Adaptive Learning Path Generator with TypeScript Generics

Design a type-safe, generic TypeScript module for dynamically generating personalized student learning paths using machine learning algorithms. The system should support multiple curriculum models, track individual student performance metrics, and automatically adjust recommended learning sequences. Implement strong typing for student profiles, learning objectives, and adaptive recommendation logic using Nest.js. Include comprehensive type guards to ensure data integrity and prevent runtime errors in curriculum adaptation.