Transforming Curriculum Authoring
In collaboration with Cognizant and Galvia, Cambridge Mathematics embarked on a transformative journey to streamline and expedite this process, ultimately achieving unprecedented levels of efficiency.
About the client
Cambridge University, renowned for its academic excellence, faced a pressing challenge in its Mathematics department. The University’s authoring team, comprising six to seven highly dedicated individuals, was tasked with the arduous responsibility of aggregating data from research papers, national curricula, textbooks, and other relevant documents.
They had a tough job of collecting data from various sources like research papers, textbooks, and more. Their goal was to carefully study and put together all this information into a structured plan for Cambridge Mathematics. This plan was used to create class materials, and exams, and help with research projects. The problem was that doing this by hand was very hard and took a lot of time. It also made it tricky to customise the curriculum for different places. In a nutshell, the math department had a big job collecting and organising data for Cambridge Mathematics, and doing it manually was tough and time-consuming.
The Challenge
The primary challenge faced by Cambridge Mathematics was the time-consuming nature of the data extraction and analysis process. The authoring team had to sift through vast amounts of academic content, including research papers and diverse curricula, to extract and organise pertinent information manually. This process not only strained their resources but also posed difficulties in adapting the curriculum to meet the unique needs of different regions.
Key Objectives
Cognizant, in partnership with Galvia, proposed a groundbreaking solution leveraging artificial intelligence and advanced machine learning techniques. The solution aimed to automate the data ingestion, semantic analysis, and integration processes, ultimately reducing the burden on the authoring team and increasing efficiency.
Data Cleansing
Model Training
Semantic Analysis and Integration into the Framework
Results
The implementation of Cognizant and Galvia’s AI solution yielded remarkable results:
- Faster Work: The AI system made everything much quicker. It helped the team do their work faster and with less effort. It also allowed the authoring team to focus on higher-value tasks.
- Working Together: The new way of doing things made it easier for Cambridge University to work with other schools all around the world. They could share teaching materials more easily.
Cognizant and Galvia’s collaboration with Cambridge Mathematics exemplifies the transformative potential of artificial intelligence in the field of education. By automating complex data analysis and integration tasks, the partnership successfully alleviated the burden on academic staff and significantly improved work efficiency. The ability to rapidly adapt curricula to international standards demonstrated the system’s versatility and impact on global education initiatives.
This case study illustrates how innovative AI solutions can revolutionise traditional workflows, drive efficiency, and enable academic institutions to excel in their mission to provide high-quality education on a global scale. Cambridge Mathematics’s partnership with Cognizant and Galvia serves as a testament to the power of AI-driven solutions in modernising education.
