库帕思高质量教育思维链（Chain-of-Thought）数据集-物理篇（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 scale of 1 million entries, with 300,000 entries released as the initial open-source batch, covering core content of three foundational disciplines at the higher education stage. For Mathematics, it includes Advanced Mathematics, Probability Theory and Mathematical Statistics, Discrete Mathematics, and Linear Algebra; for Physics and Computer Science, it covers key and difficult points in each chapter of their respective disciplines. The dataset focuses on scenarios such as classroom teaching, independent practice and skill assessment, and is refined into multiple ability dimensions including concept understanding, formula derivation, logical analysis and comprehensive application, providing a solid foundation for the construction 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

该数据集专注于物理学科的定理推导和综合分析，包含简答与推导类题目，旨在辅助智能教学系统还原推导过程并提升模型的物理建模能力。数据经过严格的质量控制，采用JSON Lines格式，其核心特色在于为每个问题提供了由大语言模型生成的采样答案及详细的思考链，并经过自动化评估以确保高质量。数据集以教学与推理双赋能为目标，全量开放以支持教育智能化和AI模型的实际应用。