库帕思高质量教育思维链（Chain-of-Thought）数据集-数学篇（下篇）

本次开源数据集总量达100万条，首批开源30万条，覆盖高等教育阶段三大基础学科的核心内容。数学包含高等数学、概率论与数理统计、离散数学、线性代数；物理与计算机则涵盖各自学科各章节重点难点。数据集聚焦课堂教学、自主练习、技能评估等场景，细化至概念理解、公式推导、逻辑分析、综合应用等多种能力维度，为教育智能系统与大模型推理能力的构建提供坚实根基。

This open-source dataset has a total of 1 million entries, with 300,000 entries released as the first open-source batch, covering the core content of three foundational disciplines at the higher education level. The subject of Mathematics includes Advanced Mathematics, Probability Theory and Mathematical Statistics, Discrete Mathematics, and Linear Algebra; Physics and Computer Science cover the key and difficult points of each chapter in their respective disciplines. The dataset focuses on scenarios such as classroom teaching, independent practice, and skill assessment, and is categorized into multiple competency dimensions including concept comprehension, formula derivation, logical analysis, and comprehensive application, providing a solid foundation for the development of educational intelligent systems and the construction of reasoning capabilities for large language models.

搜集汇总

背景与挑战

背景概述

该数据集聚焦于线性代数、概率论与数理统计等高等数学领域，包含多种题型，旨在通过提供标准答案及附带思考链的模型采样结果，支撑智能学习系统进行个性化推送并强化AI模型的数学推理能力。所有数据经过严格清洗与评估，以JSONL格式提供，采用MIT许可协议，服务于教育智能化和大模型研发的实际场景。