Development of an intelligent platform for predicting curriculum management in higher education under the AUN-QA framework

This research aims to study and define the user requirements and operational capabilities required to develop an intelligent platform for forecasting and managing higher education courses under the AUN-QA framework using documentary research, platform design, and technology suitability assessment. The samples studied include personnel, instructors, course administrators, and IT specialists selected by the purposive method. Data were analyzed using statistics and standard deviation calculations. The results show that the developed platform should have five main components: user data control with AWS IAM and React, access security, SmartEduQA system for data storage and analysis, data presentation with Microsoft Power BI, and a serverless storage system. The platform is designed to meet the needs of administrators in forecasting the labor market and managing courses, instructors in analyzing data according to AUN-QA standards, and staff in managing data quickly and supporting interactive display. This platform can help make higher education course management efficient and aligned with AUN-QA standards.