From keywords to natural language: Integrating AI into a first-year information literacy course

This presentation examines the integration of natural language AI search tools into a newly designed, required information literacy course at the American University of Kuwait. Our approach combines traditional lexical keyword searching with emerging semantic search technologies (ChatGPT, Perplexity, Microsoft Copilot, and SciSpace), creating a novel model for teaching information and digital literacy in the AI era. Through structured comparative exercises with 109 students, we demonstrate how this integration improves research skills and source evaluation while addressing AI limitations, supported by preliminary Spring 2025 data.

Our framework tackles challenges faced by American-style universities in the Middle East, particularly the limited availability of regional scholarly content in traditional databases. Through faculty-librarian collaboration, we show how semantic search tools help bridge regional research gaps while reinforcing critical AI content evaluation. Our hybrid approach blends natural language processing with traditional keyword methods, offering adaptable implementation strategies for AMICAL institutions.

Attendees will gain:

• A clear model for integrating semantic search in information literacy instruction
• Practical methods for teaching AI content evaluation
• Techniques for tackling regional research challenges in American international institutions
• Sample assessment tools and implementation strategies