Work in Progress: Use of Natural Language Processing in the Evaluation of University Satisfaction Level

Jimy Oblitas Cruz, Anabel Pineda-Briseno

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The aim of this study is to examine the use of NLP in an extensive amount of satisfaction feedback in the process and experience of university students from the engineering faculty. The NLP process used was sentiment analysis, which uses artificial intelligence for the extraction of textual data and can classify it as positive, neutral, and negative. The results of the NLP were compared with the manual analysis of the same feedback, finding differences in the results of both methods. Finally, we conclude that the sentiment analysis method is feasible to implement in the context of measuring student satisfaction, and it can become an effective tool with the possibility of working in real-time to generate useful information for making university decisions.

Original languageEnglish
Title of host publicationEDUNINE 2024 - 8th IEEE World Engineering Education Conference
Subtitle of host publicationEmpowering Engineering Education: Breaking Barriers through Research and Innovation, Proceedings
EditorsClaudio da Rocha Brito, Melany M. Ciampi
ISBN (Electronic)9798350348729
DOIs
StatePublished - 2024
Event8th IEEE World Engineering Education Conference, EDUNINE 2024 - Hybid, Guatemala City, Guatemala
Duration: 10 Mar 202413 Mar 2024

Publication series

NameEDUNINE 2024 - 8th IEEE World Engineering Education Conference: Empowering Engineering Education: Breaking Barriers through Research and Innovation, Proceedings

Conference

Conference8th IEEE World Engineering Education Conference, EDUNINE 2024
Country/TerritoryGuatemala
CityHybid, Guatemala City
Period10/03/2413/03/24

Keywords

  • NLP
  • pysentiment
  • sentiment analysis
  • university satisfaction level

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