Advanced Analytics Techniques

• 1: Predictive Analytics
• 2: Machine Learning Models
• 3: Emerging Technologies Integration
• 3.1: Quantum Computing
• 3.2: Generative AI

1 - Predictive Analytics

• Forecasting: Predict future performance or potential disengagement.

• Intervention Triggers: Automatically alert educators about risk trends.

• Scenario Modeling: Evaluate “what-if” cases by adjusting timetables or tasks.

2 - Machine Learning Models

• Training: Update models with new user data to maintain relevance.
• Growth Mapping: Plot how a learner’s metrics have evolved, identifying stable trends or anomalies.
• Algorithm Selection: Switch between neural networks, decision trees, or SVMs depending on data type and complexity.

3 - Emerging Technologies Integration

To maintain a cutting-edge system, plans are in place to incorporate advancements in technology.

3.1 - Quantum Computing

• Applications: Explore quantum-based solutions for large-scale data sets.
• Readiness: Maintain forward compatibility scoped for future quantum tools.
• Research and Development: Collaborate with academic or private quantum labs to pilot new approaches.

3.2 - Generative AI

• Content Generation: Automatically create personalized practice questions or reading materials.
• Advanced Forecasting: Model advanced scenarios for resource allocation or dropout prevention.
• NLP: Integrate intelligent tutors or chatbots for student Q&A.