Publication
A data science maturity model applied to students' modeling
| dc.contributor.author | Cavique, Luís | |
| dc.contributor.author | Pombalinho, Paulo | |
| dc.contributor.author | Correia, Luís | |
| dc.date.accessioned | 2025-10-14T09:52:03Z | |
| dc.date.available | 2025-10-14T09:52:03Z | |
| dc.date.issued | 2023-12-06 | |
| dc.description.abstract | Maturity models define a series of levels, each representing an increased complexity in information systems. Data Science appears in the Business Intelligence (BI) and Business Analytics (BA) literature. This work applies the _IABE maturity model, which includes two additional levels: Data Engineering (DE) at the bottom and Business Experimentation (BE) at the top. This study uses the _IABE model for students' modeling in the ModEst project. For this purpose, the Public Administration organism is the Directorate-General for Statistics of Education and Science (DGEEC) of the Portuguese Education Ministry. DGEEC provided vast data on two million students per year in the Portuguese school system, from pre-scholar to doctoral programs. This work presents the comprehensible _IABE maturity model to extract new knowledge from the DGEEC dataset. The method applied is _IABE, where after the DE level, wh-questions are formulated and answered with the most appropriate techniques at each maturity level. This work's novelty is applying the maturity model _IABE to a unique dataset for the first time. Wh-questions are stated at the BI level using data summarization; at the BA level, predictive models are performed, and counterfactual approaches are presented at the BE level. | eng |
| dc.description.sponsorship | The authors would like to acknowledge the LASIGE Research Unit, ref. UIDB/00408/2020 and ref. UIDP/00408/2020, and the support of ModEst project, DSAIPA/DS/0039/2018, FCT, Portugal. | |
| dc.identifier.doi | 10.28991/ESJ-2023-07-06-08 | |
| dc.identifier.issn | 2610-9182 | |
| dc.identifier.uri | http://hdl.handle.net/10400.2/20356 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.relation | LASIGE - Extreme Computing | |
| dc.relation | Student flow modelling in the Portuguese educational system | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Maturity model | |
| dc.subject | Wh-question | |
| dc.subject | Students' modeling | |
| dc.subject | Business intelligence | |
| dc.subject | Business analytics | |
| dc.subject | Causality | |
| dc.title | A data science maturity model applied to students' modeling | eng |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.awardTitle | LASIGE - Extreme Computing | |
| oaire.awardTitle | Student flow modelling in the Portuguese educational system | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00408%2F2020/PT | |
| oaire.awardURI | http://hdl.handle.net/10400.2/20355 | |
| oaire.citation.title | Emerging Science Journal | |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| oaire.fundingStream | Concurso de Projetos de Investigação Científica e Desenvolvimento Tecnológico em Ciência dos dados e inteligência artificial na Administração Pública - 2018 | |
| oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |
| person.familyName | Cavique | |
| person.familyName | Pombalinho | |
| person.familyName | Correia | |
| person.givenName | Luís | |
| person.givenName | Paulo | |
| person.givenName | Luís | |
| person.identifier | F-3440-2016 | |
| person.identifier.ciencia-id | 911E-84AC-3956 | |
| person.identifier.ciencia-id | AF18-066F-60F6 | |
| person.identifier.ciencia-id | CC18-5389-6CBA | |
| person.identifier.orcid | 0000-0002-5590-1493 | |
| person.identifier.orcid | 0000-0001-7583-6791 | |
| person.identifier.orcid | 0000-0003-2439-1168 | |
| person.identifier.rid | M-3656-2013 | |
| person.identifier.scopus-author-id | 56865595100 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
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