Catering for Students' Well-being during COVID-19 Social Distancing: A Case Study from a University Campus

COVID-19 gave rise to discussions around designing for life during the pandemic, in particular related to health, leisure and education. In 2020, an online survey aimed at university students (N=225) pointed the authors to various challenges related to well-being in terms of studying, socializing, community, and safety during the COVID-19 pandemic. These results shaped the crowdsensing-enabled service design of a mobile application, Tecnico GO!, aimed at supporting students' well-being. Considering the constant changing context caused by the pandemic, we present a study conducted during the academic year 2021-2022 and if/how the App's features continue to respond to student's needs. The evaluation of the App focused on 12 semi-structured interviews and think-aloud protocols. Findings cluster around three themes: a) Supporting the study experience;b) Building a sense of community;c) Improving gamification for better participation. Discussion elaborates on the student's perceptions around well-being during pandemics. Students' insights of the App are overall positive and highlight that crowdsensing-enabled design does contribute to learning, community and safety, but the gamification as currently deployed does not. © 2022 ACM.

Promoting a safe return to university campuses during the COVID-19 pandemic: Crowdsensing room occupancy

We describe the work behind a privacy-preserving, crowdsensing approach that promotes social distancing upon the return of students to University. Our main motivation is enabling visualizations that predict room occupancy based on the number of connected devices to particular access points, via anonymous reports about these predictions, and via an unenforced booking system that allows users to communicate their intents about room use. © 2021 ACM.

Addressing the Challenges of COVID-19 Social Distancing Through Passive Wi-Fi and Ubiquitous Analytics: A Real World Deployment

During the COVID-19 pandemic, social distancing measures were employed to contain its spread. This paper describes the deployment and testing of a passive Wi-Fi scanning system to help people keep track of crowded spaces, hence comply with social distancing measures. The system is based on passive Wi-Fi sensing to detect human presence in 93 locations around a medium-sized European Touristic Island. This data is then used in website plugins and a mobile application to inform citizens and tourists about the locations’ crowdedness with real-time and historical data. To understand how people react to this type of information, we deployed online questionnaires in situ to collect user insights regarding the usefulness, safety, and privacy concerns. Results show that users considered the occupancy data reported by the system as positively related to their perception. Furthermore, the public display of this data made them feel safer while travelling and planning their commute. © 2021, IFIP International Federation for Information Processing.

Collecting Qualitative Data During COVID-19

The current pandemic situation leads researchers to reflect on conducting qualitative research, completely changing how they conduct participatory research. As it became clear that the pandemic would last many months, researchers started to redesign their planned research in digital spaces through social media channels and participatory online tools. From communicating with participants over Zoom (or other similar applications) to sharing information on exclusive online groups, digital platforms have become, for many, the only way to work, learn, or be entertained. This situation offered a significant opportunity to think creatively about research engagement and reflect on which aspects truly require researchers to be “on the ground” to conduct face-to-face participatory sessions to gather qualitative data. Qualitative researchers must use this opportunity to reflect while using digital tools for distance research. This paper is inspired by the work the authors are conducting in MEMEX – a European-funded project promoting social inclusion by developing collaborative storytelling tools related to cultural heritage and at the same time facilitating encounters and interactions between communities at risk of social exclusion. Thus, the work here presented reflects on the digital tools and techniques to collect qualitative data when the researchers cannot meet the participants face-to-face due to pandemics safety measures or other restrictions. © 2021, IFIP International Federation for Information Processing.

A data visualization interactive exploration of human mobility data during the COVID-19 outbreak: a case study

In this paper, we present a real-world study where a community-based tracking infrastructure has been put to good use for understanding human mobility during the COVID-19 outbreak, in order to contrast its diffusion. In particular, the infrastructure, deployed in 81 points of interests (POIs) across the Madeira Islands (Portugal), can collect a massive amount of spatio-temporal data, that can be enriched with potentially independent data sources of additional values (such as the official number of people affected by the coronavirus disease), and crowdsourced data collected by citizens. These enriched hyper-local data can be manipulated to provide i) stakeholders with a visual tool to contrast COVID-19 diffusion through human mobility monitoring, and ii) citizens with an interactive tool to visualize, in real-time, how crowded is a POI and plan their daily activities, and contribute to the data acquisition. Here we present the deployed community-based infrastructure and the data visualization interactive web application, designed to extract meaningful information from human mobility data during the COVID-19 outbreak.