论文标题
机器学习和NLP的潜力来处理学生的反馈（一项简短的调查）
The Potential of Machine Learning and NLP for Handling Students' Feedback (A Short Survey)
论文作者
论文摘要
本文回顾了近年来使用数据挖掘技术发表的学生反馈论文的文献。特别是，重点是强调那些使用机器学习或深度学习方法的论文。学生反馈评估是一个热门话题，最近引起了很多关注。由于最近的流行病爆发，这种重要性增加了很多，这促使许多大学通过电子学习平台和包括大规模开放在线课程（MOOC）在内的工具将教学从校园内的物理班级转变为在线。现在评估学生的反馈更加重要。因此，这份简短的调查论文重点介绍了自动语言处理领域的最新趋势，这些趋势是关于自动学生反馈评估的主题。它介绍了该领域通常使用的技术，并讨论了一些未来的研究方向。
This article provides a review of the literature of students' feedback papers published in recent years employing data mining techniques. In particular, the focus is to highlight those papers which are using either machine learning or deep learning approaches. Student feedback assessment is a hot topic which has attracted a lot of attention in recent times. The importance has increased manyfold due to the recent pandemic outbreak which pushed many colleges and universities to shift teaching from on-campus physical classes to online via eLearning platforms and tools including massive open online courses (MOOCs). Assessing student feedback is even more important now. This short survey paper, therefore, highlights recent trends in the natural language processing domain on the topic of automatic student feedback assessment. It presents techniques commonly utilized in this domain and discusses some future research directions.
