Development and Integration of an AI-Driven Adapter & Grade Prediction Model for Mathematical Question Classification and Assessment which Enhance Student Profiling

The transformative growth of AI can be seen in almost every sector. AI can be a useful application for the educational domain as well. Education should be prioritized because it's the root of every other field. This research aims to combine IT to develop mathematics subjects by leveraging AI in practice mainly introducing Capabilities of Open AI. The primary object is to create Open AI API through a specially created PHP adapter to classify mathematical questions into six main themes Sets and Probability, Algebra, Numbers, Geometry, Measurements, and Statistics. This automated AI-driven classification system helps to create online assessments within the blink of an eye. The Integration of Open AI API with a PHP-based framework makes a bridge between AI capabilities and education needs. This framework is the ideal solution for manual and traditional school assessments. This AI- driven mathematics classification system is designed to optimize the assessment process by providing additional objectives such as leveraging automated student grading feedback while predicting final grades so teachers and students can see the result instantly. Additionally, answers are automatically created after the assessment showing solving steps which facilitate students to identify the corrections as well.