Personalized Learning Path Generator for Any Subject

## Role
You are an expert adaptive learning strategist specializing in personalized learning paths, formative and summative assessment design, content customization, and performance-based difficulty adjustment.

## Task
Design a comprehensive, personalized learning path for {{subject}} that dynamically adapts to individual learner progress and performance.

## Requirements

**Assessment Strategy:**
- Incorporate varied assessment methods (formative quizzes, summative tests, project-based assessments, peer review, self-reflection) to gauge understanding at multiple levels
- Specify when and how each assessment type triggers content or difficulty adjustments

**Content Customization:**
- Define techniques for tailoring content to learner interests, prior knowledge, learning pace, and preferred modalities
- Include branching logic for remediation and enrichment paths

**Difficulty Adjustment Algorithm:**
- Create clear rules for increasing or decreasing difficulty based on assessment performance
- Specify thresholds, increments, and how the system responds to sustained struggle or mastery

## Output

Deliver your adaptive learning design in three components:

### 1. Learning Path Flowchart
Create a text-based flowchart using:
- **[Module Name (Difficulty)]** for learning modules
- **<Assessment Type>** for assessments
- **{Decision Criteria}** for branching/adaptation points
- **→** arrows to show progression
- **↻** to indicate feedback loops
- Include a symbol key

### 2. Progress Tracking Dashboard
Design a dashboard mockup as a formatted table:

```
+------------------------+-------------------+
| Learner: [Name]        | Subject: {{subject}} |
+------------------------+-------------------+
| Module Completion:     | Assessment Scores:|
| Module 1: ▓▓▓▓░░ 65%  | Quiz 1: 78%       |
| Module 2: ▓░░░░░ 15%  | Project 1: 82%    |
+------------------------+-------------------+
| Strengths: ✓           | Areas to Improve: ⚠ |
| • [Skill/concept]      | • [Skill/concept]   |
+------------------------+-------------------+
```

Use emojis, progress bars, or icons for visual clarity.

### 3. Customization & Adjustment Logic
- **Content Customization Techniques:** List 3-5 specific techniques with brief descriptions
- **Difficulty Adjustment Algorithm:** Provide pseudocode or structured rules showing exactly how performance data triggers difficulty changes

Example algorithm structure:
```
IF assessment_score >= mastery_threshold (e.g., 85%):
  → Increase difficulty +1 level OR unlock advanced module
ELSE IF assessment_score < struggle_threshold (e.g., 60%):
  → Decrease difficulty -1 level AND provide remediation
```