GENERATIVE AI: CHALLENGES TO ACADEMIC QUALITY
https://doi.org/10.55452/1998-6688-2023-20-3-17-25
Abstract
This study explores the intricate relationship between Generative Artificial Intelligence and Academic Quality, two domains that have robust technical and historical underpinnings. Originating from divergent research fields, an understanding of the impact of one on the other necessitates a foundational familiarity with both. We offer a comprehensive review that serves as a bedrock for future scholarly dialogue. We articulate key insights into how emerging generative technologies are anticipated to influence academic quality. Concurrently, we note that these technological advancements are emerging at a time of significant transformation and diversification within higher education. While it is premature to proffer definitive predictions, we argue that the impact of these technologies will be institution-specific, contingent upon the unique mission and vision of each educational entity. Our analysis and reflection suggests that institutions emphasizing critical thinking and innovation stand to gain more from the integration of Generative Artificial Intelligence technologies than those primarily focused on career preparation for students.
About the Authors
Yeralan Sencer
ADA University
Azerbaijan
Azerbaijan
Sencer Yeralan, PhD Professor
Baku
Ancona Lee Laura
UNIP
Brazil
Brazil
Laura Ancona Lee, PhD, Dean Academic Internationalization
S˜ao Paulo
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Review
For citations:
Sencer Ye., Laura A.L. GENERATIVE AI: CHALLENGES TO ACADEMIC QUALITY. Herald of the Kazakh-British technical university. 2023;20(3):17-25. https://doi.org/10.55452/1998-6688-2023-20-3-17-25
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