Machine Learning in Education: Innovations, Impacts, and Ethical Considerations
Machine Learning (ML) has recently emerged as a powerful tool with significant potential to revolutionize education, bringing about fundamental changes in pedagogy and research. Its applications span various domains within academia, including administration, instructional method enhancement, and gra...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/11083534/ |
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| author | Ersin Elbasi Muhammad Nadeem Yehia Ibrahim Alzoubi Ahmet E. Topcu Greeshma Varghese |
| author_facet | Ersin Elbasi Muhammad Nadeem Yehia Ibrahim Alzoubi Ahmet E. Topcu Greeshma Varghese |
| author_sort | Ersin Elbasi |
| collection | DOAJ |
| description | Machine Learning (ML) has recently emerged as a powerful tool with significant potential to revolutionize education, bringing about fundamental changes in pedagogy and research. Its applications span various domains within academia, including administration, instructional method enhancement, and grade prediction. This study illustrates how ML can enhance the effectiveness of research, instruction, and study strategies by adapting to student needs and leveraging new communication tools within virtual learning environments. The literature review included various research articles sourced IEEE Xplore, Scopus, Web of Science, PubMed, Google Scholar, and ScienceDirect. The inclusion criteria encompassed studies that explicitly defined Artificial Intelligence (AI) within the medical education sector and were published in English with peer review. This study delves into the potential applications of ML and its associated benefits, which can aid researchers in implementing AI-based educational systems. |
| format | Article |
| id | doaj-art-ae4582e18d004541b71d1e6ca4b04185 |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-ae4582e18d004541b71d1e6ca4b041852025-08-20T03:13:58ZengIEEEIEEE Access2169-35362025-01-011312874112877010.1109/ACCESS.2025.359013411083534Machine Learning in Education: Innovations, Impacts, and Ethical ConsiderationsErsin Elbasi0https://orcid.org/0000-0002-8603-1435Muhammad Nadeem1https://orcid.org/0000-0002-1358-6085Yehia Ibrahim Alzoubi2https://orcid.org/0000-0003-4329-4072Ahmet E. Topcu3https://orcid.org/0000-0003-1929-5358Greeshma Varghese4https://orcid.org/0000-0003-2318-6947College of Engineering and Technology, American University of the Middle East, Kuwait City, KuwaitCollege of Engineering and Technology, American University of the Middle East, Kuwait City, KuwaitCollege of Business Administration, American University of the Middle East, Kuwait City, KuwaitCollege of Engineering and Technology, American University of the Middle East, Kuwait City, KuwaitCollege of Engineering and Technology, American University of the Middle East, Kuwait City, KuwaitMachine Learning (ML) has recently emerged as a powerful tool with significant potential to revolutionize education, bringing about fundamental changes in pedagogy and research. Its applications span various domains within academia, including administration, instructional method enhancement, and grade prediction. This study illustrates how ML can enhance the effectiveness of research, instruction, and study strategies by adapting to student needs and leveraging new communication tools within virtual learning environments. The literature review included various research articles sourced IEEE Xplore, Scopus, Web of Science, PubMed, Google Scholar, and ScienceDirect. The inclusion criteria encompassed studies that explicitly defined Artificial Intelligence (AI) within the medical education sector and were published in English with peer review. This study delves into the potential applications of ML and its associated benefits, which can aid researchers in implementing AI-based educational systems.https://ieeexplore.ieee.org/document/11083534/Artificial intelligencemachine learningeducationpersonalized learningintelligent content generation |
| spellingShingle | Ersin Elbasi Muhammad Nadeem Yehia Ibrahim Alzoubi Ahmet E. Topcu Greeshma Varghese Machine Learning in Education: Innovations, Impacts, and Ethical Considerations IEEE Access Artificial intelligence machine learning education personalized learning intelligent content generation |
| title | Machine Learning in Education: Innovations, Impacts, and Ethical Considerations |
| title_full | Machine Learning in Education: Innovations, Impacts, and Ethical Considerations |
| title_fullStr | Machine Learning in Education: Innovations, Impacts, and Ethical Considerations |
| title_full_unstemmed | Machine Learning in Education: Innovations, Impacts, and Ethical Considerations |
| title_short | Machine Learning in Education: Innovations, Impacts, and Ethical Considerations |
| title_sort | machine learning in education innovations impacts and ethical considerations |
| topic | Artificial intelligence machine learning education personalized learning intelligent content generation |
| url | https://ieeexplore.ieee.org/document/11083534/ |
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