Open Knowledge Tracing Service
A tool that supports accurate diagnosis and effective learning by providing Knowledge Tracing—the core component of Intelligent Tutoring Systems—as a Model Context Protocol server.
The Challenge
No Learning Science Integration
Current LLM tutors lack proper integration with learning science principles for personalization.
Domain-Specific Limitations
Systems rely on domain-specific interfaces, limiting scalability and accessibility across subjects.
Lack of Research Data
Insufficient datasets to support research on improving LLM-based educational experiences.
Our Solution
We develop an MCP (Model Context Protocol) server that enables existing LLM services like ChatGPT to be adapted into personalized tutoring systems. Our Knowledge Tracing methodology:
- Can be applied to newly generated questions without relying on historical data
- Works regardless of memory type (declarative or procedural)
- Operates effectively in natural language interaction environments
Key Features
Progress Metrics
Intuitive representation of learner progress with target-time optimization for exams and interviews.
ChatGPT Apps Integration
Seamless integration with ChatGPT Apps and Claude Artifacts for familiar user experiences.
Open Dataset
Contributing valuable research data for the learning science community.