Rising value of data in contemporary higher education
| dc.authorid | 0009-0006-1242-9172 | |
| dc.authorid | 0000-0002-7981-3121 | |
| dc.contributor.author | Eşkinat, Ali | en_US |
| dc.contributor.author | Teker, Suat | en_US |
| dc.date.accessioned | 2025-07-09T12:41:33Z | |
| dc.date.available | 2025-07-09T12:41:33Z | |
| dc.date.issued | 2024-12-31 | |
| dc.department | Işık Üniversitesi, İktisadi, İdari ve Sosyal Bilimler Fakültesi, İşletme Bölümü | en_US |
| dc.department | Işık University, Faculty of Economics, Administrative and Social Sciences, Department of Management | en_US |
| dc.description.abstract | Purpose - The purpose of this study is to reflect the importance of effective use of data to predict and improve academic success as an essential criterion for assessing the quality of higher education institutions in the 21st Century. This paper intends to clarify importance of data and its evaluation components, namely Educational Data Mining (EDM), Learning Analytics (LA), Artificial intelligence (AI) and Machine Learning (ML), as integral part of Fifth Generation Universities (UNIVERSITY 5.0) era in the globalized competitive higher education sector. For this reason, this paper advocates “Rising Value of Data in Contemporary Higher Education” for the university of the new age. Methodology - The study employs a literature review aiming to reflect the new atmosphere and requirements in the higher education system based on selected topics. A comprehensive analysis on the game changer role of data in the higher education institutions was considered. The aim was to identify the difference created by effective use of data in higher education institutions to predict and improve academic success in the competitive academic environment of the new era. Findings - The analysis reveals that higher education institutions should understand the essential role of educational data with the expansion of digital revolution and rapid change in technologies in the 21st Century and design their strategies accordingly. Notably, it is clearly seen that the universities have not only effectively use educational data and its evaluation components namely Educational Data Mining (EDM), Learning Analytics (LA), Artificial intelligence (AI) and Machine Learning (ML) but also internalize the reality of their rising value to predict and improve academic success as well as creating a significant financial contribution to their development. As a matter of the fact, universities established many projects and effectively used their Learning Analytics (LA) tools. Besides, the emergence of Artificial intelligence (AI) and Machine Learning (ML) enhanced the efficiency and effectiveness of management operations. Conclusion - Findings may be concluded that universities need to apply the effective use of data particularly in the context of new era like Industry 5.0, Society 5.0 and University 5.0 to obtain academic success, which is considered as an essential criterion for assessing the quality of higher education institutions. Indeed, universities have to follow a data- driven culture as greater demands of universities already appeared for retention, completion and graduation rates of students to improve student success. As a matter of fact, the effective use of Educational Data Mining (EDM) and Learning Analytics (LA) is going on for the last two decades in higher education institutions. Indeed, Artificial intelligence (AI) and Machine Learning (ML) are effective in data management as two impressive game changers for universities changing educational world from the financial perspective. For this reason, it may be argued that the effective use of data and its evaluation components, namely Educational Data Mining (EDM), Learning Analytics (LA), Artificial intelligence (AI) and Machine Learning (ML) are considered as the integral part of Fifth Generation Universities (UNIVERSITY 5.0) era in the globalized competitive higher education sector of 21st Century. | en_US |
| dc.description.version | Publisher's Version | en_US |
| dc.identifier.citation | Eşkinat, A. & Teker, S. (2024). Rising value of data in contemporary higher education, 20(1), 41-46. doi:https://doi.org/10.17261/Pressacademia.2024.1923 | en_US |
| dc.identifier.endpage | 46 | |
| dc.identifier.issn | 2459-0762 | |
| dc.identifier.issue | 1 | |
| dc.identifier.startpage | 41 | |
| dc.identifier.uri | https://hdl.handle.net/11729/6546 | |
| dc.identifier.uri | https://doi.org/10.17261/Pressacademia.2024.1923 | |
| dc.identifier.volume | 20 | |
| dc.institutionauthor | Teker, Suat | en_US |
| dc.institutionauthorid | 0000-0002-7981-3121 | |
| dc.language.iso | en | en_US |
| dc.peerreviewed | Yes | en_US |
| dc.publicationstatus | Published | en_US |
| dc.publisher | Suat Teker | en_US |
| dc.relation.ispartof | PressAcademia Procedia | en_US |
| dc.relation.publicationcategory | Makale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.subject | Higher education | en_US |
| dc.subject | Educational data mining | en_US |
| dc.subject | Learning analytics | en_US |
| dc.subject | Artificial intelligence and machine learning | en_US |
| dc.subject | University 5.0 | en_US |
| dc.title | Rising value of data in contemporary higher education | en_US |
| dc.type | Article | en_US |
| dspace.entity.type | Publication | en_US |
