PathLab Content

Structured learning content for PassionSeed — a gamified mobile learning platform where students discover their passions through interactive paths, AI conversations, and achievement-based progression.

What is PathLab?

PathLab is PassionSeed's core learning delivery system. It transforms traditional coursework into gamified learning paths where students progress through daily activities, unlock nodes on visual learning maps, and engage with AI tutors and NPC characters.

Think of it as a learning management system meets RPG progression — complete with sprites, boss nodes, branching dialogues, and AI-powered coaching.

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Content Types

PathLab supports two main categories of activities: Content (learning material) and Assessment (evaluation).

Content Activities

Type	Description	Example
video / short_video	Embedded video content	Tutorial walkthroughs, lectures
text / daily_prompt	Articles, prompts, written content	Reading assignments, daily questions
image	Image-based learning material	Diagrams, infographics
pdf	PDF documents	Worksheets, reading packets
canva_slide	Canva presentations	Slide decks, visual guides
resource_link	External links	Reference materials, tools
npc_chat	Branching NPC conversations	Scenario-based roleplay, guided decision trees
ai_chat	Dynamic AI tutoring	Career exploration, brainstorming, reflection

Assessment Activities

Type	Description	Grading
quiz	Multiple choice questions	Auto-graded
daily_reflection	Guided reflection prompts	Instructor/TA graded
text_answer	Long-form written responses	Instructor/TA graded
file_upload	Project submissions, documents	Instructor/TA graded
checklist	Task completion lists	Auto-checked

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System Architecture

Learning Maps (Visual Pathways)

Interactive node-based maps built with React Flow:

• Nodes — Individual learning topics with content and assessments
• Paths — Connections defining prerequisite relationships
• Sprites — Gamified visuals for nodes (crystals, bosses, custom images)
• Unlocking — Nodes unlock based on completion of prerequisites

Activity Structure

Path
├── Path Days (daily lessons)
│   ├── Activities
│   │   ├── Content (video, text, ai_chat, npc_chat, etc.)
│   │   └── Assessment (quiz, reflection, file_upload, etc.)
│   └── Progress Tracking
└── Cohort Enrollments

Progress & Gamification

• Status States: locked → unlocked → in_progress → submitted → passed/failed
• Leaderboards: Rank students by completion speed and grades
• Visual Feedback: Color-coded nodes (green=passed, red=failed, blue=submitted, orange=in-progress)
• Time Tracking: Estimated minutes per activity, actual time spent

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Key Features

🤖 AI Chat Activities

Objective-driven conversations with AI tutors:

• Custom system prompts define the AI's role (career counselor, study coach, etc.)
• Real-time progress analysis (0-100% completion)
• Automatic completion detection when objectives are met
• Full conversation history persistence

🎭 NPC Conversation System

Branching dialogue trees for scenario-based learning:

• Question nodes, statement nodes, and endings
• Conditional choices based on previous selections
• NPC avatars with emotions and personality
• Progress tracking through choice history

📝 Draft Activity System

Work-in-progress workflow for content creators:

• Save incomplete activities as drafts
• Visual draft badges and missing-field indicators
• RLS policies protect students from accessing unfinished content
• Automatic completeness validation

🗺️ Map Editor

Visual drag-and-drop editor for building learning paths:

• Create nodes, connect with paths, arrange layouts
• Configure content and assessments per node
• Batch operations for complex map updates
• Real-time preview of student experience

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Database Schema (Summary)

Core Tables

• paths — Learning paths/curricula
• path_days — Daily lessons within a path
• path_activities — Individual learning activities
• path_content — Activity content (video, text, AI config, etc.)
• path_assessment — Activity assessments (quizzes, reflections, etc.)

Progress Tracking

• path_activity_progress — Student activity completion status
• path_ai_chat_sessions — AI chat session state
• path_npc_conversation_progress — NPC dialogue progress

Map System

• learning_maps — Top-level learning maps
• map_nodes — Individual nodes
• node_paths — Connections between nodes
• student_node_progress — Node completion tracking

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Activity Configuration

AI Chat Metadata

{
  "system_prompt": "You are a supportive career counselor...",
  "objective": "Help student identify 3 potential career paths",
  "completion_criteria": "Student has listed 3 careers with explanations",
  "model": "passion-6",
  "max_messages": 30
}

NPC Chat Metadata

{
  "conversation_id": "uuid-of-conversation-tree",
  "allow_restart": false,
  "show_history": true
}

Quiz Assessment

{
  "assessment_type": "quiz",
  "points_possible": 100,
  "quiz_questions": [
    {
      "question_text": "What is a variable?",
      "options": ["A storage location", "A function", "A loop"],
      "correct_answer": 0
    }
  ]
}

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Content Creation Workflow

1. Create a Path — Define the learning journey
2. Add Path Days — Structure into daily lessons
3. Create Activities — Add content and assessments per day
4. Configure Content — Set up videos, AI prompts, NPC conversations
5. Set Assessments — Define quizzes, reflections, or submissions
6. Enroll Cohorts — Assign student groups to the path
7. Publish — Make activities live (non-draft) for students

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Tech Stack

• Frontend: Next.js 15, React, TypeScript, Tailwind CSS
• Visualization: React Flow (node-based maps)
• Backend: Supabase (PostgreSQL, Auth, Real-time)
• AI: Custom models (passion-6) for chat activities
• Mobile: React Native with Expo

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Related Repositories

• passionseed/docs — System documentation and design specs
• passionseed/mobile — React Native mobile app
• passionseed/web — Next.js web dashboard

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Part of the PassionSeed learning platform — Discover Your Passion, Ignite Your Potential.