Revolutionizing Education: A Proposal for School-Provided Personal Large Language Models to Foster Authentic Learning in an AI-Driven Era

This report addresses the global crisis in education caused by widespread student reliance on large language models (LLMs) such as ChatGPT, Gemini, and Perplexity, which has led to a sharp decline in authentic learning and exam performance. Institutions have responded by diluting curricula and assessments, undermining long-term preparedness. The proposed solution is a comprehensive roadmap for deploying school-provided personal LLMs as ethical, dedicated learning companions. These systems offer hint-based Socratic tutoring, multimodal support for diverse learners, adaptive testing, progress tracking, and educator reports. Academic integrity is maintained through single-interface submissions, external LLM detection (e.g., watermarking), and in-person final examinations carrying substantial weight. The framework introduces dual certification—one for completion and another for verified proficiency benchmarked against standards like OECD PISA—while replacing rigid examination boards (e.g., IB, CBSE) with a unified, flexible system that mandates core subjects amid elective choice. Implementation begins with pilots in elite private schools, scaling equitably thereafter. Recent 2025–2026 advancements in the U.S., Kazakhstan, and independent institutions demonstrate feasibility using open-source LLMs and existing platforms (e.g., Google Classroom). This working paper provides educators, policymakers, and administrators with an actionable blueprint to transform AI from a disruptive force into a catalyst for resilient, authentic learning.