论文标题
自适应忘记曲线的间隔重复语言学习
Adaptive Forgetting Curves for Spaced Repetition Language Learning
论文作者
论文摘要
心理学家,教育家和认知科学家都广泛探索了遗忘曲线。在智能辅导系统的背景下,为每个用户和知识组件(例如词汇单词)建模遗忘曲线应该使我们能够制定最佳的修订策略,以抵消内存衰减并确保长期保留。在这项研究中,我们探讨了包括心理和语言特征的各种遗忘曲线模型,并使用这些模型来预测英语学习者作为第二语言的单词回忆的概率。我们使用来自在线词汇教学平台的数据评估模型及其功能的影响,并发现单词复杂性是一个非常有用的功能,可以通过神经网络模型成功地学习。
The forgetting curve has been extensively explored by psychologists, educationalists and cognitive scientists alike. In the context of Intelligent Tutoring Systems, modelling the forgetting curve for each user and knowledge component (e.g. vocabulary word) should enable us to develop optimal revision strategies that counteract memory decay and ensure long-term retention. In this study we explore a variety of forgetting curve models incorporating psychological and linguistic features, and we use these models to predict the probability of word recall by learners of English as a second language. We evaluate the impact of the models and their features using data from an online vocabulary teaching platform and find that word complexity is a highly informative feature which may be successfully learned by a neural network model.