Proposal for an AI-Driven Learning Platform with Gamification for K-12 Students

The rapid evolution of generative artificial intelligence has introduced transformative possibilities for personalized education, particularly in addressing the diverse pacing needs of primary and secondary school students. However, the manual creation of high-quality, individualized practice material remains a significant burden for educators and learners alike. This paper presents a specialized web application designed to bridge this gap by automating the generation of tailored educational content. By leveraging OpenAI’s Large Language Models (LLMs) integrated via Azure cloud services, the platform transforms static uploaded materials into dynamic practice sets, including contextual references and mock examinations. The system architecture employs a Vue.js frontend for a responsive user experience and a robust C# backend to manage data processing and secure authentication. To sustain student engagement, the application integrates gamification mechanics—such as peer challenges and merit-based rewards—converting traditional study routines into an interactive, competitive environment. Beyond the functional features, this study details critical architectural decisions regarding cost optimization in AI token usage and strategies for system scalability. Preliminary user testing indicates that the fusion of automated content generation with gamified engagement significantly improves knowledge retention and collaborative learning, offering a scalable model for AI-driven pedagogical tools.