Application of data mining in the study of behavioral and emotional disorders of children of divorce resulting in educational failure in high school students

Data mining is the process of discovering valid, new and understandable models or models in a large database and trying to extract knowledge from the mass of existing data. Data mining can identify hidden patterns and relationships in databases using a set of statistical and modeling methods, and this knowledge can help to understand high-risk behaviors, help educate and improve programs to improve academic performance and reduce academic failure and aggression. This article first introduces data mining and its techniques, and then considering the decline in students academic achievement is one of the major challenges in managing school educational affairs and youth mental health is one of the most important issues in psychology and sociology, social damages in dealing with divorced children and educational failure of students are discussed. Finally, the application of data mining in examining the dropout rate and predicting the academic status of students in the coming years will be discussed in order to identify students who will face educational failure and continuing their education would be difficult. It is hoped that this article will be an effective step towards institutionalizing modern data mining knowledge in the education system and will highlight the system s prominent goals in improving students academic performance and performance and how best to deal with divorced children, abnormal behaviors, and student’s educational failure. This technique can be applied by managers, advisors, and educational and training planning personnel.