Personalized Applications of Large Language Models in Pre-University Computer Science Education: Bridging Global Equity, Mitigating Bias, and Addressing Structural Challenges

All raw data, analysis materials, and supplementary resources (including questionnaire data, programming code, computational data, statistical outputs, course materials, summaries, templates, lesson plans, and descriptive notes) have been publicly archived on Zenodo to ensure transparency, replicability, and academic sharing. The materials comply with China's Personal Information Protection Law (2021) and UNESCO (2025) ethical guidelines, with anonymization to protect privacy. Access via: https://doi.org/ 10.5281/zenodo.17571306