智慧教育体现了教育信息化发展的新境界，表达了一种技术以智慧性方式促进教育变革与创新的诉求，这一目标的实现离不开学习分析技术。学习分析的核心就是观察和理解学习行为，以倒溯方式考察影响行为产生的需要、动机等因素，以及行为所携带的目的、个性、环境等元素，从而加以利用以优化学习过程及其发生的环境。而一个好的行为模型将大大助力于对这些信息的收集、分析与理解。学习活动流模型的提出补充了以往学习行为分析所没考虑的学习来源的多元化以及学习活动的持续性问题。借鉴活动流的描述机制，情景化注意元数据被加以改造并得到学习活动流的描述模型，而基于学习活动流的学习情境分析则探讨了对这一行为模型的学习分析应用，并以信息感知和资源推送为例展示了其实践应用。%As a new realm of the development of e-education, smart education expresses a demand of using technology in in-telligent ways to promote educational revolution and innovation. The achievement of this objective is inseparable from learning analyt-ics. The core of learning analytics is to observe and understand learning behaviors. By investigating the factors (e.g. needs, motiva-tions) which impact these behaviors, and the information (e.g. purpose, personality, context) which is carried by these behaviors, the learning process and learning environment can be optimized. A good behavior model will greatly contribute to collecting, analyzing and understanding above-mentioned information. So the concept of learning activity streams can solve the problems of diversification of learning sources and persistence of learning process which haven’t been considered before. The description model of learning ac-tivity streams is built by learning from description mechanisms of activity streams and contextualized attention metadata. Finally, its practical applications are discussed on the theme of learning context analysis, and demonstrated through two cases of information per-ception and resource push.
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