This paper presents a cognitive tutor powered by Davinci 003 API that generates and evaluates personalized questions for students on any topic they choose. The tutor adapts to the student's level of understanding and fosters knowledge transfer by generating questions that relate the topic to different domains. This solution has the potential to improve student learning outcomes by providing personalized and adaptive questions that challenge them at their optimal level of difficulty. The feasibility of this solution has been demonstrated through a working prototype developed using Microsoft PowerApps. Additional research could reveal how affective computing principles could be integrated into the system to analyze the emotional valence of the user and how the system could be tuned to meet the specific needs of learners across the ASD spectrum. This solution is novel and offers more comprehensive support to a diverse range of learners than existing AI tutors, such as Quizlet's Q-Chat. The paper also includes an equity statement that outlines the author's commitment to promoting educational equity and addressing potential biases in the project.

翻译：本文提出一种基于Davinci 003 API驱动的认知教学系统，能够为任意学科的学生生成并评估个性化问题。该系统通过生成跨领域关联题目来适应学生理解水平并促进知识迁移，其解决方案通过提供最优难度挑战的个性化自适应问题，具有提升学生学习成效的潜力。该方案的可行性已通过基于Microsoft PowerApps开发的工作原型得到验证。后续研究可探索如何将情感计算原理融入系统以分析用户情感效价，以及如何针对自闭谱系障碍（ASD）学习者的特定需求进行系统调适。本方案具有创新性，相比Quizlet的Q-Chat等现有AI教学系统，能为多样化学习者群体提供更全面的支持。本文还包含一份公平性声明，阐述了作者在促进教育公平和解决项目中潜在偏见方面的承诺。