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AI-Enabled UX Research Masterclass (December 2025)
December
2025
Costs
$50.00 USD
Taught by
Morgan Denner
Starts
Dec 1, 2025
Ends
Jan 10, 2025
Gallery
Key Audiences
UX Design
UX Research
Product Owner
Product Manager
Summary
There are many ways to test user experiences and learn from users besides interviews. UX Research follows the Scientific Method to create assumptions and test them with experiments. Researchers must ensure they're building objective tests; building subjective tests can lead to poor results and poor UX. This class teaches students how to build objective experiments for any kind of research method, and how to analyze the results of data using the power of AI. In the class you will learn all aspects of experiment-building, analysis, and storytelling through data that comes from primary research. You'll practice with real test plans based on a real research subject.
Why Take This Class?
This class can help anyone who is trying to master skills of research learn how to approach the experimentation side of research, and how to analyze the data that comes from qualitative research. With these skills you will be able to empower teams to become human-centered at any organization in the world, and do it in quick and comprehensive ways.
Learning Objectives
Build objective experiments that reduce and remove bias for any kind of research method.
Utilize AI tools to build efficient analysis of data that’s qualitative and quantitative.
Create research plans and test measurements for any kind of qualitative or quantitative UX research method.
Create and Evaluate AI research analysis.
Determine statistical significance of research results that are qualitative in nature.
Tell a story out of the data that comes from qualitative and quantitative research.
Reading Assignments
Hall, E., & Stark, K. (2019). Just enough research. A Book Apart.
Krug, S., & Matcho, M. (2010). Rocket surgery made easy: The do-it-yourself guide to finding and fixing usability problems. New Riders.
Curriculum
Week 1 - Introduction to UX Research Methods
Lecture
Types of UX research methods
Evaluative
Generative
Examples of Generative research
Interviews
Surveys
Contextual Inquiry
Observations / Ethnography
Examples of Evaluative research
Usability Tests
Prototype Concept Tests
A / B Prototype Tests
Types of bias in UX research to avoid
Experimental design bias
Order bias
Facilitation bias
Cognitive bias
Class Time
Research examples
Research AMA
Homework
None
Week 2 - Building Objective Experiments
Lecture
Prototype Testing methods in detail
Prototype concept tests
Usability tests
A/B tests
Creating the experiment
Test selection
Background and building Context around the test
Research goals
Research Questions
Assumptions and Implications
Method Documentation
Methodology
In-Between Subjects and Within Subjects Research
Participants
Materials
Measurements
Understanding and Documenting Limitations of the Research
Class Time
Prioritizing Research Questions
Determining a Research Method
Building a Test Plan
Homework
Homework 1
Week 3 - Building Qualitative Research Measurements
Lecture
Task Completion Measurements
Task success measurements
“Think Aloud Protocol” and task analysis
Pattern Analysis
Tracking what People Do
Tracking what People Say
Tracking Mental Models
Observation Measurements and Implicit Feedback
Quantifying the qualitative data
Observation measurements
Implicit feedback tracking
A/B testing
Control Variables and Test Variables
The difference between control and test
Using the control and the test to build an experiment
Latin Square and Avoiding Order Bias
What is Order Bias
How do you Remove Order Bias
When to use Latin Square
Class Time
Building Task Measurements
Building Observation Measurements
Homework
Homework 2
Week 4 - Storytelling Around the Results and Analysis
Lecture
Running tests without bias
Research ethics 101
Scripts for facilitation
How to handle improvised moments
Asking questions properly
Knowing when to pause or when to speak
Scaffolding test participants
Analyzing the data in results
Affinity map
Pattern analysis
Rainbow tables
Tracking the results of assumption forming
AI-Based Analysis
Prompting
Giving AI the data
Evaluating responses
Statistical Significance Calculations with AI
How to tell the story of the results
Describing the goals and outcomes
Telling the story through the lens of the experience
Helping others empathize with the user
Forming new assumptions from results
Recommending action items and next steps from research
Class Time
Analyzing the Research Results with AI
Statistical Significance Calculations
Report Building
Homework
Homework 3
Week 5 - AFTER HOLIDAY - Setting Up and Running an Experiment
Lecture
No lecture, all working sessions
Class Time
Analyzing the Research Results with AI
Statistical Significance Calculations
Report Building
Homework
Homework 3
