Adaptive Learning Material Recommendation in Online Language Education
Adaptive Learning Material Recommendation in Online Language Education
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DOI：
10.1007/978-3-030-23207-8_55
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发表时间：
2019-05
期刊：
影响因子：
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通讯作者：
Shuhan Wang;Hao Wu;Ji Hun Kim;Erik Andersen
中科院分区：
文献类型：
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作者：
Shuhan Wang;Hao Wu;Ji Hun Kim;Erik Andersen
在在线语言教育中，推荐与学生知识相匹配的学习材料是一项挑战，因为我们通常缺乏有关材料难度和每个学生能力的信息。我们提出了一种改进的层次结构来建模语料库中的词汇知识，并引入了一种自适应算法来推荐在线语言学习者的阅读文本。我们用日语学习工具评估了我们的方法，发现在材料推荐中加入适应性显著提高了参与度。
In online language education, it is challenging to recommend learning materials that match the student’s knowledge since we typically lack information about the difficulty of materials and the abilities of each student. We propose a refined hierarchical structure to model vocabulary knowledge in a corpus and introduce an adaptive algorithm to recommend reading texts for online language learners. We evaluated our approach with a Japanese learning tool, finding that adding adaptivity into material recommendation significantly increased engagement.