distinct diseases quickly and automatically. In this paper, based on 5434 records of COVID cases collected from a popular data science community and using Rapid Miner Studio software, an attempt is put forward to develop a predictive model based on frequent pattern growth algorithm of association rule mining to determine the likelihood of COVID-19 in a patient. It identifies breathing problem, fever, dry cough, sore throat, abroad travel and attended large gathering as the main indicators of COVID-19. Employing the same clinical dataset, a linear regression model is also proposed having a moderately high coefficient of determination of 0.739 in accurately predicting the occurrence of COVID-19. A decision support system can also be developed using the association rules to ease out and automate early detection of other diseases. © 2023 by the authors.

Concern for Self-Health During the COVID-19 Pandemic in Canada: How to Tell an Intersectional Story Using Quantitative Data?

Rooted in Black feminism, intersectionality theory entered critical legal studies and travelled to public health and beyond. This chapter demonstrates one of many ways to apply intersectionality theory using a descriptive intercategorical approach to quantitative data. In so doing, I attempt to tell an intersectional story to make visible the intersectional inequalities for Canadians' concerns for self-health during the first wave of COVID-19 pandemic. For pedagogical purposes, I share a subset of Statistics Canada's COVID-19 Impacts Survey 2020 dataset of 239,143 participants and Stata code to encourage students to practice estimating intersectional outcomes and ask questions to explicate health inequalities. Although interrogating the systems of power is critical, this project does not statistically analyse but draws on the literature to discuss how interacting power structures might shape intersectional peoples' experiences. In addition, the analysed dataset is not representative of the Canadian population. Nonetheless, it might be helpful to showcase a case study on introductory-level quantitative intersectionality research. I hope, despite these limitations, this case study and the pedagogical tools will contribute to greater access to intersectionality research, generating a cadre of intersectionality data translators in public health. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Legal Education and Legal Profession During and Beyond COVID-19 Building Bonds Between Academia and Practice

Professor Suzanne Rab, professor of commercial law and practising international barrister and mediator offers a unique perspective on the challenges of digitisation and legal education in a post-COVID-19 world. Operating at the conflation of academia and practice Professor Rab explores the following themes using a blend of case study experience from the UK and from a comparative perspective: (1) the future of legal education in changing times;(2) the practitioner perspective and the digitised courtroom;(3) the academic experience and lived in experiences through COVID-19;(4) the role of online learning;(5) the implications for continuing legal education;(6) blended approaches to executive learning;(7) the impact on specific legal practices areas;(8) diversity and accessibility;(9) new world approaches to assessment of performance;and (10) humanising our legal education for the digital generation. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.

From Asymptomatics to Zombies: Visualization-Based Education of Disease Modeling for Children

Throughout the COVID-19 pandemic, visualizations became commonplace in public communications to help people make sense of the world and the reasons behind government-imposed restrictions. Though the adult population were the main target of these messages, children were affected by restrictions through not being able to see friends and virtual schooling. However, through these daily models and visualizations, the pandemic response provided a way for children to understand what data scientists really do and provided new routes for engagement with STEM subjects. In this paper, we describe the development of an interactive and accessible visualization tool to be used in workshops for children to explain computational modeling of diseases, in particular COVID-19. We detail our design decisions based on approaches evidenced to be effective and engaging such as unplugged activities and interactivity. We share reflections and learnings from delivering these workshops to 140 children and assess their effectiveness. © 2023 Owner/Author.

Through the Lens of Students: MS Teams as a Sustainable Pedagogical Tool

The COVID-19 pandemic has highlighted the need for higher education institutions to modernize and embrace the post-digital age. This study evaluates students' perspectives of utilizing MS Teams as a means of facilitating remote learning during the pandemic. The Technology Acceptance Model (TAM) was employed as the theoretical framework to examine students' views on self-efficacy, facilitating conditions, ease of use, usefulness, and intention to use. The results showcase positive views of MS Teams, with self-efficacy rated the highest among the five constructs, followed by ease of use, facilitating conditions, intention to use, and usefulness. Additionally, no significant differences were found in students' perceptions based on gender. MS Teams has proven to be a successful platform for delivering online learning and communicating, bridging the divide of distance and time in teaching and learning. As discussions about the future of higher education in the post-pandemic world have commenced among academia and university officials, it is crucial to consider the impact of COVID-19 on student learning and provide suggestions for a more sustainable and effective post-pandemic education. © 2023 IEEE.

Integration of RFID strategic value attributes mechanism decision in apparel supply chain: fuzzy AHP-TOPSIS approach

PurposeThe purpose of this paper is to identify the radio frequency identification (RFID) strategic value attributes (RFIDSVAs) mechanism selections preferences and also integration of RFID tags with technology coordination tools (IRTWTCTs) alternatives ranking performance decisions in supply chain management (SCM). RFID-enabled techno-economic feasibility decisions are enhancing the SC visibility in apparel supply chains (ASCs). The RFIDSVAs mechanism selections have performed significant agility to strategic competitive advantages, namely, inventory visibility, multi-tags ownership transfer within trusted third party, etc.Design/methodology/approachFuzzy analytical hierarchy process (FAHP) and FAHP-fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) approaches have been used to evaluate the quantitative assessment of RFIDSVA mechanisms selection decision based on weight priority orders and IRTWTCTs alternatives selection in ASC networks. The comparison of FAHP and FAHP-FTOPSIS approaches to evaluate the integrated framework develop in RFIDSVAs mechanisms and IRTWTCTs alternatives selection decisions in Indian multi-tier ASC networks.FindingsThe result found that the FAHP-FTOPSIS approaches have used to prioritizing the RFIDSVA mechanism selection weights and also identify the IRTWTCTs alternatives ranking preferences order in apparel SCM. The comparison between the FAHP and FAHP-FTOPSIS approach to quantitative assessments from RFIDSVA mechanisms and IRTWTCTs alternatives selection decisions, which enable them SC agility potential across multi-tier visibility in ASC networks. ASC stakeholders can be benefited by techno-economic feasibility decisions, RFID-enabled shop floor activities, multi-tags ownerships transfer in SCs and knowledge-based cryptography tags/items separation in SCs.Research limitations/implicationsThe research work has considered only five RFIDSVA mechanisms and also three integration of RFIDTWTCTs alternatives in multi-tier ASC. The strategic competitive advantages are achieved by RFID-enabled break-even tags price decisions and also techno-economic feasibility decision by contractual design multi-tier SC stakeholder's involvements.Practical implicationsThe pilot project study explores that the quantitative assessment decision has based on RFID-enable techno-economic feasibility in ASCs. Stakeholders can be benefited by inventory control of the financial losses, reducing the inventory inaccuracies and multi-tags ownership transfer within trusted third-party traceability in ASC networks.Originality/valueThis study explores the RFID-enabled apparel SC process and activities visibility (natural fibre's fibre producer, fibre dyeing producer, yarn spinning producer, knitting and finishing producer).

"We Speak Visually": User-Generated Icons for Better Video-Mediated Mixed-Group Communications Between Deaf and Hearing Participants

Since the outbreak of the COVID-19 pandemic, videoconferencing technology has been widely adopted as a convenient, powerful, and fundamental tool that has simplified many day-to-day tasks. However, video communication is dependent on audible conversation and can be strenuous for those who are Hard of Hearing. Communication methods used by the Deaf and Hard of Hearing community differ significantly from those used by the hearing community, and a distinct language gap is evident in workspaces that accommodate workers from both groups. Therefore, we integrated users in both groups to explore ways to alleviate obstacles in mixed-group videoconferencing by implementing user-generated icons. A participatory design methodology was employed to investigate how the users overcome language differences. We observed that individuals utilized icons within video-mediated meetings as a universal language to reinforce comprehension. Herein, we present design implications from these findings, along with recommendations for future icon systems to enhance and support mixed-group conversations. © 2023 ACM.

Social Distancing Monitoring and Contact Tracing on CCTV Footage

Social distancing is one of the most effective measures to prevent the spread of the COVID-19 disease. Most methods of enforcing this in the Philippines resort to manual methods. As such, a video-based social distancing monitoring tool can help ensure constant enforcement of social distancing due to the availability and up-time of CCTV cameras in various areas. This can be achieved by using object detection and tracking techniques. Object detection can be used to detect people within an area, and tracking can be used to watch people who get into close contact with one another. Contact tracing can also be performed by processing the social distancing measurements and tracking information. This information can be stored to keep a record of who has a high risk of infection based on who they came into contact with and for how long. We introduce a social distancing monitoring and contact tracing framework using the EfficientDet object detector and DeepSORT tracker. This framework is used to monitor social distancing violations and keep a record of violations associated to the tracked people. © 2022 IEEE.

Role of Multimedia in Education and its Impact on Academic Achievements

Multimedia is a diversified and powerful means to strengthen and aid the education methodology, by making learning interactive and interesting, this paper further justifies the same. The Internet acts as a gateway between multimedia producers and consumers. It is free from discipline boundaries. Several tools allow nontechnical educators to deal with diverse multimedia to create the learning material. These tools should stand fit some parameters, briefly discussed. Its employment is rapidly magnifying, enabling self-learning, which was boosted in the Covid era. This paper emphasizes on to prevent traditional teaching from being used as a supplement but should be primary. Various hiccups in its efficient use in education still prevail but are heading toward resolution. © 2023 Bharati Vidyapeeth, New Delhi.

From Resistance to Resilience: Teachers' Adaptation Process to Mediating Digital Devices in Pre-COVID-19, during COVID-19, and Post-COVID-19 Classrooms in Nepal

This qualitative study explores the implementation and adoption process of the use of digital devices and tools in teaching and learning before, during, and after the COVID-19 pandemic in Nepal. Using Rogers' diffusion of innovation theory as a framework, the study examines the adoption and adaptation of digital devices by in-service secondary mathematics teachers (n = 62) and the teachers' perceptions of and preferences for instructional modalities. The findings suggest that, despite the increased reliance on digital devices during the pandemic, there is a lower likelihood of them being used in face-to-face classrooms in developing countries, such as Nepal. The adoption of online learning had not yet reached the adoption stage, even after the onset of the COVID-19 pandemic. Prior to the pandemic, online learning was not widely adopted by teachers in developing countries societies. The study also provides important insights into the challenges of and opportunities provided by using digital devices in post-COVID-19 classrooms, and its implications for policymakers and educators in Nepal. © 2023 by the authors.

What Motivate Students to Continue Using Online Collaborative Tools: Post-Acceptance of Information System Approach

This paper aims to understand what motivates students at universities in Indonesia to continue using Online Collaborative Tools (OCTs) for their collaboration work. Utilising OCTs is crucial as the COVID-19 pandemic hit us in 2019 and forced all of us, particularly those who studied at university, to work online as precautionary measures. This research employs the Post-Acceptance Model of Information Systems (IS) approach to understand this issue. For an OCT to continue use, performance: effectivity, efficiency, and certainty is the key determinant, and perceived usability: perceived usefulness, perceived ease of use, and perceived enjoyment mediates confirmation and satisfaction and the intention to continue use. A total of 354 participants are involved in the data analysis employing Structural Equation Modelling (SEM). Our results revealed that while the relationship between confirmation and satisfaction is partially mediated by perceived ease of use and enjoyment, the relationship between confirmation and intention to continue use is also partially mediated by perceived usefulness and enjoyment, and satisfaction. We found that the intention to continue using the OCT can be determined by 67.9% (substantial) of the variance of the model. Our research contributes theoretically to the IS research in this context and practically to the OCT discourse. Limitations and future research directions are discussed © 2023, International Journal of Emerging Technologies in Learning.All Rights Reserved.

Navigating crisis, navigating ICTs: A study of Indian migrant workers during the pandemic

In this note, we present the preliminary findings from a qualitative interview-based study among migrant workers in India who went through much hardship in the wake of one of most strict pandemic-induced lockdown in 2020. Through this study, we narrate the four ways in which digital technologies enabled the relief and crisis mitigation efforts targeted to migrant workers and how that in turn shaped the workers' experience of the crisis and associated relief efforts. We argue that more flexible use of familiar digital tools and channels, collaboration across state and non-state actors and assistance from human intermediaries in navigating ICTs make for more effective and inclusive relief measures. © 2022 ACM.