Natural language processing for analysis of student online sentiment in a postgraduate program

  • Truc D Pham The Mind Lab, Auckland, New Zealand
  • Darcy Vo The Mind Lab, Auckland, New Zealand
  • Frank Li The Mind Lab, Auckland, New Zealand
  • Karen Baker The Mind Lab, Auckland, New Zealand
  • Binglan Han The Mind Lab, Auckland, New Zealand
  • Lucie Lindsay The Mind Lab, Auckland, New Zealand
  • Mohsen Pashna Tech Futures Lab, Auckland, New Zealand
  • Rich Rowley Tech Futures Lab, Auckland, New Zealand
Keywords: Sentiment analysis; online learning; online interaction; postgraduate studies

Abstract

Higher education institutes are continually looking for new and better ways to support and understand the learning experience of their students. One possible option is to use sentiment analysis tools to investigate the attitudes and emotions of students when they are interacting on social media about their course experience. In this study, we analysed the social media posts, from a closed programme-based community, of more than 300 students in a single programme cohort by processing the dataset with the Google cloud-based Natural Language Processing API for sentiment analysis. The sentiment scores and magnitudes were then visualised to help explore the research question ‘How does a natural language processing tool help analyse student online sentiment in a postgraduate program?’ The results have provided a better understanding of students’ online sentiment relating to the activities and assessments of the programme as well as the variation of that sentiment over the timeline of the programme.

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Published
2020-09-08
How to Cite
PhamT. D., VoD., LiF., BakerK., HanB., LindsayL., PashnaM., & RowleyR. (2020). Natural language processing for analysis of student online sentiment in a postgraduate program. Pacific Journal of Technology Enhanced Learning, 2(2), 15-30. https://doi.org/10.24135/pjtel.v2i2.4