The main features that influence the academic success of bachelors’ students at Nova School of Business and Economics
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/132927 |
Resumo: | Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence |
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The main features that influence the academic success of bachelors’ students at Nova School of Business and EconomicsAcademic SuccessStudent SuccessEducational Data MiningMachine LearningFeaturesSDG 4 - Quality educationDissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceThe prediction of academic success is a major topic in higher education, especially among the academic community. In this dissertation, we are going to present a data mining approach taking into consideration the features that are the most relevant in terms of successful academic achievement of the Bachelors’ programs at Nova School of Business and Economics (Nova SBE). Initially, we are going to perform a literature review in order to understand the framework of academic success and also to make a summary of previous research on the field of educational data mining when used to assess student success. Subsequently, the empirical approach will start being developed with the extraction of socio-economic, socio-demographic, and academic data of students, which will result in our main dataset. Later, and after the data discovery, data cleansing, and transformation activities, a set of features are going to be taken into consideration according to their relevance for the subject. Based on the dataset containing these features, several predictive data-driven techniques are going to be applied, resulting in models which are going to be assessed in order to understand if the selected features are relevant enough to answer our problem or if there is a need to substitute them by other attributes. This process will result in several iterations that will confer credibility and robustness to the model that demonstrates the best performance in classifying students’ academic success. In the end, it is intended that the insights extracted from the model will provide the school key stakeholders with enough knowledge to capacitate them to take actions that will result in the maximization of the students learning success.Henriques, Roberto André PereiraRUNJacob, David Lázaro2022-02-15T15:56:12Z2022-01-182022-01-18T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/132927TID:202941493enginfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:11:36Zoai:run.unl.pt:10362/132927Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:47:38.566327Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
The main features that influence the academic success of bachelors’ students at Nova School of Business and Economics |
title |
The main features that influence the academic success of bachelors’ students at Nova School of Business and Economics |
spellingShingle |
The main features that influence the academic success of bachelors’ students at Nova School of Business and Economics Jacob, David Lázaro Academic Success Student Success Educational Data Mining Machine Learning Features SDG 4 - Quality education |
title_short |
The main features that influence the academic success of bachelors’ students at Nova School of Business and Economics |
title_full |
The main features that influence the academic success of bachelors’ students at Nova School of Business and Economics |
title_fullStr |
The main features that influence the academic success of bachelors’ students at Nova School of Business and Economics |
title_full_unstemmed |
The main features that influence the academic success of bachelors’ students at Nova School of Business and Economics |
title_sort |
The main features that influence the academic success of bachelors’ students at Nova School of Business and Economics |
author |
Jacob, David Lázaro |
author_facet |
Jacob, David Lázaro |
author_role |
author |
dc.contributor.none.fl_str_mv |
Henriques, Roberto André Pereira RUN |
dc.contributor.author.fl_str_mv |
Jacob, David Lázaro |
dc.subject.por.fl_str_mv |
Academic Success Student Success Educational Data Mining Machine Learning Features SDG 4 - Quality education |
topic |
Academic Success Student Success Educational Data Mining Machine Learning Features SDG 4 - Quality education |
description |
Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-02-15T15:56:12Z 2022-01-18 2022-01-18T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/132927 TID:202941493 |
url |
http://hdl.handle.net/10362/132927 |
identifier_str_mv |
TID:202941493 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
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info:eu-repo/semantics/openAccess |
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openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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