V-Math: An Agentic Approach to the Vietnamese National High School Graduation Mathematics Exams
This addresses the need for scalable and equitable mathematics preparation for Vietnamese high school students and teachers, though it appears incremental as it builds on existing AI and educational technologies.
The paper tackled the problem of preparing Vietnamese high school students for national mathematics exams by developing V-Math, an autonomous agentic framework that integrates AI agents for question generation, solving, and tutoring, resulting in high solution accuracy and enhanced practice materials.
This paper develops an autonomous agentic framework called V-Math that aims to assist Vietnamese high school students in preparing for the National High School Graduation Mathematics Exams (NHSGMEs). The salient framework integrates three specialized AI agents: a specification-matrix-conditioned question generator, a solver/explainer for detailed step-by-step reasoning, and a personalized tutor that adapts to student performance. Beyond enabling self-paced student practice, V-Math supports teachers by generating innovative, compliant exam questions and building diverse, high-quality question banks. This reduces manual workload and enriches instructional resources. We describe the system architecture, focusing on practice modes for learners and teacher-oriented features for question generation. Preliminary evaluations demonstrate that V-Math produces matrix-aligned exams with high solution accuracy, delivers coherent explanations, and enhances the variety of practice materials. These results highlight its potential to support scalable, equitable mathematics preparation aligned with national standards while also empowering teachers through AI-assisted exam creation.