Caleb Sponheim Ph.D. is a User Experience Specialist with Nielsen Norman Group. A former computational neuroscientist, his expertise includes quantitative user experience research, statistics, analytics, and data science.
Measurement error is the error we introduce when we measure or observe something about our users. It can come from different sources, such as the number of participants, individual variation between participants, testing environment, or other outside factors. This video helps understand and communicate such measurement errors.
A Flow State is an enjoyable mental state of extreme focus provided by the perfect balance of challenge and skill. Follow our 3 tips to design products that allow users to enter the flow state.
Large language models like ChatGPT can lie to elicit approval from users. This phenomenon, called sycophancy, can be detected in state-of-the-art models.
False positives and negatives are common errors in quantitative studies that can lead to harmful business decisions. To avoid these mistakes recruit large enough sample sizes, representative participants, and control for confounding variables.
The ELIZA effect describes users' tendency to quickly attribute human characteristics to artificial systems when the interaction feels human-like. This is why people fall in love with AI.
Users quickly attribute human-like characteristics to artificial systems, which reflect their personality back to them. This phenomenon is called the ELIZA effect.
Confounding variables interfere with quantitative studies, leading to inaccurate results. Avoid introducing such variables by randomizing your study’s conditions and keeping your research questions focused.
