Identification of the satisfaction of university students through sentiment analysis: a systematic review

Abstract

In these times it is necessary to use tools based on artificial intelligence (AI) that contribute to improving the quality of university education for the benefit of students. This article aims to define the state of the question on the application of sentiment analysis in the identification of student satisfaction, based on the systematic review of scientific publications. The research is of an exploratory level and of a mixed approach. The data collection method was based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA) declaration, managing to focus the review based on 27 publications, downloaded from Scopus, ERIC, and Google Scholar. From the systematic review, the following conclusions were reached: the fields of application to a greater extent are found in the academic field and university well-being. Likewise, regarding the contributions achieved, these focused to a greater extent on aspects of the teaching activity, valuing their performance and contributing to their feedback for the redesign of didactic strategies. Finally, in terms of limitations, they focused mainly on the low student participation regarding the use of sentiment analysis to identify student satisfaction; this is due to the lack of regulations or regulations for it is application in the university environment.