Advanced analytics and AI
Use integrated data with advanced analytics and artificial intelligence for system improvements and visibility into teaching, learning, and administration progress within and across classrooms and schools.
The knowledge economy is prompting countries/regions to improve their competitive advantage by investing in education. At the national/regional level, this means policymakers are relying on the analysis of learner data to inform their decision-making. From Nigeria to Germany, nations are acknowledging the importance of using data for evidence-based education planning. Data sets are collected to help countries/regions gauge the status of their education systems and identify gaps in schooling. Analytics are also used to provide trend analysis and comparisons between different regions within a country/region. Digital tools provide detailed, real-time information to help educators make informed decisions about learner performance. Data analytics now has the power to revolutionize education by translating national/regional-level policies into practice.
To understand one nation's journey, read Hungarian government unlocks the power of AI and big data to improve its education system to uncover reasons behind the high learner dropout rate.
Review the Data and education transformation report. Think about where your school falls in the educational analytics maturity model.
With your leadership team, use the educational analytics maturity model to assess what level you currently identify with most closely. What steps do you need to take to move to the next level? Develop a realistic timeline for executing these steps.
What tools does your school currently use to proactively intervene when a learner is struggling academically, emotionally, or socially?