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Application of Pattern Recognition Techniques for MathE Questions Difficulty Level Definition

2024Conference paper Restricted access
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dc.contributor.authorAzevedo, Beatriz Flamia
dc.contributor.authorSouza, Roberto Molina de
dc.contributor.authorPacheco, Maria F.
dc.contributor.authorFernandes, Florbela P.
dc.contributor.authorPereira, Ana I.
dc.date.accessioned2024-10-08T10:31:59Z
dc.date.available2024-10-08T10:31:59Z
dc.date.issued2024
dc.description.abstractActive learning is a modern educational strategy that involves students in the learning process through diverse interactive and participatory activities. The MathE platform is an international online platform created to support students and lecturers in the Mathematics teaching and learning process. This platform offers a tool to aid and engage students, ensuring new and creative ways to encourage them to improve their mathematical skills. The study proposed in this paper refers to a comprehensive investigation of the patterns that may exist within the set of questions available on the MathE platform. The objective is to investigate how to evaluate the student’s opinions about the question’s difficulty levels based on the variables extracted from student answers collected through surveys applied among the platform’s users. Moreover, a comparative study between variables is performed using correlation and hypothesis tests. Furthermore, based on the results obtained for samples of different sizes, it was possible to define the most appropriate number of answers that should be considered to categorize the question’s difficulty level. The results demonstrated that the variables extracted could be used to carry out the question level, and 30 answers are the most appropriate number of questions that must be used to categorize the question level.pt_PT
dc.description.sponsorshipThis work has been supported by FCT Fundação para a Ciência e Tecnologia within the R&D Units Project Scope UIDB/05757/2020, UIDP/05757/2020, SusTEC LA/P/0007/2021 and Erasmus Plus KA2 within the project 2021-1-PT01-KA220- HED-000023288. Beatriz Flamia Azevedo is supported by FCT Grant Reference SFRH/BD/07427/2021.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAzevedo, Beatriz Flamia; Souza, Roberto Molina de; Pacheco, Maria F.; Fernandes, Florbela P.; Pereira, Ana I. (2024). Application of Pattern Recognition Techniques for MathE Questions Difficulty Level Definition. In 3rd International Conference on Optimization, Learning Algorithms and Applications (OL2A 2023). Cham: Springer Nature, Vol. 1, p. 300–315. ISBN 978-3-031-53024-1pt_PT
dc.identifier.doi10.1007/978-3-031-53025-8_21pt_PT
dc.identifier.isbn978-3-031-53024-1
dc.identifier.isbn978-3-031-53025-8
dc.identifier.urihttp://hdl.handle.net/10198/30360
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringer Naturept_PT
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relationAssociate Laboratory for Sustainability and Tecnology in Mountain Regions
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectActive learningpt_PT
dc.subjectE-learningpt_PT
dc.subjectHigher educationpt_PT
dc.subjectMathematicspt_PT
dc.titleApplication of Pattern Recognition Techniques for MathE Questions Difficulty Level Definitionpt_PT
dc.typeconference paper
dspace.entity.typePublication
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardTitleAssociate Laboratory for Sustainability and Tecnology in Mountain Regions
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F05757%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0007%2F2020/PT
oaire.citation.endPage315pt_PT
oaire.citation.startPage300pt_PT
oaire.citation.title3rd International Conference on Optimization, Learning Algorithms and Applications (OL2A 2023)pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
person.familyNameAzevedo
person.familyNamePacheco
person.familyNameFernandes
person.familyNamePereira
person.givenNameBeatriz Flamia
person.givenNameMaria F.
person.givenNameFlorbela P.
person.givenNameAna I.
person.identifier.ciencia-id181E-855C-E62C
person.identifier.ciencia-idF319-DAC3-8F15
person.identifier.ciencia-id501D-6FD0-CC53
person.identifier.ciencia-id0716-B7C2-93E4
person.identifier.orcid0000-0002-8527-7409
person.identifier.orcid0000-0001-7915-0391
person.identifier.orcid0000-0001-9542-4460
person.identifier.orcid0000-0003-3803-2043
person.identifier.ridF-3168-2010
person.identifier.scopus-author-id36802474600
person.identifier.scopus-author-id35179471000
person.identifier.scopus-author-id15071961600
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsrestrictedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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