Statistical report on the pedagogical experiment on the use of IIS GPT during mathematics and physics lessons (2019-2024)

This report presents the results of a five-year pedagogical experiment conducted by the International Innovative School on the integration of artificial intelligence (AI) tools in the teaching of mathematics and physics in secondary education. A total of 2,500 students participated in the experiment, which aimed to assess the long-term impact of AI-supported learning on student outcomes, engagement and satisfaction. The study assessed twelve core parameters across three domains: A: feedback quality, including response timeliness (A1), readability (A2), amount of additional explanation (A3), visual clarity (A4), and inaccuracies (A5); B: cognitive and performance impact, such as motivation (B1), error correction behaviour (B2), and test performance (B3); C: engagement and personalisation, including classroom participation (C1), satisfaction (C2), and degree of feedback individualisation (C3). Over the course of the experiment, AI-based tools - including adaptive learning systems, chatbots, and visual explanation platforms - were systematically integrated into classroom delivery and homework support. The results show consistent improvements across almost all parameters. In particular, 82% of students reported timely and helpful responses (A1), while test performance (B3) increased by an average of 21%. Engagement (C1) and satisfaction (C2) metrics increased significantly, especially when feedback was tailored (C3). Teachers observed fewer misunderstandings (A5) and more targeted clarifications (A3). The findings suggest that with proper pedagogical integration, AI technologies can meaningfully enhance STEM education by supporting personalisation, motivation and clarity in learning.本报告呈现了国际创新学校开展的一项为期五年的教学实验成果，该实验聚焦人工智能（AI）工具在中学数学与物理教学中的整合应用。本次实验共有2500名学生参与，旨在评估人工智能辅助学习对学生学习成果、参与度与满意度的长期影响。本研究从三大领域共12项核心指标展开评估：A域：反馈质量，涵盖响应及时性（A1）、可读性（A2）、额外解释量（A3）、视觉清晰度（A4）与反馈不准确情况（A5）；B域：认知与绩效影响，包括学习动机（B1）、纠错行为（B2）与测试成绩（B3）；C域：参与度与个性化程度，涵盖课堂参与度（C1）、满意度（C2）与反馈个性化程度（C3）。实验期间，研究团队将自适应学习系统、聊天机器人、可视化讲解平台等基于人工智能的工具系统性地整合至课堂教学与课后作业辅导环节。实验结果显示，几乎所有指标均呈现出持续改善的态势。具体而言，82%的学生表示反馈及时且具有助益（A1），测试成绩（B3）平均提升21%。课堂参与度（C1）与满意度（C2）指标显著提升，尤其在反馈实现个性化定制（C3）的情况下效果更为突出。教师们观察到，反馈的不准确情况（A5）有所减少，针对性补充讲解（A3）的频次有所增加。研究结果表明，通过恰当的教学整合，人工智能技术可通过支持学习个性化、提升学习动机与增强教学清晰度，切实推动STEM教育的发展。