国开在线学习数据集

国开在线学习数据集主要面向自适应学习关键技术研究，尤其针对“行业知识图谱驱动的学习路径规划”任务需求，主要记录了截取自2022年春季国家开放大学《计算机应用基础》视频观看数据。该数据集支撑了专利《一种自适应测试方法及装置》、《试题推荐方法、装置、电子设备及存储介质》。本数据集可深度赋能教育技术研究与系统开发。一方面，结合视频观看行为的时间戳、频率、暂停/回放等细粒度数据，可构建学习者知识掌握状态模型，为个性化学习路径推荐提供依据；另一方面，其与行业知识图谱的深度融合，支持动态生成符合职业能力发展需求的学习序列，优化成人教育场景下的教学效率。本数据集的特色价值体现在三方面：其一，聚焦成人教育领域，填补了传统研究以K12或高等教育为主的局限性，其真实场景数据为职业能力导向的学习规划提供基准；其二，视频观看行为与知识图谱的关联标注，支持从时序行为到知识体系的映射分析，为多模态学习行为建模提供新范式；其三，严格的隐私脱敏处理保障了教育数据开放共享的合规性，为跨机构教育研究协作树立范例。该数据集预期推动行业知识图谱与自适应学习的深度融合，促进职业教育数字化转型，助力教育公平与终身学习体系建设。

The National Open University Online Learning Dataset is mainly developed for research on key technologies of adaptive learning, especially targeting the task requirement of "industry knowledge graph-driven learning path planning". It primarily records video viewing data of the course "Fundamentals of Computer Applications" from the National Open University in spring 2022. This dataset supports the patents titled "An Adaptive Testing Method and Device" and "Question Recommendation Method, Device, Electronic Equipment and Storage Medium". This dataset can deeply empower educational technology research and system development. On one hand, with fine-grained data such as timestamps, viewing frequency, pause/playback behaviors of video learning, it can construct a learner's knowledge mastery state model, providing a basis for personalized learning path recommendation. On the other hand, its in-depth integration with industry knowledge graphs supports the dynamic generation of learning sequences that meet the needs of professional competency development, optimizing teaching efficiency in adult education scenarios. The distinctive value of this dataset is reflected in three aspects: First, it focuses on the field of adult education, filling the gap of traditional research that mainly centers on K12 or higher education. Its real-scenario data provides a benchmark for competency-oriented learning planning. Second, the associated annotation of video viewing behaviors and knowledge graphs supports the mapping analysis from temporal behaviors to knowledge systems, offering a new paradigm for multimodal learning behavior modeling. Third, strict privacy desensitization processing ensures the compliance of open sharing of educational data, setting a precedent for cross-institutional educational research collaboration. This dataset is expected to promote the in-depth integration of industry knowledge graphs and adaptive learning, facilitate the digital transformation of vocational education, and contribute to educational equity and the construction of a lifelong learning system.

搜集汇总

背景与挑战

背景概述

国开在线学习数据集是一个面向自适应学习研究的开放数据集，基于2022年春季国家开放大学《计算机应用基础》课程的视频观看行为记录，包含时间戳、频率等细粒度数据。该数据集特色在于聚焦成人教育领域，将视频观看行为与行业知识图谱关联标注，支持个性化学习路径规划和职业能力发展研究，并经过隐私脱敏处理以保障合规共享。