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A Personalized Task Recommendation System for Vocabulary Learning Based on Readability and Diversity

机译:基于可读性和多样性的词汇学习的个性化任务推荐系统

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Vocabulary learning is the foundation of language acquisition for second language learners. To assist language learners' vocabulary learning, this research investigated a personalized task recommendation system based on readability and diversity. A word learning theory, the involvement load hypothesis, has also been applied as the theoretical framework of the system to facilitate task recommendation. Ten Chinese learners of English were invited to participate in the research and used the system for vocabulary learning for around two weeks. These students were all intermediate learners. The participants' learning experience, outcomes, motivation and attitude were measured respectively using questionnaires, pretests, posttests, and interviews. The results showed that the participants were very satisfied with the learning experience, and positive learning outcomes and attitudes were observed. Many students stated that they would love to keep using the proposed recommendation system for future language learning. It is also suggested that the wide use of this system will benefit many self-access language learners.
机译:词汇学习是第二语言学习者语言习得的基础。为了协助语言学习者的词汇学习,本研究调查了基于可读性和多样性的个性化任务推荐系统。一个词学习理论,参与负荷假设,也已被应用于系统的理论框架,以促进任务推荐。邀请十中国学习英语学习者参加该研究,并使用该系统在两周内进行词汇学习。这些学生都是中级学习者。参与者的学习经验,结果,动机和态度分别使用调查问卷,预测试,后塔和访谈来测量。结果表明,参与者对学习经验非常满意,并观察到积极的学习结果和态度。许多学生表示,他们很乐意继续使用拟议的建议制度来进行未来的语言学习。还建议使用该系统的广泛使用将使许多自动访问语言学习者受益。

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