Within the scope of the training, the integration of contemporary artificial intelligence tools into course design, content development, academic research processes, and active learning practices in higher education was addressed through practical examples. The program particularly focused on the following applications:
Rayyan AI: Utilizing AI-supported screening in systematic literature review processes, filtering articles based on key concepts, and organizing research data; practical applications in graduate-level research methodology courses.
Napkin AI: Transforming text-based content into visual schemas, concept maps, and instructional materials; supporting conceptual structuring and brainstorming activities within active learning environments.
Web of Science data retrieval practices: Enhancing data-driven academic decision-making skills through citation analysis, impact factor examination, field mapping, and bibliometric data analysis.
We would like to extend our sincere appreciation to the CILT-AI Coordination Office, Assistant Professor Adem Yurdunkulu for his valuable contribution to the training, and all participating academics for their strong engagement. We hope that innovative and technology-enhanced teaching practices will continue to expand across our university.
