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AI-Mediated Learning Assessment Tool

A comprehensive 5×4 diagnostic framework for personalized educational interventions.

Live Demo

Try the tool

Overview

This tool implements a research-based assessment framework that evaluates learners across five critical dimensions:

  • Cognitive Processing - Information processing speed, working memory, attention regulation, metacognitive awareness
  • Socioeconomic Factors - Resource availability, family support, economic stress, technology access
  • Emotional Well-being - Academic anxiety, motivation, self-efficacy, stress management
  • Learning Style Preferences - Modality preferences, social vs individual learning, processing style
  • Cultural Learning Context - Authority expectations, struggle tolerance, communication style, independence expectations

Features

  • 20-Indicator Assessment - Comprehensive evaluation across all dimensions
  • Real-time Risk Calculation - Inverse scoring system where higher performance = lower risk
  • Interactive Matrix Display - Visual representation of cross-dimensional relationships
  • Personalized Recommendations - AI-powered suggestions based on individual profiles
  • Live GPT-5 Chat Interface - Chat with Dr. Menon for personalized learning strategies
  • Cultural Learning Analysis - Novel dimension based on educational psychology research
  • Auto-advance Interface - Streamlined user experience with collapsible sections
  • Markdown-enabled Chat - Full table and formatting support in AI responses

Research Foundation

This tool is based on extensive research in educational psychology and AI-mediated learning. The 5×4 diagnostic matrix creates 20 key indicators that interact across dimensions to provide comprehensive learner profiles.

Key Innovations

  1. Cultural Learning Dimension - First framework to systematically assess cultural learning preferences
  2. Cross-dimensional Analysis - Advanced interaction mapping between assessment dimensions
  3. AI Integration - Live GPT-5 powered recommendations and chat interface
  4. Risk Calculation Algorithm - Inverse relationship modeling for accurate academic risk assessment

Research Paper

Read the full paper - Pending Peer Review

Usage

  1. Complete Assessment - Rate yourself on 20 indicators across 5 dimensions
  2. Review Profile - Examine your diagnostic matrix and risk assessment
  3. Get Recommendations - Receive personalized AI-powered learning strategies
  4. Chat with Dr. Menon - Ask questions and get specific advice based on your profile

Technical Implementation

  • Frontend: Pure HTML5, CSS3, JavaScript (ES6+)
  • AI Integration: Azure OpenAI GPT-5 API
  • Responsive Design: Mobile-friendly interface
  • No Dependencies: Self-contained single-file application
  • Markdown Parser: Custom implementation for chat formatting

Development

Local Development

# Clone the repository
git clone https://github.com/menonpg/ai-learning-assessment.git
cd ai-learning-assessment

# Configure API credentials (optional - for chat feature)
cp config.template.js config.js
# Edit config.js with your Azure OpenAI credentials

# Run locally
python -m http.server 8000
# Or just open index.html in your browser
open index.html

Security & Configuration

  • Assessment Tool: Works perfectly without any configuration
  • AI Chat Feature: Requires Azure OpenAI credentials in config.js
  • API Keys: Never committed to repository (see DEPLOYMENT.md)
  • Graceful Degradation: Shows helpful message when chat is not configured

See DEPLOYMENT.md for detailed setup instructions.

Citation

If you use this tool in your research, please cite:

@misc{menon2024ai_learning_assessment,
  title={AI-Mediated Learning Assessment Tool: A 5×4 Diagnostic Framework for Personalized Educational Interventions},
  author={Menon, Prahlad},
  year={2024},
  howpublished={\url{https://github.com/menonpg/ai-learning-assessment}},
  note={PhD, PMP - ThinkCreate.ai}
}

Author

Dr. Prahlad Menon, PhD, PMP

License

MIT License - see LICENSE file

Contributing

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

Acknowledgments

  • Research foundation based on educational psychology literature
  • Cultural learning dimensions inspired by cross-cultural educational research
  • AI integration powered by Azure OpenAI GPT-5

Developed at ThinkCreate.ai - Advancing AI-mediated learning through research and innovation.