针对学生反馈的自适应自然语言目标

Y. A. Kolchinski, S. Ruan, Dan Schwartz, E. Brunskill
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引用次数: 5

摘要

在辅导软件中,针对学生自然语言输入的反馈是使软件更有效的一个有希望的途径。作为一个案例研究,我们使用自然语言处理(NLP)构建了这样一个系统,为在线学习任务中的学生提供自适应反馈。我们发现,相对于传统的选择题定向,NLP定向机制能够从较少的学生互动中提供最佳反馈,并推广到以前未见过的提示。
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Adaptive natural-language targeting for student feedback
In tutoring software, targeting feedback to students' natural-language inputs is a promising avenue for making the software more effective. As a case study, we built such a system using Natural Language Processing (NLP) to provide adaptive feedback to students in an online learning task. We found that the NLP targeting mechanism, relative to more traditional multiple-choice targeting, was able to provide optimal feedback from fewer student interactions and generalize to previously unseen prompts.
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