AI Question Generation
Advanced AI system for generating unique, contextually appropriate questions in real-time.
AI Generation Capabilities
Question Types
- Multiple Choice: Traditional MCQ with distractors
- True/False: Binary choice questions
- Fill-in-the-Blank: Complete sentence or phrase questions
- Scenario-Based: Real-world application questions
- Problem Solving: Mathematical and logical reasoning questions
Content Generation
- Topic-Aware: Generates questions specific to subject modules
- Difficulty-Calibrated: Creates questions at specified difficulty levels
- Language-Flexible: Supports multiple languages for question generation
- Format-Diverse: Varies question presentation and style
Generation Process
Input Parameters
- Subject Modules: Topics to focus question generation
- Difficulty Level: Target difficulty (Easy, Medium, Hard)
- Question Count: Number of questions needed
- Language: Language for question generation
- Custom Instructions: Specific requirements or focus areas
AI Processing
- Topic Analysis: AI analyzes the subject domain and modules
- Content Research: Draws from knowledge base and training data
- Question Formulation: Creates question stem and answer options
- Distractor Generation: Creates plausible incorrect answers
- Quality Validation: Reviews generated content for accuracy
Output Quality
- Factual Accuracy: Questions based on verified information
- Appropriate Difficulty: Calibrated to requested difficulty level
- Clear Language: Unambiguous question phrasing
- Valid Distractors: Plausible but clearly incorrect options
Customization Options
Generation Settings
- Focus Areas: Emphasize specific topics or skills
- Question Style: Formal, conversational, or technical tone
- Real-World Context: Include practical scenarios and examples
- Cognitive Level: Target specific thinking skills (recall, analysis, synthesis)
Advanced Features
- Learning Objective Alignment: Generate questions matching specific learning goals
- Bloom's Taxonomy: Target specific cognitive levels
- Competency Mapping: Align with skill frameworks and standards
- Cultural Sensitivity: Adapt content for different cultural contexts
Quality Assurance
Automated Validation
- Grammar Check: Ensure proper grammar and syntax
- Fact Verification: Cross-reference with reliable sources
- Difficulty Verification: Confirm appropriate challenge level
- Bias Detection: Screen for unfair or discriminatory content
Human Review Options
- Expert Review: Subject matter expert validation
- Peer Review: Community-based quality checking
- Usage Analytics: Performance data to validate question quality
- Continuous Improvement: AI learning from question performance data