A Data Warehousing Framework for Predictive Analytics in Higher Education: A Focus on Student at-Risk Identification
This paper will examine the development of a data warehouse aimed at improving decision-making in higher education, which focuses on the identification of students at-risk of academic failure through machine learning techniques. This research utilizes South East European University (SEEU) as a case...
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| Format: | Article |
| Language: | English |
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Sciendo
2024-12-01
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| Series: | SEEU Review |
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| Online Access: | https://doi.org/10.2478/seeur-2024-0020 |
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| _version_ | 1832570294243426304 |
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| author | Ismaili Burim Besimi Adrian |
| author_facet | Ismaili Burim Besimi Adrian |
| author_sort | Ismaili Burim |
| collection | DOAJ |
| description | This paper will examine the development of a data warehouse aimed at improving decision-making in higher education, which focuses on the identification of students at-risk of academic failure through machine learning techniques. This research utilizes South East European University (SEEU) as a case study to show how data warehousing can integrate various student data—including demographics, academic performance, grades, attendance, and engagement—into an integrated framework that enables predictive analytics. |
| format | Article |
| id | doaj-art-3490be27f1694471b7288e2ba0f97c42 |
| institution | Kabale University |
| issn | 1857-8462 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Sciendo |
| record_format | Article |
| series | SEEU Review |
| spelling | doaj-art-3490be27f1694471b7288e2ba0f97c422025-02-02T15:49:09ZengSciendoSEEU Review1857-84622024-12-01192435710.2478/seeur-2024-0020A Data Warehousing Framework for Predictive Analytics in Higher Education: A Focus on Student at-Risk IdentificationIsmaili Burim0Besimi Adrian11Faculty of Contemporary Sciences and Technologies, South East European University, Tetovo, North Macedonia2Faculty of Contemporary Sciences and Technologies, South East European University, Tetovo, North MacedoniaThis paper will examine the development of a data warehouse aimed at improving decision-making in higher education, which focuses on the identification of students at-risk of academic failure through machine learning techniques. This research utilizes South East European University (SEEU) as a case study to show how data warehousing can integrate various student data—including demographics, academic performance, grades, attendance, and engagement—into an integrated framework that enables predictive analytics.https://doi.org/10.2478/seeur-2024-0020data warehousehigher educationdata efficientstudent progressdecision making |
| spellingShingle | Ismaili Burim Besimi Adrian A Data Warehousing Framework for Predictive Analytics in Higher Education: A Focus on Student at-Risk Identification SEEU Review data warehouse higher education data efficient student progress decision making |
| title | A Data Warehousing Framework for Predictive Analytics in Higher Education: A Focus on Student at-Risk Identification |
| title_full | A Data Warehousing Framework for Predictive Analytics in Higher Education: A Focus on Student at-Risk Identification |
| title_fullStr | A Data Warehousing Framework for Predictive Analytics in Higher Education: A Focus on Student at-Risk Identification |
| title_full_unstemmed | A Data Warehousing Framework for Predictive Analytics in Higher Education: A Focus on Student at-Risk Identification |
| title_short | A Data Warehousing Framework for Predictive Analytics in Higher Education: A Focus on Student at-Risk Identification |
| title_sort | data warehousing framework for predictive analytics in higher education a focus on student at risk identification |
| topic | data warehouse higher education data efficient student progress decision making |
| url | https://doi.org/10.2478/seeur-2024-0020 |
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