Artificial intelligence, generative artificial intelligence and research integrity: a hybrid systemic review
Abstract Current advances in academic research stem from two main sources: artificial intelligence technologies and the specific field of generative artificial intelligence. However, the ethical use of these technologies and their implications for academic integrity has not been sufficiently investi...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2025-07-01
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| Series: | Smart Learning Environments |
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| Online Access: | https://doi.org/10.1186/s40561-025-00403-3 |
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| author | Khalid H. Arar Hamit Özen Gülşah Polat Selahattin Turan |
| author_facet | Khalid H. Arar Hamit Özen Gülşah Polat Selahattin Turan |
| author_sort | Khalid H. Arar |
| collection | DOAJ |
| description | Abstract Current advances in academic research stem from two main sources: artificial intelligence technologies and the specific field of generative artificial intelligence. However, the ethical use of these technologies and their implications for academic integrity has not been sufficiently investigated. Therefore, this research examines the ethical use of artificial intelligence technologies and Generative Artificial Intelligence in academic research. It focuses on the current field conditions, detection of research trends, and critical gaps. The study uses a combination of bibliometric and thematic content analysis methods to examine the methodological framework of AI, GenAI, and academic integrity from an interdisciplinary perspective. The research reveals that GenAI integration speed has accelerated across all research stages, including academic writing, literature review, data analysis, and hypothesis development. The study also identifies risks such as biased algorithms, plagiarism risk, false information production, and potential damage to academic integrity. The research ethics approaches developed by academic institutions and journals have not reached maturity in the context of AI. Future research on GenAI within academic processes requires forming ethical principles integrated with oversight systems and policy frameworks. |
| format | Article |
| id | doaj-art-71918cba6e0d4e7f9a5bc64685c26c35 |
| institution | Kabale University |
| issn | 2196-7091 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Smart Learning Environments |
| spelling | doaj-art-71918cba6e0d4e7f9a5bc64685c26c352025-08-20T03:43:31ZengSpringerOpenSmart Learning Environments2196-70912025-07-0112112910.1186/s40561-025-00403-3Artificial intelligence, generative artificial intelligence and research integrity: a hybrid systemic reviewKhalid H. Arar0Hamit Özen1Gülşah Polat2Selahattin Turan3Educational Leadership and Policy, Texas State UniversityCollege of Education, Eskişehir Osmangazi UniversityEducational Sciences Institute, Eskişehir Osmangazi UniversityCollege of Education, Bursa Uludağ UniversityAbstract Current advances in academic research stem from two main sources: artificial intelligence technologies and the specific field of generative artificial intelligence. However, the ethical use of these technologies and their implications for academic integrity has not been sufficiently investigated. Therefore, this research examines the ethical use of artificial intelligence technologies and Generative Artificial Intelligence in academic research. It focuses on the current field conditions, detection of research trends, and critical gaps. The study uses a combination of bibliometric and thematic content analysis methods to examine the methodological framework of AI, GenAI, and academic integrity from an interdisciplinary perspective. The research reveals that GenAI integration speed has accelerated across all research stages, including academic writing, literature review, data analysis, and hypothesis development. The study also identifies risks such as biased algorithms, plagiarism risk, false information production, and potential damage to academic integrity. The research ethics approaches developed by academic institutions and journals have not reached maturity in the context of AI. Future research on GenAI within academic processes requires forming ethical principles integrated with oversight systems and policy frameworks.https://doi.org/10.1186/s40561-025-00403-3Artificial intelligenceGenerative artificial intelligenceResearch integrityEthicsBibliometric analysisSystematic review |
| spellingShingle | Khalid H. Arar Hamit Özen Gülşah Polat Selahattin Turan Artificial intelligence, generative artificial intelligence and research integrity: a hybrid systemic review Smart Learning Environments Artificial intelligence Generative artificial intelligence Research integrity Ethics Bibliometric analysis Systematic review |
| title | Artificial intelligence, generative artificial intelligence and research integrity: a hybrid systemic review |
| title_full | Artificial intelligence, generative artificial intelligence and research integrity: a hybrid systemic review |
| title_fullStr | Artificial intelligence, generative artificial intelligence and research integrity: a hybrid systemic review |
| title_full_unstemmed | Artificial intelligence, generative artificial intelligence and research integrity: a hybrid systemic review |
| title_short | Artificial intelligence, generative artificial intelligence and research integrity: a hybrid systemic review |
| title_sort | artificial intelligence generative artificial intelligence and research integrity a hybrid systemic review |
| topic | Artificial intelligence Generative artificial intelligence Research integrity Ethics Bibliometric analysis Systematic review |
| url | https://doi.org/10.1186/s40561-025-00403-3 |
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