MOOCCubeX慕课教育资源数据集

MOOCCubeX慕课教育资源数据集主要面向自适应学习关键技术研究，尤其针对"跨媒体自适应智能推荐技术"任务需求，主要记录了大规模、多样化的公开慕课资源和外部教育资源，以及学生的学习、练习和讨论的数据记录。该数据集支撑了论文《Leveraging Transferable Knowledge Concept Graph Embedding for Cold-Start Cognitive Diagnosis》和专利《试题推荐方法、装置、设备、存储介质及产品》。本数据集可服务于多模态教育技术研究，例如基于知识图谱的课程资源关联分析、学习行为时序建模、跨平台资源推荐算法开发等。本数据集填补了大规模多模态教育数据集的空白，其价值体现在三方面：其一，覆盖视频、文本、交互行为等多模态数据，支持跨媒体特征融合技术的验证与创新；其二，超3亿条行为数据为模型训练提供真实场景支撑；其三，标准化的课程元数据与知识体系构建方法，为教育资源的语义对齐与跨平台迁移学习奠定基础。该数据集预期推动自适应学习技术从单一习题推荐向多模态、全流程的智能教育服务升级，促进教育技术、认知科学与人工智能的跨领域协同创新。

MOOCCubeX: A MOOC Educational Resource Dataset
This dataset is primarily designed for key technical research on adaptive learning, particularly catering to the task requirements of cross-modal adaptive intelligent recommendation technology. It records large-scale, diverse public MOOC resources, external educational resources, as well as data logs of students' learning, practice and discussion activities.

This dataset has supported the paper *Leveraging Transferable Knowledge Concept Graph Embedding for Cold-Start Cognitive Diagnosis* and the patent *Question Recommendation Method, Apparatus, Device, Storage Medium and Product*.

It can support multi-modal educational technology research, such as knowledge graph-based course resource correlation analysis, learning behavior temporal modeling, cross-platform resource recommendation algorithm development, and other related research directions.

This dataset fills the gap in large-scale multi-modal educational datasets, with its values embodied in three aspects: First, it covers multi-modal data including videos, texts, interactive behaviors and other types, enabling the verification and innovation of cross-modal feature fusion technologies; Second, it contains over 300 million behavioral data entries, providing real-world scenario support for model training; Third, the standardized course metadata and knowledge system construction approach lays a foundation for semantic alignment of educational resources and cross-platform transfer learning.

This dataset is expected to drive the upgrading of adaptive learning technology from single exercise recommendation to multi-modal, full-process intelligent educational services, and promote cross-disciplinary collaborative innovation among educational technology, cognitive science and artificial intelligence.

搜集汇总

背景与挑战

背景概述

MOOCCubeX慕课教育资源数据集是一个大规模、多模态的教育数据集，主要用于自适应学习技术研究，包含丰富的慕课资源、学生学习行为数据，支持跨媒体特征融合和智能推荐算法的开发。数据集覆盖视频、文本、交互行为等多模态数据，数据量达29.77GB，为教育技术研究提供了真实场景支撑。