AI-Powered Quiz Question Generation System

Project Overview

A backend microservice that automatically generates educational quiz questions using AI. The system enables educators to create diverse, topic-specific questions with minimal effort, enhancing learning experiences through AI-assisted content creation.

Core Problem Statement

Educators spend significant time creating quiz questions, which often leads to:

• Limited question variety
• Time constraints reducing question quality
• Difficulty creating questions at different difficulty levels
• Lack of explanation for correct answers

Solution

An automated system that:

1. Generates questions in multiple formats (MCQ, True/False, Short Answer)
2. Provides difficulty level customization
3. Includes answer explanations
4. Supports topic-based generation
5. Ensures educational accuracy through AI

Key Users & Use Cases

1. Educators: Generate quiz questions for their courses
2. Platform Administrators: Moderate and approve generated content
3. Students (future): Take quizzes with AI-generated questions

Technical Architecture

• Backend: Java Spring Boot (REST APIs)
• AI Integration: HuggingFace Inference API
• Database: PostgreSQL (structured data) + Redis (caching)
• Security: JWT-based authentication with role-based access
• Documentation: OpenAPI/Swagger

Must-Have Features

1. Question Generation API

   • Accepts: Topic, question count, difficulty level, question type
   • Returns: Generated questions with options and correct answers
   • Rate limiting: Max 20 questions per request

2. Question Management

   • Store generated questions
   • Approval workflow (pending → approved → archived)
   • Search/filter by topic, difficulty, status

3. Security & Access Control

   • JWT authentication
   • Role-based permissions (Admin, Teacher, Student)
   • Secure API key management via environment variables

4. Error Handling & Resilience

   • Fallback question generation
   • AI service failure handling
   • Input validation

Technical Requirements

• Framework: Spring Boot 3.x with Spring Security
• Database: PostgreSQL with JPA/Hibernate
• Caching: Redis for rate limiting and session management
• API Client: Spring WebClient for HuggingFace API calls
• Documentation: OpenAPI 3.0 with Swagger UI
• Testing: JUnit 5, Mockito, Integration tests

Success Metrics

• Question generation success rate: >90%
• Response time: <5 seconds per question
• API availability: 99.9%
• User satisfaction: >4/5 rating from educators

Future Extensions

1. Batch Processing: Generate questions in bulk for entire courses
2. Quality Scoring: AI evaluates question quality
3. Multi-language Support: Generate questions in different languages
4. Analytics Dashboard: Track question usage and effectiveness
5. Export Options: Export to various formats (JSON, CSV, Moodle XML)