The Potential of Machine Learning and NLP for Handling Students' Feedback (A Short Survey)

• URL: http://arxiv.org/abs/2011.05806v1
• Date: Sat, 7 Nov 2020 17:28:40 GMT
• Title: The Potential of Machine Learning and NLP for Handling Students' Feedback (A Short Survey)
• Authors: Maryam Edalati
• Abstract summary: 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.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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