Piloting course for ACIAR Learn
miragenews.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from miragenews.com Daily Mail and Mail on Sunday newspapers.
Bad Düben: Polizei kontrolliert Verkehr vor Schulen
lvz.de - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from lvz.de Daily Mail and Mail on Sunday newspapers.
E-Learning System Use During Emergency: An Empirical Study During the COVID-19 Pandemic
Faculty of Education, Education Technology Department, King Faisal University, Alahsa, Saudi Arabia
The pandemic of COVID-19 quickly led to the closure of universities and colleges around the world, hoping that the guidance of social distancing from public health authorities will help flatten the curve of infection and minimize the overall fatalities from the epidemic. The e-learning framework, however, is the best solution to enable students to learn about the quality of education. The aim of this research was to examine variables reflecting the actual use of the e-learning system during the COVID-19 pandemic among university students. The perceived ease of use and perceived usefulness are positively correlated with facilitating condition, perceived control, and self-efficacy, which in turn influences students’ attitude toward use, which in turn affects the actual use of the e-learning system
Abstract
Several methods have been devised to mitigate the effects of outlier values on survey estimates. If outliers are a concern for estimation of population quantities, it is even more necessary to pay attention to them in a small area estimation (SAE) context,where sample size is usually very small and the estimation in often model based. In this paper we set two goals: The first is to review recent developments in outlier robust SAE. In particular, we focus on the use of partial bias corrections when outlier robust fitted values under a working model generate biased predictions from sample data containing representative outliers.Then we propose an outlier robust bootstrap MSE estimator for M-quantile based small area predictors which considers a bounded-block-bootstrap approach. We illustrate these methods through model based and design based simulations and in the context of a particular survey data set that has many of the outlier characteristics that are observed in busines