Predictors of teacher burnout during the COVID-19 pandemic with machine learning

Key Points

• This research aims to identify factors that predict teacher burnout during the COVID-19 pandemic using machine learning techniques.
• Utilized machine learning algorithms to analyze data on teacher mental health during the pandemic.
• Collected data from surveys regarding stress and working conditions.
• Conducted predictive modeling to identify key factors contributing to burnout.
• Identified several significant predictors of teacher burnout related to workload and emotional stress.
• Machine learning models demonstrated high accuracy in predicting burnout levels among teachers.
• Results suggest that mental health support is critical for teachers during crises.