库帕思高质量教育思维链（Chain-of-Thought）数据集-物理篇（上篇）

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 released as the initial open-source batch, covering the core content of three foundational disciplines at the higher education level. For mathematics, it includes Advanced Mathematics, Probability Theory and Mathematical Statistics, Discrete Mathematics, and Linear Algebra; Physics and Computer Science cover the key and challenging points of each chapter in their respective disciplines. The dataset targets scenarios including classroom teaching, independent practice, and skill evaluation, and is categorized into multiple ability dimensions such as concept understanding, formula derivation, logical analysis, and comprehensive application, providing a solid foundation for the development of educational intelligent systems and the reasoning capabilities of large language models (LLMs).

搜集汇总

背景与挑战

背景概述

该数据集聚焦物理学科的客观题，旨在为教育智能化提供标准化数据支撑，以提升模型在物理基础知识点的辨析与答题准确性。其核心特色在于为每个问题提供了由大语言模型生成的多个采样答案及详细的思考链，并经过自动化评估确保数据质量，采用JSON Lines格式便于模型训练与应用。