Publication:
Artificial neural network model to predict student performance using nonpersonal information

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Knowledge Reusinges
dc.contributor.authorChavez, Heyul
dc.contributor.authorChávez Arias, Bill
dc.contributor.authorContreras Rosas, Sebastián
dc.contributor.authorÁlvarez Rodríguez, José María
dc.contributor.authorRaymundo, Carlos
dc.date.accessioned2023-02-28T11:41:53Z
dc.date.available2023-02-28T11:41:53Z
dc.date.issued2023-02-09
dc.description.abstractIn recent years, artificial intelligence has played an important role in education, wherein one of the most commonly used applications is forecasting students¿ academic performance based on personal information such as social status, income, address, etc. This study proposes and develops an artificial neural network model capable of determining whether a student will pass a certain class without using personal or sensitive information that may compromise student privacy. For model training, we used information regarding 32,000 students collected from The Open University of the United Kingdom, such as number of times they took the course, average number of evaluations, course pass rate, average use of virtual materials per date and number of clicks in virtual classrooms. Attributes selected for the model are as follows: 93.81% accuracy, 94.15% precision, 95.13% recall, and 94.64% F1-score. These results will help the student authorities to take measures to avoid withdrawal and underachievement.en
dc.identifier.bibliographicCitationChavez, H., Chavez-Arias, B., Contreras-Rosas, S., Álvarez-Rodríguez, J.M., Raymundo, C. (2023). Artificial neural network model to predict student performance using nonpersonal information. Frontiers in Education, 8, 1106679en
dc.identifier.doihttps//doi.org/10.3389/feduc.2023.1106679
dc.identifier.issn2504-284X
dc.identifier.publicationfirstpage1
dc.identifier.publicationlastpage11
dc.identifier.publicationtitleFrontiers in Educationen
dc.identifier.publicationvolume8
dc.identifier.urihttps://hdl.handle.net/10016/36691
dc.identifier.uxxiAR/0000032144
dc.language.isoengen
dc.publisherFrontiers Mediaen
dc.rights© 2023, The Autors
dc.rightsAtribución 3.0 España
dc.rights.accessRightsopen accessen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/
dc.subject.ecienciaInformáticaes
dc.subject.otherprivacyen
dc.subject.otherpersonal dataen
dc.subject.otherneural networksen
dc.subject.otherforecastingen
dc.subject.otheracademic performanceen
dc.titleArtificial neural network model to predict student performance using nonpersonal informationen
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
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