| Title: |
Rising value of data in contemporary higher education |
| Authors: |
Eşkinat, Ali; Teker, Suat |
| Publisher Information: |
Suat Teker |
| Publication Year: |
2024 |
| Collection: |
Işık Üniversitesi: DSpace Repository |
| Subject Terms: |
Higher education; Educational data mining; Learning analytics; Artificial intelligence and machine learning; University 5.0 |
| Description: |
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) ... |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
English |
| Relation: |
PressAcademia Procedia; Makale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı; https://hdl.handle.net/11729/6546; https://doi.org/10.17261/Pressacademia.2024.1923; 20; 41; 46 |
| DOI: |
10.17261/Pressacademia.2024.1923 |
| Availability: |
https://hdl.handle.net/11729/6546; https://doi.org/10.17261/Pressacademia.2024.1923 |
| Rights: |
info:eu-repo/semantics/openAccess |
| Accession Number: |
edsbas.967ACBC4 |
| Database: |
BASE |