OVERVIEW

Educators and school districts are now realizing that High-Quality Instructional Materials (HQIM), together with strong teaching, have a direct and significant effect on student achievement. Access to reliable,
top-tier teaching resources not only strengthens teacher preparedness but also fuels their confidence, creating a foundation for excellence. By sharing proven teaching methods, identifying curricula gaps, and leveraging data-driven instructional improvements, educational ecosystems are now shifting towards a sustainable model that delivers enriched learning outcomes and measurable long-term value.

CLIENT

A US-based K-12 educational consortium engaged in reimagining curriculum effectiveness and personalized learning at scale wanted to create an agile HQIM ecosystem to enable K-12 institutions across districts to collaboratively train AI models.
They partnered with Quantrium to develop an AI platform that delivered maximum impact and ROI on the instructional content used by school districts by enabling:

• Access to real-time classroom data from across the consortium.
• Creation and sharing of a dynamic, standards-aligned curriculum.
• Data privacy and security.
• Dissemination of best practices from high-performing schools.

THE QUANTRIUM LEAP FORWARD

Seamlessly combining curriculum delivery, teacher feedback, and AI-driven iterative processes, Quantrium’s scalable, intelligent platform incorporated key functionalities, which included:

• Using AI model training methods to share patterns of success from strong learning outcomes while keeping data localised for privacy & security.
• Identifying curriculum gaps and monitoring instructor innovation, suggesting improvements to bridge teaching gaps.
• Deploying a robust effect estimation approach to give instructors the ability to test and measure interventions.

IMPACT

• Scalable dissemination of proven teaching strategies and curriculum innovations from individual instructors to entire districts, driving system-wide educational improvement.
• Empowered instructors to conduct controlled pilot tests of interventions.
• Data-driven validation before district-level adoption.
• Risk mitigation and optimal resource allocation.

TECHNOLOGY STACK

Scikit-learn

TensorFlow

Federated (TFF)

Causal ML (DoWhy)

PyBKT

MLFlow

MongoDB

MariaDB

GenAI

LLMs (OpenAI, Google Gemini)

Knowledge Graphs