For decades, digital product and service design focused on quantifiable performance metrics: clicks, errors, task completion rates, and time on task. These numbers were easy to capture and simple to benchmark, which made them ideal for early UX and HCI work. But as our understanding of human behavior grew, it became clear that these metrics reveal only the surface of the user experience. They tell us what people did, not why they did it or how they felt while doing it, a patt

Understanding how people think, feel, and perform while interacting with systems requires methods that can capture the brain and body in real time without disrupting the task itself. In Human Factors (HF) and User Experience (UX) research, tools like Electroencephalography (EEG), Functional Near-Infrared Spectroscopy (fNIRS), eye tracking, and Galvanic Skin Response (GSR) provide powerful ways to study attention, emotion, and cognitive load as users engage with technology. Ha

Qualitative user experience (UX) research is undergoing a profound evolution, catalyzed by the emergence of advanced artificial intelligence (AI) tools. For decades, qualitative UX has relied on traditional methods such as interviews, usability testing, think-aloud protocols, and open-ended surveys. These approaches are rich in user insight but notoriously time-intensive and constrained by scalability. With AI, researchers now have the ability to accelerate processes, surface

Over the last year, I’ve seen “AI-powered personas” that were really just LLMs role-playing as UX researchers. We’d prompt them to “create three personas for a banking app,” and get back “Frugal Fiona,” “Investor Ivan,” and “Tech Averse Tom.” It looks impressive for five seconds until you realize it’s just polished guessing. That’s not using AI. That’s outsourcing imagination. The real value of AI in UX isn’t about inventing users. It’s about discovering them. As a cognitive

Artificial Intelligence (specifically Machine Learning) has opened new possibilities for understanding user behavior. Yet, its value in UX research depends entirely on how and when it is applied. As researchers seeking to uncover why  people behave the way they do, we often rely on summarizing performance through simple aggregates: average task completion time, average satisfaction scores, or average conversion rates. However, the so-called “average user” is largely a conveni

When UX researchers hear “Structural Equation Modeling,” it often sounds like something reserved for academic journals or data scientists with specialized training. However, SEM is one of the most valuable frameworks for understanding how complex UX systems actually work. UX researchers rarely stop at asking what is happening. They want to know why and how. SEM is designed for precisely that. It is most useful when survey or telemetry data appear too messy for simple averages

Duration:  5 sessions × 2 hours (10 hours total) Audience:  UX designers and researchers  Instructor:  Mohsen Rafiei, Ph.D. Format:  Online, hands-on sessions using simple tools (Jamovi, JASP, R). Registration Fee for all 5 sessions: $850 Email : Admin@Puxlab.com The Quantitative UX (From Basics to Modeling) course takes UX researchers, and designers on a full learning journey, from the very basics of quantitative thinking to advanced analytical methods used in modern researc

دکتر محسن رفیعی استاد روان‌شناسی دانشگاه آرکانزاس و بنیان‌گذار آزمایشگاه تجربهٔ ادراکی کاربر است. او پس از دریافت دکترای روانشناسی...