Relevance Assessment in Search Engines

User research to investigate information behavior impacted by human biases

HIGHLIGHTS

This project investigates how transparent and interactive AI interfaces can improve users’ engagement, trust calibration, and decision quality during fact-checking tasks.
I designed and evaluated a web-based system that visualizes how AI models assess the credibility and stance of online articles, allowing users to adjust these parameters in real time.
The goal was to understand how AI transparency and user control influence attention, cognitive load, and responsible use of automated fact-checkers.

Role: Lead UX Researcher (Experimental Design, Cognitive Measurement, Eye-Tracking Analysis)
Timeline: January 2021 – December 2023
Collaborators: Dr. Gavindya Jayawardena, Dr. Jacek Gwizdka