【作 者】：
武法提， 黄石华， 殷宝媛
【关 键 词 】：
互联网+教育； 场景感知； 学习者特征； 学习者建模
【栏 目】：
学习环境与资源
【中文摘要】：
“互联网+教育”时代，以往传统的学习场景正不断被重构，新型的学习场景逐渐向动态化、多元化、碎片化的模式发展，使得基于场景挖掘的新型个性化学习服务模式的重要性越发凸显。而学习者模型作为个性化学习服务系统的核心部件，目前还无法满足新时代下高精准的个性化服务要求。基于此，文章提出一种基于场景感知的学习者建模方法，该方法是基于近些年有关学习者特征分析模型研究的分析结果，融合学习者的场景特性，设计了一个6维度学习者特征分析模型，在此基础上，融合场景感知建模方法和频繁序列挖掘算法，计算不同学习场景下各维度学习者特征值，由此构建一个具有场景特性的个性化学习者模型，并基于该模型探讨了个性化学习服务推荐演化框架。
【英文摘要】：
In the era of "Internet + education", as traditional learning scenes are constantly being reconstructed, the new learning scenes are gradually developing into dynamic, diversified and fragmented models, which makes new personalized learning service models based on scene mining more and more important. However, the learner model, as the core component of the personalized learning service system, cannot meet the high-precision personalized service requirements in the new era. Therefore, this paper proposes a learner modeling method based on context awareness. On the basis of the analysis results of recent studies on learner feature analysis models, together with the scene features of learners, a 6-dimensional learner feature analysis model is designed. Then, the context-awareness modeling method and frequent sequence mining algorithm are used to calculate the value of learner feature in each dimension under different learning scenes, and a personalized learner model with scene features is constructed. Finally, based on that model, the evolution framework of personalized learning service recommendation is discussed.