Big data for poor students

By Jin-Yong Cai

Executive Vice President and Chief Executive Officer of the International Finance Corporation, a member of the World Bank Group.

Countries need skilled and talented people to generate the innovations that underpin long-term economic growth. This is as true in developed as it is in developing economies. But it will not happen without investment in education and training. If we are to end poverty, reduce unemployment, and stem rising economic inequality, we must find new, better, and cheaper ways to teach - and on a vast scale.

This goal may seem to be beyond even wealthier countries' means; but the intelligent collection, analysis, and use of educational data could make a big difference. And, fortunately, we live in an age in which information technology gives us the right tools to broaden access to high-quality, affordable education. Big data - high-volume, complex data sets that businesses use to analyze and predict consumer behavior - can provide teachers and companies with unprecedented amounts of information about student learning patterns, helping schools to personalize instruction in increasingly sophisticated ways.

The World Bank Group and its private-sector lending arm, the International Finance Corporation (IFC), are trying to harness this potential to support national education systems. A recently launched initiative, called the Systems Approach for Better Education Results (SABER), collects and shares comparative data on educational policies and institutions from countries around the world.

In the private sector, the ability to collect information about teacher-student interaction, and interaction between students and learning systems, can have a profound impact. In Kenya, for example, Bridge International Academies is using adaptive learning on a large scale. An IFC client founded by three American entrepreneurs, Bridge runs 259 nursery and primary schools, with monthly tuition averaging $6. It is a massive learning laboratory for students and educators alike.

Bridge tests different approaches to teaching standard skills and concepts by deploying two versions of a lesson at the same time in a large number of classrooms. The lessons are delivered by teachers from standardized, scripted plans, via tablets that also track how long the teachers spend on each lesson. Exam results are recorded on the teacher's tablet, with more than 250,000 scores logged every 21 days. From these data, Bridge's evaluation team determines which lesson is most effective and distributes that lesson throughout the rest of the Academy's network.

We know that a host of issues can cause a student's performance to decline - scorching summer heat in classrooms without air conditioning, problems at home, or poor-quality teachers, to name a few. But when one gathers results on a large scale, variables flatten out, and the important differences emerge. That is the great value of big data.

Another case is SABIS, a provider of K-12 education in the United States, Europe, Asia, the Middle East, and North Africa. SABIS mines large data sets to ensure high standards and enhance academic performance for more than 63,000 students. Continuous tracking of annual student academic performance yields more than 14 million data points that are used to shape instruction, achieve learning objectives, and ensure consistency across the company's network of schools in 15 countries.

Knewton, an adaptive learning platform that personalizes digital courses using predictive analytics, is another company at the forefront of the data revolution. With tailored content and instruction, even classrooms without private-school resources can provide individual learning. As a result, teachers spend their time in the most effective way possible - solving problems with students - instead of delivering undifferentiated lessons.

These benefits do not come without risk. We are only beginning to grapple with how big data's tremendous potential for learning can be harnessed while protecting students' privacy. In some cases, data-collection technology is outpacing our ability to decide how it should be collected, stored, and shared. No matter how rigorously data are secured, there is still a need for a clear licensing structure for its use. In many developing countries, there are no regulations for data privacy at all.

The interface between data and education holds the promise of new educational products for improved learning, with large potential benefits, especially for the poor. To realize those benefits - and to do so responsibly - we must ensure that data collection is neither excessive nor inappropriate, and that it supports learning. The private sector, governments, and institutions such as the World Bank Group need to formulate rules for how critical information on student performance is gathered, shared, and used. Parents and students deserve no less.

Copyright: Project Syndicate


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