Victims of Educator-Targeted Bullying: A Qualitative Study on Teacher Harmful Experience

Bullying in school has become an international concern in recent years, and the issue became urgent after school closure during COVID Pandemic. International studies have identified teacher-targeted bullying by students as a real and harmful issue for teacher wellbeing. Our paper sets out discursive issues surrounding bullying against teachers as targets of intentional bullying. It reports on the findings of a small-scale, extant, qualitative research study on commenters' understanding of the antecedents of teacher-targeted bullying. The aim was to gain insights into the teachers´ targeted bullying from the perspective of teacher victims. We conducted a qualitative descriptive research design stemming from semi-structured interviews with victims of teacher-targeted bullying. A thematic content analysis of the data was generated from interviews with seventeen victimized teachers as a snowball sampling. The sample consisted of male (n = 7) and female (n = 10) participants from urban school locations in the capital of Czech Republic. The focus of our study was to determine how the teachers who had been experiencing bullying by their students described and perceived the nature and consequences attributed to such bullying. The findings indicate that the victims of teacher-targeted bullying were exposed repeatedly over long time verbal and nonverbal bullying, ignoring the teaching activities and other threats directed against teachers. Our results suggest bullying had a negative influence on the victims' private lives (family, colleagues), physical and mental health and self-esteem. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

System of Quality Assurance in the University Education During COVID-19 Crisis

Due to the prevention of the risk of the spread of COVID-19 caused by the new coronavirus SARS-CoV-2, distance education becomes a reality and places new challenges and qualification requirements for teachers of technical subjects and social sciences, as well as the school management. Digital competences correspond to life skills [7, 11, 12] and are therefore considered as a key area for the training of future teachers [1]. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Monitoring and Forecasting COVID-19: Heuristic Regression, Susceptible-Infected-Removed Model and, Spatial Stochastic.

The COVID-19 pandemic has had worldwide devastating effects on human lives, highlighting the need for tools to predict its development. The dynamics of such public-health threats can often be efficiently analyzed through simple models that help to make quantitative timely policy decisions. We benchmark a minimal version of a Susceptible-Infected-Removed model for infectious diseases (SIR) coupled with a simple least-squares Statistical Heuristic Regression (SHR) based on a lognormal distribution. We derive the three free parameters for both models in several cases and test them against the amount of data needed to bring accuracy in predictions. The SHR model is ≈ ±2% accurate about 20 days past the second inflexion point in the daily curve of cases, while the SIR model reaches a similar accuracy a fortnight before. All the analyzed cases assert the utility of SHR and SIR approximants as a valuable tool to forecast the disease's evolution. Finally, we have studied simulated stochastic individual-based SIR dynamics, which yields a detailed spatial and temporal view of the disease that cannot be given by SIR or SHR methods.