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Making education more effective, equitable and available to every child in the world has long been the holy grail for education technologists and entrepreneurs, who have developed countless solutions, like massive open online courses. Now, with advances in artificial intelligence (AI), we can take this a step further and pursue adaptive education.

The core promise of adaptive education is an intelligent, 1:1 experience for every student. Research has long established that students who receive personalized, one-on-one tutoring from human teachers outscore their peers on final exams. As early as 1984, Dr. Benjamin Bloom, the late educational psychologist, showed that students who receive personalized tutoring score higher than almost all of their fellow students who attend standard classroom lectures.

The implications are dramatic: We can build a computer-based tutor for millions of students around the world.

Adaptive education represents a paradigm shiftfrom the conventional model (an instructor-centric, passive learning experience) to an intelligent one (a learner-centric, interactive, active learning experience). In the adaptive model, each student is paired with a virtual coach. Its a concept that can be scaled to millions of students at a fraction of the cost of human tutors.

The full spectrum of technology innovation in education has long been understood using the SAMR frameworkfor substitution, augmentation, modification and redefinition. Adaptive education powered by AI, not surprisingly, fits into the final stage of redefinition, where transformative experiences truly happen and learning itself is redefined. (For more information on these perspectives, check out Rewiring Education, for which I co-wrote a Chinese version.)

How far away are we from putting adaptive learning platforms to work? In order to deliver on their promise, companies must first build an adaptive learning engine that can acquire, store and analyze data. At my company, we have invested heavily in the most advanced machine learning algorithms and continue to conduct research that can improve not only our products but also the AI and science that drives them.

Derek Haoyang Li

For example, one machine learning model we developedcalled a multidimensional probabilistic knowledge stateuses data from learners to measure their proficiency across a wide range of variables. The application module that uses an AI algorithm can measure a students approximate proficiency level on each of 500 knowledge factors using just 25-30 questions.

For years, conventional education has been defined, in part, by geography and the financial means to pursue college degrees. New types of online learning in recent years have been helpful in overcoming some of those limitations, but they havent solved the core challenge that adaptive AI canto shift the teaching model from one-to-many to one-to-one.

Ultimately, I believe adaptive systemswith the combination of AI and human coaching represent our best hope for giving all students the chance to reach their full potential.

CREDIT: Klaus Vedfelt/GettyImages; Courtesy of Derek Haoyang Li

See the rest here:
How AI Can Realize The Promise Of Adaptive Education - Forbes