CFA Learning Platform

What It Is

An adaptive learning system for CFA exam preparation. Users progress through topic levels, complete assessments in multiple formats, and receive AI-generated explanations for incorrect answers. The system tracks performance and adjusts difficulty based on demonstrated mastery.

The Problem

CFA pass rates are below 50%. Common issues:

• No structured progression through prerequisites
• Static content that does not adapt to user performance
• Difficulty identifying knowledge gaps
• Limited feedback on practice questions

The Solution

Structured, adaptive learning:

• Topic dependency mapping with prerequisite requirements
• Multiple assessment formats (MCQ, calculation, written, case study)
• AI-generated explanations for answers
• Performance tracking with gap identification
• Difficulty adjustment based on mastery

How It Works

1. User selects topic or follows recommended path
2. System presents content with prerequisite checks
3. Assessment tests understanding (MCQ, calculation, or written)
4. AI analyzes responses and provides feedback
5. Performance determines next topic or retry
6. Mastery exams verify readiness for each level

Assessment Types

Technical Architecture

Learning Engine

• Prerequisite tracking
• Topic dependency graph
• Adaptive difficulty
• Spaced repetition scheduling

Assessment System

• MCQ engine with randomization
• Calculation validator
• AI rubric for written responses
• Case study framework

AI Layer

• GPT/Claude for answer explanations
• NLP for written response analysis
• Knowledge gap prediction
• Study plan recommendations

Infrastructure

• React/Next.js frontend
• Node.js/Express APIs
• PostgreSQL and MongoDB
• Redis caching
• JWT authentication

Development Status

Use Cases

CFA Candidates Structured preparation for Levels I, II, and III with adaptive pacing.

Self-Learners Custom topic selection with AI-guided study plans.

Institutions Employee training with group analytics and custom content.