Extract from an article by Mona Mourshed, Marc Krawitz, and Emma Dorn
By applying advanced analytics and machine learning, we have identified factors that play a critical role in student achievement.
A well-educated citizenry is an economic and social necessity. Policy makers, educators, and parents all over the world want students to understand and be able to apply their knowledge of math, reading, and science. Yet improving educational outcomes has proved elusive. Some countries, states and municipalities have made great strides, but many continue to struggle. Educators continue to debate what matters and what works.
In this series of reports, we take a data-driven approach to consider a few of the most active debates: Do mindsets matter? If so, to what extent? What teaching practices work best? Does technology help? Our data comes from the Program for International Student Assessment (PISA), administered by the Organisation for Economic Co-operation and Development (OECD). Broad in scale and scope, PISA covered more than half a million students in 72 countries in 2015. What makes PISA so powerful is that it goes beyond the numbers, asking students, principals, teachers, and parents a series of questions about their practice, attitudes, behaviors, and resources…(continues)
SOURCE: Mona Mourshed, Marc Krawitz, and Emma Dorn, “How to improve student educational outcomes: New insights from data analytics”, McKinsey & Company, September 2017
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