  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.
