Predicting students' performance using survey data

dc.contributor.authorOliveira, Catarina Félix de
dc.contributor.authorSobral, Sónia Rolland
dc.date.accessioned2020-04-17T09:47:50Z
dc.date.available2020-04-17T09:47:50Z
dc.date.issued2020
dc.description.abstractThe acquisition of competences for the development of computer programs is one of the main challenges faced by computer science students. As a result of not being able to develop the abilities needed (for example, abstraction), students drop out the subjects and sometimes even the course. There is a need to study the causes of student success (or failure) in introductory curricular units to check for behaviours or characteristics that may be determinant and thus try to prevent and change said causes. The students of one programming curricular unit were invited to answer four surveys. We use machine learning techniques to try to predict the students’ grades based on the answers obtained on the surveys. The results obtained enable us to plan the semester accordingly, by anticipating how many students might need extra support. We hope to increase the students’ motivation and, with this, increase their interest on the subject. This way we aim to accomplish our ultimate goal: reducing the drop out and increasing the overall average student performance.pt_PT
dc.identifier.citationFelix, C., & Sobral, S. R. (2020). Predicting students' performance using survey data. In Proceedings of the EDUCON2020 – IEEE Global Engineering Education Conference, Porto, Portugal, 27-30 April 2020. Disponível no Repositório UPT, http://hdl.handle.net/11328/3050pt_PT
dc.identifier.urihttp://hdl.handle.net/11328/3050
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.rightsopen accesspt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectStudent profilingpt_PT
dc.subjectStudent performancept_PT
dc.subjectProgrammingpt_PT
dc.subjectMachine learningpt_PT
dc.subjectEducational data miningpt_PT
dc.titlePredicting students' performance using survey datapt_PT
dc.typeconferenceObjectpt_PT
degois.publication.locationPorto, Portugalpt_PT
degois.publication.titleEDUCON2020pt_PT
dspace.entity.typePublicationen
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