Project title: TAIHU: User Research for a Conversational AI Knowledge Discovery Platform Context: A multi-year research project at National Taiwan University to build a conversational AI platform that helps humanities scholars explore primary-source databases. My role: As a research assistant, I drafted the interview guide, conducted the year-2 interviews, analyzed interview data to develop personas, supported journey mapping through qualitative coding, and analyzed survey data quantitatively. Methods: Interviews, qualitative coding, personas, journey mapping, survey analysis. Scale: Interviews with 10+ scholars; a year-2 usability study with 130+ participants (system trial, A/B testing of model responses, surveys, interviews); a year-3 two-week longitudinal study with 30+ participants.

Outcome: The persona "Eleanor" represents an experienced humanities professor who uses AI rarely and holds a cautious attitude toward it, somewhere between negative and neutral. She finds collecting and reading primary and secondary materials the most time-consuming stage of her research, and that is where she would most want AI assistance. She has tried AI before but found it unreliable, so she prefers to handle things herself for now, and she worries about long-term effects such as students losing basic skills and AI limiting creativity. The persona captures a group of scholars who want help with materials but need to be able to trust it.

Design implication: For scholars like Eleanor, assistance with finding and reading materials needs to be reliable and verifiable before it can earn trust.