Riquelme, FabiánFabiánRiquelmeEduardo PuraivanMarcelo De LeónJarnishs Beltran2025-08-252025-08-252021-06-2310.23919/cisti52073.2021.94763122-s2.0-85115736010https://cris-uv-2.scimago.es/handle/123456789/5652Student 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.enacceso restringidoComputer Networks And CommunicationsInformation Systemsconference paper