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Artificial Intelligence has changed many aspects of lives since it provides the technological services and tools that help to make decisions in everyday life. The present paper aims to highlight the role of education data mining in improving the quality of the educational process. Education data mining techniques can discover information that can assist educators in establishing pedagogical decisions when designing or modifying an environment or teaching approach. Also, education data mining can help predict students' failure or dropout. So present paper going to define educational data mining, why educational data mining is important, the goals of using educational data mining, and where educational data mining can be applied. Later, the paper develops some recent examples of studies that have had utilized educational data mining to enhance the educational process and predictive models that help educators in making educational decisions and building suitable prevention programs to improve the Quality of educational process.

This research paper aims to investigate the relationship between Total Quality Management and ISO specification through a quality audit by identifying ISO specifications in the pursuit of continuous improvement, in addition to exposure to the importance of total quality and the stages of its application, and to identify the responsibility of the quality auditor and the presentation of the stages to be followed in the quality audit. The study concluded that obtaining the ISO certification does not replace the quality management system, which represents the point of view of the stakeholders because it is a continuous improvement. In addition, the Total Quality Management System is based on documented specifications that describe the periodic audit from the customer's point of view and concern themselves with continuous updating based on the improvements produced by the Total Quality Program.