Adaptive & Intelligent Systems

Guided Learning

Break complex tasks into guided steps, adapting to user knowledge levels.

What is Guided Learning?

Guided Learning is an AI design pattern that breaks complex tasks into manageable step-by-step experiences, adapting to each user's knowledge level and pace. Instead of overwhelming users with all features at once, the system progressively introduces concepts with contextual hints and adjusts difficulty based on performance. It's perfect for onboarding new users to complex tools, educational platforms, or any application with a steep learning curve. Examples include Duolingo adapting language lessons to your skill level, Figma's interactive tutorials highlighting relevant UI elements, or GitHub Codespaces guiding environment setup based on your selections.

Problem

Complex AI systems overwhelm users with too many options, causing confusion and poor adoption.

Solution

Create step-by-step learning experiences with contextual hints and adaptive difficulty to progressively guide users.

Real-World Examples

Implementation

Figma Make Prompt

Guidelines & Considerations

Implementation Guidelines

1

Start simple; gradually introduce complexity.

2

Show clear progress indicators and next steps.

3

Use contextual hints for unfamiliar concepts.

4

Allow skipping ahead or revisiting steps.

5

Provide immediate feedback on user actions.

6

Include checkpoints to maintain motivation.

7

Adapt difficulty based on user performance.

Design Considerations

1

Balance guidance with user autonomy.

2

Support diverse learning styles and paces.

3

Avoid blocking expert users with mandatory steps.

4

Allow non-linear content navigation.

5

Design clear error recovery paths.

6

Avoid cognitive overload at each step.

7

Ensure responsive design across devices.

8

Monitor drop-off points for improvements.

Related Patterns

Related Guides