Emotion-based decision support tool for learning processes
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Date
2021
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Abstract
Student stress is a problem that hinders the teaching-learning
processes, and that has increased considerably since the
beginning of the Covid-19 pandemic. This article introduces a
framework for the development of an emotion-based decision
support tool for learning processes. As a case study, we consider
undergraduate students starting their academic year virtually in
the context of a pandemic. Through the application of the
PANAS questionnaire and NLP techniques on free-text
responses, students' emotions are automatically classified as
positive and negative, as well as a level of basic emotions of the
Plutchik model. The results allow to identify the most frequent
sentiments in students. Also, they show concordances between
both measurement instruments and a high capacity for the
classification of emotions.
Description
Keywords
E-learning, Sentiment analysis, PANAS, Covid-19, Decision support tool