The historic public health crisis of the pandemic spawned an unprecedented crisis in public education. While “Operation Warp Speed” provided a swift solution to the public health impacts of the COVID-19 pandemic, the unfinished learning caused by school building shutdowns has, in some ways, proven even harder to cure. The answer to solving the educational crisis harks back to a strategy established in the 12th century at Oxford University: tutoring. This is widely known to be the best way to teach anyone anything and one of the few interventions capable of overcoming pandemic-induced learning loss. That’s why the US Secretary of Education encouraged schools around the country to focus pandemic relief funding on tutoring. Yet the public education crisis has been slow to resolve – especially for students from low-income backgrounds.
Why have we not made more progress?
Because no one knows how to scale this. The key barrier has nothing to do with pedagogy and everything to do with economics: Cost. There is simply not enough money to support every student who was negatively affected by the pandemic. Tutoring is expensive, and cost is the enemy of scale.
This talk will discuss why tutoring is so much more effective than any other educational strategy, the ways in which strategic use of AI and computer-assisted learning (CAL) tools could help reduce the costs and hence increase the scalability of the benefits of tutoring, and what the most important improvements in AI and CAL software are needed to make progress.
