Ux Psychology: Why Good Designs Still Fail
Published 4/2026
Created by Cristina Sampaio, PhD
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 6 Lectures ( 3h 0m ) | Size: 1.5 GB
What you'll learn
✓ Why users struggle, not just where
✓ Why users misunderstand even well-designed interfaces
✓ How to dignose hidden cognitive friction in UX
✓ A practical framework for analyzing UX problems
Requirements
● No
Description
You've followed best practices.
The layout is clean.
Yet, users still struggle.
Usability problems are not random; they are typically the result of predictable cognitive limitations. In this course, you will learn how to identify where an interface is likely to fail cognitively, why those failures occur, and how to reason about risk before users encounter it.
This course is not about trends, patterns, or best practices. It is about diagnosis.
It is designed for designers, with or without a psychology background, who want to move beyond opinion-driven critique and toward a more disciplined, evidence-based understanding of user behavior.
The course introduces a Cognitive Risk Audit, a practical framework for evaluating UX designs through four lenses: perception, attention, memory, and expectations. This framework is designed to support critique, review, and decision-making in real design contexts.
You will learn to anticipate where users are likely to miss information, lose track of context, or misinterpret what they see, even in well-structured layouts. The goal is not just to improve interfaces, but to develop a way of thinking that makes cognitive risks visible early, before they become usability problems in real use.
Users don't fail. Interfaces fail the mind in consistent, predictable ways.
Who this course is for
■ UX/UI designers who want to move beyond best practices and understand underlying cognitive mechanisms
■ Product designers dealing with unexpected user errors or confusion
■ UX researchers who want a more structured way to interpret behavior and diagnose/anticipate failures
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um Code Inhalt zu sehen!