智能备课助手数据集

本数据集基于全学科、全学段的教材电子版、优秀教案、名师课件、配套习题及教学短视频片段，经过深度加工与创造性编排构建而成。原始素材被赋予多维教学标签，涵盖知识认知层次（记忆/理解/应用/分析/评价/创造）、教学策略适配（情景导入/探究讲解/小组协作等）、多模态特征（情感基调、语速、动画/实验标识）及学生认知风格（认知负荷、思维类型）。同时，数据集构建了知识概念图谱与典型教学流程模板，将离散素材按照“教学单元-知识图谱-素材序列”进行结构化编排，并生成增强型元数据（亮点标签、教学价值描述）。最终形成一套兼具资源广度与教学深度的智能化教学素材库，为AI备课模型提供高质量的训练数据。This dataset is constructed based on electronic textbooks spanning all academic disciplines and educational stages, high-quality lesson plans, courseware developed by distinguished educators, supporting exercises, and short teaching video clips, following in-depth processing and creative organization. Original materials are annotated with multi-dimensional teaching tags, covering the hierarchy of knowledge cognition (memory, comprehension, application, analysis, evaluation, creation), adaptation of teaching strategies (e.g., scenario-based introduction, inquiry-based explanation, group collaboration), multimodal features (emotional tone, speech rate, animation/experiment markers), and students' cognitive styles (cognitive load, thinking patterns). Meanwhile, the dataset constructs knowledge concept graphs and typical teaching process templates, structures discrete materials according to the framework of "teaching unit - knowledge graph - material sequence", and generates enhanced metadata including highlight tags and teaching value descriptions. Ultimately, an intelligent teaching material repository with both extensive resource coverage and profound instructional depth is established, providing high-quality training data for AI lesson-preparation models.

搜集汇总

背景与挑战

背景概述

该数据集是一个面向全学科和全学段的智能化教学资源库，基于教材、教案、课件、习题和视频等原始素材构建。它经过深度加工，通过多维教学标签、知识概念图谱和教学流程模板进行结构化编排，增强了元数据描述。最终旨在为AI备课模型提供高质量、兼具资源广度和教学深度的训练数据，支持教学策略适配和学生认知分析。