ABSTRACT
A learning environment is a diverse platform where users are engaged and interacted to learn new skills by any means of learning methodology. Nowadays the millennial students are fast learners and expecting a new learning environment and methodology to enhance their skills in learning and acquiring knowledge. Though they possess many good skills they are under various pressurized social and family environments due to COVID-19 pandemic which lead to get depressed quickly. The traditional teaching learning methodology is also increasing their stress. This stress will affect the cognitive functioning among the students and the mentors and further leads the students to hate their subjects and slowly reduce their involvement and interaction with subject instructors. To overcome the above problem, the instructors should have the responsibility to incorporate an arsenal of strategies that would inoculate learners against the negative attitude by providing enough positive experiences during this post COVID situation. The proposed work gives a brief description about the online and off line learning environments and their impact on the education with societal aspects. It collaborates the research from different traditions and gives description about the connections that can be drawn between the teacher-student interactions and with the peer interaction through case studies. © 2022, Rajarambapu Institute Of Technology. All rights reserved.
ABSTRACT
The main aim of the study is to understand the behavioural practices of people in Madurai Corporation in the context of COVID-19 (Coronavirus Disease). The major findings of the study are that a little more than two-third of the respondents (67.2 per cent) wash hands frequently, more than two-third of the respondents (68.6 per cent) wear masks every time, a little more than one-fifth of the respondents (21 per cent) maintain 6 feet of distancing from others, nearly two-fifth of the respondents (38.7 per cent) report to the nearest government health Centre, if developed any ailments.
ABSTRACT
The 2019 novel coronavirus (2019-nCoV) outbreak is declared as a pandemic by the World Health Organization. This chapter presents a simplified approach of the 2019-nCoV outbreak in Malaysia, based on a simple mathematical model and limited reference data. The profound model predictions is based on the actual data on the date of confirmation excluding deaths, considering the recovered will have the possibility to get infected again. The 14 days incubation characteristics are used in the computations as pronounced by CDC to improve the prediction characteristics. This includes the four stages of recovery characteristics in any pandemic cases towards cluster segregation, contact tracing towards flattening the growth curve. The model from china was taken as reference and the Malaysian recovery phase analyses and compared with the measures in place. The computational approach for the dataset available is presented and the similarity measure is a good reference point in handling the pandemic of this size in future. © 2022, Institute of Technology PETRONAS Sdn Bhd.