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The analysis of students opinion about the teachers skills using supervised learning

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dc.contributor.author PENTIUC, Stefan-Gheorghe
dc.contributor.author BILIUS, Laura-Bianca
dc.date.accessioned 2022-04-12T10:59:20Z
dc.date.available 2022-04-12T10:59:20Z
dc.date.issued 2021
dc.identifier.citation PENTIUC, Stefan-Gheorghe, BILIUS, Laura-Bianca. The analysis of students opinion about the teachers skills using supervised learning. In: Electronics, Communications and Computing: proc. of. the 11th Intern. Conf.: Technical University of Moldova, October 21-22, 2021. Chişinău, 2021, p. 47. ISBN 978-9975-4264-8-0.
dc.identifier.isbn 978-9975-4264-8-0
dc.identifier.uri http://repository.utm.md/handle/5014/20079
dc.description Only Abstract en_US
dc.description.abstract The System for biannual teachers’ evaluation made by students, acquires a large amount of information that becomes difficult to be analyzed by a manager. It is true that delivers a final score, but it is calculated based only on the answers to the questions with several pre-defined answer options. In their questionnaire, there are also open questions in which students can express themselves freely. These answers contain valuable information, but an educational manager needs a long time to read them all individually. In this paper is proposed an automatic module for interpreting the answers. The module will report to the educational manager only the answers that need to be analyzed. The module uses natural language processing techniques, and supervised machine learning for selecting the answers to be analyzed in a certain context. en_US
dc.language.iso en en_US
dc.publisher Universitatea Tehnică a Moldovei en_US
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/us/ *
dc.subject educational manager en_US
dc.subject natural language en_US
dc.subject supervised learning en_US
dc.title The analysis of students opinion about the teachers skills using supervised learning en_US
dc.type Article en_US


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  • 2021
    Proceedings of the 11th IC|ECCO; October 21-22, 2021

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Attribution-NonCommercial-NoDerivs 3.0 United States Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States

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