【作 者】：
王冬青，韩 后， 邱美玲， 凌海燕
【关 键 词 】：
情境感知； 智慧课堂； 动态生成性数据； 数据采集
【栏 目】：
理论探讨
【中文摘要】：
智慧教学过程中动态生成数据具有多源异构、非完整、关联性强等特征，传统方法难以进行有效采集与存储，建立统一的数据采集规范与存储机制，高效采集与分析过程性数据成为当前智慧教育研究亟待解决的问题。文章基于情境感知技术提出智慧教学数据采集模型，采用用户、任务、位置、时间、设备、基础设施六类信息表示智慧教学情境，基于xAPI规范与Caliper框架从行为、事件、活动、目标四个层面定义动态生成性数据描述框架与云端数据交换机制，解决云端环境下基于教学情境的多源、异构数据采集问题，为建立教育大数据模型和发展教育大数据云服务提供新思路与方法。
【英文摘要】：
The data generated dynamically in smart learning are characterized by heterogeneity, incompleteness and strong correlation. For it is difficult to collect and store those data effectively by using traditional methods, to establish unified norms and storage mechanism of data collection for collecting and analyzing the process data effectively becomes an urgent problem in smart education. This paper builds a model of smart learning data acquisition based on context-aware technology, adopting six types of information including users, tasks, location, time, devices and infrastructure to indicate the context of smart learning. Based on xAPI specifications and Caliper framework, this paper uses four layers to define the dynamic generation of data description framework and cloud data exchange mechanism in order to solve the problem of multi-source and heterogeneous data acquisition based on teaching situations in the cloud environment, and provide new ideas and methods for establishing a big data model and developing a big data cloud service in education.