Project Constellation
Using education analytics to inform education strategies
We aim to empower education systems around the world to provide students with the best learning opportunities and improve student learning outcomes, through shared knowledge and technological resources designed to enable the ethical and responsible application of AI in education.
What are Open Education Analytics and Project Constellation?
As education systems transition to remote and hybrid learning, more teaching and learning takes place in the digital environment, giving us new data signals that can be more easily collected and reported. Education systems deploying digital learning platforms need to know how their learners are engaging on these platforms and how learning is progressing. At the same time, new cloud data tools make analyzing data simpler, faster, and more cost effective.
We have a historic opportunity for education analytics to help the global education community understand what works and what doesn’t, as students shift to new modalities of learning.
Project Constellation
Project Constellation is a collaboration between education systems dedicated to advancing the use of education analytics and AI in order to maximize learning outcomes.
The goal is to build an international community with common approaches to education analytics and AI. Leading education systems can explore effective strategies and practices for using AI in education, including participating in co-creation and innovation to speed up national AI development in education.
Open education analytics
Education analytics is the process of collecting and analysing data on learners and their environments in order to understand how to optimise teaching and learning. Microsoft is working with its partner-systems to develop a set of technical resources that will empower them to build capacity and pursue education analytics at a much faster pace. These resources are made available publicly through an open-source community called Open Education Analytics on Github. Together, members of Project Constellation are setting the foundation for the future of broad capacity -building in education analytics across the education sector.
What problems are this solution solving?
✓ Shifting education systems' data to modern cloud data services to enable real-time analytics and AI
✓ Leveraging the power of AI and ML to improve student learning outcomes
✓ Equipping educational institutions with the resources they need to apply AI/ML ethically and responsibly, with reduced effort
4 Components of Project Constellation
In order to enable each system to achieve the best learning outcomes Project Constellation provides access to a wide range of shared resources including technology, best practices, shared analytics, educational materials and more.
Analytics and AI Skills Development
Systems can develop their own internal expertise on data analytics and data management by leveraging Microsoft Learn – a powerful portal for remote and independent learning providing specific courses and curriculums, designed to equip data engineers and data scientists with the skills they need to accelerate analytics and AI in education.
Open Education Analytics Tech Assets
Microsoft and its partners have developed a set of technological resources which are being published in an open-source format on GitHub. These resources include a standard architecture for education analytics and AI in the cloud, modern data security and privacy tools, special scripts with data pipelines, and data visualisation and reporting templates. New and reusable assets will be shared publicly for other systems to use as they develop.
Principles of Responsible AI
To ensure the appropriate and ethical use of student data across education systems, Project Constellation has developed processes of applying Microsoft’s Responsible AI Principles throughout the community’s shared work and resources. These principles are well-aligned with international standards for the responsible and ethical use of AI. They are: fairness, reliability and safety, privacy and security, inclusion, transparency and accountability.
Shared Education Analytics
In order to determine which strategies on education analytics work best, as well as how the approach may differ from one system to another, members of Project Constellation share and discuss their data and AI Use Cases. This enables each system to adapt their practice, leading to longer engagement, improved teacher and student wellbeing, and stronger learning outcomes. These insights are then made public for other education systems to use.
Analytics and AI Skills Development
Microsoft empowers every member of Project Constellation to develop their own expertise on AI and education analytics using a set of special learning paths and modules available in Microsoft Learn. These paths cover various topics related to data gathering and data analytics.
Open education analytics
Data engineering basics
Open education analytics data science
Data science basic
Tools for acting on AI
Machine learning
Getting Started with Education Analytics and AI in Project Constellation
Project Constellation has developed a step-by-step process to enable systems to quickly get set up with Azure, establish a goal, and start using education analytics to extract valuable insights from within the system.
Step 1: Define your Use Case and understand the Principles for Responsible AI
• Review the Principles for Responsible AI
• Review the Use Case Template that applies those Principles to Education
• Identify stakeholders and define the problem that you are trying to solve with data
Step 2: Develop your Use Case
• Begin designing your Use Case using the Use Case Template
• Identify potential datasets
• Review plan with stakeholders
Step 3: Set up your proof of concept for the Use Case
• Set up the Open Education Analytics architecture on Azure
• Ingest your key datasets
• Explore data with Power BI
• Discuss early insights with stakeholders
Step 4: Start Education Analytics
• Decide what to model and how to model it
• Document your assumptions and decisions
• Test your data for fairness
• Use AutoML to build your model
• Discuss insights with stakeholders, plan how to act on the insights, and start small pilots to test them out
Who is this solution meant for?
Organizations who are leading digital transformation in education are eligible to join the program. This includes:
✓ National, state, province or regional Ministries of Education
✓ District or city education authorities
✓ International organizations responsible for education
✓ Large school chains or multi-academy trusts
