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Supervised machine learning for automatic assessment of free-text answers

2021Conference paper Restricted access
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dc.contributor.authorRocha, Fabio Gomes
dc.contributor.authorRodriguez, Guillermo Horacio
dc.contributor.authorAndrade, Eli Emanuel F.
dc.contributor.authorGuimarães, Adolfo
dc.contributor.authorGonçalves, Vitor
dc.contributor.authorFerraz Sabino, Rosimeri
dc.date.accessioned2021-12-07T09:46:36Z
dc.date.available2021-12-07T09:46:36Z
dc.date.issued2021
dc.description.abstractThe learning assessment seeks to collect data that allows for identifying learning gaps for teacher decision-making. Hence, teachers need to plan and select various assessment instruments that enable the verification of learning evolution. Considering that a more significant number of evaluation instruments and modalities increase the teachers’ workload, the adoption of machine learning might support the assessing actions and amplify the potential of students’ observation and follow-up. This article aims to analyze machine learning algorithms for automatic classification of free-text answers, i.e., evaluating descriptive questions written in Portuguese. We utilized a dataset of 9981 free-text answers for 17 questions. After pre-processing the data, we used eight classification algorithms. In conclusion, we highlight that the Logistic Regression, ExtraTrees, Random Forest, and Multi-layer Perceptron algorithms obtained results above 0.9 of F-score for both multi-class and binary classification.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationRocha, Fabio; Rodriguez, Guillermo Horacio; Andrade, Eli Emanuel F.; Guimarães, Adolfo; Gonçalves, Vitor; Ferraz Sabino, Rosimeri (2021) Supervised Machine Learning for Automatic Assessment of Free-Text Answers. In Batyrshin I.; Gelbukh A.; Sidorov G. (Eds.) 20th Mexican International Conference on Artificial Intelligence, MICAI 2021. Mexico City: Springer Science and Business Media Deutschland GmbH. ISBN 978-303089819-9pt_PT
dc.identifier.doi10.1007/978-3-030-89820-5_1pt_PT
dc.identifier.isbn978-3-030-89819-9
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/10198/24469
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringer Science and Business Media Deutschland GmbHpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectLearning assessmentpt_PT
dc.subjectSupervised machine learningpt_PT
dc.subjectMulti-class classificationpt_PT
dc.subjectFree-text answerspt_PT
dc.subjectTeacher decision makingpt_PT
dc.titleSupervised machine learning for automatic assessment of free-text answerspt_PT
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferencePlaceMexico Citypt_PT
oaire.citation.endPage12pt_PT
oaire.citation.startPage3pt_PT
oaire.citation.title20th Mexican International Conference on Artificial Intelligence, MICAI 2021pt_PT
oaire.citation.volume13068pt_PT
person.familyNameGonçalves
person.givenNameVítor
person.identifier.ciencia-idA310-FFD6-55A1
person.identifier.orcid0000-0002-0645-6776
rcaap.rightsrestrictedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication51ba4541-fca8-4932-ac25-2fe98006bdb9
relation.isAuthorOfPublication.latestForDiscovery51ba4541-fca8-4932-ac25-2fe98006bdb9

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