The Application of Machine Learning Techniques for Investigating and Analyzing Student Bullying Phenomenon: A Practical Binary Logistic Regression Study

The aim of the current research is to determine the factors influencing the spread of bullying in secondary schools. The sample consisted of (15) students participating in the teacher training adaptation program at the University of Hildesheim. To achieve the research objectives, a questionnaire was created that identified the most influential factors in the prevalence of bullying in school, consisting of six statements, all of binary type. The results showed that four variables (Electronic games that incite violence - The bullying student's environment helps him to bully his colleagues-Neglect of school administration and Negligence of punishment-Neglect of parents) had an influence on school dispersion During the the remaining independent variables (parental separation & There is no strong bond between parents and school) had no significant and noticeable influence on the prevalence of bullying in school.