Author
Listed:
- Artem Artyukhov
(Institute of Public Administration and Business, Higher School of Economics and Innovation of Lublin, 20-209 Lublin, Poland
Faculty of Commerce, University of Economics in Bratislava, 852-35 Bratislava, Slovakia
Academic and Research Institute of Business, Economics and Management, Sumy State University, 40-007 Sumy, Ukraine)
- Tomasz Wołowiec
(Institute of Public Administration and Business, Higher School of Economics and Innovation of Lublin, 20-209 Lublin, Poland)
- Nadiia Artyukhova
(Faculty of Commerce, University of Economics in Bratislava, 852-35 Bratislava, Slovakia
Academic and Research Institute of Business, Economics and Management, Sumy State University, 40-007 Sumy, Ukraine)
- Sylwester Bogacki
(Institute of Public Administration and Business, Higher School of Economics and Innovation of Lublin, 20-209 Lublin, Poland)
- Tetiana Vasylieva
(Academic and Research Institute of Business, Economics and Management, Sumy State University, 40-007 Sumy, Ukraine)
Abstract
This article investigates the relationship between Sustainable Development Goal 4 (SDG 4), academic integrity as its part, and artificial intelligence (AI) through a bibliometric analysis, assessing whether this intersection represents a clash or win-win cooperation. SDG 4 aims to ensure equitable access to quality education, while AI technologies have the potential to enhance educational practices but demote academic integrity. By analyzing a comprehensive body of the literature, this study identifies key trends and thematic areas where AI is applied in educational settings, particularly concerning maintaining academic integrity. The findings reveal a growing body of research highlighting AI’s role in personalizing learning experiences, improving educational accessibility, and supporting educators’ teaching methodologies. However, challenges such as ethical considerations, data privacy, and the digital divide are also addressed, indicating potential conflicts that need to be navigated. Ultimately, this analysis suggests that while there are significant opportunities for synergy between AI and SDG 4, the management of careful implementation and policy frameworks is essential to ensure that AI serves as a tool for promoting inclusive and sustainable education rather than exacerbating existing inequalities. AI transforms science management by enhancing data analysis, streamlining research processes, and improving decision-making, ultimately leading to more efficient and effective scientific research and innovation. The findings reveal that while AI can facilitate personalized learning and enhance educational accessibility, it also poses challenges related to academic misconduct, such as plagiarism and the misuse of AI-generated content. This duality highlights the need for educational institutions to develop robust frameworks that leverage AI’s capabilities while safeguarding academic integrity. The article concludes that a collaborative approach, integrating AI into educational practices with a strong emphasis on ethical considerations and integrity, can lead to a synergistic relationship that supports the goals of SDG 4. Recommendations for future research and practical implications for managers, educators, scientists, and policymakers are also discussed, emphasizing the importance of fostering an educational environment that embraces innovation while upholding ethical standards.
Suggested Citation
Artem Artyukhov & Tomasz Wołowiec & Nadiia Artyukhova & Sylwester Bogacki & Tetiana Vasylieva, 2024.
"SDG 4, Academic Integrity and Artificial Intelligence: Clash or Win-Win Cooperation?,"
Sustainability, MDPI, vol. 16(19), pages 1-23, September.
Handle:
RePEc:gam:jsusta:v:16:y:2024:i:19:p:8483-:d:1488753
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:19:p:8483-:d:1488753. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.