Designing and Analyzing Experiments in Human-Computer Interaction

Creating intuitive digital experiences requires more than just good design instincts; it demands rigorous, empirical validation. This text-based course introduces you to the core methodologies used to scientifically evaluate how humans interact with technology. You will transition from making subjective design choices to conducting structured, objective user research. Through clear written explanations, practical examples, and step-by-step analysis walk-throughs, you will learn how to formulate testable hypotheses, design controlled studies, and interpret behavioral data to make informed product decisions. What you'll learn: Understand the fundamental terminology of human-computer interaction (HCI) research and experimental design; Identify independent, dependent, and confounding variables to isolate the true impact of design changes; Select and recruit diverse participant groups while incorporating modern accessibility and ethical standards; Choose the appropriate statistical tests to analyze user performance, error rates, and subjective feedback; Apply modern remote evaluation frameworks to test interfaces across different devices and environments; Interpret experimental results to generate actionable, data-backed design recommendations. The course begins with foundational definitions of HCI evaluation before guiding you through study design, variable selection, quantitative analysis, and reporting. You will practice applying these concepts through written scenarios and analysis exercises designed to simulate real-world product testing. This course is designed for aspiring UX researchers, product managers, and software developers who want a structured introduction to empirical evaluation. No prior statistical or research background is required. Start reading today to build a scientific foundation for your user experience decisions.