ABSTRACT
Tertiary education in Hong Kong has dramatically changed after the outbreak of COVID-19. Teaching pedagogy and delivery method have been transformed into “Contactless Learning and Teaching” and online learning. However, the focus has been on online learning while seldom analyzing the effect of “Contactless Learning and Teaching” among previous research. This research addressed this gap by studying 156 university students in Hong Kong. ATLAS, a mobile app integrated with iBeacon technology was developed to deliver learning materials in “Contactless Learning and Teaching”. The findings indicated that students who spent more time on “Contactless Learning and Teaching” have better academic performance. The active participation in “Contactless Learning and Teaching” and better academic results could also be explained by the Technology Acceptance Model in this study. The current study proves that iBeacon displays the potential of delivering learning and teaching materials amid the pandemic using the “Contactless Learning and Teaching” approach. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Subject(s)
Anesthesia, Epidural/methods , COVID-19 , Cesarean Section , Infection Control , Patient Care Management , Pregnancy Complications, Infectious , SARS-CoV-2/isolation & purification , Adult , COVID-19/diagnosis , COVID-19/physiopathology , COVID-19/therapy , COVID-19 Nucleic Acid Testing , Cesarean Section/instrumentation , Cesarean Section/methods , Delivery Rooms/organization & administration , Elective Surgical Procedures/methods , Female , Gestational Age , Humans , Infant, Newborn , Infection Control/methods , Infection Control/organization & administration , Patient Care Management/methods , Patient Care Management/organization & administration , Pregnancy , Pregnancy Complications, Infectious/physiopathology , Pregnancy Complications, Infectious/therapy , Pregnancy Complications, Infectious/virology , Pregnancy OutcomeABSTRACT
Understanding the relationship between the built environment and the risk of COVID-19 transmission is essential to respond to the pandemic. This study explores the relationship between the built environment and COVID-19 risk using the confirmed cases data collected in Hong Kong. Using the information on the residential buildings and places visited for each case from the dataset, we assess the risk of COVID-19 and explore their geographic patterns at the level of Tertiary Planning Unit (TPU) based on incidence rate (R1) and venue density (R2). We then investigate the associations between several built-environment variables (e.g., nodal accessibility and green space density) and COVID-19 risk using global Poisson regression (GPR) and geographically weighted Poisson regression (GWPR) models. The results indicate that COVID-19 risk tends to be concentrated in particular areas of Hong Kong. Using the incidence rate as an indicator to assess COVID-19 risk may underestimate the risk of COVID-19 transmission in some suburban areas. The GPR and GWPR models suggest a close and spatially heterogeneous relationship between the selected built-environment variables and the risk of COVID-19 transmission. The study provides useful insights that support policymakers in responding to the COVID-19 pandemic and future epidemics.