Human Research in Rehabilitation (Sep 2024)

From Theory to Practice: A Holistic Study of the Application of Artificial Intelligence Methods and Techniques in Higher Education and Science

  • Suada A. Dzogovic,
  • Blagojka Zdravkovska-Adamova,
  • Harun Serpil

DOI
https://doi.org/10.21554/hrr.092406
Journal volume & issue
Vol. 14, no. 2
pp. 293 – 311

Abstract

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This study endeavors to conduct an exhaustive analysis of the integration of artificial intelligence (AI) into educational and scientific practices, and to elucidate potential pathways for progress in this domain. It involves reflecting on the impact of AI across various education domains, the advancement of scientific methodologies and discoveries, and the broader societal development. With the help of a systematic review of the relevant literature, examples, and trends of the application of AI in education and science are studied, emphasizing their methodological and conceptual basis. The qualitative approach of this study is based on a systematic analytical review of academic publications, with an attempt to identify key topics and trends in the integration of AI in the fields of education and science. The critical analysis of relevant research assesses the reliability of the presented evidence and applied research methods, and examines the differences and convergence of the approaches of different authors. This methodological approach allows a more profound analysis of AI's impact, while also exploring AI as an advanced research methodology and analyzing various perspectives and contributions of authors within the realms of education and science. The results demonstrate that AI integration significantly contributes to improving educational processes, fostering student creativity, and enhancing scientific practices. Furthermore, the study identifies research gaps, emphasizing the need to explore ethical implications, long-term impacts, and inclusive models of AI. Based on these findings, further studies employing longitudinal/ experimental methods and large dataset analyses are recommended. The findings are expected to advance research by deepening our understanding of the complex interactions between artificial intelligence, education, and science.

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