تنبؤات الذكاء الاصطناعي في تأثير العنف المدرسي على الطالب ومعالجتها إعلاميا

Abstract

Artificial intelligence predictions in the impact of school violence on students and its media processing

      The research aims to select a group of students and classify their data into two categories, whether the student think to leave school or not because of being exposed to school violence, represented by reasons (characteristics) in appearance of verbal, physical and psychological violence such as hitting, mockery, failure, etc. Decision tree algorithm was used to classify the data and support it with random forest algorithm and logistic regression. The decisions resulting from the tree were future predictions of whether the student would leave school. The phenomenon of school violence was also described, and its negative effects were identified to reduce the severity of the phenomenon of school violence by teachers towards students.

     The researchers relied on the descriptive approach to the phenomenon and machine learning tools in the analysis process. The research community consisted of public and private primary schools within the city of Tripoli. A random sample of 10 schools consisting of (289) individuals was selected, and the questionnaire tool was used to collect data.

    The most important results reached by the research are some predictions such as mockery, hitting and kicking together lead the student to think about leaving school, while failure alone does not lead to this. With this prediction, a model can be built that can be used by the Ministry of Education to address the phenomenon through the available media, while educational media specialists or mass media play a role in employing media activities and developing plans intentionally to achieve the desired goals such as informing the student of the requirements for staying in schools