Résumé:
In terms of speed learning, the integration of Artificial Intelligence (AI) into
academic research offers significant advantages for PhD students to use
advanced research methodology techniques in their research works. The present
conference probes into the use of AI as a digital supervisor that helps PhD
students to refine the historical research methodology for better results. AI
driven technologies like natural language processing, machine learning, and
data visualization allow researchers to analyze vast archival materials, recognize
patterns, and establish links between different sources. These technologies help
improve research questions, discover previously missed insights, and
communicate findings more clearly and cohesively. The research emphasizes
how AI can improve data analysis, decrease researcher bias, and offer varied
perspectives, enhancing historical investigation. Nevertheless, it also deals with
significant hurdles, such as ethical issues, the danger of excessive dependence,
and the constraints of AI in deciphering the subtle and subjective elements of
historical accounts. Students can combine AI with traditional academic
mentorship to blend technological efficiency with critical thinking skills necessary
for historiography. The analysis showed that AI does not serve as a substitute
for human supervisors but as an additional tool that improves the learning and
research process. Its value in academia lies in its ability to promote rigorous
methods, expand research horizons, and support creative approaches.
Incorporating AI as a virtual advisor can enable PhD students to effectively
navigate intricate historical research with accuracy, innovation, and a stronger
involvement in interdisciplinary approaches.
