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dc.rights.licenserestrictedAccess-
dc.contributor.authorBursać M.-
dc.contributor.authorBlagojević, Marija-
dc.contributor.authorMilošević, Danijela-
dc.date.accessioned2021-04-20T17:11:10Z-
dc.date.available2021-04-20T17:11:10Z-
dc.date.issued2019-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/10979-
dc.description.abstract© Springer Nature Switzerland AG 2019. This paper presents an overview of the research related to the prediction of the success of the participants in the Technical Drawing course. In order to determine the student’s success, a data mining model was created supported by artificial intelligence. The proposed model gives an overview of the input data on the basis of which it is possible to determine the success of the student’s using artificial neural networks. The results of the prediction give a presentation of the performance of students at the beginning of the course, which gives professors enough time to influence the students and encourage them.-
dc.rightsinfo:eu-repo/semantics/restrictedAccess-
dc.sourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.titleEarly prediction of student success based on data mining and artificial neural network-
dc.typeconferenceObject-
dc.identifier.doi10.1007/978-3-030-37429-7_3-
dc.identifier.scopus2-s2.0-85081917193-
Налази се у колекцијама:Faculty of Technical Sciences, Čačak

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