UX Digest - best posts

An Intro to Bayesian Thinking for UX Research: Updating Beliefs with Data Bayesian thinking in UX means starting with a prior belief based on historical data, then mathematically updating it with new evidence. In the example, a prior 78% completion rate combined with 18/20 successes produced an updated 86% estimate—pulled toward the data but not all the way, preventing overreaction to a small sample NNG: GenAI for Complex Questions, Search for Critical Facts Users choose AI to explore and synthesize information; but they rely on traditional search when accuracy and trust are critical Tool: Atlassian Rovo — From Loom User Interviews to Product Backlog Atlassian uses Rovo to turn Loom user interviews into structured Confluence documentation. The AI agent ingests video links and produces reports with timestamps, quotes, and clear analysis—but humans still review and decide which insights become Jira tickets. Structure lives in templates, not prompts Case Study: Learning Platform to Solve Student Attendance and Travel Challenges A learning platform designed to solve student attendance and travel issues by enabling remote access to live and recorded classes. Research showed long commutes caused learning fatigue, with over 90% of students wanting hybrid options. The solution structures content for three user roles and simplifies workflows. Testing confirmed users completed tasks without guidance, with 60% faster access to missed sessions AI: Giving a Toddler Keys to a Hellcat - A Student’s Honest Take on AI in UX Research AI gives students speed but not the judgment to use it wisely. Polished outputs skip the messy work that builds real research instincts. The risk is graduating prompt engineers instead of researchers who truly understand people Experience: What a Farmers Market Taught Me About User Research A user research study at a farmers market found visitors struggled to plan due to a lack of practical online information, leading to a proposal for an interactive vendor map. The real lessons were about presentation: introduce quotes with context, show prototypes, avoid vague language, and make the audience feel empowered to build something better 💳 Basics: UX questionnaires. Is it rocket science? Design principles explain choices, but only user feedback validates them. Questionnaires are essential for that—intuition isn't enough Interesting: No, VR can’t make you walk in others’ shoes VR triggers short emotional reactions but not lasting empathy. Real understanding requires context and reflection—things brief simulations can't provide. It works best as a complement to education, not as a standalone tool for social change @uxdigest